Professor Montse Garcia-Closas
Group Leader: Integrative Cancer Epidemiology
Biography
Professor Montserrat García-Closas is a Professor of Epidemiology and Group Leader for the Integrative Epidemiology Group. She co-leads the Cancer Epidemiology and Prevention Unit, a joint initiative from the ICR and Imperial College London, and holds an honorary appointment at The Royal Marsden Hospital.
Professor Montserrat García-Closas received her M.D. from the University of Barcelona, Spain, a Master of Public Health in quantitative methods, and a Doctorate of Public Health in epidemiology from the Harvard School of Public Health.
She joined the Division of Cancer Epidemiology and Genetics (DCEG) of the National Cancer Institute in the USA in 1996 as a postdoctoral fellow, became a tenure-track investigator in 1999 and a tenured senior investigator in 2007. From 2008-2010, she was a visiting scientist at the Department of Oncology and Strangeways Laboratory, Cambridge University, U.K.
In 2010, she became a Professor of Epidemiology at the Division of Genetic and Epidemiology at the ICR. In 2015, she returned to DCEG as Deputy Director and senior investigator. She served as Interim Branch Chief for the Integrative Tumor Epidemiology Branch (ITEB) from 2016-2020, and as Director of the Trans-Divisional Research Program (TDRP) from 2020-2023. In 2023 she returned to the ICR in London as Professor of Epidemiology.
Professor García-Closas investigates the causes of cancer with the aim of understanding carcinogenic processes and improving risk assessment for precision prevention. She carries out a multidisciplinary research program on the genetic susceptibility, etiologic heterogeneity, and risk prediction for breast cancer.
She is principal investigator (PI) of the Breast Cancer Now Generations Study, a prospective cohort study of 110,000 women in the UK to study cancer aetiology and its outcomes, and the Male Breast Cancer Study, a case-control study of over 1,000 men with breast cancer and 1,000 controls to study the genetic and environmental causes of male breast cancer. Professor García-Closas also contributes to molecular epidemiology studies of bladder and other cancers. She has published over 400 peer-reviewed papers, as well as book chapters and review articles.
Professor García-Closas is a founder member of several large consortia. She served as the Chair of the Coordinating Committee for the International Consortium of Case-Control Studies of Bladder Cancer from 2005-2011, and since 2006 she co-Chairs the Pathology and Survival Working Group of the Breast Cancer Association Consortium (BCAC).
Professor Garcia-Closas co-led the European Commission Horizon 2020-funded Breast CAncer STratification (BCAST) Project within BCAC. She initiated and is the Chair of the Scientific Steering Committee for the Confluence Project which brings together multiple consortia for trans-ancestry genetic susceptibility studies of female and male breast cancer.
She is an active member of the NCI Cohort Consortium, where she co-leads the U01 Multi-factorial Breast Cancer Risk Prediction Accounting for Ethnic and Tumor Diversity to develop a comprehensive tool to predict breast cancer risk, overall and by sub-types, across major racial/ethnic groups in the U.S.
She served as the founding PI of Connect for Cancer Prevention (2016-2023), a new prospective study of 100,000 adults in the USA, and she currently serves in the International Advisory Committee.
Dr.P.H. Epidemiology, Harvard School of Public Health, Boston.
M.P.M. Quantitative Methods, Harvard School of Public Health, Boston.
MD, University of Barcelona, Spain.
Merit Award, NIH, 2001.
Intramural Research Award, National Cancer Institute, 2004.
Mentor of Merit Award, National Cancer Institute, 2007.
Merit Award, NIH, 2008.
Editorial BoardsCancer Epidemiology, Biomarkers & Prevention, 2005.
AACR Cancer Epidemiology and Prevention Awards Committee, Member, AACR, 2009-2011.
Scientific Review Committee for the 2010 Landon Foundation-AACR INNOVATOR Award for Cancer Prevention Research, Member, AACR, 2010-2010.
Member of the 2011 AACR Annual Meeting Education Committee, Member, AACR, 2010-2010.
Program Committee for the 2010 AACR Annual Meeting, Member, AACR, 2009-2010.
External Scientific Committee for the Multicenter Case-Control Study in Spain, Centre for Research in Environmental Epidemiology (CREAL), Member, CREAL, 2009.
Scientific Advisory Board for the Sister Study, Member, National Institute of Environmental Health Sciences, Research, 2007.
Steering Committee of the Molecular Epidemiology Working Group, Member, AACR, 2007-2009.
Search Committee for Tenure-track/Tenure Investigator, Laboratory of Translational Genetics, Member, National Cancer Institute, 2007.
Estrogen Receptor Negative Breast Cancer Health Disparities Work Group, Member, National Cancer Institute, 2007-2008.
Search Committee for Branch Chief, Member, National Cancer Institute, 2007.
Search Committee for Tenure-track Investigator, Biostatics Branch, Member, National Cancer Institute, 2007.
Etiology and Early Marker Studies (EEMS) Review Panel for PLCO Studies, Member, National Cancer Institute, 2006-2008.
Tenure-track Search Committee, Occupational & Environmental Epidemiology Branch, Member, National Cancer Institute, 2005.
Tenure-track Search Committee, Biostatistics Branch, Member, National Cancer Institute, 2005.
Epidemiology & Biostatistics Subsection, Planning Committee of the AACR 96th Annual Meeting, Chair, American Association for Cancer Research, 2004.
Technical Evaluation of Protocols Committee, Member, National Cancer Institute, 2003.
Technical Evaluation of Questionnaires Committee, Member, National Cancer Institute, 1998.
Related pages
Types of Publications
Journal articles
Genome-wide association studies have identified approximately 200 genetic risk loci for breast cancer, but the causal variants and target genes are mostly unknown. We sought to fine-map all known breast cancer risk loci using genome-wide association study data from 172,737 female breast cancer cases and 242,009 controls of African, Asian and European ancestry. We identified 332 independent association signals for breast cancer risk, including 131 signals not reported previously, and for 50 of them, we narrowed the credible causal variants down to a single variant. Analyses integrating functional genomics data identified 195 putative susceptibility genes, enriched in PI3K/AKT, TNF/NF-κB, p53 and Wnt/β-catenin pathways. Single-cell RNA sequencing or in vitro experiment data provided additional functional evidence for 105 genes. Our study uncovered large numbers of association signals and candidate susceptibility genes for breast cancer, uncovered breast cancer genetics and biology, and supported the value of including multi-ancestry data in fine-mapping analyses.
<h4>Background</h4>The stromal microenvironment (SME) is integral to breast cancer (BC) biology, impacting metastatic proclivity and treatment response. Emerging data indicate that host factors may impact the SME, but the relationship between pre-diagnostic host factors and SME phenotype remains poorly characterized, particularly among women of African ancestry.<h4>Methods</h4>We conducted a case-only analysis involving 792 BC patients (17-84 years) from the Ghana Breast Health Study (GBHS). High-accuracy machine-learning algorithms were applied to standard H&E-stained images to characterize SME phenotypes (including percent tumor-associated connective tissue stroma, Ta-CTS (%), and tumor-associated stromal cellular density, Ta-SCD (%)). Associations between pre-diagnostic host factors and SME phenotypes were assessed in multivariable linear regression models.<h4>Results</h4>Decreasing Ta-CTS and increasing Ta-SCD were associated with aggressive, mostly high-grade tumors (p-value<0.001). Several pre-diagnostic host factors were associated with Ta-SCD independently of tumor characteristics. Compared with nulliparous women, parous women had higher levels of Ta-SCD [mean (standard deviation, SD) = 31.3% (7.6%) vs. 28.9% (7.1%); p-value=0.01]. Similarly, women with a positive family history of breast cancer had higher levels of Ta-SCD than those without family history [mean (SD) = 33.0% (7.5%)] vs. 30.9% (7.6%); p-value=0.03]. Conversely, increasing body size was associated with decreasing Ta-SCD [mean (SD) = 32.0% (7.4%), 31.3% (7.3%), and 29.0% (8.0%) for slight, average, and large body sizes, respectively, p-value=0.005].<h4>Conclusions</h4>Epidemiological risk factors were associated with varying degrees of stromal cellularity in tumors, independently of clinicopathological characteristics.<h4>Impact</h4>The findings raise the possibility that epidemiological risk factors may partly influence tumor biology via the SME.
<h4>Objectives</h4>Absolute risk models estimate an individual's future disease risk over a specified time interval. Applications utilizing server-side risk tooling, the R-based iCARE (R-iCARE), to build, validate, and apply absolute risk models, face limitations in portability and privacy due to their need for circulating user data in remote servers for operation. We overcome this by porting iCARE to the web platform.<h4>Materials and methods</h4>We refactored R-iCARE into a Python package (Py-iCARE) and then compiled it to WebAssembly (Wasm-iCARE)-a portable web module, which operates within the privacy of the user's device.<h4>Results</h4>We showcase the portability and privacy of Wasm-iCARE through 2 applications: for researchers to statistically validate risk models and to deliver them to end-users. Both applications run entirely on the client side, requiring no downloads or installations, and keep user data on-device during risk calculation.<h4>Conclusions</h4>Wasm-iCARE fosters accessible and privacy-preserving risk tools, accelerating their validation and delivery.
The associations of certain factors, such as age and menopausal hormone therapy, with breast cancer risk are known to differ for interval and screen-detected cancers. However, the extent to which associations of other established breast cancer risk factors differ by mode of detection is unclear. We investigated associations of a wide range of risk factors using data from a large UK cohort with linkage to the National Health Service Breast Screening Programme, cancer registration, and other health records. We used Cox regression to estimate adjusted relative risks (RRs) and 95% confidence intervals (CIs) for associations between risk factors and breast cancer risk. A total of 9421 screen-detected and 5166 interval cancers were diagnosed in 517,555 women who were followed for an average of 9.72 years. We observed the following differences in risk factor associations by mode of detection: greater body mass index (BMI) was associated with a smaller increased risk of interval (RR per 5 unit increase 1.07, 95% CI 1.03-1.11) than screen-detected cancer (RR 1.27, 1.23-1.30); having a first-degree family history was associated with a greater increased risk of interval (RR 1.81, 1.68-1.95) than screen-detected cancer (RR 1.52, 1.43-1.61); and having had previous breast surgery was associated with a greater increased risk of interval (RR 1.85, 1.72-1.99) than screen-detected cancer (RR 1.34, 1.26-1.42). As these differences in associations were relatively unchanged after adjustment for tumour grade, and are in line with the effects of these factors on mammographic density, they are likely to reflect the effects of these risk factors on screening sensitivity.
Co-observation of a gene variant with a pathogenic variant in another gene that explains the disease presentation has been designated as evidence against pathogenicity for commonly used variant classification guidelines. Multiple variant curation expert panels have specified, from consensus opinion, that this evidence type is not applicable for the classification of breast cancer predisposition gene variants. Statistical analysis of sequence data for 55,815 individuals diagnosed with breast cancer from the BRIDGES sequencing project was undertaken to formally assess the utility of co-observation data for germline variant classification. Our analysis included expected loss-of-function variants in 11 breast cancer predisposition genes and pathogenic missense variants in BRCA1, BRCA2, and TP53. We assessed whether co-observation of pathogenic variants in two different genes occurred more or less often than expected under the assumption of independence. Co-observation of pathogenic variants in each of BRCA1, BRCA2, and PALB2 with the remaining genes was less frequent than expected. This evidence for depletion remained after adjustment for age at diagnosis, study design (familial versus population-based), and country. Co-observation of a variant of uncertain significance in BRCA1, BRCA2, or PALB2 with a pathogenic variant in another breast cancer gene equated to supporting evidence against pathogenicity following criterion strength assignment based on the likelihood ratio and showed utility in reclassification of missense BRCA1 and BRCA2 variants identified in BRIDGES. Our approach has applicability for assessing the value of co-observation as a predictor of variant pathogenicity in other clinical contexts, including for gene-specific guidelines developed by ClinGen Variant Curation Expert Panels.
<h4>Purpose</h4>Mammographic density phenotypes, adjusted for age and body mass index (BMI), are strong predictors of breast cancer risk. BMI is associated with mammographic density measures, but the role of circulating sex hormone concentrations is less clear. We investigated the relationship between BMI, circulating sex hormone concentrations, and mammographic density phenotypes using Mendelian randomization (MR).<h4>Methods</h4>We applied two-sample MR approaches to assess the association between genetically predicted circulating concentrations of sex hormones [estradiol, testosterone, sex hormone-binding globulin (SHBG)], BMI, and mammographic density phenotypes (dense and non-dense area). We created instrumental variables from large European ancestry-based genome-wide association studies and applied estimates to mammographic density phenotypes in up to 14,000 women of European ancestry. We performed analyses overall and by menopausal status.<h4>Results</h4>Genetically predicted BMI was positively associated with non-dense area (IVW: β = 1.79; 95% CI = 1.58, 2.00; p = 9.57 × 10<sup>-63</sup>) and inversely associated with dense area (IVW: β = - 0.37; 95% CI = - 0.51,- 0.23; p = 4.7 × 10<sup>-7</sup>). We observed weak evidence for an association of circulating sex hormone concentrations with mammographic density phenotypes, specifically inverse associations between genetically predicted testosterone concentration and dense area (β = - 0.22; 95% CI = - 0.38, - 0.053; p = 0.009) and between genetically predicted estradiol concentration and non-dense area (β = - 3.32; 95% CI = - 5.83, - 0.82; p = 0.009), although results were not consistent across a range of MR approaches.<h4>Conclusion</h4>Our findings support a positive causal association between BMI and mammographic non-dense area and an inverse association between BMI and dense area. Evidence was weaker and inconsistent for a causal effect of circulating sex hormone concentrations on mammographic density phenotypes. Based on our findings, associations between circulating sex hormone concentrations and mammographic density phenotypes are weak at best.
<h4>Background</h4>Breast cancer consists of distinct molecular subtypes. Studies have reported differences in risk factor associations with breast cancer subtypes, especially by tumor estrogen receptor (ER) status, but their consistency across racial and ethnic populations has not been comprehensively evaluated.<h4>Methods</h4>We conducted a qualitative, scoping literature review using the Preferred Reporting Items for Systematic Reviews and Meta-analysis, extension for Scoping Reviews to investigate consistencies in associations between 18 breast cancer risk factors (reproductive, anthropometric, lifestyle, and medical history) and risk of ER-defined subtypes in women who self-identify as Asian, Black or African American, Hispanic or Latina, or White. We reviewed publications between January 1, 1990 and July 1, 2022. Etiologic heterogeneity evidence (convincing, suggestive, none, or inconclusive) was determined by expert consensus.<h4>Results</h4>Publications per risk factor ranged from 14 (benign breast disease history) to 66 (parity). Publications were most abundant for White women, followed by Asian, Black or African American, and Hispanic or Latina women. Etiologic heterogeneity evidence was strongest for parity, followed by age at first birth, postmenopausal body mass index, oral contraceptive use, and estrogen-only and combined menopausal hormone therapy. Evidence was limited for other risk factors. Findings were consistent across racial and ethnic groups, although the strength of evidence varied.<h4>Conclusion</h4>The literature supports etiologic heterogeneity by ER for some established risk factors that are consistent across race and ethnicity groups. However, in non-White populations evidence is limited. Larger, more comparable data in diverse populations are needed to better characterize breast cancer etiologic heterogeneity.
We performed genome-wide association studies of breast cancer including 18,034 cases and 22,104 controls of African ancestry. Genetic variants at 12 loci were associated with breast cancer risk (P < 5 × 10<sup>-8</sup>), including associations of a low-frequency missense variant rs61751053 in ARHGEF38 with overall breast cancer (odds ratio (OR) = 1.48) and a common variant rs76664032 at chromosome 2q14.2 with triple-negative breast cancer (TNBC) (OR = 1.30). Approximately 15.4% of cases with TNBC carried six risk alleles in three genome-wide association study-identified TNBC risk variants, with an OR of 4.21 (95% confidence interval = 2.66-7.03) compared with those carrying fewer than two risk alleles. A polygenic risk score (PRS) showed an area under the receiver operating characteristic curve of 0.60 for the prediction of breast cancer risk, which outperformed PRS derived using data from females of European ancestry. Our study markedly increases the population diversity in genetic studies for breast cancer and demonstrates the utility of PRS for risk prediction in females of African ancestry.
Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease.
<h4>Background</h4>Prolactin, a hormone produced by the pituitary gland, regulates breast development and may contribute to breast cancer etiology. However, most epidemiologic studies of prolactin and breast cancer have been restricted to single, often small, study samples with limited exploration of effect modification.<h4>Methods</h4>The Biomarkers in Breast Cancer Risk Prediction consortium includes 8,279 postmenopausal women sampled from four prospective cohort studies, of whom 3,441 were diagnosed with invasive breast cancer after enrollment. Prolactin concentrations were measured for all study participants on plasma samples collected when all women were postmenopausal and before any breast cancer diagnosis using ELISA assays. Pooled, unconditional logistic regression models, adjusted for confounders, estimated odd ratios (OR) for associations of prolactin and postmenopausal breast cancer risk overall and stratified by breast cancer risk factors.<h4>Results</h4>Higher plasma prolactin concentrations were positively associated with postmenopausal breast cancer risk (> 13.2 ng/mL vs. < 7.9 ng/mL, OR: 1.20, 95% CI: 1.06, 1.36; P-trend < 0.001). Although associations did not appear to vary by time since blood draw or most breast cancer risk factors, associations were primarily observed in current users of postmenopausal hormones at blood draw (> 13.2 ng/mL vs. < 7.9 ng/mL, current users, OR: 1.58, 95% CI: 1.27, 1.96, P-trend < 0.001; non-current users, OR: 1.08, 95% CI: 0.93, 1.27, P-trend = 0.11; P-heterogeneity = 0.06).<h4>Conclusion</h4>Prolactin may be a risk factor for postmenopausal breast cancer, particularly in the context of postmenopausal hormone use. Investigations of prolactin interactions with other hormonal factors may further inform breast cancer etiology.
<h4>Background</h4>Expansion of genome-wide association studies across population groups is needed to improve our understanding of shared and unique genetic contributions to breast cancer. We performed association and replication studies guided by a priori linkage findings from African ancestry (AA) relative pairs.<h4>Methods</h4>We performed fixed-effect inverse-variance weighted meta-analysis under three significant AA breast cancer linkage peaks (3q26-27, 12q22-23, and 16q21-22) in 9241 AA cases and 10 193 AA controls. We examined associations with overall breast cancer as well as estrogen receptor (ER)-positive and negative subtypes (193,132 SNPs). We replicated associations in the African-ancestry Breast Cancer Genetic Consortium (AABCG).<h4>Results</h4>In AA women, we identified two associations on chr12q for overall breast cancer (rs1420647, OR = 1.15, p = 2.50×10-6; rs12322371, OR = 1.14, p = 3.15×10-6), and one for ER-negative breast cancer (rs77006600, OR = 1.67, p = 3.51×10-6). On chr3, we identified two associations with ER-negative disease (rs184090918, OR = 3.70, p = 1.23×10-5; rs76959804, OR = 3.57, p = 1.77×10-5) and on chr16q we identified an association with ER-negative disease (rs34147411, OR = 1.62, p = 8.82×10-6). In the replication study, the chr3 associations were significant and effect sizes were larger (rs184090918, OR: 6.66, 95% CI: 1.43, 31.01; rs76959804, OR: 5.24, 95% CI: 1.70, 16.16).<h4>Conclusion</h4>The two chr3 SNPs are upstream to open chromatin ENSR00000710716, a regulatory feature that is actively regulated in mammary tissues, providing evidence that variants in this chr3 region may have a regulatory role in our target organ. Our study provides support for breast cancer variant discovery using prioritization based on linkage evidence.
African-ancestry (AA) participants are underrepresented in genetics research. Here, we conducted a transcriptome-wide association study (TWAS) in AA female participants to identify putative breast cancer susceptibility genes. We built genetic models to predict levels of gene expression, exon junction, and 3' UTR alternative polyadenylation using genomic and transcriptomic data generated in normal breast tissues from 150 AA participants and then used these models to perform association analyses using genomic data from 18,034 cases and 22,104 controls. At Bonferroni-corrected P < 0.05, we identified six genes associated with breast cancer risk, including four genes not previously reported (CTD-3080P12.3, EN1, LINC01956 and NUP210L). Most of these genes showed a stronger association with risk of estrogen-receptor (ER) negative or triple-negative than ER-positive breast cancer. We also replicated the associations with 29 genes reported in previous TWAS at P < 0.05 (one-sided), providing further support for an association of these genes with breast cancer risk. Our study sheds new light on the genetic basis of breast cancer and highlights the value of conducting research in AA populations.
<h4>Purpose</h4>Most breast biopsies are diagnosed as benign breast disease (BBD), with 1.5- to fourfold increased breast cancer (BC) risk. Apart from pathologic diagnoses of atypical hyperplasia, few factors aid in BC risk assessment of these patients. We assessed whether a 313-SNP polygenic risk score (PRS) stratifies risk of BBD patients.<h4>Patients and methods</h4>We pooled data from five Breast Cancer Association Consortium case-control studies (mean age = 59.9 years), including 6,706 cases and 8,488 controls. Using logistic regression, we estimated BC risk associations by self-reported BBD history and strata of PRS, with median PRS category among women without BBD as the referent. We assessed interactions and mediation of BBD and PRS with BC risk.<h4>Results</h4>BBD history was associated with increased BC risk (OR = 1.48, 95% CI: 1.37-1.60; p < .001). PRS increased BC risk, irrespective of BBD history (p-interaction = 0.48), with minimal evidence of mediation of either factor by the other. Women with BBD and PRS in the highest tertile had over 2-fold increased odds of BC (OR = 2.73, 95% CI: 2.41-3.09) and those with BBD and PRS in the lowest tertile experienced reduced BC risk (OR = 0.79, 95% CI: 0.70-0.91), compared to the reference group. Women with BBD and PRS in the highest decile had a 3.7- fold increase (95% CI: 3.00-4.61) compared to those with median PRS without BBD.<h4>Conclusion</h4>BC risks are elevated among women with BBD and increase progressively with PRS, suggesting that optimal combinations of these factors may improve risk stratification.
Known risk loci for endometrial cancer explain approximately one third of familial endometrial cancer. However, the association of germline copy number variants (CNVs) with endometrial cancer risk remains relatively unknown. We conducted a genome-wide analysis of rare CNVs overlapping gene regions in 4115 endometrial cancer cases and 17,818 controls to identify functionally relevant variants associated with disease. We identified a 1.22-fold greater number of CNVs in DNA samples from cases compared to DNA samples from controls (p = 4.4 × 10<sup>-63</sup>). Under three models of putative CNV impact (deletion, duplication, and loss of function), genome-wide association studies identified 141 candidate gene loci associated (p < 0.01) with endometrial cancer risk. Pathway analysis of the candidate loci revealed an enrichment of genes involved in the 16p11.2 proximal deletion syndrome, driven by a large recurrent deletion (chr16:29,595,483-30,159,693) identified in 0.15% of endometrial cancer cases and 0.02% of control participants. Together, these data provide evidence that rare copy number variants have a role in endometrial cancer susceptibility and that the proximal 16p11.2 BP4-BP5 region contains 25 candidate risk gene(s) that warrant further analysis to better understand their role in human disease.
Breast cancer includes several subtypes with distinct characteristic biological, pathologic, and clinical features. Elucidating subtype-specific genetic etiology could provide insights into the heterogeneity of breast cancer to facilitate the development of improved prevention and treatment approaches. In this study, we conducted pairwise case-case comparisons among five breast cancer subtypes by applying a case-case genome-wide association study (CC-GWAS) approach to summary statistics data of the Breast Cancer Association Consortium. The approach identified 13 statistically significant loci and eight suggestive loci, the majority of which were identified from comparisons between triple-negative breast cancer (TNBC) and luminal A breast cancer. Associations of lead variants in 12 loci remained statistically significant after accounting for previously reported breast cancer susceptibility variants, among which, two were genome-wide significant. Fine mapping implicated putative functional/causal variants and risk genes at several loci, e.g., 3q26.31/TNFSF10, 8q22.3/NACAP1/GRHL2, and 8q23.3/LINC00536/TRPS1, for TNBC as compared with luminal cancer. Functional investigation further identified rs16867605 at 8q22.3 as a SNP that modulates the enhancer activity of GRHL2. Subtype-informative polygenic risk scores (PRS) were derived, and patients with a high subtype-informative PRS had an up to two-fold increased risk of being diagnosed with TNBC instead of luminal cancers. The CC-GWAS PRS remained statistically significant after adjusting for TNBC PRS derived from traditional case-control GWAS in The Cancer Genome Atlas and the African Ancestry Breast Cancer Genetic Consortium. The CC-GWAS PRS was also associated with overall survival and disease-specific survival among patients with breast cancer. Overall, these findings have advanced our understanding of the genetic etiology of breast cancer subtypes, particularly for TNBC. Significance: The discovery of subtype-informative genetic risk variants for breast cancer advances our understanding of the etiologic heterogeneity of breast cancer, which could accelerate the identification of targets and personalized strategies for prevention and treatment.
<h4>Background</h4>A high body mass index (BMI, kg/m<sup>2</sup>) is associated with decreased risk of breast cancer before menopause, but increased risk after menopause. Exactly when this reversal occurs in relation to menopause is unclear. Locating that change point could provide insight into the role of adiposity in breast cancer etiology.<h4>Methods</h4>We examined the association between BMI and breast cancer risk in the Premenopausal Breast Cancer Collaborative Group, from age 45 up to breast cancer diagnosis, loss to follow-up, death, or age 55, whichever came first. Analyses included 609,880 women in 16 prospective studies, including 9956 who developed breast cancer before age 55. We fitted three BMI hazard ratio (HR) models over age-time: constant, linear, or nonlinear (via splines), applying piecewise exponential additive mixed models, with age as the primary time scale. We divided person-time into four strata: premenopause; postmenopause due to natural menopause; postmenopause because of interventional loss of ovarian function (bilateral oophorectomy (BO) or chemotherapy); postmenopause due to hysterectomy without BO. Sensitivity analyses included stratifying by BMI in young adulthood, or excluding women using menopausal hormone therapy.<h4>Results</h4>The constant BMI HR model provided the best fit for all four menopausal status groups. Under this model, the estimated association between a five-unit increment in BMI and breast cancer risk was HR=0.87 (95% CI: 0.85, 0.89) before menopause, HR=1.00 (95% CI: 0.96, 1.04) after natural menopause, HR=0.99 (95% CI: 0.93, 1.05) after interventional loss of ovarian function, and HR=0.88 (95% CI: 0.76, 1.02) after hysterectomy without BO.<h4>Conclusion</h4>The BMI breast cancer HRs remained less than or near one during the 45-55 year age range indicating that the transition to a positive association between BMI and risk occurs after age 55.
Normal tissues adjacent to the tumor (NATs) may harbor early breast carcinogenesis events driven by field cancerization. Although previous studies have characterized copy-number (CN) and transcriptomic alterations, the evolutionary history of NATs in breast cancer (BC) remains poorly characterized. Utilizing whole-genome sequencing (WGS), methylation profiling, and RNA sequencing (RNA-seq), we analyzed paired germline, NATs, and tumor samples from 43 individuals with BC in Hong Kong (HK). We found that single-nucleotide variants (SNVs) were common in NATs, with one-third of NAT samples exhibiting SNVs in driver genes, many of which were present in paired tumor samples. The most frequently mutated genes in both tumor and NAT samples were PIK3CA, TP53, GATA3, and AKT1. In contrast, large-scale aberrations such as somatic CN alterations (SCNAs) and structural variants (SVs) were rarely detected in NAT samples. We generated phylogenetic trees to investigate the evolutionary history of paired NAT and tumor samples. They could be categorized into tumor only, shared, and multiple-tree groups, the last of which is concordant with non-genetic field cancerization. These groups exhibited distinct genomic and epigenomic characteristics in both NAT and tumor samples. Specifically, NAT samples in the shared-tree group showed higher number of mutations, while NAT samples belonging to the multiple-tree group showed a less inflammatory tumor microenvironment (TME), characterized by a higher proportion of regulatory T cells (Tregs) and lower presence of CD14 cell populations. In summary, our findings highlight the diverse evolutionary history in BC NAT/tumor pairs and the impact of field cancerization and TME in shaping the genomic evolutionary history of tumors.
<b>Motivation:</b> Epidemiological studies face two important challenges: the need to ingest ever more complex data types, and mounting concerns about participant privacy and data governance. These two challenges are compounded by the expectation that data infrastructure will eventually need to facilitate cross-registration of participants by multiple epidemiological studies. <b>Implementation:</b> The portable web-service epiDonate was developed using the serverless model known as FaaS (Function-as-a-Service). The reference implementation uses nodejs. The implementation relies on a simple tokenization scheme, mediated by a public API, that a) distinguishes admin from participant roles, with b) extensible permission configuration operating a read/write structure. <b>General Features:</b> The critical design feature of epiDonate is the absence of business logic on the server-side (the web service). The simplicity removes the need to customize virtual machines and enables ecosystems of multiple web Applications backed by one or more data donation deployments. <b>Availability:</b> https://episphere.github.io/donate.
Evidence from literature, including the BRIDGES study, indicates that germline protein truncating variants (PTVs) in FANCM confer moderately increased risk of ER-negative and triple-negative breast cancer (TNBC), especially for women with a family history of the disease. Association between FANCM missense variants (MVs) and breast cancer risk has been postulated. In this study, we further used the BRIDGES study to test 689 FANCM MVs for association with breast cancer risk, overall and in ER-negative and TNBC subtypes, in 39,885 cases (7566 selected for family history) and 35,271 controls of European ancestry. Sixteen common MVs were tested individually; the remaining rare 673 MVs were tested by burden analyses considering their position and pathogenicity score. We also conducted a meta-analysis of our results and those from published studies. We did not find evidence for association for any of the 16 variants individually tested. The rare MVs were significantly associated with increased risk of ER-negative breast cancer by burden analysis comparing familial cases to controls (OR = 1.48; 95% CI 1.07-2.04; P = 0.017). Higher ORs were found for the subgroup of MVs located in functional domains or predicted to be pathogenic. The meta-analysis indicated that FANCM MVs overall are associated with breast cancer risk (OR = 1.22; 95% CI 1.08-1.38; P = 0.002). Our results support the definition from previous analyses of FANCM as a moderate-risk breast cancer gene and provide evidence that FANCM MVs could be low/moderate risk factors for ER-negative and TNBC subtypes. Further genetic and functional analyses are necessary to clarify better the increased risks due to FANCM MVs.
<i>FANCM</i> germline protein truncating variants (PTVs) are moderate-risk factors for ER-negative breast cancer. We previously described the spectrum of <i>FANCM</i> PTVs in 114 European breast cancer cases. In the present, larger cohort, we report the spectrum and frequency of four common and 62 rare <i>FANCM</i> PTVs found in 274 carriers detected among 44,803 breast cancer cases. We confirmed that p.Gln1701* was the most common PTV in Northern Europe with lower frequencies in Southern Europe. In contrast, p.Gly1906Alafs*12 was the most common PTV in Southern Europe with decreasing frequencies in Central and Northern Europe. We verified that p.Arg658* was prevalent in Central Europe and had highest frequencies in Eastern Europe. We also confirmed that the fourth most common PTV, p.Gln498Thrfs*7, might be a founder variant from Lithuania. Based on the frequency distribution of the carriers of rare PTVs, we showed that the <i>FANCM</i> PTVs spectra in Southwestern and Central Europe were much more heterogeneous than those from Northeastern Europe. These findings will inform the development of more efficient <i>FANCM</i> genetic testing strategies for breast cancer cases from specific European populations.
Data sharing is essential for reproducibility of epidemiologic research, replication of findings, pooled analyses in consortia efforts, and maximizing study value to address multiple research questions. However, barriers related to confidentiality, costs, and incentives often limit the extent and speed of data sharing. Epidemiological practices that follow Findable, Accessible, Interoperable, Reusable (FAIR) principles can address these barriers by making data resources findable with the necessary metadata, accessible to authorized users, and interoperable with other data, to optimize the reuse of resources with appropriate credit to its creators. We provide an overview of these principles and describe approaches for implementation in epidemiology. Increasing degrees of FAIRness can be achieved by moving data and code from on-site locations to remote, accessible ("Cloud") data servers, using machine-readable and nonproprietary files, and developing open-source code. Adoption of these practices will improve daily work and collaborative analyses and facilitate compliance with data sharing policies from funders and scientific journals. Achieving a high degree of FAIRness will require funding, training, organizational support, recognition, and incentives for sharing research resources, both data and code. However, these costs are outweighed by the benefits of making research more reproducible, impactful, and equitable by facilitating the reuse of precious research resources by the scientific community.
<h4>Background</h4>Hair relaxers and skin lighteners have been commonly used by African women, with suggestions that they may have hormonal activity.<h4>Objectives</h4>To investigate the relationship of hair relaxer and skin lightener use to serum estrogen/estrogen metabolite levels.<h4>Methods</h4>We utilized the postmenopausal population-based controls of the Ghana Breast Health Study to estimate adjusted geometric means (GM) and 95% confidence intervals of individual circulating estrogen levels by hair relaxer/skin lightener exposure categories.<h4>Results</h4>Of the 585 postmenopausal women included in our analysis, 80.2% reported hair relaxer use and 29.4% skin lightener use. Ever hair relaxer use was positively associated with estriol (adjusted GM 95.4 pmol/L vs. never 74.5, p value = 0.02) and 16-epiestriol (20.4 vs. 16.8, p value = 0.05) particularly among users of lye-based hair relaxers. Positive associations between scalp burns and unconjugated estrogens were observed (e.g., unconjugated estrone: 5+ scalp burns 76.9 [59.6-99.2] vs. no burns 64.0 [53.7-76.3], p-trend = 0.03). No association was observed between use of skin lighteners and circulating estrogens.<h4>Significance</h4>This study presents evidence that circulating 16-pathway estrogens (i.e., estriol and 16-epiestriol) may be increased in users of lye-based hair relaxer products. Among hair relaxer users, unconjugated estrogen levels were elevated in women with a greater number of scalp burns.<h4>Impact statement</h4>In this population-based study of hair relaxer and skin lightener use among postmenopausal women in Ghana, altered estrogen metabolism was observed with hair relaxer use, particularly among women using lye-based products or with a greater number of scalp burns. In contrast, skin lightener use was not associated with differences in estrogen metabolism in this population. Continued investigation of the potential biological impact on breast cancer risk of hair relaxer use is warranted.
<h4>Background</h4>Adult obesity is a strong risk factor for endometrial cancer (EC); however, associations of early life obesity with EC are inconclusive. We evaluated associations of young adulthood (18-21 years) and adulthood (at enrolment) body mass index (BMI) and weight change with EC risk in the Epidemiology of Endometrial Cancer Consortium (E2C2).<h4>Methods</h4>We pooled data from nine case-control and 11 cohort studies in E2C2. We performed multivariable logistic regression analyses to estimate odds ratios (OR) and 95% confidence intervals (95% CI) for BMI (kg/m2) in young adulthood and adulthood, with adjustment for BMI in adulthood and young adulthood, respectively. We evaluated categorical changes in weight (5-kg increments) and BMI from young adulthood to adulthood, and stratified analyses by histology, menopausal status, race and ethnicity, hormone replacement therapy (HRT) use and diabetes.<h4>Results</h4>We included 14 859 cases and 40 859 controls. Obesity in adulthood (OR = 2.85, 95% CI = 2.47-3.29) and young adulthood (OR = 1.26, 95% CI = 1.06-1.50) were positively associated with EC risk. Weight gain and BMI gain were positively associated with EC; weight loss was inversely associated with EC. Young adulthood obesity was more strongly associated with EC among cases diagnosed with endometrioid histology, those who were pre/perimenopausal, non-Hispanic White and non-Hispanic Black, among never HRT users and non-diabetics.<h4>Conclusions</h4>Young adulthood obesity is associated with EC risk, even after accounting for BMI in adulthood. Weight gain is also associated with EC risk, whereas weight loss is inversely associated. Achieving and maintaining a healthy weight over the life course is important for EC prevention efforts.
Disease heterogeneity is ubiquitous in biomedical and clinical studies. In genetic studies, researchers are increasingly interested in understanding the distinct genetic underpinning of subtypes of diseases. However, existing set-based analysis methods for genome-wide association studies are either inadequate or inefficient to handle such multicategorical outcomes. In this paper, we proposed a novel set-based association analysis method, sequence kernel association test (SKAT)-MC, the sequence kernel association test for multicategorical outcomes (nominal or ordinal), which jointly evaluates the relationship between a set of variants (common and rare) and disease subtypes. Through comprehensive simulation studies, we showed that SKAT-MC effectively preserves the nominal type I error rate while substantially increases the statistical power compared to existing methods under various scenarios. We applied SKAT-MC to the Polish breast cancer study (PBCS), and identified gene FGFR2 was significantly associated with estrogen receptor (ER)+ and ER- breast cancer subtypes. We also investigated educational attainment using UK Biobank data ( N = 127 , 127 $N=127,127$ ) with SKAT-MC, and identified 21 significant genes in the genome. Consequently, SKAT-MC is a powerful and efficient analysis tool for genetic association studies with multicategorical outcomes. A freely distributed R package SKAT-MC can be accessed at https://github.com/Zhiwen-Owen-Jiang/SKATMC.
<h4>Background</h4>The rule of thumb that there is little gain in statistical power by obtaining more than 4 controls per case, is based on type-1 error α = 0.05. However, association studies that evaluate thousands or millions of associations use smaller α and may have access to plentiful controls. We investigate power gains, and reductions in p-values, when increasing well beyond 4 controls per case, for small α.<h4>Methods</h4>We calculate the power, the median expected p-value, and the minimum detectable odds-ratio (OR), as a function of the number of controls/case, as α decreases.<h4>Results</h4>As α decreases, at each ratio of controls per case, the increase in power is larger than for α = 0.05. For α between 10<sup>-6</sup> and 10<sup>-9</sup> (typical for thousands or millions of associations), increasing from 4 controls per case to 10-50 controls per case increases power. For example, a study with power = 0.2 (α = 5 × 10<sup>-8</sup>) with 1 control/case has power = 0.65 with 4 controls/case, but with 10 controls/case has power = 0.78, and with 50 controls/case has power = 0.84. For situations where obtaining more than 4 controls per case provides small increases in power beyond 0.9 (at small α), the expected p-value can decrease by orders-of-magnitude below α. Increasing from 1 to 4 controls/case reduces the minimum detectable OR toward the null by 20.9%, and from 4 to 50 controls/case reduces by an additional 9.7%, a result which applies regardless of α and hence also applies to "regular" α = 0.05 epidemiology.<h4>Conclusions</h4>At small α, versus 4 controls/case, recruiting 10 or more controls/cases can increase power, reduce the expected p-value by 1-2 orders of magnitude, and meaningfully reduce the minimum detectable OR. These benefits of increasing the controls/case ratio increase as the number of cases increases, although the amount of benefit depends on exposure frequencies and true OR. Provided that controls are comparable to cases, our findings suggest greater sharing of comparable controls in large-scale association studies.
Our proof-of-concept study reveals the potential of risk stratification by the combined effects of age, polygenic risk scores (PRS), and non-genetic risk factors in increasing the risk-benefit balance of rapidly emerging non-invasive multicancer early detection (MCED) liquid biopsy tests. We develop and validate sex-specific pan-cancer risk scores (PCRSs), defined by the combination of body mass index, smoking, family history of cancers, and cancer-specific polygenic risk scores (PRSs), to predict the absolute risk of developing at least one of the many common cancer types. We demonstrate the added value of PRSs in improving the predictive performance of the risk factors only model and project the positive and negative predictive values for two promising multicancer screening tests across risk strata defined by age and PCRS.
<h4>Background</h4>Few studies have examined epigenetic age acceleration (AA), the difference between DNA methylation (DNAm) predicted age and chronological age, in relation to somatic genomic features in paired cancer and normal tissue, with less work done in non-European populations. In this study, we aimed to examine DNAm age and its associations with breast cancer risk factors, subtypes, somatic genomic profiles including mutation and copy number alterations and other aging markers in breast tissue of Chinese breast cancer (BC) patients from Hong Kong.<h4>Methods</h4>We performed genome-wide DNA methylation profiling of 196 tumor and 188 paired adjacent normal tissue collected from Chinese BC patients in Hong Kong (HKBC) using Illumina MethylationEPIC array. The DNAm age was calculated using Horvath's pan-tissue clock model. Somatic genomic features were based on data from RNA sequencing (RNASeq), whole-exome sequencing (WES), and whole-genome sequencing (WGS). Pearson's correlation (r), Kruskal-Wallis test, and regression models were used to estimate associations of DNAm AA with somatic features and breast cancer risk factors.<h4>Results</h4>DNAm age showed a stronger correlation with chronological age in normal (Pearson r = 0.78, P < 2.2e-16) than in tumor tissue (Pearson r = 0.31, P = 7.8e-06). Although overall DNAm age or AA did not vary significantly by tissue within the same individual, luminal A tumors exhibited increased DNAm AA (P = 0.004) while HER2-enriched/basal-like tumors exhibited markedly lower DNAm AA (P = < .0001) compared with paired normal tissue. Consistent with the subtype association, tumor DNAm AA was positively correlated with ESR1 (Pearson r = 0.39, P = 6.3e-06) and PGR (Pearson r = 0.36, P = 2.4e-05) gene expression. In line with this, we found that increasing DNAm AA was associated with higher body mass index (P = 0.039) and earlier age at menarche (P = 0.035), factors that are related to cumulative exposure to estrogen. In contrast, variables indicating extensive genomic instability, such as TP53 somatic mutations, high tumor mutation/copy number alteration burden, and homologous repair deficiency were associated with lower DNAm AA.<h4>Conclusions</h4>Our findings provide additional insights into the complexity of breast tissue aging that is associated with the interaction of hormonal, genomic, and epigenetic mechanisms in an East Asian population.
<h4>Background</h4>Genomic regions identified by genome-wide association studies (GWAS) for bladder cancer risk provide new insights into etiology.<h4>Objective</h4>To identify new susceptibility variants for bladder cancer in a meta-analysis of new and existing genome-wide genotype data.<h4>Design, setting, and participants</h4>Data from 32 studies that includes 13,790 bladder cancer cases and 343,502 controls of European ancestry were used for meta-analysis.<h4>Outcome measurements and statistical analyses</h4>Log-additive associations of genetic variants were assessed using logistic regression models. A fixed-effects model was used for meta-analysis of the results. Stratified analyses were conducted to evaluate effect modification by sex and smoking status. A polygenic risk score (PRS) was generated on the basis of known and novel susceptibility variants and tested for interaction with smoking.<h4>Results and limitations</h4>Multiple novel bladder cancer susceptibility loci (6p.22.3, 7q36.3, 8q21.13, 9p21.3, 10q22.1, 19q13.33) as well as improved signals in three known regions (4p16.3, 5p15.33, 11p15.5) were identified, bringing the number of independent markers at genome-wide significance (p < 5 × 10<sup>-8</sup>) to 24. The 4p16.3 (FGFR3/TACC3) locus was associated with a stronger risk for women than for men (p-interaction = 0.002). Bladder cancer risk was increased by interactions between smoking status and genetic variants at 8p22 (NAT2; multiplicative p value for interaction [p<sub>M-I</sub>] = 0.004), 8q21.13 (PAG1; p<sub>M-I</sub> = 0.01), and 9p21.3 (LOC107987026/MTAP/CDKN2A; p<sub>M-I</sub> = 0.02). The PRS based on the 24 independent GWAS markers (odds ratio per standard deviation increase 1.49, 95% confidence interval 1.44-1.53), which also showed comparable results in two prospective cohorts (UK Biobank, PLCO trial), revealed an approximately fourfold difference in the lifetime risk of bladder cancer according to the PRS (e.g., 1st vs 10th decile) for both smokers and nonsmokers.<h4>Conclusions</h4>We report novel loci associated with risk of bladder cancer that provide clues to its biological underpinnings. Using 24 independent markers, we constructed a PRS to stratify lifetime risk. The PRS combined with smoking history, and other established risk factors, has the potential to inform future screening efforts for bladder cancer.<h4>Patient summary</h4>We identified new genetic markers that provide biological insights into the genetic causes of bladder cancer. These genetic risk factors combined with lifestyle risk factors, such as smoking, may inform future preventive and screening strategies for bladder cancer.
<h4>Background</h4>Polygenic risk score (PRS), calculated based on genome-wide association studies (GWASs), can improve breast cancer (BC) risk assessment. To date, most BC GWASs have been performed in individuals of European (EUR) ancestry, and the generalisation of EUR-based PRS to other populations is a major challenge. In this study, we examined the performance of EUR-based BC PRS models in Ashkenazi Jewish (AJ) women.<h4>Methods</h4>We generated PRSs based on data on EUR women from the Breast Cancer Association Consortium (BCAC). We tested the performance of the PRSs in a cohort of 2161 AJ women from Israel (1437 cases and 724 controls) from BCAC (BCAC cohort from Israel (BCAC-IL)). In addition, we tested the performance of these EUR-based BC PRSs, as well as the established 313-SNP EUR BC PRS, in an independent cohort of 181 AJ women from Hadassah Medical Center (HMC) in Israel.<h4>Results</h4>In the BCAC-IL cohort, the highest OR per 1 SD was 1.56 (±0.09). The OR for AJ women at the top 10% of the PRS distribution compared with the middle quintile was 2.10 (±0.24). In the HMC cohort, the OR per 1 SD of the EUR-based PRS that performed best in the BCAC-IL cohort was 1.58±0.27. The OR per 1 SD of the commonly used 313-SNP BC PRS was 1.64 (±0.28).<h4>Conclusions</h4>Extant EUR GWAS data can be used for generating PRSs that identify AJ women with markedly elevated risk of BC and therefore hold promise for improving BC risk assessment in AJ women.
<h4>Purpose</h4>A polygenic risk score (PRS) consisting of 313 common genetic variants (PRS<sub>313</sub>) is associated with risk of breast cancer and contralateral breast cancer. This study aimed to evaluate the association of the PRS<sub>313</sub> with clinicopathologic characteristics of, and survival following, breast cancer.<h4>Methods</h4>Women with invasive breast cancer were included, 98,397 of European ancestry and 12,920 of Asian ancestry, from the Breast Cancer Association Consortium (BCAC), and 683 women from the European MINDACT trial. Associations between PRS<sub>313</sub> and clinicopathologic characteristics, including the 70-gene signature for MINDACT, were evaluated using logistic regression analyses. Associations of PRS<sub>313</sub> (continuous, per standard deviation) with overall survival (OS) and breast cancer-specific survival (BCSS) were evaluated with Cox regression, adjusted for clinicopathologic characteristics and treatment.<h4>Results</h4>The PRS<sub>313</sub> was associated with more favorable tumor characteristics. In BCAC, increasing PRS<sub>313</sub> was associated with lower grade, hormone receptor-positive status, and smaller tumor size. In MINDACT, PRS<sub>313</sub> was associated with a low risk 70-gene signature. In European women from BCAC, higher PRS<sub>313</sub> was associated with better OS and BCSS: hazard ratio (HR) 0.96 (95% CI, 0.94 to 0.97) and 0.96 (95% CI, 0.94 to 0.98), but the association disappeared after adjustment for clinicopathologic characteristics (and treatment): OS HR, 1.01 (95% CI, 0.98 to 1.05) and BCSS HR, 1.02 (95% CI, 0.98 to 1.07). The results in MINDACT and Asian women from BCAC were consistent.<h4>Conclusion</h4>An increased PRS<sub>313</sub> is associated with favorable tumor characteristics, but is not independently associated with prognosis. Thus, PRS<sub>313</sub> has no role in the clinical management of primary breast cancer at the time of diagnosis. Nevertheless, breast cancer mortality rates will be higher for women with higher PRS<sub>313</sub> as increasing PRS<sub>313</sub> is associated with an increased risk of disease. This information is crucial for modeling effective stratified screening programs.
The Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial is a prospective cohort study of nearly 155,000 U.S. volunteers aged 55-74 at enrollment in 1993-2001. We developed the PLCO Atlas Project, a large resource for multi-trait genome-wide association studies (GWAS), by genotyping participants with available DNA and genomic consent. Genotyping on high-density arrays and imputation was performed, and GWAS were conducted using a custom semi-automated pipeline. Association summary statistics were generated from a total of 110,562 participants of European, African and Asian ancestry. Application programming interfaces (APIs) and open-source software development kits (SKDs) enable exploring, visualizing and open data access through the PLCO Atlas GWAS Explorer website, promoting Findable, Accessible, Interoperable, and Re-usable (FAIR) principles. Currently the GWAS Explorer hosts association data for 90 traits and >78,000,000 genomic markers, focusing on cancer and cancer-related phenotypes. New traits will be posted as association data becomes available. The PLCO Atlas is a FAIR resource of high-quality genetic and phenotypic data with many potential reuse opportunities for cancer research and genetic epidemiology.
Forecasting methods are notoriously difficult to interpret, particularly when the relationship between the data and the resulting forecasts is not obvious. Interpretability is an important property of a forecasting method because it allows the user to complement the forecasts with their own knowledge, a process which leads to more applicable results. In general, mechanistic methods are more interpretable than non-mechanistic methods, but they require explicit knowledge of the underlying dynamics. In this paper, we introduce EpiForecast, a tool which performs interpretable, non-mechanistic forecasts using interactive visualization and a simple, data-focused forecasting technique based on empirical dynamic modelling. EpiForecast's primary feature is a four-plot interactive dashboard which displays a variety of information to help the user understand how the forecasts are generated. In addition to point forecasts, the tool produces distributional forecasts using a kernel density estimation method-these are visualized using color gradients to produce a quick, intuitive visual summary of the estimated future. To ensure the work is FAIR and privacy is ensured, we have released the tool as an entirely in-browser web-application.
<h4>Background</h4>Genome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.<h4>Methods</h4>Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.<h4>Results</h4>Assuming a 1 × 10<sup>-5</sup> prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (OR<sub>int</sub> = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (OR<sub>int</sub> = 0.91, 95% CI 0.88-0.94).<h4>Conclusions</h4>Overall, the contribution of G×E interactions to the heritability of breast cancer is very small. At the population level, multiplicative G×E interactions do not make an important contribution to risk prediction in breast cancer.
Evidence linking coding germline variants in breast cancer (BC)-susceptibility genes other than BRCA1, BRCA2, and CHEK2 with contralateral breast cancer (CBC) risk and breast cancer-specific survival (BCSS) is scarce. The aim of this study was to assess the association of protein-truncating variants (PTVs) and rare missense variants (MSVs) in nine known (ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53) and 25 suspected BC-susceptibility genes with CBC risk and BCSS. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated with Cox regression models. Analyses included 34,401 women of European ancestry diagnosed with BC, including 676 CBCs and 3,449 BC deaths; the median follow-up was 10.9 years. Subtype analyses were based on estrogen receptor (ER) status of the first BC. Combined PTVs and pathogenic/likely pathogenic MSVs in BRCA1, BRCA2, and TP53 and PTVs in CHEK2 and PALB2 were associated with increased CBC risk [HRs (95% CIs): 2.88 (1.70-4.87), 2.31 (1.39-3.85), 8.29 (2.53-27.21), 2.25 (1.55-3.27), and 2.67 (1.33-5.35), respectively]. The strongest evidence of association with BCSS was for PTVs and pathogenic/likely pathogenic MSVs in BRCA2 (ER-positive BC) and TP53 and PTVs in CHEK2 [HRs (95% CIs): 1.53 (1.13-2.07), 2.08 (0.95-4.57), and 1.39 (1.13-1.72), respectively, after adjusting for tumor characteristics and treatment]. HRs were essentially unchanged when censoring for CBC, suggesting that these associations are not completely explained by increased CBC risk, tumor characteristics, or treatment. There was limited evidence of associations of PTVs and/or rare MSVs with CBC risk or BCSS for the 25 suspected BC genes. The CBC findings are relevant to treatment decisions, follow-up, and screening after BC diagnosis.
<h4>Background</h4>Breast cancer (BC) patients with a germline CHEK2 c.1100delC variant have an increased risk of contralateral BC (CBC) and worse BC-specific survival (BCSS) compared to non-carriers.<h4>Aim</h4>To assessed the associations of CHEK2 c.1100delC, radiotherapy, and systemic treatment with CBC risk and BCSS.<h4>Methods</h4>Analyses were based on 82,701 women diagnosed with a first primary invasive BC including 963 CHEK2 c.1100delC carriers; median follow-up was 9.1 years. Differential associations with treatment by CHEK2 c.1100delC status were tested by including interaction terms in a multivariable Cox regression model. A multi-state model was used for further insight into the relation between CHEK2 c.1100delC status, treatment, CBC risk and death.<h4>Results</h4>There was no evidence for differential associations of therapy with CBC risk by CHEK2 c.1100delC status. The strongest association with reduced CBC risk was observed for the combination of chemotherapy and endocrine therapy [HR (95% CI): 0.66 (0.55-0.78)]. No association was observed with radiotherapy. Results from the multi-state model showed shorter BCSS for CHEK2 c.1100delC carriers versus non-carriers also after accounting for CBC occurrence [HR (95% CI): 1.30 (1.09-1.56)].<h4>Conclusion</h4>Systemic therapy was associated with reduced CBC risk irrespective of CHEK2 c.1100delC status. Moreover, CHEK2 c.1100delC carriers had shorter BCSS, which appears not to be fully explained by their CBC risk.
<h4>Background</h4>Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes.<h4>Methods</h4>We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry.<h4>Results</h4>In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 × 10<sup>-6</sup>) and AC058822.1 (P = 1.47 × 10<sup>-4</sup>), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C.<h4>Conclusions</h4>Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 × 10<sup>-5</sup>), demonstrating the importance of diversifying study cohorts.
We assessed the PREDICT v 2.2 for prognosis of breast cancer patients with pathogenic germline BRCA1 and BRCA2 variants, using follow-up data from 5453 BRCA1/2 carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC). PREDICT for estrogen receptor (ER)-negative breast cancer had modest discrimination for BRCA1 carrier patients overall (Gönen & Heller unbiased concordance 0.65 in CIMBA, 0.64 in BCAC), but it distinguished clearly the high-mortality group from lower risk categories. In an analysis of low to high risk categories by PREDICT score percentiles, the observed mortality was consistently lower than the expected mortality, but the confidence intervals always included the calibration slope. Altogether, our results encourage the use of the PREDICT ER-negative model in management of breast cancer patients with germline BRCA1 variants. For the PREDICT ER-positive model, the discrimination was slightly lower in BRCA2 variant carriers (concordance 0.60 in CIMBA, 0.65 in BCAC). Especially, inclusion of the tumor grade distorted the prognostic estimates. The breast cancer mortality of BRCA2 carriers was underestimated at the low end of the PREDICT score distribution, whereas at the high end, the mortality was overestimated. These data suggest that BRCA2 status should also be taken into consideration with tumor characteristics, when estimating the prognosis of ER-positive breast cancer patients.
Epidemiologic data on insecticide exposures and breast cancer risk are inconclusive and mostly from high-income countries. Using data from 1071 invasive pathologically confirmed breast cancer cases and 2096 controls from the Ghana Breast Health Study conducted from 2013 to 2015, we investigated associations with mosquito control products to reduce the spread of mosquito-borne diseases, such as malaria. These mosquito control products were insecticide-treated nets, mosquito coils, repellent room sprays, and skin creams for personal protection against mosquitos. Multivariable and polytomous logistic regression models were used to estimate odds ratios (OR<sub>adj</sub>) and 95% confidence intervals (CI) with breast cancer risk-adjusted for potential confounders and known risk factors. Among controls, the reported use of mosquito control products were mosquito coils (65%), followed by insecticide-treated nets (56%), repellent room sprays (53%), and repellent skin creams (15%). Compared to a referent group of participants unexposed to mosquito control products, there was no significant association between breast cancer risk and mosquito coils. There was an association in breast cancer risk with reported use of insecticide-treated nets; however, that association was weak and not statistically significant. Participants who reported using repellent sprays were at elevated risks compared to women who did not use any mosquito control products, even after adjustment for all other mosquito control products (OR = 1.42, 95% CI=1.15-1.75). We had limited power to detect an association with repellent skin creams. Although only a few participants reported using repellent room sprays weekly/daily or < month-monthly, no trends were evident with increased frequency of use of repellent sprays, and there was no statistical evidence of heterogeneity by estrogen receptor (ER) status (p-het > 0.25). Our analysis was limited when determining if an association existed with repellent skin creams; therefore, we cannot conclude an association. We found limited evidence of risk associations with widely used mosquito coils and insecticide-treated nets, which are reassuring given their importance for malaria prevention. Our findings regarding specific breast cancer risk associations, specifically those observed between repellent sprays, require further study.
FGFR3 and PIK3CA are among the most frequently mutated genes in bladder tumors. We hypothesized that recurrent mutations in these genes might be caused by common carcinogenic exposures such as smoking and other factors. We analyzed 2,816 bladder tumors with available data on FGFR3 and/or PIK3CA mutations, focusing on the most recurrent mutations detected in ≥10% of tumors. Compared to tumors with other FGFR3/PIK3CA mutations, FGFR3-Y375C was more common in tumors from smokers than never-smokers (P = 0.009), while several APOBEC-type driver mutations were enriched in never-smokers: FGFR3-S249C (P = 0.013) and PIK3CA-E542K/PIK3CA-E545K (P = 0.009). To explore possible causes of these APOBEC-type mutations, we analyzed RNA sequencing (RNA-seq) data from 798 bladder tumors and detected several viruses, with BK polyomavirus (BKPyV) being the most common. We then performed IHC staining for polyomavirus (PyV) Large T-antigen (LTAg) in an independent set of 211 bladder tumors. Overall, by RNA-seq or IHC-LTAg, we detected PyV in 26 out of 1,010 bladder tumors with significantly higher detection (P = 4.4 × 10-5), 25 of 554 (4.5%) in non-muscle-invasive bladder cancers (NMIBC) versus 1 of 456 (0.2%) of muscle-invasive bladder cancers (MIBC). In the NMIBC subset, the FGFR3/PIK3CA APOBEC-type driver mutations were detected in 94.7% (18/19) of PyV-positive versus 68.3% (259/379) of PyV-negative tumors (P = 0.011). BKPyV tumor positivity in the NMIBC subset with FGFR3- or PIK3CA-mutated tumors was also associated with a higher risk of progression to MIBC (P = 0.019). In conclusion, our results support smoking and BKPyV infection as risk factors contributing to bladder tumorigenesis in the general patient population through distinct molecular mechanisms.<h4>Prevention relevance</h4>Tobacco smoking likely causes one of the most common mutations in bladder tumors (FGFR3-Y375C), while viral infections might contribute to three others (FGFR3-S249C, PIK3CA-E542K, and PIK3CA-E545K). Understanding the causes of these mutations may lead to new prevention and treatment strategies, such as viral screening and vaccination.
<h4>Background</h4>Online questionnaires are commonly used to collect information from participants in epidemiological studies. This requires building questionnaires using machine-readable formats that can be delivered to study participants using web-based technologies such as progressive web applications. However, the paucity of open-source markup standards with support for complex logic make collaborative development of web-based questionnaire modules difficult. This often prevents interoperability and reusability of questionnaire modules across epidemiological studies.<h4>Results</h4>We developed an open-source markup language for presentation of questionnaire content and logic, Quest, within a real-time renderer that enables the user to test logic (e.g., skip patterns) and view the structure of data collection. We provide the Quest markup language, an in-browser markup rendering tool, questionnaire development tool and an example web application that embeds the renderer, developed for The Connect for Cancer Prevention Study.<h4>Conclusion</h4>A markup language can specify both the content and logic of a questionnaire as plain text. Questionnaire markup, such as Quest, can become a standard format for storing questionnaires or sharing questionnaires across the web. Quest is a step towards generation of FAIR data in epidemiological studies by facilitating reusability of questionnaires and data interoperability using open-source tools.
<h4>Motivation</h4>Currently, the Polygenic Score (PGS) Catalog curates over 400 publications on over 500 traits corresponding to over 3000 polygenic risk scores (PRSs). To assess the feasibility of privately calculating the underlying multivariate relative risk for individuals with consumer genomics data, we developed an in-browserPRS calculator for genomic data that does not circulate any data or engage in any computation outside of the user's personal device.<h4>Results</h4>A prototype personal risk score calculator, created for research purposes, was developed to demonstrate how the PGS Catalog can be privately and readily applied to readily available direct-to-consumer genetic testing services, such as 23andMe. No software download, installation, or configuration is needed. The PRS web calculator matches individual PGS catalog entries with an individual's 23andMe genome data composed of 600k to 1.4 M single-nucleotide polymorphisms (SNPs). Beta coefficients provide researchers with a convenient assessment of risk associated with matched SNPs. This in-browser application was tested in a variety of personal devices, including smartphones, establishing the feasibility of privately calculating personal risk scores with up to a few thousand reference genetic variations and from the full 23andMe SNP data file (compressed or not).<h4>Availability and implementation</h4>The PRScalc web application is developed in JavaScript, HTML, and CSS and is available at GitHub repository (https://episphere.github.io/prs) under an MIT license. The datasets were derived from sources in the public domain: [PGS Catalog, Personal Genome Project].
<h4>Background</h4>Endometrial cancer risk stratification may help target interventions, screening, or prophylactic hysterectomy to mitigate the rising burden of this cancer. However, existing prediction models have been developed in select cohorts and have not considered genetic factors.<h4>Methods</h4>We developed endometrial cancer risk prediction models using data on postmenopausal White women aged 45-85 years from 19 case-control studies in the Epidemiology of Endometrial Cancer Consortium (E2C2). Relative risk estimates for predictors were combined with age-specific endometrial cancer incidence rates and estimates for the underlying risk factor distribution. We externally validated the models in 3 cohorts: Nurses' Health Study (NHS), NHS II, and the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial.<h4>Results</h4>Area under the receiver operating characteristic curves for the epidemiologic model ranged from 0.64 (95% confidence interval [CI] = 0.62 to 0.67) to 0.69 (95% CI = 0.66 to 0.72). Improvements in discrimination from the addition of genetic factors were modest (no change in area under the receiver operating characteristic curves in NHS; PLCO = 0.64 to 0.66). The epidemiologic model was well calibrated in NHS II (overall expected-to-observed ratio [E/O] = 1.09, 95% CI = 0.98 to 1.22) and PLCO (overall E/O = 1.04, 95% CI = 0.95 to 1.13) but poorly calibrated in NHS (overall E/O = 0.55, 95% CI = 0.51 to 0.59).<h4>Conclusions</h4>Using data from the largest, most heterogeneous study population to date (to our knowledge), prediction models based on epidemiologic factors alone successfully identified women at high risk of endometrial cancer. Genetic factors offered limited improvements in discrimination. Further work is needed to refine this tool for clinical or public health practice and expand these models to multiethnic populations.
Light-at-night triggers the decline of pineal gland melatonin biosynthesis and secretion and is an IARC-classified probable breast-cancer risk factor. We applied a large-scale molecular epidemiology approach to shed light on the putative role of melatonin in breast cancer. We investigated associations between breast-cancer risk and polymorphisms at genes of melatonin biosynthesis/signaling using a study population of 44,405 women from the Breast Cancer Association Consortium (22,992 cases, 21,413 population-based controls). Genotype data of 97 candidate single nucleotide polymorphisms (SNPs) at 18 defined gene regions were investigated for breast-cancer risk effects. We calculated adjusted odds ratios (ORs) and 95% confidence intervals (CI) by logistic regression for the main-effect analysis as well as stratified analyses by estrogen- and progesterone-receptor (ER, PR) status. SNP-SNP interactions were analyzed via a two-step procedure based on logic regression. The Bayesian false-discovery probability (BFDP) was used for all analyses to account for multiple testing. Noteworthy associations (BFDP < 0.8) included 10 linked SNPs in tryptophan hydroxylase 2 (TPH2) (e.g. rs1386492: OR = 1.07, 95% CI 1.02-1.12), and a SNP in the mitogen-activated protein kinase 8 (MAPK8) (rs10857561: OR = 1.11, 95% CI 1.04-1.18). The SNP-SNP interaction analysis revealed noteworthy interaction terms with TPH2- and MAPK-related SNPs (e.g. rs1386483<sub>R</sub> ∧ rs1473473<sub>D</sub> ∧ rs3729931<sub>D</sub>: OR = 1.20, 95% CI 1.09-1.32). In line with the light-at-night hypothesis that links shift work with elevated breast-cancer risks our results point to SNPs in TPH2 and MAPK-genes that may impact the intricate network of circadian regulation.
The human fecal and oral microbiome may play a role in the etiology of breast cancer through modulation of endogenous estrogen metabolism. This study aimed to investigate associations of circulating estrogens and estrogen metabolites with the fecal and oral microbiome in postmenopausal African women. A total of 117 women with fecal (N = 110) and oral (N = 114) microbiome data measured by 16S rRNA gene sequencing, and estrogens and estrogen metabolites data measured by liquid chromatography tandem mass spectrometry were included. The outcomes were measures of the microbiome and the independent variables were the estrogens and estrogen metabolites. Estrogens and estrogen metabolites were associated with the fecal microbial Shannon index (global <i>P < </i>0.01). In particular, higher levels of estrone (β = 0.36, <i>P = </i>0.03), 2-hydroxyestradiol (β = 0.30, <i>P = </i>0.02), 4-methoxyestrone (β = 0.51, <i>P = </i>0.01), and estriol (β = 0.36, <i>P</i> = 0.04) were associated with higher levels of the Shannon index, while 16alpha-hydroxyestrone (β = -0.57, <i>P < </i>0.01) was inversely associated with the Shannon index as indicated by linear regression. Conjugated 2-methoxyestrone was associated with oral microbial unweighted UniFrac as indicated by MiRKAT (<i>P < </i>0.01) and PERMANOVA, where conjugated 2-methoxyestrone explained 2.67% of the oral microbial variability, but no other estrogens or estrogen metabolites were associated with any other beta diversity measures. The presence and abundance of multiple fecal and oral genera, such as fecal genera from families <i>Lachnospiraceae</i> and <i>Ruminococcaceae</i>, were associated with several estrogens and estrogen metabolites as indicated by zero-inflated negative binomial regression. Overall, we found several associations of specific estrogens and estrogen metabolites and the fecal and oral microbiome. <b>IMPORTANCE</b> Several epidemiologic studies have found associations of urinary estrogens and estrogen metabolites with the fecal microbiome. However, urinary estrogen concentrations are not strongly correlated with serum estrogens, a known risk factor for breast cancer. To better understand whether the human fecal and oral microbiome were associated with breast cancer risk via the regulation of estrogen metabolism, we conducted this study to investigate the associations of circulating estrogens and estrogen metabolites with the fecal and oral microbiome in postmenopausal African women. We found several associations of parent estrogens and several estrogen metabolites with the microbial communities, and multiple individual associations of estrogens and estrogen metabolites with the presence and abundance of multiple fecal and oral genera, such as fecal genera from families <i>Lachnospiraceae</i> and <i>Ruminococcaceae,</i> which have estrogen metabolizing properties. Future large, longitudinal studies to investigate the dynamic changes of the fecal and oral microbiome and estrogen relationship are needed.
A large number of variants identified through clinical genetic testing in disease susceptibility genes, are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion), can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analyses of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of <i>BRCA1</i> and <i>BRCA2</i> variants from the Breast Cancer Association Consortium (BCAC), and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity - findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared to classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and pre-formatted excel calculators for implementation of the method for rare variants in <i>BRCA1</i>, <i>BRCA2</i> and other high-risk genes with known penetrance.
Polygenic risk scores (PRSs) increasingly predict complex traits; however, suboptimal performance in non-European populations raise concerns about clinical applications and health inequities. We developed CT-SLEB, a powerful and scalable method to calculate PRSs, using ancestry-specific genome-wide association study summary statistics from multiancestry training samples, integrating clumping and thresholding, empirical Bayes and superlearning. We evaluated CT-SLEB and nine alternative methods with large-scale simulated genome-wide association studies (~19 million common variants) and datasets from 23andMe, Inc., the Global Lipids Genetics Consortium, All of Us and UK Biobank, involving 5.1 million individuals of diverse ancestry, with 1.18 million individuals from four non-European populations across 13 complex traits. Results demonstrated that CT-SLEB significantly improves PRS performance in non-European populations compared with simple alternatives, with comparable or superior performance to a recent, computationally intensive method. Moreover, our simulation studies offered insights into sample size requirements and SNP density effects on multiancestry risk prediction.
<h4>Background</h4>Risk estimates for women carrying germline mutations in breast cancer susceptibility genes are mainly based on studies of European ancestry women.<h4>Methods</h4>We investigated associations between pathogenic variants (PV) in 34 genes with breast cancer risk in 871 cases [307 estrogen receptor (ER)-positive, 321 ER-negative, and 243 ER-unknown] and 1,563 controls in the Ghana Breast Health Study (GBHS), and estimated lifetime risk for carriers. We compared results with those for European, Asian, and African American ancestry women.<h4>Results</h4>The frequency of PV in GBHS for nine breast cancer genes was 8.38% in cases and 1.22% in controls. Relative risk estimates for overall breast cancer were: (OR, 13.70; 95% confidence interval (CI), 4.03-46.51) for BRCA1, (OR, 7.02; 95% CI, 3.17-15.54) for BRCA2, (OR, 17.25; 95% CI, 2.15-138.13) for PALB2, 5 cases and no controls carried TP53 PVs, and 2.10, (0.72-6.14) for moderate-risk genes combined (ATM, BARD1, CHEK2, RAD51C, RAD52D). These estimates were similar to those previously reported in other populations and were modified by ER status. No other genes evaluated had mutations associated at P < 0.05 with overall risk. The estimated lifetime risks for mutation carriers in BRCA1, BRCA2, and PALB2 and moderate-risk genes were 18.4%, 9.8%, 22.4%, and 3.1%, respectively, markedly lower than in Western populations with higher baseline risks.<h4>Conclusions</h4>We confirmed associations between PV and breast cancer risk in Ghanaian women and provide absolute risk estimates that could inform counseling in Ghana and other West African countries.<h4>Impact</h4>These findings have direct relevance for breast cancer genetic counseling for women in West Africa.
<h4>Background</h4>Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear.<h4>Methods</h4>Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes.<h4>Results</h4>Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions.<h4>Conclusion</h4>This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.
<h4>Background</h4>By-products are formed when disinfectants react with organic matter in source water. The most common class of disinfection by-products, trihalomethanes (THMs), have been linked to bladder cancer. Several studies have shown exposure-response associations with THMs in drinking water and bladder cancer risk. Few epidemiologic studies have evaluated gene-environment interactions for total THMs (TTHMs) with known bladder cancer susceptibility variants.<h4>Objectives</h4>In this study, we investigated the combined effect on bladder cancer risk contributed by TTHMs, bladder cancer susceptibility variants identified through genome-wide association studies, and variants in several candidate genes.<h4>Methods</h4>We analyzed data from two large case-control studies-the New England Bladder Cancer Study (n/n=989 cases/1,162 controls), a population-based study, and the Spanish Bladder Cancer Study (n/n=706 cases/772 controls), a hospital-based study. Because of differences in exposure distributions and metrics, we estimated effects of THMs and genetic variants within each study separately using adjusted logistic regression models to calculate odds ratios (ORs) and 95% confidence intervals (CI) with and without interaction terms, and then combined the results using meta-analysis.<h4>Results</h4>Of the 16 loci showing strong evidence of association with bladder cancer, rs907611 at 11p15.5 [leukocyte-specific protein 1 (<i>LSP1</i> region)] showed the strongest associations in the highest exposure category in each study, with evidence of interaction in both studies and in meta-analysis. In the highest exposure category, we observed OR=1.66 (95% CI: 1.17, 2.34, p-trend=0.005) for those with the rs907611-GG genotype and p-interaction=0.02. No other genetic variants tested showed consistent evidence of interaction.<h4>Discussion</h4>We found novel suggestive evidence for a multiplicative interaction between a putative bladder carcinogen, TTHMs, and genotypes of rs907611. Given the ubiquitous exposure to THMs, further work is needed to replicate and extend this finding and to understand potential molecular mechanisms. https://doi.org/10.1289/EHP9895.
<h4>Importance</h4>Rare germline genetic variants in several genes are associated with increased breast cancer (BC) risk, but their precise contributions to different disease subtypes are unclear. This information is relevant to guidelines for gene panel testing and risk prediction.<h4>Objective</h4>To characterize tumors associated with BC susceptibility genes in large-scale population- or hospital-based studies.<h4>Design, setting, and participants</h4>The multicenter, international case-control analysis of the BRIDGES study included 42 680 patients and 46 387 control participants, comprising women aged 18 to 79 years who were sampled independently of family history from 38 studies. Studies were conducted between 1991 and 2016. Sequencing and analysis took place between 2016 and 2021.<h4>Exposures</h4>Protein-truncating variants and likely pathogenic missense variants in ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53.<h4>Main outcomes and measures</h4>The intrinsic-like BC subtypes as defined by estrogen receptor, progesterone receptor, and ERBB2 (formerly known as HER2) status, and tumor grade; morphology; size; stage; lymph node involvement; subtype-specific odds ratios (ORs) for carrying protein-truncating variants and pathogenic missense variants in the 9 BC susceptibility genes.<h4>Results</h4>The mean (SD) ages at interview (control participants) and diagnosis (cases) were 55.1 (11.9) and 55.8 (10.6) years, respectively; all participants were of European or East Asian ethnicity. There was substantial heterogeneity in the distribution of intrinsic subtypes by gene. RAD51C, RAD51D, and BARD1 variants were associated mainly with triple-negative disease (OR, 6.19 [95% CI, 3.17-12.12]; OR, 6.19 [95% CI, 2.99-12.79]; and OR, 10.05 [95% CI, 5.27-19.19], respectively). CHEK2 variants were associated with all subtypes (with ORs ranging from 2.21-3.17) except for triple-negative disease. For ATM variants, the association was strongest for the hormone receptor (HR)+ERBB2- high-grade subtype (OR, 4.99; 95% CI, 3.68-6.76). BRCA1 was associated with increased risk of all subtypes, but the ORs varied widely, being highest for triple-negative disease (OR, 55.32; 95% CI, 40.51-75.55). BRCA2 and PALB2 variants were also associated with triple-negative disease. TP53 variants were most strongly associated with HR+ERBB2+ and HR-ERBB2+ subtypes. Tumors occurring in pathogenic variant carriers were of higher grade. For most genes and subtypes, a decline in ORs was observed with increasing age. Together, the 9 genes were associated with 27.3% of all triple-negative tumors in women 40 years or younger.<h4>Conclusions and relevance</h4>The results of this case-control study suggest that variants in the 9 BC risk genes differ substantially in their associated pathology but are generally associated with triple-negative and/or high-grade disease. Knowing the age and tumor subtype distributions associated with individual BC genes can potentially aid guidelines for gene panel testing, risk prediction, and variant classification and guide targeted screening strategies.
Germline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.
<h4>Objectives</h4>Physical inactivity and sedentary behaviour are associated with higher breast cancer risk in observational studies, but ascribing causality is difficult. Mendelian randomisation (MR) assesses causality by simulating randomised trial groups using genotype. We assessed whether lifelong physical activity or sedentary time, assessed using genotype, may be causally associated with breast cancer risk overall, pre/post-menopause, and by case-groups defined by tumour characteristics.<h4>Methods</h4>We performed two-sample inverse-variance-weighted MR using individual-level Breast Cancer Association Consortium case-control data from 130 957 European-ancestry women (69 838 invasive cases), and published UK Biobank data (n=91 105-377 234). Genetic instruments were single nucleotide polymorphisms (SNPs) associated in UK Biobank with wrist-worn accelerometer-measured overall physical activity (n<sub>snps</sub>=5) or sedentary time (n<sub>snps</sub>=6), or accelerometer-measured (n<sub>snps</sub>=1) or self-reported (n<sub>snps</sub>=5) vigorous physical activity.<h4>Results</h4>Greater genetically-predicted overall activity was associated with lower breast cancer overall risk (OR=0.59; 95% confidence interval (CI) 0.42 to 0.83 per-standard deviation (SD;~8 milligravities acceleration)) and for most case-groups. Genetically-predicted vigorous activity was associated with lower risk of pre/perimenopausal breast cancer (OR=0.62; 95% CI 0.45 to 0.87,≥3 vs. 0 self-reported days/week), with consistent estimates for most case-groups. Greater genetically-predicted sedentary time was associated with higher hormone-receptor-negative tumour risk (OR=1.77; 95% CI 1.07 to 2.92 per-SD (~7% time spent sedentary)), with elevated estimates for most case-groups. Results were robust to sensitivity analyses examining pleiotropy (including weighted-median-MR, MR-Egger).<h4>Conclusion</h4>Our study provides strong evidence that greater overall physical activity, greater vigorous activity, and lower sedentary time are likely to reduce breast cancer risk. More widespread adoption of active lifestyles may reduce the burden from the most common cancer in women.
<h4>Background</h4>Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain.<h4>Methods</h4>We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated.<h4>Results</h4>The most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47-2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set.<h4>Conclusions</h4>These results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility.
<h4>Background</h4>DNA methylation in blood may reflect adverse exposures accumulated over the lifetime and could therefore provide potential improvements in the prediction of cancer risk. A substantial body of research has shown associations between epigenetic aging and risk of disease, including cancer. Here we aimed to study epigenetic measures of aging and lifestyle-related factors in association with risk of breast cancer.<h4>Methods</h4>Using data from four prospective case-control studies nested in three cohorts of European ancestry participants, including a total of 1,655 breast cancer cases, we calculated three methylation-based measures of lifestyle factors (body mass index [BMI], tobacco smoking and alcohol consumption) and seven measures of epigenetic aging (Horvath-based, Hannum-based, PhenoAge and GrimAge). All measures were regression-adjusted for their respective risk factors and expressed per standard deviation (SD). Odds ratios (OR) and 95% confidence intervals (CI) were calculated using conditional or unconditional logistic regression and pooled using fixed-effects meta-analysis. Subgroup analyses were conducted by age at blood draw, time from blood sample to diagnosis, oestrogen receptor-positivity status and tumour stage.<h4>Results</h4>None of the measures of epigenetic aging were associated with risk of breast cancer in the pooled analysis: Horvath 'age acceleration' (AA): OR per SD = 1.02, 95%CI: 0.95-1.10; AA-Hannum: OR = 1.03, 95%CI:0.95-1.12; PhenoAge: OR = 1.01, 95%CI: 0.94-1.09 and GrimAge: OR = 1.03, 95%CI: 0.94-1.12, in models adjusting for white blood cell proportions, body mass index, smoking and alcohol consumption. The BMI-adjusted predictor of BMI was associated with breast cancer risk, OR per SD = 1.09, 95%CI: 1.01-1.17. The results for the alcohol and smoking methylation-based predictors were consistent with a null association. Risk did not appear to substantially vary by age at blood draw, time to diagnosis or tumour characteristics.<h4>Conclusion</h4>We found no evidence that methylation-based measures of aging, smoking or alcohol consumption were associated with risk of breast cancer. A methylation-based marker of BMI was associated with risk and may provide insights into the underlying associations between BMI and breast cancer.
Polygenic risk scores (PRSs) are useful for predicting breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remains relatively low. We aim to develop optimal PRSs for the prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in AA women. The AA dataset comprised 9235 cases and 10 184 controls from four genome-wide association study (GWAS) consortia and a GWAS study in Ghana. We randomly divided samples into training and validation sets. We built PRSs using individual-level AA data by a forward stepwise logistic regression and then developed joint PRSs that combined (1) the PRSs built in the AA training dataset and (2) a 313-variant PRS previously developed in women of European ancestry. PRSs were evaluated in the AA validation set. For overall breast cancer, the odds ratio per standard deviation of the joint PRS in the validation set was 1.34 [95% confidence interval (CI): 1.27-1.42] with the area under receiver operating characteristic curve (AUC) of 0.581. Compared with women with average risk (40th-60th PRS percentile), women in the top decile of the PRS had a 1.98-fold increased risk (95% CI: 1.63-2.39). For PRSs of ER-positive and ER-negative breast cancer, the AUCs were 0.608 and 0.576, respectively. Compared with existing methods, the proposed joint PRSs can improve prediction of breast cancer risk in AA women.
<h4>Background</h4>Several anthropometric measures have been associated with hormone-related cancers, and it has been shown that estrogen metabolism in postmenopausal women plays an important role in these relationships. However, little is known about circulating estrogen levels in African women, and the relevance to breast cancer or breast cancer risk factors. To shed further light on the relationship of anthropometric factors and estrogen levels in African women, we examined whether measured body mass index (BMI), waist-to-hip ratio (WHR), height, and self-reported body size were associated with serum estrogens/estrogen metabolites in a cross-sectional analysis among postmenopausal population-based controls of the Ghana Breast Health Study.<h4>Methods</h4>Fifteen estrogens/estrogen metabolites were quantified using liquid chromatography-tandem mass spectrometry in serum samples collected from postmenopausal female controls enrolled in the Ghana Breast Health Study, a population-based case-control study conducted in Accra and Kumasi. Geometric means (GMs) of estrogens/estrogen metabolites were estimated using linear regression, adjusting for potential confounders.<h4>Results</h4>Measured BMI (≥ 30 vs. 18.5-24.9 kg/m<sup>2</sup>) was positively associated with parent estrogens (multivariable adjusted GM for unconjugated estrone: 78.90 (66.57-93.53) vs. 50.89 (43.47-59.59), p-value < 0.0001; and unconjugated estradiol: 27.83 (21.47-36.07) vs. 13.26 (10.37-16.95), p-value < 0.0001). Independent of unconjugated estradiol, measured BMI was associated with lower levels of 2-pathway metabolites and higher levels of 16-ketoestradriol. Similar patterns of association were found with WHR; however, the associations were not entirely independent of BMI. Height was not associated with postmenopausal estrogens/estrogen metabolite levels in African women.<h4>Conclusions</h4>We observed strong associations between measured BMI and parent estrogens and estrogen metabolite patterns that largely mirrored relations that have previously been associated with higher breast cancer risk in postmenopausal White women. The consistency of the BMI-estrogen metabolism associations in our study with those previously noted among White women suggests that estrogens likely explain part of the BMI-postmenopausal breast cancer risk in both groups. These findings merit evaluation in Black women, including prospective studies.
<h4>Background</h4>Prediction of contralateral breast cancer (CBC) risk is challenging due to moderate performances of the known risk factors. We aimed to improve our previous risk prediction model (PredictCBC) by updated follow-up and including additional risk factors.<h4>Methods</h4>We included data from 207,510 invasive breast cancer patients participating in 23 studies. In total, 8225 CBC events occurred over a median follow-up of 10.2 years. In addition to the previously included risk factors, PredictCBC-2.0 included CHEK2 c.1100delC, a 313 variant polygenic risk score (PRS-313), body mass index (BMI), and parity. Fine and Gray regression was used to fit the model. Calibration and a time-dependent area under the curve (AUC) at 5 and 10 years were assessed to determine the performance of the models. Decision curve analysis was performed to evaluate the net benefit of PredictCBC-2.0 and previous PredictCBC models.<h4>Results</h4>The discrimination of PredictCBC-2.0 at 10 years was higher than PredictCBC with an AUC of 0.65 (95% prediction intervals (PI) 0.56-0.74) versus 0.63 (95%PI 0.54-0.71). PredictCBC-2.0 was well calibrated with an observed/expected ratio at 10 years of 0.92 (95%PI 0.34-2.54). Decision curve analysis for contralateral preventive mastectomy (CPM) showed the potential clinical utility of PredictCBC-2.0 between thresholds of 4 and 12% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers.<h4>Conclusions</h4>Additional genetic information beyond BRCA1/2 germline mutations improved CBC risk prediction and might help tailor clinical decision-making toward CPM or alternative preventive strategies. Identifying patients who benefit from CPM, especially in the general breast cancer population, remains challenging.
<h4>Background</h4>Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2).<h4>Method</h4>The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance.<h4>Results</h4>Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3 × 10<sup>-6</sup>) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted.<h4>Conclusion</h4>The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predictions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration.
<h4>Background</h4>TP53 and estrogen receptor (ER) both play essential roles in breast cancer development and progression, with recent research revealing cross-talk between TP53 and ER signaling pathways. Although many studies have demonstrated heterogeneity of risk factor associations across ER subtypes, associations by TP53 status have been inconsistent.<h4>Methods</h4>This case-case analysis included incident breast cancer cases (47% Black) from the Carolina Breast Cancer Study (1993-2013). Formalin-fixed paraffin-embedded tumor samples were classified for TP53 functional status (mutant-like/wild-type-like) using a validated RNA signature. For IHC-based TP53 status, mutant-like was classified as at least 10% positivity. We used two-stage polytomous logistic regression to evaluate risk factor heterogeneity due to RNA-based TP53 and/or ER, adjusting for each other and for PR, HER2, and grade. We then compared this with the results when using IHC-based TP53 classification.<h4>Results</h4>The RNA-based classifier identified 55% of tumors as TP53 wild-type-like and 45% as mutant-like. Several hormone-related factors (oral contraceptive use, menopausal status, age at menopause, and pre- and postmenopausal body mass index) were associated with TP53 mutant-like status, whereas reproductive factors (age at first birth and parity) and smoking were associated with ER status. Multiparity was associated with both TP53 and ER. When classifying TP53 status using IHC methods, no associations were observed with TP53. Associations observed with RNA-based TP53 remained after accounting for basal-like subtype.<h4>Conclusions</h4>This case-case study found breast cancer risk factors associated with RNA-based TP53 and ER.<h4>Impact</h4>RNA-based TP53 and ER represent an emerging etiologic schema of interest in breast cancer prevention research.
TP53 and estrogen receptor (ER) are essential in breast cancer development and progression, but TP53 status (by DNA sequencing or protein expression) has been inconsistently associated with survival. We evaluated whether RNA-based TP53 classifiers are related to survival. Participants included 3213 women in the Carolina Breast Cancer Study (CBCS) with invasive breast cancer (stages I-III). Tumors were classified for TP53 status (mutant-like/wildtype-like) using an RNA signature. We used Cox proportional hazards models to estimate covariate-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for breast cancer-specific survival (BCSS) among ER- and TP53-defined subtypes. RNA-based results were compared to DNA- and IHC-based TP53 classification, as well as Basal-like versus non-Basal-like subtype. Findings from the diverse (50% Black), population-based CBCS were compared to those from the largely white METABRIC study. RNA-based TP53 mutant-like was associated with BCSS among both ER-negatives and ER-positives (HR (95% CI) = 5.38 (1.84-15.78) and 4.66 (1.79-12.15), respectively). Associations were attenuated when using DNA- or IHC-based TP53 classification. In METABRIC, few ER-negative tumors were TP53-wildtype-like, but TP53 status was a strong predictor of BCSS among ER-positives. In both populations, the effect of TP53 mutant-like status was similar to that for Basal-like subtype. RNA-based measures of TP53 status are strongly associated with BCSS and may have value among ER-negative cancers where few prognostic markers have been robustly validated. Given the role of TP53 in chemotherapeutic response, RNA-based TP53 as a prognostic biomarker could address an unmet need in breast cancer.
<h4>Background</h4>Rigorous evaluation of the calibration and discrimination of breast-cancer risk-prediction models in prospective cohorts is critical for applications under clinical guidelines. We comprehensively evaluated an integrated model incorporating classical risk factors and a 313-variant polygenic risk score (PRS) to predict breast-cancer risk.<h4>Methods</h4>Fifteen prospective cohorts from six countries with 239 340 women (7646 incident breast-cancer cases) of European ancestry aged 19-75 years were included. Calibration of 5-year risk was assessed by comparing expected and observed proportions of cases overall and within risk categories. Risk stratification for women of European ancestry aged 50-70 years in those countries was evaluated by the proportion of women and future cases crossing clinically relevant risk thresholds.<h4>Results</h4>Among women <50 years old, the median (range) expected-to-observed ratio for the integrated model across 15 cohorts was 0.9 (0.7-1.0) overall and 0.9 (0.7-1.4) at the highest-risk decile; among women ≥50 years old, these were 1.0 (0.7-1.3) and 1.2 (0.7-1.6), respectively. The proportion of women identified above a 3% 5-year risk threshold (used for recommending risk-reducing medications in the USA) ranged from 7.0% in Germany (∼841 000 of 12 million) to 17.7% in the USA (∼5.3 of 30 million). At this threshold, 14.7% of US women were reclassified by adding the PRS to classical risk factors, with identification of 12.2% of additional future cases.<h4>Conclusion</h4>Integrating a 313-variant PRS with classical risk factors can improve the identification of European-ancestry women at elevated risk who could benefit from targeted risk-reducing strategies under current clinical guidelines.
<h4>Background</h4>Reproductive factors have been shown to be differentially associated with risk of estrogen receptor (ER)-positive and ER-negative breast cancer. However, their associations with intrinsic-like subtypes are less clear.<h4>Methods</h4>Analyses included up to 23 353 cases and 71 072 controls pooled from 31 population-based case-control or cohort studies in the Breast Cancer Association Consortium across 16 countries on 4 continents. Polytomous logistic regression was used to estimate the association between reproductive factors and risk of breast cancer by intrinsic-like subtypes (luminal A-like, luminal B-like, luminal B-HER2-like, HER2-enriched-like, and triple-negative breast cancer) and by invasiveness. All statistical tests were 2-sided.<h4>Results</h4>Compared with nulliparous women, parous women had a lower risk of luminal A-like, luminal B-like, luminal B-HER2-like, and HER2-enriched-like disease. This association was apparent only after approximately 10 years since last birth and became stronger with increasing time (odds ratio [OR] = 0.59, 95% confidence interval [CI] = 0.49 to 0.71; and OR = 0.36, 95% CI = 0.28 to 0.46 for multiparous women with luminal A-like tumors 20 to less than 25 years after last birth and 45 to less than 50 years after last birth, respectively). In contrast, parous women had a higher risk of triple-negative breast cancer right after their last birth (for multiparous women: OR = 3.12, 95% CI = 2.02 to 4.83) that was attenuated with time but persisted for decades (OR = 1.03, 95% CI = 0.79 to 1.34, for multiparous women 25 to less than 30 years after last birth). Older age at first birth (Pheterogeneity < .001 for triple-negative compared with luminal A-like breast cancer) and breastfeeding (Pheterogeneity < .001 for triple-negative compared with luminal A-like breast cancer) were associated with lower risk of triple-negative breast cancer but not with other disease subtypes. Younger age at menarche was associated with higher risk of all subtypes; older age at menopause was associated with higher risk of luminal A-like but not triple-negative breast cancer. Associations for in situ tumors were similar to luminal A-like.<h4>Conclusions</h4>This large and comprehensive study demonstrates a distinct reproductive risk factor profile for triple-negative breast cancer compared with other subtypes, with implications for the understanding of disease etiology and risk prediction.
Advances in knowledge about breast cancer risk factors have led to the development of more comprehensive risk models. These integrate information on a variety of risk factors such as lifestyle, genetics, family history, and breast density. These risk models have the potential to deliver more personalised breast cancer prevention. This is through improving accuracy of risk estimates, enabling more effective targeting of preventive options and creating novel prevention pathways through enabling risk estimation in a wider variety of populations than currently possible. The systematic use of risk tools as part of population screening programmes is one such example. A clear understanding of how such tools can contribute to the goal of personalised prevention can aid in understanding and addressing barriers to implementation. In this paper we describe how emerging models, and their associated tools can contribute to the goal of personalised healthcare for breast cancer through health promotion, early disease detection (screening) and improved management of women at higher risk of disease. We outline how addressing specific challenges on the level of communication, evidence, evaluation, regulation, and acceptance, can facilitate implementation and uptake.
Continuous risk of recurrence scores (CRS) based on tumor gene expression are vital prognostic tools for breast cancer. Studies have shown that Black women (BW) have higher CRS than White women (WW). Although systemic injustices contribute substantially to breast cancer disparities, evidence of biological and germline contributions is emerging. In this study, we investigated germline genetic associations with CRS and CRS disparity using approaches modeled after transcriptome-wide association studies (TWAS). In the Carolina Breast Cancer Study, using race-specific predictive models of tumor expression from germline genetics, we performed race-stratified (<i>N</i> = 1,043 WW, 1,083 BW) linear regressions of three CRS (ROR-S: PAM50 subtype score; proliferation score; ROR-P: ROR-S plus proliferation score) on imputed tumor genetically regulated tumor expression (GReX). Bayesian multivariate regression and adaptive shrinkage tested GReX-prioritized genes for associations with tumor PAM50 expression and subtype to elucidate patterns of germline regulation underlying GReX-CRS associations. At FDR-adjusted <i>P</i> < 0.10, 7 and 1 GReX prioritized genes among WW and BW, respectively. Among WW, CRS were positively associated with <i>MCM10</i>, <i>FAM64A</i>, <i>CCNB2</i>, and <i>MMP1</i> GReX and negatively associated with <i>VAV3</i>, <i>PCSK6</i>, and <i>GNG11</i> GReX. Among BW, higher <i>MMP1</i> GReX predicted lower proliferation score and ROR-P. GReX-prioritized gene and PAM50 tumor expression associations highlighted potential mechanisms for GReX-prioritized gene to CRS associations. Among patients with breast cancer, differential germline associations with CRS were found by race, underscoring the need for larger, diverse datasets in molecular studies of breast cancer. These findings also suggest possible germline <i>trans</i>-regulation of PAM50 tumor expression, with potential implications for CRS interpretation in clinical settings. SIGNIFICANCE: This study identifies race-specific genetic associations with breast cancer risk of recurrence scores and suggests mediation of these associations by PAM50 subtype and expression, with implications for clinical interpretation of these scores.
<h4>Motivation</h4>The Division of Cancer Epidemiology and Genetics (DCEG) and the Division of Cancer Prevention (DCP) at the National Cancer Institute (NCI) have recently generated genome-wide association study (GWAS) data for multiple traits in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Genomic Atlas project. The GWAS included 110 000 participants. The dissemination of the genetic association data through a data portal called GWAS Explorer, in a manner that addresses the modern expectations of FAIR reusability by data scientists and engineers, is the main motivation for the development of the open-source JavaScript software development kit (SDK) reported here.<h4>Results</h4>The PLCO GWAS Explorer resource relies on a public stateless HTTP application programming interface (API) deployed as the sole backend service for both the landing page's web application and third-party analytical workflows. The core PLCOjs SDK is mapped to each of the API methods, and also to each of the reference graphic visualizations in the GWAS Explorer. A few additional visualization methods extend it. As is the norm with web SDKs, no download or installation is needed and modularization supports targeted code injection for web applications, reactive notebooks (Observable) and node-based web services.<h4>Availability and implementation</h4>code at https://github.com/episphere/plco; project page at https://episphere.github.io/plco.
<h4>Background</h4>Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene-environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this.<h4>Methods</h4>We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P<0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test.<h4>Results</h4>After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the <i>C13orf45</i> gene and age at first full-term pregnancy (P<sub>GXE</sub>=4.44×10<sup>-6</sup>).<h4>Conclusion</h4>In this transcriptome-informed genome-wide gene-environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk.<h4>Impact</h4>Our study suggests a limited role of gene-environment interactions in breast cancer risk.
Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values < 5 × 10<sup>-8</sup> as genome-wide significant, and p-values < 1 × 10<sup>-5</sup> as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values < 1 × 10<sup>5</sup>. The strongest evidence was found for rs4674019 (p-value = 2.27 × 10<sup>-7</sup>), which showed genome-wide significant interaction (p-value = 3.8 × 10<sup>-8</sup>) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT-breast cancer risk association.
The oral microbiome, like the fecal microbiome, may be related to breast cancer risk. Therefore, we investigated whether the oral microbiome was associated with breast cancer and nonmalignant breast disease, and its relationship with the fecal microbiome in a case-control study in Ghana. A total of 881 women were included (369 breast cancers, 93 nonmalignant cases and 419 population-based controls). The V4 region of the 16S rRNA gene was sequenced from oral and fecal samples. Alpha-diversity (observed amplicon sequence variants [ASVs], Shannon index and Faith's Phylogenetic Diversity) and beta-diversity (Bray-Curtis, Jaccard and weighted and unweighted UniFrac) metrics were computed. MiRKAT and logistic regression models were used to investigate the case-control associations. Oral sample alpha-diversity was inversely associated with breast cancer and nonmalignant breast disease with odds ratios (95% CIs) per every 10 observed ASVs of 0.86 (0.83-0.89) and 0.79 (0.73-0.85), respectively, compared to controls. Beta-diversity was also associated with breast cancer and nonmalignant breast disease compared to controls (P ≤ .001). The relative abundances of Porphyromonas and Fusobacterium were lower for breast cancer cases compared to controls. Alpha-diversity and presence/relative abundance of specific genera from the oral and fecal microbiome were strongly correlated among breast cancer cases, but weakly correlated among controls. Particularly, the relative abundance of oral Porphyromonas was strongly, inversely correlated with fecal Bacteroides among breast cancer cases (r = -.37, P ≤ .001). Many oral microbial metrics were strongly associated with breast cancer and nonmalignant breast disease, and strongly correlated with fecal microbiome among breast cancer cases, but not controls.
Cancer heterogeneities hold the key to a deeper understanding of cancer etiology and progression and the discovery of more precise cancer therapy. Modern pathological and molecular technologies offer a powerful set of tools to profile tumor heterogeneities at multiple levels in large patient populations, from DNA to RNA, protein and epigenetics, and from tumor tissues to tumor microenvironment and liquid biopsy. When coupled with well-validated epidemiologic methodology and well-characterized epidemiologic resources, the rich tumor pathological and molecular tumor information provide new research opportunities at an unprecedented breadth and depth. This is the research space where Molecular Pathological Epidemiology (MPE) emerged over a decade ago and has been thriving since then. As a truly multidisciplinary field, MPE embraces collaborations from diverse fields including epidemiology, pathology, immunology, genetics, biostatistics, bioinformatics, and data science. Since first convened in 2013, the International MPE Meeting series has grown into a dynamic and dedicated platform for experts from these disciplines to communicate novel findings, discuss new research opportunities and challenges, build professional networks, and educate the next-generation scientists. Herein, we share the proceedings of the Fifth International MPE meeting, held virtually online, on May 24 and 25, 2021. The meeting consisted of 21 presentations organized into the three main themes, which were recent integrative MPE studies, novel cancer profiling technologies, and new statistical and data science approaches. Looking forward to the near future, the meeting attendees anticipated continuous expansion and fruition of MPE research in many research fronts, particularly immune-epidemiology, mutational signatures, liquid biopsy, and health disparities.
Recent genomic studies suggest that Asian breast cancer (BC) may have distinct somatic features; however, most comparisons of BC genomic features across populations did not account for differences in age, subtype, and sequencing methods. In this study, we analyzed whole-exome sequencing (WES) data to characterize <b>s</b>omatic copy number alterations (SCNAs) and mutation profiles in 98 Hong Kong BC (HKBC) patients and compared with those from The Cancer Genome Atlas of European ancestry (TCGA-EA, N = 686), which had similar distributions of age at diagnosis and PAM50 subtypes as in HKBC. We developed a two-sample Poisson model to compare driver gene selection pressure, which reflects the effect sizes of cancer driver genes, while accounting for differences in sample size, sequencing platforms, depths, and mutation calling methods. We found that somatic mutation and SCNA profiles were overall very similar between HKBC and TCGA-EA. The selection pressure for small insertions and deletions (indels) in <i>GATA3</i> (false discovery rate (FDR) corrected p < 0.01) and single-nucleotide variants (SNVs) in <i>TP53</i> (nominal p = 0.02, FDR corrected p = 0.28) was lower in HKBC than in TCGA-EA. Among the 13 signatures of single-base substitutions (SBS) that are common in BC, we found a suggestively higher contribution of SBS18 and a lower contribution of SBS1 in HKBC than in TCGA-EA, while the two <i>APOBEC</i>-induced signatures showed similar prevalence<b>.</b> Our results suggest that the genomic landscape of BC was largely very similar between HKBC and TCGA-EA, despite suggestive differences in some driver genes and mutational signatures that warrant future investigations in large and diverse Asian populations.
<h4>Purpose</h4>In addition to impacting incidence, risk factors for breast cancer may also influence recurrence and survival from the disease. However, it is unclear how these factors affect combinatorial biomarkers for aiding treatment decision-making in breast cancer.<h4>Methods</h4>Patients were 8179 women with histologically confirmed invasive breast cancer, diagnosed and treated in a large cancer hospital in Beijing, China. Individual clinicopathological (tumor size, grade, lymph nodes) and immunohistochemical (IHC: ER, PR, HER2, KI67) markers were used to define clinically relevant combinatorial prognostic biomarkers, including the Nottingham Prognostic Index (NPI: combining size, grade, nodes) and IHC4 score (combining ER, PR, HER2, KI67). Odds ratios (ORs) and 95% confidence intervals (CIs) for associations between breast cancer risk factors and quartiles (Q1-Q4) of NPI and IHC4 were assessed in multivariable polytomous logistic regression models.<h4>Results</h4>Overall, increasing parity (OR<sub>trend</sub>(95% CI) = 1.20(1.05-1.37);P<sub>trend</sub> = 0.007), overweight (OR(95% CI)<sub>vs normal</sub> = 1.60(1.29-1.98)), and obesity (OR(95% CI) <sub>vs normal</sub> = 2.12(1.43-3.14)) were associated with higher likelihood of developing tumors with high (Q4) versus low (Q1) NPI score. Conversely, increasing age (OR<sub>trend</sub>(95% CI) = 0.75(0.66-0.84);P<sub>trend</sub> < 0.001) and positive family history of breast cancer (FHBC) (OR(95% CI) = 0.66(0.45-0.95)) were inversely associated with NPI. Only body mass index (BMI) was associated with IHC4, with overweight (OR(95% CI) <sub>vs normal</sub> = 0.82(0.66-1.02)) and obese (OR(95% CI) <sub>vs normal</sub> = 0.52(0.36-0.76)) women less likely to develop high IHC4 tumors. Notably, elevated BMI was associated with higher NPI irrespective of hormone receptor-expression status.<h4>Conclusions</h4>Our findings indicate that factors affecting breast cancer incidence, particularly age, parity, FHBC, and BMI, may impact clinically relevant prognostic biomarkers with implications for surveillance, prognostication, and counseling.
<h4>Purpose</h4>Tumor-associated stroma is comprised of fibroblasts, tumor-infiltrating lymphocytes (TIL), macrophages, endothelial cells, and other cells that interactively influence tumor progression through inflammation and wound repair. Although gene-expression signatures reflecting wound repair predict breast cancer survival, it is unclear whether combined density of tumor-associated stromal cells, a morphologic proxy for inflammation and wound repair signatures on routine hematoxylin and eosin (H&E)-stained sections, is of prognostic relevance.<h4>Methods</h4>By applying machine learning to digitized H&E-stained sections for 2,084 breast cancer patients from China (<i>n</i> = 596; 24-55 years), Poland (<i>n</i> = 810; 31-75 years), and the United States (<i>n</i> = 678; 55-78 years), we characterized tumor-associated stromal cellular density (SCD) as the percentage of tumor-stroma that is occupied by nucleated cells. Hazard ratios (HR) and 95% confidence intervals (CI) for associations between SCD and clinical outcomes [recurrence (China) and mortality (Poland and the United States)] were estimated using Cox proportional hazard regression, adjusted for clinical variables.<h4>Results</h4>SCD was independently predictive of poor clinical outcomes in hormone receptor-positive (luminal) tumors from China [multivariable HR (95% CI)<sub>fourth(Q4) vs. first(Q1) quartile</sub> = 1.86 (1.06-3.26); <i>P</i> <sub>trend</sub> = 0.03], Poland [HR (95% CI)<sub>Q4 vs. Q1</sub> = 1.80 (1.12-2.89); <i>P</i> <sub>trend</sub> = 0.01], and the United States [HR (95% CI)<sub>Q4 vs. Q1</sub> = 2.42 (1.33-4.42); <i>P</i> <sub>trend</sub> = 0.002]. In general, SCD provided more prognostic information than most classic clinicopathologic factors, including grade, size, PR, HER2, IHC4, and TILs, predicting clinical outcomes irrespective of menopausal or lymph nodal status. SCD was not predictive of outcomes in hormone receptor-negative tumors.<h4>Conclusions</h4>Our findings support the independent prognostic value of tumor-associated SCD among ethnically diverse luminal breast cancer patients.<h4>Impact</h4>Assessment of tumor-associated SCD on standard H&E could help refine prognostic assessment and therapeutic decision making in luminal breast cancer.
Our study describes breast cancer risk loci using a cross-ancestry GWAS approach. We first identify variants that are associated with breast cancer at P < 0.05 from African ancestry GWAS meta-analysis (9241 cases and 10193 controls), then meta-analyze with European ancestry GWAS data (122977 cases and 105974 controls) from the Breast Cancer Association Consortium. The approach identifies four loci for overall breast cancer risk [1p13.3, 5q31.1, 15q24 (two independent signals), and 15q26.3] and two loci for estrogen receptor-negative disease (1q41 and 7q11.23) at genome-wide significance. Four of the index single nucleotide polymorphisms (SNPs) lie within introns of genes (KCNK2, C5orf56, SCAMP2, and SIN3A) and the other index SNPs are located close to GSTM4, AMPD2, CASTOR2, and RP11-168G16.2. Here we present risk loci with consistent direction of associations in African and European descendants. The study suggests that replication across multiple ancestry populations can help improve the understanding of breast cancer genetics and identify causal variants.
Circulating tumor DNA (ctDNA) sequencing studies could provide novel insights into the molecular pathology of cancer in sub-Saharan Africa. In 15 patient plasma samples collected at the time of diagnosis as part of the Ghana Breast Health Study and unselected for tumor grade and subtype, ctDNA was detected in a majority of patients based on whole- genome sequencing at high (30×) and low (0.1×) depths. Breast cancer driver copy number alterations were observed in the majority of patients.
<h4>Motivation</h4>Mortality Tracker is an in-browser application for data wrangling, analysis, dissemination and visualization of public time series of mortality in the United States. It was developed in response to requests by epidemiologists for portable real time assessment of the effect of COVID-19 on other causes of death and all-cause mortality. This is performed by comparing 2020 real time values with observations from the same week in the previous 5 years, and by enabling the extraction of temporal snapshots of mortality series that facilitate modeling the interdependence between its causes.<h4>Results</h4>Our solution employs a scalable 'Data Commons at Web Scale' approach that abstracts all stages of the data cycle as in-browser components. Specifically, the data wrangling computation, not just the orchestration of data retrieval, takes place in the browser, without any requirement to download or install software. This approach, where operations that would normally be computed server-side are mapped to in-browser SDKs, is sometimes loosely described as Web APIs, a designation adopted here.<h4>Availabilityand implementation</h4>https://episphere.github.io/mortalitytracker; webcast demo: youtu.be/ZsvCe7cZzLo.<h4>Supplementary information</h4>Supplementary data are available at Bioinformatics online.
A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10<sup>-31</sup>).
<h4>Background</h4>Artificial intelligence (AI) is fast becoming the tool of choice for scalable and reliable analysis of medical images. However, constraints in sharing medical data outside the institutional or geographical space, as well as difficulties in getting AI models and modeling platforms to work across different environments, have led to a "reproducibility crisis" in digital medicine.<h4>Methods</h4>This study details the implementation of a web platform that can be used to mitigate these challenges by orchestrating a digital pathology AI pipeline, from raw data to model inference, entirely on the local machine. We discuss how this federated platform provides governed access to data by consuming the Application Program Interfaces exposed by cloud storage services, allows the addition of user-defined annotations, facilitates active learning for training models iteratively, and provides model inference computed directly in the web browser at practically zero cost. The latter is of particular relevance to clinical workflows because the code, including the AI model, travels to the user's data, which stays private to the governance domain where it was acquired.<h4>Results</h4>We demonstrate that the web browser can be a means of democratizing AI and advancing data socialization in medical imaging backed by consumer-facing cloud infrastructure such as Box.com. As a case study, we test the accompanying platform end-to-end on a large dataset of digital breast cancer tissue microarray core images. We also showcase how it can be applied in contexts separate from digital pathology by applying it to a radiology dataset containing COVID-19 computed tomography images.<h4>Conclusions</h4>The platform described in this report resolves the challenges to the findable, accessible, interoperable, reusable stewardship of data and AI models by integrating with cloud storage to maintain user-centric governance over the data. It also enables distributed, federated computation for AI inference over those data and proves the viability of client-side AI in medical imaging.<h4>Availability</h4>The open-source application is publicly available at , with a short video demonstration at .
<h4>Background</h4>Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.<h4>Methods</h4>We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.<h4>Results</h4>Protein-truncating variants in 5 genes (<i>ATM</i>, <i>BRCA1</i>, <i>BRCA2</i>, <i>CHEK2</i>, and <i>PALB2</i>) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (<i>BARD1</i>, <i>RAD51C</i>, <i>RAD51D</i>, and <i>TP53</i>) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in <i>ATM</i> and <i>CHEK2</i>, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in <i>BARD1</i>, <i>BRCA1</i>, <i>BRCA2</i>, <i>PALB2</i>, <i>RAD51C</i>, and <i>RAD51D</i>, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in <i>ATM</i>, <i>CHEK2</i>, and <i>TP53</i> were associated with a risk of breast cancer overall with a P value of less than 0.001. For <i>BRCA1</i>, <i>BRCA2</i>, and <i>TP53</i>, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.<h4>Conclusions</h4>The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).
The gut microbiota may play a role in breast cancer etiology by regulating hormonal, metabolic and immunologic pathways. We investigated associations of fecal bacteria with breast cancer and nonmalignant breast disease in a case-control study conducted in Ghana, a country with rising breast cancer incidence and mortality. To do this, we sequenced the V4 region of the 16S rRNA gene to characterize bacteria in fecal samples collected at the time of breast biopsy (N = 379 breast cancer cases, N = 102 nonmalignant breast disease cases, N = 414 population-based controls). We estimated associations of alpha diversity (observed amplicon sequence variants [ASVs], Shannon index, and Faith's phylogenetic diversity), beta diversity (Bray-Curtis and unweighted/weighted UniFrac distance), and the presence and relative abundance of select taxa with breast cancer and nonmalignant breast disease using multivariable unconditional polytomous logistic regression. All alpha diversity metrics were strongly, inversely associated with odds of breast cancer and for those in the highest relative to lowest tertile of observed ASVs, the odds ratio (95% confidence interval) was 0.21 (0.13-0.36; P<sub>trend</sub> < .001). Alpha diversity associations were similar for nonmalignant breast disease and breast cancer grade/molecular subtype. All beta diversity distance matrices and multiple taxa with possible estrogen-conjugating and immune-related functions were strongly associated with breast cancer (all Ps < .001). There were no statistically significant differences between breast cancer and nonmalignant breast disease cases in any microbiota metric. In conclusion, fecal bacterial characteristics were strongly and similarly associated with breast cancer and nonmalignant breast disease. Our findings provide novel insight into potential microbially-mediated mechanisms of breast disease.
Single germline nucleotide pathogenic variants have been identified in 12 breast cancer predisposition genes, but structural deletions in these genes remain poorly characterized. We conducted in-depth whole genome sequencing (WGS) in genomic DNA samples obtained from 1340 invasive breast cancer cases and 675 controls of African ancestry. We identified 25 deletions in the intragenic regions of ten established breast cancer predisposition genes based on a consensus call from six state-of-the-art SV callers. Overall, no significant case-control difference was found in the frequency of these deletions. However, 1.0% of cases and 0.3% of controls carried any of the eight putative protein-truncating rare deletions located in BRCA1, BRCA2, CDH1, TP53, NF1, RAD51D, RAD51C and CHEK2, resulting in an odds ratio (OR) of 3.29 (95% CI 0.74-30.16). We also identified a low-frequency deletion in NF1 associated with breast cancer risk (OR 1.93, 95% CI 1.14-3.42). In addition, we detected 56 deletions, including six putative protein-truncating deletions, in suspected breast predisposition genes. This is the first large study to systematically search for structural deletions in breast cancer predisposition genes. Many of the deletions, particularly those resulting in protein truncations, are likely to be pathogenic. Results from this study, if confirmed in future large-scale studies, could have significant implications for genetic testing for this common cancer.
Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P < 10<sup>-8</sup>, at 5 loci, which are not associated with risk in the general population. They include rs60882887 at 11p11.2 where MADD, SP11 and EIF1, genes previously implicated in BC biology, are predicted as potential targets. These findings will contribute towards customising BC polygenic risk scores for BRCA1 and BRCA2 mutation carriers.
<h4>Background</h4>Polygenic risk scores (PRSs) have been demonstrated to identify women of European, Asian, and Latino ancestry at elevated risk of developing breast cancer (BC). We evaluated the performance of existing PRSs trained in European ancestry populations among women of African ancestry.<h4>Methods</h4>We assembled genotype data for women of African ancestry, including 9241 case subjects and 10 193 control subjects. We evaluated associations of 179- and 313-variant PRSs with overall and subtype-specific BC risk. PRS discriminatory accuracy was assessed using area under the receiver operating characteristic curve. We also evaluated a recalibrated PRS, replacing the index variant with variants in each region that better captured risk in women of African ancestry and estimated lifetime absolute risk of BC in African Americans by PRS category.<h4>Results</h4>For overall BC, the odds ratio per SD of the 313-variant PRS (PRS313) was 1.27 (95% confidence interval [CI] = 1.23 to 1.31), with an area under the receiver operating characteristic curve of 0.571 (95% CI = 0.562 to 0.579). Compared with women with average risk (40th-60th PRS percentile), women in the top decile of PRS313 had a 1.54-fold increased risk (95% CI = 1.38-fold to 1.72-fold). By age 85 years, the absolute risk of overall BC was 19.6% for African American women in the top 1% of PRS313 and 6.7% for those in the lowest 1%. The recalibrated PRS did not improve BC risk prediction.<h4>Conclusion</h4>The PRSs stratify BC risk in women of African ancestry, with attenuated performance compared with that reported in European, Asian, and Latina populations. Future work is needed to improve BC risk stratification for women of African ancestry.
Breast cancer metastasis accounts for most of the deaths from breast cancer. Identification of germline variants associated with survival in aggressive types of breast cancer may inform understanding of breast cancer progression and assist treatment. In this analysis, we studied the associations between germline variants and breast cancer survival for patients with distant metastases at primary breast cancer diagnosis. We used data from the Breast Cancer Association Consortium (BCAC) including 1062 women of European ancestry with metastatic breast cancer, 606 of whom died of breast cancer. We identified two germline variants on chromosome 1, rs138569520 and rs146023652, significantly associated with breast cancer-specific survival (P = 3.19 × 10<sup>-8</sup> and 4.42 × 10<sup>-8</sup>). In silico analysis suggested a potential regulatory effect of the variants on the nearby target genes SDE2 and H3F3A. However, the variants showed no evidence of association in a smaller replication dataset. The validation dataset was obtained from the SNPs to Risk of Metastasis (StoRM) study and included 293 patients with metastatic primary breast cancer at diagnosis. Ultimately, larger replication studies are needed to confirm the identified associations.
<h4>Background</h4>Epidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk.<h4>Methods</h4>We carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry.<h4>Results</h4>For pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (-49.2%, 95% CI -56.1% to -41.1%, P = 3.1 × 10<sup>-18</sup>); in follow-up analyses, rs45446698-C was also associated with lower progesterone (-26.7%, 95% CI -39.4% to -11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82-0.91, P = 6.9 × 10<sup>-8</sup>).<h4>Conclusions</h4>The CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women.
We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.
<h4>Purpose</h4>Exome- and whole-genome sequencing of muscle-invasive bladder cancer has revealed important insights into the molecular landscape; however, there are few studies of non-muscle-invasive bladder cancer with detailed risk factor information.<h4>Experimental design</h4>We examined the relationship between smoking and other bladder cancer risk factors and somatic mutations and mutational signatures in bladder tumors. Targeted sequencing of frequently mutated genes in bladder cancer was conducted in 322 formalin-fixed paraffin-embedded bladder tumors from a population-based case-control study. Logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals (CI), evaluating mutations and risk factors. We used SignatureEstimation to extract four known single base substitution mutational signatures and Poisson regression to calculate risk ratios (RR) and 95% CIs, evaluating signatures and risk factors.<h4>Results</h4>Non-silent <i>KDM6A</i> mutations were more common in females than males (OR = 1.83; 95% CI, 1.05-3.19). There was striking heterogeneity in the relationship between smoking status and established single base substitution signatures: current smoking status was associated with greater <i>ERCC2-</i>Signature mutations compared with former (<i>P</i> = 0.024) and never smoking (RR = 1.40; 95% CI, 1.09-1.80; <i>P</i> = 0.008), former smoking was associated with greater APOBEC-Signature13 mutations (<i>P</i> = 0.05), and never smoking was associated with greater APOBEC-Signature2 mutations (RR = 1.54; 95% CI, 1.17-2.01; <i>P</i> = 0.002). There was evidence that smoking duration (the component most strongly associated with bladder cancer risk) was associated with <i>ERCC2-</i>Signature mutations and APOBEC-Signature13 mutations among current (<i>P</i> <sub>trend</sub> = 0.005) and former smokers (<i>P</i> = 0.0004), respectively.<h4>Conclusions</h4>These data quantify the contribution of bladder cancer risk factors to mutational burden and suggest different signature enrichments among never, former, and current smokers.
Epidemiologic studies often rely on questionnaire data, exposure measurement tools, and/or biomarkers to identify risk factors and the underlying carcinogenic processes. An emerging and promising complementary approach to investigate cancer etiology is the study of somatic "mutational signatures" that endogenous and exogenous processes imprint on the cellular genome. These signatures can be identified from a complex web of somatic mutations thanks to advances in DNA sequencing technology and analytical algorithms. This approach is at the core of the Sherlock-Lung study (2018-ongoing), a retrospective case-only study of over 2,000 lung cancers in never-smokers (LCINS), using different patterns of mutations observed within LCINS tumors to trace back possible exposures or endogenous processes. Whole genome and transcriptome sequencing, genome-wide methylation, microbiome, and other analyses are integrated with data from histological and radiological imaging, lifestyle, demographic characteristics, environmental and occupational exposures, and medical records to classify LCINS into subtypes that could reveal distinct risk factors. To date, we have received samples and data from 1,370 LCINS cases from 17 study sites worldwide and whole-genome sequencing has been completed on 1,257 samples. Here, we present the Sherlock-Lung study design and analytical strategy, also illustrating some empirical challenges and the potential for this approach in future epidemiologic studies.
<h4>Background</h4>Pancreatic cancer (PC) is a complex disease in which both non-genetic and genetic factors interplay. To date, 40 GWAS hits have been associated with PC risk in individuals of European descent, explaining 4.1% of the phenotypic variance.<h4>Methods</h4>We complemented a new conventional PC GWAS (1D) with genome spatial autocorrelation analysis (2D) permitting to prioritize low frequency variants not detected by GWAS. These were further expanded via Hi-C map (3D) interactions to gain additional insight into the inherited basis of PC. In silico functional analysis of public genomic information allowed prioritization of potentially relevant candidate variants.<h4>Results</h4>We identified several new variants located in genes for which there is experimental evidence of their implication in the biology and function of pancreatic acinar cells. Among them is a novel independent variant in NR5A2 (rs3790840) with a meta-analysis p value = 5.91E-06 in 1D approach and a Local Moran's Index (LMI) = 7.76 in 2D approach. We also identified a multi-hit region in CASC8-a lncRNA associated with pancreatic carcinogenesis-with a lowest p value = 6.91E-05. Importantly, two new PC loci were identified both by 2D and 3D approaches: SIAH3 (LMI = 18.24), CTRB2/BCAR1 (LMI = 6.03), in addition to a chromatin interacting region in XBP1-a major regulator of the ER stress and unfolded protein responses in acinar cells-identified by 3D; all of them with a strong in silico functional support.<h4>Conclusions</h4>This multi-step strategy, combined with an in-depth in silico functional analysis, offers a comprehensive approach to advance the study of PC genetic susceptibility and could be applied to other diseases.
<h4>Background</h4>The etiology of male breast cancer (MBC) is poorly understood. In particular, the extent to which the genetic basis of MBC differs from female breast cancer (FBC) is unknown. A previous genome-wide association study of MBC identified 2 predisposition loci for the disease, both of which were also associated with risk of FBC.<h4>Methods</h4>We performed genome-wide single nucleotide polymorphism genotyping of European ancestry MBC case subjects and controls in 3 stages. Associations between directly genotyped and imputed single nucleotide polymorphisms with MBC were assessed using fixed-effects meta-analysis of 1380 cases and 3620 controls. Replication genotyping of 810 cases and 1026 controls was used to validate variants with P values less than 1 × 10-06. Genetic correlation with FBC was evaluated using linkage disequilibrium score regression, by comprehensively examining the associations of published FBC risk loci with risk of MBC and by assessing associations between a FBC polygenic risk score and MBC. All statistical tests were 2-sided.<h4>Results</h4>The genome-wide association study identified 3 novel MBC susceptibility loci that attained genome-wide statistical significance (P < 5 × 10-08). Genetic correlation analysis revealed a strong shared genetic basis with estrogen receptor-positive FBC. Men in the top quintile of genetic risk had a fourfold increased risk of breast cancer relative to those in the bottom quintile (odds ratio = 3.86, 95% confidence interval = 3.07 to 4.87, P = 2.08 × 10-30).<h4>Conclusions</h4>These findings advance our understanding of the genetic basis of MBC, providing support for an overlapping genetic etiology with FBC and identifying a fourfold high-risk group of susceptible men.
<h4>Background</h4>Given the high heterogeneity among breast tumors, associations between common germline genetic variants and survival that may exist within specific subgroups could go undetected in an unstratified set of breast cancer patients.<h4>Methods</h4>We performed genome-wide association analyses within 15 subgroups of breast cancer patients based on prognostic factors, including hormone receptors, tumor grade, age, and type of systemic treatment. Analyses were based on 91,686 female patients of European ancestry from the Breast Cancer Association Consortium, including 7531 breast cancer-specific deaths over a median follow-up of 8.1 years. Cox regression was used to assess associations of common germline variants with 15-year and 5-year breast cancer-specific survival. We assessed the probability of these associations being true positives via the Bayesian false discovery probability (BFDP < 0.15).<h4>Results</h4>Evidence of associations with breast cancer-specific survival was observed in three patient subgroups, with variant rs5934618 in patients with grade 3 tumors (15-year-hazard ratio (HR) [95% confidence interval (CI)] 1.32 [1.20, 1.45], P = 1.4E-08, BFDP = 0.01, per G allele); variant rs4679741 in patients with ER-positive tumors treated with endocrine therapy (15-year-HR [95% CI] 1.18 [1.11, 1.26], P = 1.6E-07, BFDP = 0.09, per G allele); variants rs1106333 (15-year-HR [95% CI] 1.68 [1.39,2.03], P = 5.6E-08, BFDP = 0.12, per A allele) and rs78754389 (5-year-HR [95% CI] 1.79 [1.46,2.20], P = 1.7E-08, BFDP = 0.07, per A allele), in patients with ER-negative tumors treated with chemotherapy.<h4>Conclusions</h4>We found evidence of four loci associated with breast cancer-specific survival within three patient subgroups. There was limited evidence for the existence of associations in other patient subgroups. However, the power for many subgroups is limited due to the low number of events. Even so, our results suggest that the impact of common germline genetic variants on breast cancer-specific survival might be limited.
<h4>Background</h4>It is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype.<h4>Methods</h4>We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer-specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype.<h4>Results</h4>There was no evidence of heterogeneous associations between risk factors and mortality by subtype (<i>P</i> <sub>adj</sub> > 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5-25 kg/m<sup>2</sup> [HR (95% confidence interval (CI), 1.19 (1.06-1.34)]; current versus never smoking [1.37 (1.27-1.47)], high versus low physical activity [0.43 (0.21-0.86)], age ≥30 years versus <20 years at first pregnancy [0.79 (0.72-0.86)]; >0-<5 years versus ≥10 years since last full-term birth [1.31 (1.11-1.55)]; ever versus never use of oral contraceptives [0.91 (0.87-0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen-progestin therapy [0.61 (0.54-0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02-1.21) for current versus never smoking.<h4>Conclusions</h4>We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype.<h4>Impact</h4>Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.
<h4>Background</h4>The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) and the Tyrer-Cuzick breast cancer risk prediction models are commonly used in clinical practice and have recently been extended to include polygenic risk scores (PRS). In addition, BOADICEA has also been extended to include reproductive and lifestyle factors, which were already part of Tyrer-Cuzick model. We conducted a comparative prospective validation of these models after incorporating the recently developed 313-variant PRS.<h4>Methods</h4>Calibration and discrimination of 5-year absolute risk was assessed in a nested case-control sample of 1337 women of European ancestry (619 incident breast cancer cases) aged 23-75 years from the Generations Study.<h4>Results</h4>The extended BOADICEA model with reproductive/lifestyle factors and PRS was well calibrated across risk deciles; expected-to-observed ratio (E/O) at the highest risk decile :0.97 (95 % CI 0.51 - 1.86) for women younger than 50 years and 1.09 (0.66 - 1.80) for women 50 years or older. Adding reproductive/lifestyle factors and PRS to the BOADICEA model improved discrimination modestly in younger women (area under the curve (AUC) 69.7 % vs. 69.1%) and substantially in older women (AUC 64.6 % vs. 56.8%). The Tyrer-Cuzick model with PRS showed evidence of overestimation at the highest risk decile: E/O = 1.54(0.81 - 2.92) for younger and 1.73 (1.03 - 2.90) for older women.<h4>Conclusion</h4>The extended BOADICEA model identified women in a European-ancestry population at elevated breast cancer risk more accurately than the Tyrer-Cuzick model with PRS. With the increasing availability of PRS, these analyses can inform choice of risk models incorporating PRS for risk stratified breast cancer prevention among women of European ancestry.
<h4>Background</h4>Despite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk.<h4>Methods</h4>We applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy.<h4>Results</h4>Genetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07-1.30, P = 0.11 × 10<sup>-2</sup>), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78-1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect.<h4>Conclusion</h4>Our MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers.
Reproductive longevity is essential for fertility and influences healthy ageing in women<sup>1,2</sup>, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations<sup>3</sup>. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.
<h4>Background</h4>Although racial/ethnic disparities in U.S. COVID-19 death rates are striking, focusing on COVID-19 deaths alone may underestimate the true effect of the pandemic on disparities. Excess death estimates capture deaths both directly and indirectly caused by COVID-19.<h4>Objective</h4>To estimate U.S. excess deaths by racial/ethnic group.<h4>Design</h4>Surveillance study.<h4>Setting</h4>United States.<h4>Participants</h4>All decedents.<h4>Measurements</h4>Excess deaths and excess deaths per 100 000 persons from March to December 2020 were estimated by race/ethnicity, sex, age group, and cause of death, using provisional death certificate data from the Centers for Disease Control and Prevention (CDC) and U.S. Census Bureau population estimates.<h4>Results</h4>An estimated 2.88 million deaths occurred between March and December 2020. Compared with the number of expected deaths based on 2019 data, 477 200 excess deaths occurred during this period, with 74% attributed to COVID-19. Age-standardized excess deaths per 100 000 persons among Black, American Indian/Alaska Native (AI/AN), and Latino males and females were more than double those in White and Asian males and females. Non-COVID-19 excess deaths also disproportionately affected Black, AI/AN, and Latino persons. Compared with White males and females, non-COVID-19 excess deaths per 100 000 persons were 2 to 4 times higher in Black, AI/AN, and Latino males and females, including deaths due to diabetes, heart disease, cerebrovascular disease, and Alzheimer disease. Excess deaths in 2020 resulted in substantial widening of racial/ethnic disparities in all-cause mortality from 2019 to 2020.<h4>Limitations</h4>Completeness and availability of provisional CDC data; no estimates of precision around results.<h4>Conclusion</h4>There were profound racial/ethnic disparities in excess deaths in the United States in 2020 during the COVID-19 pandemic, resulting in rapid increases in racial/ethnic disparities in all-cause mortality between 2019 and 2020.<h4>Primary funding source</h4>National Institutes of Health Intramural Research Program.
Cancers are routinely classified into subtypes according to various features, including histopathological characteristics and molecular markers. Previous genome-wide association studies have reported heterogeneous associations between loci and cancer subtypes. However, it is not evident what is the optimal modeling strategy for handling correlated tumor features, missing data, and increased degrees-of-freedom in the underlying tests of associations. We propose to test for genetic associations using a mixed-effect two-stage polytomous model score test (MTOP). In the first stage, a standard polytomous model is used to specify all possible subtypes defined by the cross-classification of the tumor characteristics. In the second stage, the subtype-specific case-control odds ratios are specified using a more parsimonious model based on the case-control odds ratio for a baseline subtype, and the case-case parameters associated with tumor markers. Further, to reduce the degrees-of-freedom, we specify case-case parameters for additional exploratory markers using a random-effect model. We use the Expectation-Maximization algorithm to account for missing data on tumor markers. Through simulations across a range of realistic scenarios and data from the Polish Breast Cancer Study (PBCS), we show MTOP outperforms alternative methods for identifying heterogeneous associations between risk loci and tumor subtypes. The proposed methods have been implemented in a user-friendly and high-speed R statistical package called TOP (https://github.com/andrewhaoyu/TOP).
Lung cancer in never smokers (LCINS) is a common cause of cancer mortality but its genomic landscape is poorly characterized. Here high-coverage whole-genome sequencing of 232 LCINS showed 3 subtypes defined by copy number aberrations. The dominant subtype (piano), which is rare in lung cancer in smokers, features somatic UBA1 mutations, germline AR variants and stem cell-like properties, including low mutational burden, high intratumor heterogeneity, long telomeres, frequent KRAS mutations and slow growth, as suggested by the occurrence of cancer drivers' progenitor cells many years before tumor diagnosis. The other subtypes are characterized by specific amplifications and EGFR mutations (mezzo-forte) and whole-genome doubling (forte). No strong tobacco smoking signatures were detected, even in cases with exposure to secondhand tobacco smoke. Genes within the receptor tyrosine kinase-Ras pathway had distinct impacts on survival; five genomic alterations independently doubled mortality. These findings create avenues for personalized treatment in LCINS.
Cancer Informatics for Cancer Centers (CI4CC) is a grassroots, nonprofit 501c3 organization intended to provide a focused national forum for engagement of senior cancer informatics leaders, primarily aimed at academic cancer centers anywhere in the world but with a special emphasis on the 70 National Cancer Institute-funded cancer centers. Although each of the participating cancer centers is structured differently, and leaders' titles vary, we know firsthand there are similarities in both the issues we face and the solutions we achieve. As a consortium, we have initiated a dedicated listserv, an open-initiatives program, and targeted biannual face-to-face meetings. These meetings are a place to review our priorities and initiatives, providing a forum for discussion of the strategic and pragmatic issues we, as informatics leaders, individually face at our respective institutions and cancer centers. Here we provide a brief history of the CI4CC organization and meeting highlights from the latest CI4CC meeting that took place in Napa, California from October 14-16, 2019. The focus of this meeting was "intersections between informatics, data science, and population science." We conclude with a discussion on "hot topics" on the horizon for cancer informatics.
<h4>Background</h4>The relationship between germline genetic variation and breast cancer survival is largely unknown, especially in understudied minority populations who often have poorer survival. Genome-wide association studies (GWAS) have interrogated breast cancer survival but often are underpowered due to subtype heterogeneity and clinical covariates and detect loci in non-coding regions that are difficult to interpret. Transcriptome-wide association studies (TWAS) show increased power in detecting functionally relevant loci by leveraging expression quantitative trait loci (eQTLs) from external reference panels in relevant tissues. However, ancestry- or race-specific reference panels may be needed to draw correct inference in ancestrally diverse cohorts. Such panels for breast cancer are lacking.<h4>Results</h4>We provide a framework for TWAS for breast cancer in diverse populations, using data from the Carolina Breast Cancer Study (CBCS), a population-based cohort that oversampled black women. We perform eQTL analysis for 406 breast cancer-related genes to train race-stratified predictive models of tumor expression from germline genotypes. Using these models, we impute expression in independent data from CBCS and TCGA, accounting for sampling variability in assessing performance. These models are not applicable across race, and their predictive performance varies across tumor subtype. Within CBCS (N = 3,828), at a false discovery-adjusted significance of 0.10 and stratifying for race, we identify associations in black women near AURKA, CAPN13, PIK3CA, and SERPINB5 via TWAS that are underpowered in GWAS.<h4>Conclusions</h4>We show that carefully implemented and thoroughly validated TWAS is an efficient approach for understanding the genetics underpinning breast cancer outcomes in diverse populations.
Terminal duct lobular units (TDLUs) are the predominant anatomical structures where breast cancers originate. Having lesser degrees of age-related TDLU involution, measured as higher TDLUs counts or more epithelial TDLU substructures (acini), is related to increased breast cancer risk among women with benign breast disease (BBD). We evaluated whether a recently developed polygenic risk score (PRS) based on 313-common variants for breast cancer prediction is related to TDLU involution in the background, normal breast tissue, as this could provide mechanistic clues on the genetic predisposition to breast cancer. Among 1398 women without breast cancer, higher values of the PRS were significantly associated with higher TDLU counts (<i>P</i> = 0.004), but not with acini counts (<i>P</i> = 0.808), in histologically normal tissue samples from donors and diagnostic BBD biopsies. Mediation analysis indicated that TDLU counts may explain a modest proportion (≤10%) of the association of the 313-variant PRS with breast cancer risk. These findings suggest that TDLU involution might be an intermediate step in the association between common genetic variation and breast cancer risk.
Acquired mutations are pervasive across normal tissues. However, understanding of the processes that drive transformation of certain clones to cancer is limited. Here we study this phenomenon in the context of clonal hematopoiesis (CH) and the development of therapy-related myeloid neoplasms (tMNs). We find that mutations are selected differentially based on exposures. Mutations in ASXL1 are enriched in current or former smokers, whereas cancer therapy with radiation, platinum and topoisomerase II inhibitors preferentially selects for mutations in DNA damage response genes (TP53, PPM1D, CHEK2). Sequential sampling provides definitive evidence that DNA damage response clones outcompete other clones when exposed to certain therapies. Among cases in which CH was previously detected, the CH mutation was present at tMN diagnosis. We identify the molecular characteristics of CH that increase risk of tMN. The increasing implementation of clinical sequencing at diagnosis provides an opportunity to identify patients at risk of tMN for prevention strategies.
Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.
Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.
Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.
Higher proportions of early-onset and estrogen receptor (ER) negative cancers are observed in women of African ancestry than in women of European ancestry. Differences in risk factor distributions and associations by age at diagnosis and ER status may explain this disparity. We analyzed data from 1,126 cases (aged 18-74 years) with invasive breast cancer and 2,106 controls recruited from a population-based case-control study in Ghana. Odds ratios (OR) and 95% confidence intervals (CI) were estimated for menstrual and reproductive factors using polytomous logistic regression models adjusted for potential confounders. Among controls, medians for age at menarche, parity, age at first birth, and breastfeeding/pregnancy were 15 years, 4 births, 20 years and 18 months, respectively. For women ≥50 years, parity and extended breastfeeding were associated with decreased risks: >5 births vs. nulliparous, OR 0.40 (95% CI 0.20-0.83) and 0.71 (95% CI 0.51-0.98) for ≥19 vs. <13 breastfeeding months/pregnancy, which did not differ by ER. In contrast, for earlier onset cases (<50 years) parity was associated with increased risk for ER-negative tumors (p-heterogeneity by ER = 0.02), which was offset by extended breastfeeding. Similar associations were observed by intrinsic-like subtypes. Less consistent relationships were observed with ages at menarche and first birth. Reproductive risk factor distributions are different from European populations but exhibited etiologic heterogeneity by age at diagnosis and ER status similar to other populations. Differences in reproductive patterns and subtype heterogeneity are consistent with racial disparities in subtype distributions.
<h4>Background</h4>Three tools are currently available to predict the risk of contralateral breast cancer (CBC). We aimed to compare the performance of the Manchester formula, CBCrisk, and PredictCBC in patients with invasive breast cancer (BC).<h4>Methods</h4>We analyzed data of 132,756 patients (4682 CBC) from 20 international studies with a median follow-up of 8.8 years. Prediction performance included discrimination, quantified as a time-dependent Area-Under-the-Curve (AUC) at 5 and 10 years after diagnosis of primary BC, and calibration, quantified as the expected-observed (E/O) ratio at 5 and 10 years and the calibration slope.<h4>Results</h4>The AUC at 10 years was: 0.58 (95% confidence intervals [CI] 0.57-0.59) for CBCrisk; 0.60 (95% CI 0.59-0.61) for the Manchester formula; 0.63 (95% CI 0.59-0.66) and 0.59 (95% CI 0.56-0.62) for PredictCBC-1A (for settings where BRCA1/2 mutation status is available) and PredictCBC-1B (for the general population), respectively. The E/O at 10 years: 0.82 (95% CI 0.51-1.32) for CBCrisk; 1.53 (95% CI 0.63-3.73) for the Manchester formula; 1.28 (95% CI 0.63-2.58) for PredictCBC-1A and 1.35 (95% CI 0.65-2.77) for PredictCBC-1B. The calibration slope was 1.26 (95% CI 1.01-1.50) for CBCrisk; 0.90 (95% CI 0.79-1.02) for PredictCBC-1A; 0.81 (95% CI 0.63-0.99) for PredictCBC-1B, and 0.39 (95% CI 0.34-0.43) for the Manchester formula.<h4>Conclusions</h4>Current CBC risk prediction tools provide only moderate discrimination and the Manchester formula was poorly calibrated. Better predictors and re-calibration are needed to improve CBC prediction and to identify low- and high-CBC risk patients for clinical decision-making.
<h4>Background</h4>Previous gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions.<h4>Methods</h4>Analyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions.<h4>Results</h4>Noteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth.<h4>Conclusions</h4>Overall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.
<h4>Background</h4>The International Agency for Research on Cancer (IARC) classifies diesel engine exhaust as carcinogenic to humans based on sufficient evidence for lung cancer. IARC noted, however, an increased risk of bladder cancer (based on limited evidence).<h4>Objective</h4>To evaluate the association between quantitative, lifetime occupational diesel exhaust exposure and risk of urothelial cell carcinoma of the bladder (UBC) overall and according to pathological subtypes.<h4>Methods</h4>Data from personal interviews with 1944 UBC cases, as well as formalin-fixed paraffin-embedded tumor tissue blocks, and 2135 controls were pooled from two case-control studies conducted in the U.S. and Spain. Lifetime occupational histories combined with exposure-oriented questions were used to estimate cumulative exposure to respirable elemental carbon (REC), a primary surrogate for diesel exhaust. Unconditional logistic regression and two-stage polytomous logistic regression were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for smoking and other risk factors.<h4>Results</h4>Exposure to cumulative REC was associated with an increased risk of UBC; workers with cumulative REC >396 μg/m<sup>3</sup>-years had an OR of 1.61 (95% CI, 1.08-2.40). At this level of cumulative exposure, similar results were observed in the U.S. and Spain, OR = 1.75 (95% CI, 0.97-3.15) and OR = 1.54 (95% CI, 0.89-2.68), respectively. In lagged analysis, we also observed a consistent increased risk among workers with cumulative REC >396 μg/m<sup>3</sup>-years (range of ORs = 1.52-1.93) for all lag intervals evaluated (5-40 years). When we accounted for tumor subtypes defined by stage and grade, a significant association between diesel exhaust exposure and UBC was apparent (global test for association p = 0.0019).<h4>Conclusions</h4>Combining data from two large epidemiologic studies, our results provide further evidence that diesel exhaust exposure increases the risk of UBC.
Previous research has shown that polygenic risk scores (PRSs) can be used to stratify women according to their risk of developing primary invasive breast cancer. This study aimed to evaluate the association between a recently validated PRS of 313 germline variants (PRS<sub>313</sub>) and contralateral breast cancer (CBC) risk. We included 56,068 women of European ancestry diagnosed with first invasive breast cancer from 1990 onward with follow-up from the Breast Cancer Association Consortium. Metachronous CBC risk (N = 1,027) according to the distribution of PRS<sub>313</sub> was quantified using Cox regression analyses. We assessed PRS<sub>313</sub> interaction with age at first diagnosis, family history, morphology, ER status, PR status, and HER2 status, and (neo)adjuvant therapy. In studies of Asian women, with limited follow-up, CBC risk associated with PRS<sub>313</sub> was assessed using logistic regression for 340 women with CBC compared with 12,133 women with unilateral breast cancer. Higher PRS<sub>313</sub> was associated with increased CBC risk: hazard ratio per standard deviation (SD) = 1.25 (95%CI = 1.18-1.33) for Europeans, and an OR per SD = 1.15 (95%CI = 1.02-1.29) for Asians. The absolute lifetime risks of CBC, accounting for death as competing risk, were 12.4% for European women at the 10<sup>th</sup> percentile and 20.5% at the 90<sup>th</sup> percentile of PRS<sub>313</sub>. We found no evidence of confounding by or interaction with individual characteristics, characteristics of the primary tumor, or treatment. The C-index for the PRS<sub>313</sub> alone was 0.563 (95%CI = 0.547-0.586). In conclusion, PRS<sub>313</sub> is an independent factor associated with CBC risk and can be incorporated into CBC risk prediction models to help improve stratification and optimize surveillance and treatment strategies.
In breast cancer, high levels of homeobox protein Hox-B13 (HOXB13) have been associated with disease progression of ER-positive breast cancer patients and resistance to tamoxifen treatment. Since HOXB13 p.G84E is a prostate cancer risk allele, we evaluated the association between HOXB13 germline mutations and breast cancer risk in a previous study consisting of 3,270 familial non-BRCA1/2 breast cancer cases and 2,327 controls from the Netherlands. Although both recurrent HOXB13 mutations p.G84E and p.R217C were not associated with breast cancer risk, the risk estimation for p.R217C was not very precise. To provide more conclusive evidence regarding the role of HOXB13 in breast cancer susceptibility, we here evaluated the association between HOXB13 mutations and increased breast cancer risk within 81 studies of the international Breast Cancer Association Consortium containing 68,521 invasive breast cancer patients and 54,865 controls. Both HOXB13 p.G84E and p.R217C did not associate with the development of breast cancer in European women, neither in the overall analysis (OR = 1.035, 95% CI = 0.859-1.246, P = 0.718 and OR = 0.798, 95% CI = 0.482-1.322, P = 0.381 respectively), nor in specific high-risk subgroups or breast cancer subtypes. Thus, although involved in breast cancer progression, HOXB13 is not a material breast cancer susceptibility gene.
While genome-wide association studies have identified susceptibility variants for numerous traits, their combined utility for predicting broad measures of health, such as mortality, remains poorly understood. We used data from the UK Biobank to combine polygenic risk scores (PRS) for 13 diseases and 12 mortality risk factors into sex-specific composite PRS (cPRS). These cPRS were moderately associated with all-cause mortality in independent data within the UK Biobank: the estimated hazard ratios per standard deviation were 1.10 (95% confidence interval: 1.05, 1.16) and 1.15 (1.10, 1.19) for women and men, respectively. Differences in life expectancy between the top and bottom 5% of the cPRS were estimated to be 4.79 (1.76, 7.81) years and 6.75 (4.16, 9.35) years for women and men, respectively. These associations were substantially attenuated after adjusting for non-genetic mortality risk factors measured at study entry (i.e., middle age for most participants). The cPRS may be useful in counseling younger individuals at higher genetic risk of mortality on modification of non-genetic factors.
<h4>Background</h4>Median overall survival (OS) for women with high-grade serous ovarian cancer (HGSOC) is ∼4 years, yet survival varies widely between patients. There are no well-established, gene expression signatures associated with prognosis. The aim of this study was to develop a robust prognostic signature for OS in patients with HGSOC.<h4>Patients and methods</h4>Expression of 513 genes, selected from a meta-analysis of 1455 tumours and other candidates, was measured using NanoString technology from formalin-fixed paraffin-embedded tumour tissue collected from 3769 women with HGSOC from multiple studies. Elastic net regularization for survival analysis was applied to develop a prognostic model for 5-year OS, trained on 2702 tumours from 15 studies and evaluated on an independent set of 1067 tumours from six studies.<h4>Results</h4>Expression levels of 276 genes were associated with OS (false discovery rate < 0.05) in covariate-adjusted single-gene analyses. The top five genes were TAP1, ZFHX4, CXCL9, FBN1 and PTGER3 (P < 0.001). The best performing prognostic signature included 101 genes enriched in pathways with treatment implications. Each gain of one standard deviation in the gene expression score conferred a greater than twofold increase in risk of death [hazard ratio (HR) 2.35, 95% confidence interval (CI) 2.02-2.71; P < 0.001]. Median survival [HR (95% CI)] by gene expression score quintile was 9.5 (8.3 to -), 5.4 (4.6-7.0), 3.8 (3.3-4.6), 3.2 (2.9-3.7) and 2.3 (2.1-2.6) years.<h4>Conclusion</h4>The OTTA-SPOT (Ovarian Tumor Tissue Analysis consortium - Stratified Prognosis of Ovarian Tumours) gene expression signature may improve risk stratification in clinical trials by identifying patients who are least likely to achieve 5-year survival. The identified novel genes associated with the outcome may also yield opportunities for the development of targeted therapeutic approaches.
This report describes an R package, called the Individualized Coherent Absolute Risk Estimator (iCARE) tool, that allows researchers to build and evaluate models for absolute risk and apply them to estimate an individual's risk of developing disease during a specified time interval based on a set of user defined input parameters. An attractive feature of the software is that it gives users flexibility to update models rapidly based on new knowledge on risk factors and tailor models to different populations by specifying three input arguments: a model for relative risk, an age-specific disease incidence rate and the distribution of risk factors for the population of interest. The tool can handle missing information on risk factors for individuals for whom risks are to be predicted using a coherent approach where all estimates are derived from a single model after appropriate model averaging. The software allows single nucleotide polymorphisms (SNPs) to be incorporated into the model using published odds ratios and allele frequencies. The validation component of the software implements the methods for evaluation of model calibration, discrimination and risk-stratification based on independent validation datasets. We provide an illustration of the utility of iCARE for building, validating and applying absolute risk models using breast cancer as an example.
<h4>Background</h4>External validation of risk models is critical for risk-stratified breast cancer prevention. We used the Individualized Coherent Absolute Risk Estimation (iCARE) as a flexible tool for risk model development and comparative model validation and to make projections for population risk stratification.<h4>Methods</h4>Performance of two recently developed models, one based on the Breast and Prostate Cancer Cohort Consortium analysis (iCARE-BPC3) and another based on a literature review (iCARE-Lit), were compared with two established models (Breast Cancer Risk Assessment Tool and International Breast Cancer Intervention Study Model) based on classical risk factors in a UK-based cohort of 64 874 white non-Hispanic women (863 patients) age 35-74 years. Risk projections in a target population of US white non-Hispanic women age 50-70 years assessed potential improvements in risk stratification by adding mammographic breast density (MD) and polygenic risk score (PRS).<h4>Results</h4>The best calibrated models were iCARE-Lit (expected to observed number of cases [E/O] = 0.98, 95% confidence interval [CI] = 0.87 to 1.11) for women younger than 50 years, and iCARE-BPC3 (E/O = 1.00, 95% CI = 0.93 to 1.09) for women 50 years or older. Risk projections using iCARE-BPC3 indicated classical risk factors can identify approximately 500 000 women at moderate to high risk (>3% 5-year risk) in the target population. Addition of MD and a 313-variant PRS is expected to increase this number to approximately 3.5 million women, and among them, approximately 153 000 are expected to develop invasive breast cancer within 5 years.<h4>Conclusions</h4>iCARE models based on classical risk factors perform similarly to or better than BCRAT or IBIS in white non-Hispanic women. Addition of MD and PRS can lead to substantial improvements in risk stratification. However, these integrated models require independent prospective validation before broad clinical applications.
The European Collaborative on Personalized Early Detection and Prevention of Breast Cancer (ENVISION) brings together several international research consortia working on different aspects of the personalized early detection and prevention of breast cancer. In a consensus conference held in 2019, the members of this network identified research areas requiring development to enable evidence-based personalized interventions that might improve the benefits and reduce the harms of existing breast cancer screening and prevention programmes. The priority areas identified were: 1) breast cancer subtype-specific risk assessment tools applicable to women of all ancestries; 2) intermediate surrogate markers of response to preventive measures; 3) novel non-surgical preventive measures to reduce the incidence of breast cancer of poor prognosis; and 4) hybrid effectiveness-implementation research combined with modelling studies to evaluate the long-term population outcomes of risk-based early detection strategies. The implementation of such programmes would require health-care systems to be open to learning and adapting, the engagement of a diverse range of stakeholders and tailoring to societal norms and values, while also addressing the ethical and legal issues. In this Consensus Statement, we discuss the current state of breast cancer risk prediction, risk-stratified prevention and early detection strategies, and their implementation. Throughout, we highlight priorities for advancing each of these areas.
A small number of circulating proteins have been reported to be associated with breast cancer risk, with inconsistent results. Herein, we attempted to identify novel protein biomarkers for breast cancer via the integration of genomics and proteomics data. In the Breast Cancer Association Consortium (BCAC), with 122,977 cases and 105,974 controls of European descendants, we evaluated the associations of the genetically predicted concentrations of >1,400 circulating proteins with breast cancer risk. We used data from a large-scale protein quantitative trait loci (pQTL) analysis as our study instrument. Summary statistics for these pQTL variants related to breast cancer risk were obtained from the BCAC and used to estimate odds ratios (OR) for each protein using the inverse-variance weighted method. We identified 56 proteins significantly associated with breast cancer risk by instrumental analysis (false discovery rate <0.05). Of these, the concentrations of 32 were influenced by variants close to a breast cancer susceptibility locus (ABO, 9q34.2). Many of these proteins, such as insulin receptor, insulin-like growth factor receptor 1 and other membrane receptors (OR: 0.82-1.18, p values: 6.96 × 10<sup>-4</sup> -3.28 × 10<sup>-8</sup> ), are linked to insulin resistance and estrogen receptor signaling pathways. Proteins identified at other loci include those involved in biological processes such as alcohol and lipid metabolism, proteolysis, apoptosis, immune regulation and cell motility and proliferation. Consistent associations were observed for 22 proteins in the UK Biobank data (p < 0.05). The study identifies potential novel biomarkers for breast cancer, but further investigation is needed to replicate our findings.
Known risk variants explain only a small proportion of breast cancer heritability, particularly in Asian women. To search for additional genetic susceptibility loci for breast cancer, here we perform a meta-analysis of data from genome-wide association studies (GWAS) conducted in Asians (24,206 cases and 24,775 controls) and European descendants (122,977 cases and 105,974 controls). We identified 31 potential novel loci with the lead variant showing an association with breast cancer risk at P < 5 × 10<sup>-8</sup>. The associations for 10 of these loci were replicated in an independent sample of 16,787 cases and 16,680 controls of Asian women (P < 0.05). In addition, we replicated the associations for 78 of the 166 known risk variants at P < 0.05 in Asians. These findings improve our understanding of breast cancer genetics and etiology and extend previous findings from studies of European descendants to Asian women.
Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype<sup>1-3</sup>. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10<sup>-8</sup>), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.
Genome-wide association studies (GWAS) have led to the identification of hundreds of susceptibility loci across cancers, but the impact of further studies remains uncertain. Here we analyse summary-level data from GWAS of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) and underlying effect-size distribution. All cancers show a high degree of polygenicity, involving at a minimum of thousands of loci. We project that sample sizes required to explain 80% of GWAS heritability vary from 60,000 cases for testicular to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores (PRS), compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that PRS have potential for risk stratification for cancers of breast, colon and prostate, but less so for others because of modest heritability and lower incidence.
Although most women with luminal breast cancer do well on endocrine therapy alone, some will develop fatal recurrence thereby necessitating the need to prospectively determine those for whom additional cytotoxic therapy will be beneficial. Categorical combinations of immunohistochemical measures of ER, PR, HER2, and KI67 are traditionally used to classify patients into luminal A-like and B-like subtypes for chemotherapeutic reasons, but this may lead to the loss of prognostically relevant information. Here, we compared the prognostic value of quantitative measures of these markers, combined in the IHC4-score, to categorical combinations in subtypes. Using image analysis-based scores for all four markers, we computed the IHC4-score for 2498 patients with luminal breast cancer from two European study populations. We defined subtypes (A-like (ER + and PR + : and HER2- and low KI67) and B-like (ER + and/or PR + : and HER2 + or high KI67)) by combining binary categories of these markers. Hazard ratios and 95% confidence intervals for associations with 10-year breast cancer-specific survival were estimated in Cox proportional-hazard models. We accounted for clinical prognostic factors, including grade, tumor size, lymph-nodal involvement, and age, by using the PREDICT-score. Overall, Subtypes [hazard ratio (95% confidence interval) B-like vs. A-like = 1.64 (1.25-2.14); P-value < 0.001] and IHC4-score [hazard ratio (95% confidence interval)/1 standard deviation = 1.32 (1.20-1.44); P-value < 0.001] were prognostic in univariable models. However, IHC4-score [hazard ratio (95% confidence interval)/1 standard deviation = 1.24 (1.11-1.37); P-value < 0.001; likelihood ratio chi-square (LRχ<sup>2</sup>) = 12.5] provided more prognostic information than Subtype [hazard ratio (95% confidence interval) B-like vs. A-like = 1.38 (1.02-1.88); P-value = 0.04; LRχ<sup>2 </sup>= 4.3] in multivariable models. Further, higher values of the IHC4-score were associated with worse prognosis, regardless of subtype (P-heterogeneity = 0.97). These findings enhance the value of the IHC4-score as an adjunct to clinical prognostication tools for aiding chemotherapy decision-making in luminal breast cancer patients, irrespective of subtype.
<h4>Background</h4>Environmental and genetic factors play an important role in the etiology of breast cancer. Several small blood-based DNA methylation studies have reported risk associations with methylation at individual CpGs and average methylation levels; however, these findings require validation in larger prospective cohort studies. To investigate the role of blood DNA methylation on breast cancer risk, we conducted a meta-analysis of four prospective cohort studies, including a total of 1663 incident cases and 1885 controls, the largest study of blood DNA methylation and breast cancer risk to date.<h4>Methods</h4>We assessed associations with methylation at 365,145 CpGs present in the HumanMethylation450 (HM450K) Beadchip, after excluding CpGs that did not pass quality controls in all studies. Each of the four cohorts estimated odds ratios (ORs) and 95% confidence intervals (CI) for the association between each individual CpG and breast cancer risk. In addition, each study assessed the association between average methylation measures and breast cancer risk, adjusted and unadjusted for cell-type composition. Study-specific ORs were combined using fixed-effect meta-analysis with inverse variance weights. Stratified analyses were conducted by age at diagnosis (< 50, ≥ 50), estrogen receptor (ER) status (+/-), and time since blood collection (< 5, 5-10, > 10 years). The false discovery rate (q value) was used to account for multiple testing.<h4>Results</h4>The average age at blood draw ranged from 52.2 to 62.2 years across the four cohorts. Median follow-up time ranged from 6.6 to 8.4 years. The methylation measured at individual CpGs was not associated with breast cancer risk (q value > 0.59). In addition, higher average methylation level was not associated with risk of breast cancer (OR = 0.94, 95% CI = 0.85, 1.05; P = 0.26; P for study heterogeneity = 0.86). We found no evidence of modification of this association by age at diagnosis (P = 0.17), ER status (P = 0.88), time since blood collection (P = 0.98), or CpG location (P = 0.98).<h4>Conclusions</h4>Our data indicate that DNA methylation measured in the blood prior to breast cancer diagnosis in predominantly postmenopausal women is unlikely to be associated with substantial breast cancer risk on the HM450K array. Larger studies or with greater methylation coverage are needed to determine if associations exist between blood DNA methylation and breast cancer risk.
An important premise of epidemiology is that individuals with the same disease share similar underlying etiologies and clinical outcomes. In the past few decades, our knowledge of disease pathogenesis has improved, and disease classification systems have evolved to the point where no complex disease processes are considered homogenous. As a result, pathology and epidemiology have been integrated into the single, unified field of molecular pathological epidemiology (MPE). Advancing integrative molecular and population-level health sciences and addressing the unique research challenges specific to the field of MPE necessitates assembling experts in diverse fields, including epidemiology, pathology, biostatistics, computational biology, bioinformatics, genomics, immunology, and nutritional and environmental sciences. Integrating these seemingly divergent fields can lead to a greater understanding of pathogenic processes. The International MPE Meeting Series fosters discussion that addresses the specific research questions and challenges in this emerging field. The purpose of the meeting series is to: discuss novel methods to integrate pathology and epidemiology; discuss studies that provide pathogenic insights into population impact; and educate next-generation scientists. Herein, we share the proceedings of the Fourth International MPE Meeting, held in Boston, MA, USA, on 30 May-1 June, 2018. Major themes of this meeting included 'integrated genetic and molecular pathologic epidemiology', 'immunology-MPE', and 'novel disease phenotyping'. The key priority areas for future research identified by meeting attendees included integration of tumor immunology and cancer disparities into epidemiologic studies, further collaboration between computational and population-level scientists to gain new insight on exposure-disease associations, and future pooling projects of studies with comparable data.
Fanconi anemia (FA) is a genetically heterogeneous disorder with 22 disease-causing genes reported to date. In some FA genes, monoallelic mutations have been found to be associated with breast cancer risk, while the risk associations of others remain unknown. The gene for FA type C, FANCC, has been proposed as a breast cancer susceptibility gene based on epidemiological and sequencing studies. We used the Oncoarray project to genotype two truncating FANCC variants (p.R185X and p.R548X) in 64,760 breast cancer cases and 49,793 controls of European descent. FANCC mutations were observed in 25 cases (14 with p.R185X, 11 with p.R548X) and 26 controls (18 with p.R185X, 8 with p.R548X). There was no evidence of an association with the risk of breast cancer, neither overall (odds ratio 0.77, 95%CI 0.44-1.33, p = 0.4) nor by histology, hormone receptor status, age or family history. We conclude that the breast cancer risk association of these two FANCC variants, if any, is much smaller than for BRCA1, BRCA2 or PALB2 mutations. If this applies to all truncating variants in FANCC it would suggest there are differences between FA genes in their roles on breast cancer risk and demonstrates the merit of large consortia for clarifying risk associations of rare variants.
<h4>Background</h4>We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry.<h4>Methods</h4>Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP).<h4>Results</h4>We did not find any variant associated with breast cancer-specific mortality at P < 5 × 10<sup>-8</sup>. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10<sup>-7</sup>, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84-0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10<sup>-7</sup>, HR = 1.27, 95% CI = 1.16-1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster.<h4>Conclusions</h4>We uncovered germline variants on chromosome 7 at BFDP < 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients.
Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.
Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes <i>BRCA1</i>, <i>BRCA2</i>, <i>PALB2</i>, <i>ATM</i>, and <i>CHEK2</i> are associated with breast cancer risk. <i>FANCM</i>, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants <i>FANCM</i>:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of <i>BRCA1</i> or <i>BRCA2</i>. These three variants were also studied functionally by measuring survival and chromosome fragility in <i>FANCM</i> <sup><i>-/-</i></sup> patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that <i>FANCM</i>:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, <i>P</i> = 0.034 and OR = 3.79; <i>P</i> = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for <i>FANCM</i>:p.Arg658* and found that also <i>FANCM</i>:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; <i>P</i> = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with <i>FANCM</i>:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare <i>FANCM</i> deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat <i>FANCM</i>-associated tumors.
<h4>Background</h4>Breast cancer survivors are at risk for contralateral breast cancer (CBC), with the consequent burden of further treatment and potentially less favorable prognosis. We aimed to develop and validate a CBC risk prediction model and evaluate its applicability for clinical decision-making.<h4>Methods</h4>We included data of 132,756 invasive non-metastatic breast cancer patients from 20 studies with 4682 CBC events and a median follow-up of 8.8 years. We developed a multivariable Fine and Gray prediction model (PredictCBC-1A) including patient, primary tumor, and treatment characteristics and BRCA1/2 germline mutation status, accounting for the competing risks of death and distant metastasis. We also developed a model without BRCA1/2 mutation status (PredictCBC-1B) since this information was available for only 6% of patients and is routinely unavailable in the general breast cancer population. Prediction performance was evaluated using calibration and discrimination, calculated by a time-dependent area under the curve (AUC) at 5 and 10 years after diagnosis of primary breast cancer, and an internal-external cross-validation procedure. Decision curve analysis was performed to evaluate the net benefit of the model to quantify clinical utility.<h4>Results</h4>In the multivariable model, BRCA1/2 germline mutation status, family history, and systemic adjuvant treatment showed the strongest associations with CBC risk. The AUC of PredictCBC-1A was 0.63 (95% prediction interval (PI) at 5 years, 0.52-0.74; at 10 years, 0.53-0.72). Calibration-in-the-large was -0.13 (95% PI: -1.62-1.37), and the calibration slope was 0.90 (95% PI: 0.73-1.08). The AUC of Predict-1B at 10 years was 0.59 (95% PI: 0.52-0.66); calibration was slightly lower. Decision curve analysis for preventive contralateral mastectomy showed potential clinical utility of PredictCBC-1A between thresholds of 4-10% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers.<h4>Conclusions</h4>We developed a reasonably calibrated model to predict the risk of CBC in women of European-descent; however, prediction accuracy was moderate. Our model shows potential for improved risk counseling, but decision-making regarding contralateral preventive mastectomy, especially in the general breast cancer population where limited information of the mutation status in BRCA1/2 is available, remains challenging.
<h4>Purpose</h4>In post-menopausal women, high body mass index (BMI) is an established breast cancer risk factor and is associated with worse breast cancer prognosis. We assessed the associations between BMI and gene expression of both breast tumor and adjacent tissue in estrogen receptor-positive (ER+) and estrogen receptor-negative (ER-) diseases to help elucidate the mechanisms linking obesity with breast cancer biology in 519 post-menopausal women from the Nurses' Health Study (NHS) and NHSII.<h4>Methods</h4>Differential gene expression was analyzed separately in ER+ and ER- disease both comparing overweight (BMI ≥ 25 to < 30) or obese (BMI ≥ 30) women to women with normal BMI (BMI < 25), and per 5 kg/m<sup>2</sup> increase in BMI. Analyses controlled for age and year of diagnosis, physical activity, alcohol consumption, and hormone therapy use. Gene set enrichment analyses were performed and validated among a subset of post-menopausal cases in The Cancer Genome Atlas (for tumor) and Polish Breast Cancer Study (for tumor-adjacent).<h4>Results</h4>No gene was differentially expressed by BMI (FDR < 0.05). BMI was significantly associated with increased cellular proliferation pathways, particularly in ER+ tumors, and increased inflammation pathways in ER- tumor and ER- tumor-adjacent tissues (FDR < 0.05). High BMI was associated with upregulation of genes involved in epithelial-mesenchymal transition in ER+ tumor-adjacent tissues.<h4>Conclusions</h4>This study provides insights into molecular mechanisms of BMI influencing post-menopausal breast cancer biology. Tumor and tumor-adjacent tissues provide independent information about potential mechanisms.
Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r<sub>g</sub> = 0.57, p = 4.6 × 10<sup>-8</sup>), breast and ovarian cancer (r<sub>g</sub> = 0.24, p = 7 × 10<sup>-5</sup>), breast and lung cancer (r<sub>g</sub> = 0.18, p =1.5 × 10<sup>-6</sup>) and breast and colorectal cancer (r<sub>g</sub> = 0.15, p = 1.1 × 10<sup>-4</sup>). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
<h4>Purpose</h4>Breast cancer (BC) risk prediction allows systematic identification of individuals at highest and lowest risk. We extend the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk model to incorporate the effects of polygenic risk scores (PRS) and other risk factors (RFs).<h4>Methods</h4>BOADICEA incorporates the effects of truncating variants in BRCA1, BRCA2, PALB2, CHEK2, and ATM; a PRS based on 313 single-nucleotide polymorphisms (SNPs) explaining 20% of BC polygenic variance; a residual polygenic component accounting for other genetic/familial effects; known lifestyle/hormonal/reproductive RFs; and mammographic density, while allowing for missing information.<h4>Results</h4>Among all factors considered, the predicted UK BC risk distribution is widest for the PRS, followed by mammographic density. The highest BC risk stratification is achieved when all genetic and lifestyle/hormonal/reproductive/anthropomorphic factors are considered jointly. With all factors, the predicted lifetime risks for women in the UK population vary from 2.8% for the 1st percentile to 30.6% for the 99th percentile, with 14.7% of women predicted to have a lifetime risk of ≥17-<30% (moderate risk according to National Institute for Health and Care Excellence [NICE] guidelines) and 1.1% a lifetime risk of ≥30% (high risk).<h4>Conclusion</h4>This comprehensive model should enable high levels of BC risk stratification in the general population and women with family history, and facilitate individualized, informed decision-making on prevention therapies and screening.
Mosaic protein truncating variants (PTVs) in the phosphatase, Mg2+/Mn2+dependent 1D (PPM1D) gene in blood-derived DNA have been associated with increased risk of breast cancer. We analyzed PPM1D PTVs in blood from 3817 breast cancer cases and 3058 controls by deep sequencing of a previously defined region in exon 6 of PPM1D. We identified 50 of 6875 (0.73%) participants having a mosaic PPM1D PTV. We observed a higher frequency of mosaic PPM1D PTVs with increasing age (P<sub>trend</sub> = 2.9 × 10<sup>-6</sup>). We did not observe an overall association between PPM1D PTVs and increased breast cancer risk (OR = 1.51, 95% CI = 0.84-2.71). Evidence for an association was observed in a subset of cases with DNA collected 1-year or more before breast cancer diagnosis (OR = 3.44, 95% CI = 1.62-7.30, P-value = 0.001); however, no significant association was observed for the larger series of cases with DNA collected post diagnosis (OR = 1.01, 95% CI = 0.51-2.01, P-value = 0.98). Our study indicates that the PPM1D PTVs are present at higher rates than previously reported and the frequency of PPM1D PTVs increases with age. We observed limited evidence for an association between mosaic PPM1D PTVs and breast cancer risk, suggesting mosaic PPM1D PTVs in the blood likely do not influence risk of breast cancer.
Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.
Primary ovarian mucinous tumors can be difficult to distinguish from metastatic gastrointestinal neoplasms by histology alone. The expected immunoprofile of a suspected metastatic lower gastrointestinal tumor is CK7<sup>-</sup>/CK20<sup>+</sup>/CDX2<sup>+</sup>/PAX8<sup>-</sup>. This study assesses the addition of a novel marker SATB2, to improve the diagnostic algorithm. A test cohort included 155 ovarian mucinous tumors (105 carcinomas and 50 borderline tumors) and 230 primary lower gastrointestinal neoplasms (123 colorectal adenocarcinomas and 107 appendiceal neoplasms). All cases were assessed for SATB2, PAX8 CK7, CK20, and CDX2 expression on tissue microarrays. Expression was scored in a 3-tier system as absent, focal (1-50% of tumor cells) and diffuse ( >50% of tumor cells) and then categorized into either absent/present or nondiffuse/diffuse. SATB2 and PAX8 expression was further evaluated in ovarian tumors from an international cohort of 2876 patients (expansion cohort, including 159 mucinous carcinomas and 46 borderline mucinous tumors). The highest accuracy of an individual marker in distinguishing lower gastrointestinal from ovarian mucinous tumors was CK7 (91.7%, nondiffuse/diffuse cut-off) followed by SATB2 (88.8%, present/absent cut-off). The most effective combination was CK7 and SATB2 with accuracy of 95.3% using the 3-tier interpretation, absent/focal/diffuse. This combination outperformed the standard clinical set of CK7, CK20 and CDX2 (87.5%). Re-evaluation of outlier cases confirmed ovarian origin for all but one case. The accuracy of SATB2 was confirmed in the expansion cohort (91.5%). SATB2 expression was also detected in 15% of ovarian endometrioid carcinoma but less than 5% of other ovarian histotypes. A simple two marker combination of CK7 and SATB2 can distinguish lower gastrointestinal from ovarian primary mucinous tumors with greater than 95% accuracy. PAX8 and CDX2 have value as second-line markers. The utility of CK20 in this setting is low and this warrants replacement of this marker with SATB2 in clinical practice.
<h4>Background</h4>In case-control studies, population controls can help ensure generalizability; however, the selection of population controls can be challenging in environments that lack population registries. We developed a population enumeration and sampling strategy to facilitate use of population controls in a breast cancer case-control study conducted in Ghana.<h4>Methods</h4>Household enumeration was conducted in 110 census-defined geographic areas within Ghana's Ashanti, Central, Eastern, and Greater Accra Regions. A pool of potential controls (women aged 18 to 74 years, never diagnosed with breast cancer) was selected from the enumeration using systematic random sampling and frequency-matched to the anticipated distributions of age and residence among cases. Multiple attempts were made to contact potential controls to assess eligibility and arrange for study participation. To increase participation, we implemented a refusal conversion protocol in which initial non-participants were re-approached after several months.<h4>Results</h4>2,528 women were sampled from the enumeration listing, 2,261 (89%) were successfully contacted, and 2,106 were enrolled (overall recruitment of 83%). 170 women were enrolled through refusal conversion. Compared with women enrolled after being first approached, refusal conversion enrollees were younger and less likely to complete the study interview in the study hospital (13% vs. 23%). The most common reasons for non-participation were lack of interest and lack of time.<h4>Conclusions</h4>Using household enumeration and repeated contacts, we were able to recruit population controls with a high participation rate. Our approach may provide a blue-print for others undertaking epidemiologic studies in populations that lack accessible population registries.
<h4>Background</h4>In addition to the established association between general obesity and breast cancer risk, central obesity and circulating fasting insulin and glucose have been linked to the development of this common malignancy. Findings from previous studies, however, have been inconsistent, and the nature of the associations is unclear.<h4>Methods</h4>We conducted Mendelian randomization analyses to evaluate the association of breast cancer risk, using genetic instruments, with fasting insulin, fasting glucose, 2-h glucose, body mass index (BMI) and BMI-adjusted waist-hip-ratio (WHRadj BMI). We first confirmed the association of these instruments with type 2 diabetes risk in a large diabetes genome-wide association study consortium. We then investigated their associations with breast cancer risk using individual-level data obtained from 98 842 cases and 83 464 controls of European descent in the Breast Cancer Association Consortium.<h4>Results</h4>All sets of instruments were associated with risk of type 2 diabetes. Associations with breast cancer risk were found for genetically predicted fasting insulin [odds ratio (OR) = 1.71 per standard deviation (SD) increase, 95% confidence interval (CI) = 1.26-2.31, p = 5.09 × 10-4], 2-h glucose (OR = 1.80 per SD increase, 95% CI = 1.3 0-2.49, p = 4.02 × 10-4), BMI (OR = 0.70 per 5-unit increase, 95% CI = 0.65-0.76, p = 5.05 × 10-19) and WHRadj BMI (OR = 0.85, 95% CI = 0.79-0.91, p = 9.22 × 10-6). Stratified analyses showed that genetically predicted fasting insulin was more closely related to risk of estrogen-receptor [ER]-positive cancer, whereas the associations with instruments of 2-h glucose, BMI and WHRadj BMI were consistent regardless of age, menopausal status, estrogen receptor status and family history of breast cancer.<h4>Conclusions</h4>We confirmed the previously reported inverse association of genetically predicted BMI with breast cancer risk, and showed a positive association of genetically predicted fasting insulin and 2-h glucose and an inverse association of WHRadj BMI with breast cancer risk. Our study suggests that genetically determined obesity and glucose/insulin-related traits have an important role in the aetiology of breast cancer.
<h4>Background</h4>Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk.<h4>Methods</h4>Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies.<h4>Results</h4>Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38-1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28-1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45-1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile.<h4>Conclusions</h4>The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.
<h4>Background</h4>Heterogeneity of immune gene expression patterns of luminal breast cancer (BC), which is clinically heterogeneous and overall considered as low immunogenic, has not been well studied especially in non-European populations. Here, we aimed at characterizing the immune gene expression profile of luminal BC in an Asian population and associating it with patient characteristics and tumor genomic features.<h4>Methods</h4>We performed immune gene expression profiling of tumor and adjacent normal tissue in 92 luminal BC patients from Hong Kong using RNA-sequencing data and used unsupervised consensus clustering to stratify tumors. We then used luminal patients from The Cancer Genome Atlas (TCGA, N = 564) and a Korean breast cancer study (KBC, N = 112) as replication datasets.<h4>Results</h4>Based on the expression of 130 immune-related genes, luminal tumors were stratified into three distinct immune subtypes. Tumors in one subtype showed higher level of tumor-infiltrating lymphocytes (TILs), characterized by T cell gene activation, higher expression of immune checkpoint genes, higher nonsynonymous mutation burden, and higher APOBEC-signature mutations, compared with other luminal tumors. The high-TIL subtype was also associated with lower ESR1/ESR2 expression ratio and increasing body mass index. The comparison of the immune profile in tumor and matched normal tissue suggested a tumor-derived activation of specific immune responses, which was only seen in high-TIL patients. Tumors in a second subtype were characterized by increased expression of interferon-stimulated genes and enrichment for TP53 somatic mutations. The presence of three immune subtypes within luminal BC was replicated in TCGA and KBC, although the pattern was more similar in Asian populations. The germline APOBEC3B deletion polymorphism, which is prevalent in East Asian populations and was previously linked to immune activation, was not associated with immune subtypes in our study. This result does not support the hypothesis that the germline APOBEC3B deletion polymorphism is the driving force for immune activation in breast tumors in Asian populations.<h4>Conclusion</h4>Our findings suggest that immune gene expression and associated genomic features could be useful to further stratify luminal BC beyond the current luminal A/B classification and a subset of luminal BC patients may benefit from checkpoint immunotherapy, at least in Asian populations.
Limited epidemiological evidence suggests that the etiology of hormone receptor positive (HR+) breast cancer may differ by levels of histologic grade and proliferation. We pooled risk factor and pathology data on 5,905 HR+ breast cancer cases and 26,281 controls from 11 epidemiological studies. Proliferation was determined by centralized automated measures of KI67 in tissue microarrays. Odds ratios (OR), 95% confidence intervals (CI) and p-values for case-case and case-control comparisons for risk factors in relation to levels of grade and quartiles (Q1-Q4) of KI67 were estimated using polytomous logistic regression models. Case-case comparisons showed associations between nulliparity and high KI67 [OR (95% CI) for Q4 vs. Q1 = 1.54 (1.22, 1.95)]; obesity and high grade [grade 3 vs. 1 = 1.68 (1.31, 2.16)] and current use of combined hormone therapy (HT) and low grade [grade 3 vs. 1 = 0.27 (0.16, 0.44)] tumors. In case-control comparisons, nulliparity was associated with elevated risk of tumors with high but not low levels of proliferation [1.43 (1.14, 1.81) for KI67 Q4 vs. 0.83 (0.60, 1.14) for KI67 Q1]; obesity among women ≥50 years with high but not low grade tumors [1.55 (1.17, 2.06) for grade 3 vs. 0.88 (0.66, 1.16) for grade 1] and HT with low but not high grade tumors [3.07 (2.22, 4.23) for grade 1 vs. 0.85 (0.55, 1.30) for grade 3]. Menarcheal age and family history were similarly associated with HR+ tumors of different grade or KI67 levels. These findings provide insights into the etiologic heterogeneity of HR+ tumors.
Although the spliceogenic nature of the BRCA2 c.68-7T > A variant has been demonstrated, its association with cancer risk remains controversial. In this study, we accurately quantified by real-time PCR and digital PCR (dPCR), the BRCA2 isoforms retaining or missing exon 3. In addition, the combined odds ratio for causality of the variant was estimated using genetic and clinical data, and its associated cancer risk was estimated by case-control analysis in 83,636 individuals. Co-occurrence in trans with pathogenic BRCA2 variants was assessed in 5,382 families. Exon 3 exclusion rate was 4.5-fold higher in variant carriers (13%) than controls (3%), indicating an exclusion rate for the c.68-7T > A allele of approximately 20%. The posterior probability of pathogenicity was 7.44 × 10<sup>-115</sup> . There was neither evidence for increased risk of breast cancer (OR 1.03; 95% CI 0.86-1.24) nor for a deleterious effect of the variant when co-occurring with pathogenic variants. Our data provide for the first time robust evidence of the nonpathogenicity of the BRCA2 c.68-7T > A. Genetic and quantitative transcript analyses together inform the threshold for the ratio between functional and altered BRCA2 isoforms compatible with normal cell function. These findings might be exploited to assess the relevance for cancer risk of other BRCA2 spliceogenic variants.
Various subtypes of breast cancer defined by estrogen receptor (ER), progesterone receptor (PR), and HER2 exhibit etiologic differences in reproductive factors, but associations with other risk factors are inconsistent. To clarify etiologic heterogeneity, we pooled data from nine cohort studies. Multivariable, joint Cox proportional hazards regression models were used to estimate HRs and 95% confidence intervals (CI) for molecular subtypes. Of 606,025 women, 11,741 invasive breast cancers with complete tissue markers developed during follow-up: 8,700 luminal A-like (ER<sup>+</sup> or PR<sup>+</sup>/HER2<sup>-</sup>), 1,368 luminal B-like (ER<sup>+</sup> or PR<sup>+</sup>/HER2<sup>+</sup>), 521 HER2-enriched (ER<sup>-</sup>/PR<sup>-</sup>/HER2<sup>+</sup>), and 1,152 triple-negative (ER<sup>-</sup>/PR<sup>-</sup>/HER2<sup>-</sup>) disease. Ever parous compared with never was associated with lower risk of luminal A-like (HR, 0.78; 95% CI, 0.73-0.83) and luminal B-like (HR, 0.74; 95% CI, 0.64-0.87) as well as a higher risk of triple-negative disease (HR, 1.23; 95% CI, 1.02-1.50; <i>P</i> value for overall tumor heterogeneity < 0.001). Direct associations with luminal-like, but not HER2-enriched or triple-negative, tumors were found for age at first birth, years between menarche and first birth, and age at menopause (<i>P</i> value for overall tumor heterogeneity < 0.001). Age-specific associations with baseline body mass index differed for risk of luminal A-like and triple-negative breast cancer (<i>P</i> value for tumor heterogeneity = 0.02). These results provide the strongest evidence for etiologic heterogeneity of breast cancer to date from prospective studies.<b>Significance:</b> These findings comprise the largest study of prospective data to date and contribute to the accumulating evidence that etiological heterogeneity exists in breast carcinogenesis. <i>Cancer Res; 78(20); 6011-21. ©2018 AACR</i>.
E-cadherin (CDH1) is a putative tumor suppressor gene implicated in breast carcinogenesis. Yet, whether risk factors or survival differ by E-cadherin tumor expression is unclear. We evaluated E-cadherin tumor immunohistochemistry expression using tissue microarrays of 5,933 female invasive breast cancers from 12 studies from the Breast Cancer Consortium. H-scores were calculated and case-case odds ratios (OR) and 95% confidence intervals (CIs) were estimated using logistic regression. Survival analyses were performed using Cox regression models. All analyses were stratified by estrogen receptor (ER) status and histologic subtype. E-cadherin low cases (N = 1191, 20%) were more frequently of lobular histology, low grade, >2 cm, and HER2-negative. Loss of E-cadherin expression (score < 100) was associated with menopausal hormone use among ER-positive tumors (ever compared to never users, OR = 1.24, 95% CI = 0.97-1.59), which was stronger when we evaluated complete loss of E-cadherin (i.e. H-score = 0), OR = 1.57, 95% CI = 1.06-2.33. Breast cancer specific mortality was unrelated to E-cadherin expression in multivariable models. E-cadherin low expression is associated with lobular histology, tumor characteristics and menopausal hormone use, with no evidence of an association with breast cancer specific survival. These data support loss of E-cadherin expression as an important marker of tumor subtypes.
Endometrial cancer is the most commonly diagnosed cancer of the female reproductive tract in developed countries. Through genome-wide association studies (GWAS), we have previously identified eight risk loci for endometrial cancer. Here, we present an expanded meta-analysis of 12,906 endometrial cancer cases and 108,979 controls (including new genotype data for 5624 cases) and identify nine novel genome-wide significant loci, including a locus on 12q24.12 previously identified by meta-GWAS of endometrial and colorectal cancer. At five loci, expression quantitative trait locus (eQTL) analyses identify candidate causal genes; risk alleles at two of these loci associate with decreased expression of genes, which encode negative regulators of oncogenic signal transduction proteins (SH2B3 (12q24.12) and NF1 (17q11.2)). In summary, this study has doubled the number of known endometrial cancer risk loci and revealed candidate causal genes for future study.
We aimed to validate the prognostic association of p16 expression in ovarian high-grade serous carcinomas (HGSC) and to explore it in other ovarian carcinoma histotypes. p16 protein expression was assessed by clinical-grade immunohistochemistry in 6525 ovarian carcinomas including 4334 HGSC using tissue microarrays from 24 studies participating in the Ovarian Tumor Tissue Analysis consortium. p16 expression patterns were interpreted as abnormal (either overexpression referred to as block expression or absence) or normal (heterogeneous). CDKN2A (which encodes p16) mRNA expression was also analyzed in a subset (n = 2280) mostly representing HGSC (n = 2010). Association of p16 expression with overall survival (OS) was determined within histotypes as was CDKN2A expression for HGSC only. p16 block expression was most frequent in HGSC (56%) but neither protein nor mRNA expression was associated with OS. However, relative to heterogeneous expression, block expression was associated with shorter OS in endometriosis-associated carcinomas, clear cell [hazard ratio (HR): 2.02, 95% confidence (CI) 1.47-2.77, p < 0.001] and endometrioid (HR: 1.88, 95% CI 1.30-2.75, p = 0.004), while absence was associated with shorter OS in low-grade serous carcinomas (HR: 2.95, 95% CI 1.61-5.38, p = 0.001). Absence was most frequent in mucinous carcinoma (50%), and was not associated with OS in this histotype. The prognostic value of p16 expression is histotype-specific and pattern dependent. We provide definitive evidence against an association of p16 expression with survival in ovarian HGSC as previously suggested. Block expression of p16 in clear cell and endometrioid carcinoma should be further validated as a prognostic marker, and absence in low-grade serous carcinoma justifies CDK4 inhibition.
Previous studies suggested an association between atopic conditions and specific cancers. The results on the association with urothelial bladder cancer (UBC) are scarce and inconsistent. To evaluate the association between asthma and risk of UBC, we considered 936 cases and 1,022 controls from the Spanish Bladder Cancer/EPICURO Study (86% males, mean age 65.4 years), a multicenter and hospital-based case-control study conducted during 1998-2001. Participants were asked whether they had asthma and detailed information about occupational exposures, smoking habits, dietary factors, medical conditions and history of medication was collected through face-to-face questionnaires performed by trained interviewers. Since asthma and UBC might share risk factors, association between patients' characteristics and asthma was studied in UBC controls. Association between UBC and asthma was assessed using logistic regression unadjusted and adjusted for potential confounders. The complex interrelationships, direct and mediating effect of asthma on UBC, were appraised using counterfactual mediation models. Asthma was associated with a reduced risk of UBC (odds ratio (OR) = 0.54, 95% confidence interval (CI) 0.37, 0.79) after adjusting for a wide range of confounders. No mediating effect was identified. The reduced risk associated with asthma was restricted to patients with high-risk non-muscle invasive (OR = 0.25, 95%CI 0.10, 0.62) and muscle invasive UBC (OR = 0.32, 95%CI 0.15, 0.69). Our results support that asthma is associated with a decreased risk of UBC, especially among aggressive tumors. Further work on the relationship between asthma and other atopic conditions and cancer risk should shed light on the relationship between immune response mechanisms and bladder carcinogenesis.
<h4>Background</h4>Polygenic risk scores (PRS) for breast cancer can be used to stratify the population into groups at substantially different levels of risk. Combining PRS and environmental risk factors will improve risk prediction; however, integrating PRS into risk prediction models requires evaluation of their joint association with known environmental risk factors.<h4>Methods</h4>Analyses were based on data from 20 studies; datasets analysed ranged from 3453 to 23 104 invasive breast cancer cases and similar numbers of controls, depending on the analysed environmental risk factor. We evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS with reproductive history, alcohol consumption, menopausal hormone therapy (MHT), height and body mass index (BMI). We tested the null hypothesis of multiplicative joint associations for PRS and each of the environmental factors, and performed global and tail-based goodness-of-fit tests in logistic regression models. The outcomes were breast cancer overall and by estrogen receptor (ER) status.<h4>Results</h4>The strongest evidence for a non-multiplicative joint associations with the 77-SNP PRS was for alcohol consumption (P-interaction = 0.009), adult height (P-interaction = 0.025) and current use of combined MHT (P-interaction = 0.038) in ER-positive disease. Risk associations for these factors by percentiles of PRS did not follow a clear dose-response. In addition, global and tail-based goodness of fit tests showed little evidence for departures from a multiplicative risk model, with alcohol consumption showing the strongest evidence for ER-positive disease (P = 0.013 for global and 0.18 for tail-based tests).<h4>Conclusions</h4>The combined effects of the 77-SNP PRS and environmental risk factors for breast cancer are generally well described by a multiplicative model. Larger studies are required to confirm possible departures from the multiplicative model for individual risk factors, and assess models specific for ER-negative disease.
The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P < 5.82 × 10<sup>-6</sup>, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.
Investigating the most likely causal variants identified by fine-mapping analyses may improve the power to detect gene-environment interactions. We assessed the interplay between 70 single nucleotide polymorphisms identified by genetic fine-scale mapping of susceptibility loci and 11 epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER) positive (ER+) and ER negative (ER-) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene-environment interactions were identified as noteworthy (BFDP < 0.80) when assuming a true prior interaction probability of 0.01. The strongest interaction result in relation to overall breast cancer risk was found between CFLAR-rs7558475 and current smoking (OR<sub>int</sub> = 0.77, 95% CI: 0.67-0.88, p<sub>int</sub> = 1.8 × 10<sup>-4</sup> ). The interaction with the strongest statistical evidence was found between 5q14-rs7707921 and alcohol consumption (OR<sub>int</sub> =1.36, 95% CI: 1.16-1.59, p<sub>int</sub> = 1.9 × 10<sup>-5</sup> ) in relation to ER- disease risk. The remaining two gene-environment interactions were also identified in relation to ER- breast cancer risk and were found between 3p21-rs6796502 and age at menarche (OR<sub>int</sub> = 1.26, 95% CI: 1.12-1.43, p<sub>int</sub> =1.8 × 10<sup>-4</sup> ) and between 8q23-rs13267382 and age at first full-term pregnancy (OR<sub>int</sub> = 0.89, 95% CI: 0.83-0.95, p<sub>int</sub> = 5.2 × 10<sup>-4</sup> ). While these results do not suggest any strong gene-environment interactions, our results may still be useful to inform experimental studies. These may in turn, shed light on the potential interactions observed.
Terminal duct lobular units (TDLUs) are the predominant source of future breast cancers, and lack of TDLU involution (higher TDLU counts, higher acini count per TDLU and the product of the two) is a breast cancer risk factor. Numerous breast cancer susceptibility single nucleotide polymorphisms (SNPs) have been identified, but whether they are associated with TDLU involution is unknown. In a pooled analysis of 872 women from two studies, we investigated 62 established breast cancer SNPs and relationships with TDLU involution. Poisson regression models with robust variance were used to calculate adjusted per-allele relative risks (with the non-breast cancer risk allele as the referent) and 95% confidence intervals between TDLU measures and each SNP. All statistical tests were two-sided; P < 0.05 was considered statistically significant. Overall, 36 SNPs (58.1%) were related to higher TDLU counts although this was not statistically significant (p = 0.25). Six of the 62 SNPs (9.7%) were nominally associated with at least one TDLU measure: rs616488 (PEX14), rs11242675 (FOXQ1) and rs6001930 (MKL1) were associated with higher TDLU count (p = 0.047, 0.045 and 0.031, respectively); rs1353747 (PDE4D) and rs6472903 (8q21.11) were associated with higher acini count per TDLU (p = 0.007 and 0.027, respectively); and rs1353747 (PDE4D) and rs204247 (RANBP9) were associated with the product of TDLU and acini counts (p = 0.024 and 0.017, respectively). Our findings suggest breast cancer SNPs may not strongly influence TDLU involution. Agnostic genome-wide association studies of TDLU involution may provide new insights on its biologic underpinnings and breast cancer susceptibility.
<h4>Background</h4>Previous studies have shown that reproductive factors are differentially associated with breast cancer (BC) risk by subtypes. The aim of this study was to investigate associations between reproductive factors and BC subtypes, and whether these vary by age at diagnosis.<h4>Methods</h4>We used pooled data on tumor markers (estrogen and progesterone receptor, human epidermal growth factor receptor-2 (HER2)) and reproductive risk factors (parity, age at first full-time pregnancy (FFTP) and age at menarche) from 28,095 patients with invasive BC from 34 studies participating in the Breast Cancer Association Consortium (BCAC). In a case-only analysis, we used logistic regression to assess associations between reproductive factors and BC subtype compared to luminal A tumors as a reference. The interaction between age and parity in BC subtype risk was also tested, across all ages and, because age was modeled non-linearly, specifically at ages 35, 55 and 75 years.<h4>Results</h4>Parous women were more likely to be diagnosed with triple negative BC (TNBC) than with luminal A BC, irrespective of age (OR for parity = 1.38, 95% CI 1.16-1.65, p = 0.0004; p for interaction with age = 0.076). Parous women were also more likely to be diagnosed with luminal and non-luminal HER2-like BCs and this effect was slightly more pronounced at an early age (p for interaction with age = 0.037 and 0.030, respectively). For instance, women diagnosed at age 35 were 1.48 (CI 1.01-2.16) more likely to have luminal HER2-like BC than luminal A BC, while this association was not significant at age 75 (OR = 0.72, CI 0.45-1.14). While age at menarche was not significantly associated with BC subtype, increasing age at FFTP was non-linearly associated with TNBC relative to luminal A BC. An age at FFTP of 25 versus 20 years lowered the risk for TNBC (OR = 0.78, CI 0.70-0.88, p < 0.0001), but this effect was not apparent at a later FFTP.<h4>Conclusions</h4>Our main findings suggest that parity is associated with TNBC across all ages at BC diagnosis, whereas the association with luminal HER2-like BC was present only for early onset BC.
TP53 overexpression is indicative of somatic TP53 mutations and associates with aggressive tumors and poor prognosis in breast cancer. We utilized a two-stage SNP association study to detect variants associated with breast cancer survival in a TP53-dependent manner. Initially, a genome-wide study (n = 575 cases) was conducted to discover candidate SNPs for genotyping and validation in the Breast Cancer Association Consortium (BCAC). The SNPs were then tested for interaction with tumor TP53 status (n = 4,610) and anthracycline treatment (n = 17,828). For SNPs interacting with anthracycline treatment, siRNA knockdown experiments were carried out to validate candidate genes.In the test for interaction between SNP genotype and TP53 status, we identified one locus, represented by rs10916264 (p(interaction) = 3.44 × 10-5; FDR-adjusted p = 0.0011) in estrogen receptor (ER) positive cases. The rs10916264 AA genotype associated with worse survival among cases with ER-positive, TP53-positive tumors (hazard ratio [HR] 2.36, 95% confidence interval [C.I] 1.45 - 3.82). This is a cis-eQTL locus for FBXO28 and TP53BP2; expression levels of these genes were associated with patient survival specifically in ER-positive, TP53-mutated tumors. Additionally, the SNP rs798755 was associated with survival in interaction with anthracycline treatment (p(interaction) = 9.57 × 10-5, FDR-adjusted p = 0.0130). RNAi-based depletion of a predicted regulatory target gene, FAM53A, indicated that this gene can modulate doxorubicin sensitivity in breast cancer cell lines.If confirmed in independent data sets, these results may be of clinical relevance in the development of prognostic and predictive marker panels for breast cancer.
<h4>Background</h4>There is increasing evidence that elevated body mass index (BMI) is associated with reduced survival for women with breast cancer. However, the underlying reasons remain unclear. We conducted a Mendelian randomization analysis to investigate a possible causal role of BMI in survival from breast cancer.<h4>Methods</h4>We used individual-level data from six large breast cancer case-cohorts including a total of 36 210 individuals (2475 events) of European ancestry. We created a BMI genetic risk score (GRS) based on genotypes at 94 known BMI-associated genetic variants. Association between the BMI genetic score and breast cancer survival was analysed by Cox regression for each study separately. Study-specific hazard ratios were pooled using fixed-effect meta-analysis.<h4>Results</h4>BMI genetic score was found to be associated with reduced breast cancer-specific survival for estrogen receptor (ER)-positive cases [hazard ratio (HR) = 1.11, per one-unit increment of GRS, 95% confidence interval (CI) 1.01-1.22, P = 0.03). We observed no association for ER-negative cases (HR = 1.00, per one-unit increment of GRS, 95% CI 0.89-1.13, P = 0.95).<h4>Conclusions</h4>Our findings suggest a causal effect of increased BMI on reduced breast cancer survival for ER-positive breast cancer. There is no evidence of a causal effect of higher BMI on survival for ER-negative breast cancer cases.
Most non-<i>BRCA1/2</i> breast cancer families have no identified genetic cause. We used linkage and haplotype analyses in familial and sporadic breast cancer cases to identify a susceptibility locus on chromosome 6q. Two independent genome-wide linkage analysis studies suggested a 3 Mb locus on chromosome 6q and two unrelated Swedish families with a LOD >2 together seemed to share a haplotype in 6q14.1. We hypothesized that this region harbored a rare high-risk founder allele contributing to breast cancer in these two families. Sequencing of DNA and RNA from the two families did not detect any pathogenic mutations. Finally, 29 SNPs in the region were analyzed in 44,214 cases and 43,532 controls from BCAC, and the original haplotypes in the two families were suggested as low-risk alleles for European and Swedish women specifically. There was also some support for one additional independent moderate-risk allele in Swedish familial samples. The results were consistent with our previous findings in familial breast cancer and supported a breast cancer susceptibility locus at 6q14.1 around the <i>PHIP</i> gene.
Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10<sup>-8</sup> with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.
<h4>Background</h4>Postmenopausal obesity is associated with increased circulating levels of androgens and estrogens and elevated breast cancer risk. Crown-like structures (CLS; microscopic foci of dying adipocytes surrounded by macrophages) are proposed to represent sites of increased aromatization of androgens to estrogens. Accordingly, we examined relationships between CLS and sex-steroid hormones in breast adipose tissue and serum from postmenopausal breast cancer patients.<h4>Methods</h4>Formalin-fixed paraffin embedded benign breast tissues collected for research from postmenopausal women (n = 83) diagnosed with invasive breast cancer in the Polish Breast Cancer Study (PBCS) were evaluated. Tissues were immunohistochemically stained for CD68 to determine the presence of CLS per unit area of adipose tissue. Relationships were assessed between CD68 density and CLS and previously reported sex-steroid hormones quantified using radioimmunoassays in serum taken at the time of diagnosis and in fresh frozen adipose tissue taken at the time of surgery. Logistic regression analysis was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the relationships between hormones (in tertiles) and CLS.<h4>Results</h4>CLS were observed in 36% of benign breast tissues, with a higher frequency among obese versus lean women (54% versus 17%, p = 0.03). Detection of CLS was not related to individual hormone levels or breast tumor pathology characteristics. However, detection of CLS was associated with hormone ratios. Compared with women in the highest tertile of estrone:androstenedione ratio in fat, those in the lowest tertile were less likely to have CLS (OR 0.12, 95% CI 0.03-0.59). A similar pattern was observed with estradiol:testosterone ratio in serum and CLS (lowest versus highest tertile, OR 0.18, 95% CI 0.04-0.72).<h4>Conclusions</h4>CLS were more frequently identified in the breast fat of obese women and were associated with increased ratios of select estrogens:androgens in the blood and tissues, but not with individual hormones. Additional studies on CLS, tissue and blood hormone levels, and breast cancer risk are needed to understand and confirm these findings.
<h4>Purpose</h4>CHEK2*1100delC is a founder variant in European populations that confers a two- to threefold increased risk of breast cancer (BC). Epidemiologic and family studies have suggested that the risk associated with CHEK2*1100delC is modified by other genetic factors in a multiplicative fashion. We have investigated this empirically using data from the Breast Cancer Association Consortium (BCAC).<h4>Methods</h4>Using genotype data from 39,139 (624 1100delC carriers) BC patients and 40,063 (224) healthy controls from 32 BCAC studies, we analyzed the combined risk effects of CHEK2*1100delC and 77 common variants in terms of a polygenic risk score (PRS) and pairwise interaction.<h4>Results</h4>The PRS conferred odds ratios (OR) of 1.59 (95% CI: 1.21-2.09) per standard deviation for BC for CHEK2*1100delC carriers and 1.58 (1.55-1.62) for noncarriers. No evidence of deviation from the multiplicative model was found. The OR for the highest quintile of the PRS was 2.03 (0.86-4.78) for CHEK2*1100delC carriers, placing them in the high risk category according to UK NICE guidelines. The OR for the lowest quintile was 0.52 (0.16-1.74), indicating a lifetime risk close to the population average.<h4>Conclusion</h4>Our results confirm the multiplicative nature of risk effects conferred by CHEK2*1100delC and the common susceptibility variants. Furthermore, the PRS could identify carriers at a high lifetime risk for clinical actions.Genet Med advance online publication 06 October 2016.
Genetic and environmental factors are both known to contribute to susceptibility to complex diseases. Therefore, the study of gene-environment interaction (G×E) has been a focus of research for several years. In this article, select examples of G×E from the literature are described to highlight different approaches and underlying principles related to the success of these studies. These examples can be broadly categorized as studies of single metabolism genes, genes in complex metabolism pathways, ranges of exposure levels, functional approaches and model systems, and pharmacogenomics. Some studies illustrated the success of studying exposure metabolism for which candidate genes can be identified. Moreover, some G×E successes depended on the availability of high-quality exposure assessment and longitudinal measures, study populations with a wide range of exposure levels, and the inclusion of ethnically and geographically diverse populations. In several examples, large population sizes were required to detect G×Es. Other examples illustrated the impact of accurately defining scale of the interactions (i.e., additive or multiplicative). Last, model systems and functional approaches provided insights into G×E in several examples. Future studies may benefit from these lessons learned.
Little is known whether genetic variants identified in genome-wide association studies interact to increase bladder cancer risk. Recently, we identified two- and three-variant combinations associated with a particular increase of bladder cancer risk in a urinary bladder cancer case-control series (Leibniz Research Centre for Working Environment and Human Factors at TU Dortmund (IfADo), 1501 cases, 1565 controls). In an independent case-control series (Nijmegen Bladder Cancer Study, NBCS, 1468 cases, 1720 controls) we confirmed these two- and three-variant combinations. Pooled analysis of the two studies as discovery group (IfADo-NBCS) resulted in sufficient statistical power to test up to four-variant combinations by a logistic regression approach. The New England and Spanish Bladder Cancer Studies (2080 cases and 2167 controls) were used as a replication series. Twelve previously identified risk variants were considered. The strongest four-variant combination was obtained in never smokers. The combination of rs1014971[AA] near apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3A (APOBEC3A) and chromobox homolog 6 (CBX6), solute carrier family 1s4 (urea transporter), member 1 (Kidd blood group) (SLC14A1) exon single nucleotide polymorphism (SNP) rs1058396[AG, GG], UDP glucuronosyltransferase 1 family, polypeptide A complex locus (UGT1A) intron SNP rs11892031[AA] and rs8102137[CC, CT] near cyclin E1 (CCNE1) resulted in an unadjusted odds ratio (OR) of 2.59 (95% CI = 1.93-3.47; P = 1.87 × 10-10), while the individual variant ORs ranged only between 1.11 and 1.30. The combination replicated in the New England and Spanish Bladder Cancer Studies (ORunadjusted = 1.60, 95% CI = 1.10-2.33; P = 0.013). The four-variant combination is relatively frequent, with 25% in never smoking cases and 11% in never smoking controls (total study group: 19% cases, 14% controls). In conclusion, we show that four high-risk variants can statistically interact to confer increased bladder cancer risk particularly in never smokers.
Breast cancer risks conferred by many germline missense variants in the <i>BRCA1</i> and <i>BRCA2</i> genes, often referred to as variants of uncertain significance (VUS), have not been established. In this study, associations between 19 BRCA1 and 33 BRCA2 missense substitution variants and breast cancer risk were investigated through a breast cancer case-control study using genotyping data from 38 studies of predominantly European ancestry (41,890 cases and 41,607 controls) and nine studies of Asian ancestry (6,269 cases and 6,624 controls). The BRCA2 c.9104A>C, p.Tyr3035Ser (OR = 2.52; <i>P</i> = 0.04), and BRCA1 c.5096G>A, p.Arg1699Gln (OR = 4.29; <i>P</i> = 0.009) variant were associated with moderately increased risks of breast cancer among Europeans, whereas BRCA2 c.7522G>A, p.Gly2508Ser (OR = 2.68; <i>P</i> = 0.004), and c.8187G>T, p.Lys2729Asn (OR = 1.4; <i>P</i> = 0.004) were associated with moderate and low risks of breast cancer among Asians. Functional characterization of the BRCA2 variants using four quantitative assays showed reduced BRCA2 activity for p.Tyr3035Ser compared with wild-type. Overall, our results show how BRCA2 missense variants that influence protein function can confer clinically relevant, moderately increased risks of breast cancer, with potential implications for risk management guidelines in women with these specific variants. <i>Cancer Res; 77(11); 2789-99. ©2017 AACR</i>.
Automated methods are needed to facilitate high-throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large-scale studies. To address this need, we developed an automated protocol for Ki67 scoring and evaluated its performance in studies from the Breast Cancer Association Consortium. We utilized 166 TMAs containing 16,953 tumour cores representing 9,059 breast cancer cases, from 13 studies, with information on other clinical and pathological characteristics. TMAs were stained for Ki67 using standard immunohistochemical procedures, and scanned and digitized using the Ariol system. An automated algorithm was developed for the scoring of Ki67, and scores were compared to computer assisted visual (CAV) scores in a subset of 15 TMAs in a training set. We also assessed the correlation between automated Ki67 scores and other clinical and pathological characteristics. Overall, we observed good discriminatory accuracy (AUC = 85%) and good agreement (kappa = 0.64) between the automated and CAV scoring methods in the training set. The performance of the automated method varied by TMA (kappa range= 0.37-0.87) and study (kappa range = 0.39-0.69). The automated method performed better in satisfactory cores (kappa = 0.68) than suboptimal (kappa = 0.51) cores (p-value for comparison = 0.005); and among cores with higher total nuclei counted by the machine (4,000-4,500 cells: kappa = 0.78) than those with lower counts (50-500 cells: kappa = 0.41; p-value = 0.010). Among the 9,059 cases in this study, the correlations between automated Ki67 and clinical and pathological characteristics were found to be in the expected directions. Our findings indicate that automated scoring of Ki67 can be an efficient method to obtain good quality data across large numbers of TMAs from multicentre studies. However, robust algorithm development and rigorous pre- and post-analytical quality control procedures are necessary in order to ensure satisfactory performance.
<h4>Background</h4>The value of KI67 in breast cancer prognostication has been questioned due to concerns on the analytical validity of visual KI67 assessment and methodological limitations of published studies. Here, we investigate the prognostic value of automated KI67 scoring in a large, multicentre study, and compare this with pathologists' visual scores available in a subset of patients.<h4>Methods</h4>We utilised 143 tissue microarrays containing 15,313 tumour tissue cores from 8088 breast cancer patients in 10 collaborating studies. A total of 1401 deaths occurred during a median follow-up of 7.5 years. Centralised KI67 assessment was performed using an automated scoring protocol. The relationship of KI67 levels with 10-year breast cancer specific survival (BCSS) was investigated using Kaplan-Meier survival curves and Cox proportional hazard regression models adjusted for known prognostic factors.<h4>Results</h4>Patients in the highest quartile of KI67 (>12 % positive KI67 cells) had a worse 10-year BCSS than patients in the lower three quartiles. This association was statistically significant for ER-positive patients (hazard ratio (HR) (95 % CI) at baseline = 1.96 (1.31-2.93); P = 0.001) but not for ER-negative patients (1.23 (0.86-1.77); P = 0.248) (P-heterogeneity = 0.064). In spite of differences in characteristics of the study populations, the estimates of HR were consistent across all studies (P-heterogeneity = 0.941 for ER-positive and P-heterogeneity = 0.866 for ER-negative). Among ER-positive cancers, KI67 was associated with worse prognosis in both node-negative (2.47 (1.16-5.27)) and node-positive (1.74 (1.05-2.86)) tumours (P-heterogeneity = 0.671). Further classification according to ER, PR and HER2 showed statistically significant associations with prognosis among hormone receptor-positive patients regardless of HER2 status (P-heterogeneity = 0.270) and among triple-negative patients (1.70 (1.02-2.84)). Model fit parameters were similar for visual and automated measures of KI67 in a subset of 2440 patients with information from both sources.<h4>Conclusions</h4>Findings from this large-scale multicentre analysis with centrally generated automated KI67 scores show strong evidence in support of a prognostic value for automated KI67 scoring in breast cancer. Given the advantages of automated scoring in terms of its potential for standardisation, reproducibility and throughput, automated methods appear to be promising alternatives to visual scoring for KI67 assessment.
Knowledge of genetics and its implications for human health is rapidly evolving in accordance with recent events, such as discoveries of large numbers of disease susceptibility loci from genome-wide association studies, the US Supreme Court ruling of the non-patentability of human genes, and the development of a regulatory framework for commercial genetic tests. In anticipation of the increasing relevance of genetic testing for the assessment of disease risks, this Review provides a summary of the methodologies used for building, evaluating and applying risk prediction models that include information from genetic testing and environmental risk factors. Potential applications of models for primary and secondary disease prevention are illustrated through several case studies, and future challenges and opportunities are discussed.
Endometrial cancer is the most common gynecological malignancy in the developed world. Although there is evidence of genetic predisposition to the disease, most of the genetic risk remains unexplained. We present the meta-analysis results of four genome-wide association studies (4907 cases and 11 945 controls total) in women of European ancestry. We describe one new locus reaching genome-wide significance (P < 5 × 10 <sup>-</sup><sup>8</sup>) at 6p22.3 (rs1740828; P = 2.29 × 10 <sup>-</sup><sup>8</sup>, OR = 1.20), providing evidence of an additional region of interest for genetic susceptibility to endometrial cancer.
Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 × 10(-8)) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ∼11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.
<h4>Purpose</h4>Physical activity may reduce endogenous estrogens, but few studies have assessed effects on estrogen metabolism and none have evaluated sedentary behavior in relation to estrogen metabolism. We assessed relationships between accelerometer-measured physical activity and sedentary behavior and 15 urinary estrogens and estrogen metabolites (EM) among postmenopausal controls from a population-based breast cancer case-control study conducted in Poland (2000-2003).<h4>Methods</h4>Postmenopausal women (N = 542) were ages 40 to 72 yr and not currently using hormone therapy. Accelerometers, worn for 7 d, were used to derive measures of average activity (counts per day) and sedentary behavior (<100 counts per minute per day). Estrogen metabolites were measured in 12-h urine samples using liquid chromatography-tandem mass spectrometry. Estrogen metabolites were analyzed individually, in metabolic pathways (C-2, -4, or -16), and as ratios relative to parent estrogens. Geometric means of estrogen metabolites by tertiles of accelerometer-measures, adjusted for age and body mass, were computed using linear models.<h4>Results</h4>High activity was associated with lower levels of estrone and estradiol (P trend = 0.01), whereas increased sedentary time was positively associated with these parent estrogens (P trend = 0.04). Inverse associations were observed between high activity and 2-methoxyestradiol, 4-methoxyestradiol, 17-epiestriol, and 16-epiestriol (P trend = 0.03). Sedentary time was positively associated with methylated catechols in the 2- and 4-hydroxylation pathways (P trend ≤ 0.04). Women in the highest tertile of activity had increased hydroxylation at the C-2, -4, and -16 sites relative to parent estrogens (P trend ≤ 0.02), whereas increased sedentary time was associated with a lower 16-pathway/parent estrogen ratio (P trend = 0.01).<h4>Conclusions</h4>Higher activity was associated with lower urinary estrogens, possibly through increased estrogen hydroxylation and subsequent metabolism, whereas sedentary behavior may reduce metabolism.
Genome-wide association studies have found SNPs at 17q22 to be associated with breast cancer risk. To identify potential causal variants related to breast cancer risk, we performed a high resolution fine-mapping analysis that involved genotyping 517 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of genotypes for 3,134 SNPs in more than 89,000 participants of European ancestry from the Breast Cancer Association Consortium (BCAC). We identified 28 highly correlated common variants, in a 53 Kb region spanning two introns of the STXBP4 gene, that are strong candidates for driving breast cancer risk (lead SNP rs2787486 (OR = 0.92; CI 0.90-0.94; P = 8.96 × 10(-15))) and are correlated with two previously reported risk-associated variants at this locus, SNPs rs6504950 (OR = 0.94, P = 2.04 × 10(-09), r(2) = 0.73 with lead SNP) and rs1156287 (OR = 0.93, P = 3.41 × 10(-11), r(2) = 0.83 with lead SNP). Analyses indicate only one causal SNP in the region and several enhancer elements targeting STXBP4 are located within the 53 kb association signal. Expression studies in breast tumor tissues found SNP rs2787486 to be associated with increased STXBP4 expression, suggesting this may be a target gene of this locus.
We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.
<h4>Background</h4>BRCA1 interacting protein C-terminal helicase 1 (BRIP1) is one of the Fanconi Anaemia Complementation (FANC) group family of DNA repair proteins. Biallelic mutations in BRIP1 are responsible for FANC group J, and previous studies have also suggested that rare protein truncating variants in BRIP1 are associated with an increased risk of breast cancer. These studies have led to inclusion of BRIP1 on targeted sequencing panels for breast cancer risk prediction.<h4>Methods</h4>We evaluated a truncating variant, p.Arg798Ter (rs137852986), and 10 missense variants of BRIP1, in 48 144 cases and 43 607 controls of European origin, drawn from 41 studies participating in the Breast Cancer Association Consortium (BCAC). Additionally, we sequenced the coding regions of BRIP1 in 13 213 cases and 5242 controls from the UK, 1313 cases and 1123 controls from three population-based studies as part of the Breast Cancer Family Registry, and 1853 familial cases and 2001 controls from Australia.<h4>Results</h4>The rare truncating allele of rs137852986 was observed in 23 cases and 18 controls in Europeans in BCAC (OR 1.09, 95% CI 0.58 to 2.03, p=0.79). Truncating variants were found in the sequencing studies in 34 cases (0.21%) and 19 controls (0.23%) (combined OR 0.90, 95% CI 0.48 to 1.70, p=0.75).<h4>Conclusions</h4>These results suggest that truncating variants in BRIP1, and in particular p.Arg798Ter, are not associated with a substantial increase in breast cancer risk. Such observations have important implications for the reporting of results from breast cancer screening panels.
Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103-14. ©2016 AACR.
Candidate gene and genome-wide association studies (GWAS) have identified 15 independent genomic regions associated with bladder cancer risk. In search for additional susceptibility variants, we followed up on four promising single-nucleotide polymorphisms (SNPs) that had not achieved genome-wide significance in 6911 cases and 11 814 controls (rs6104690, rs4510656, rs5003154 and rs4907479, P < 1 × 10(-6)), using additional data from existing GWAS datasets and targeted genotyping for studies that did not have GWAS data. In a combined analysis, which included data on up to 15 058 cases and 286 270 controls, two SNPs achieved genome-wide statistical significance: rs6104690 in a gene desert at 20p12.2 (P = 2.19 × 10(-11)) and rs4907479 within the MCF2L gene at 13q34 (P = 3.3 × 10(-10)). Imputation and fine-mapping analyses were performed in these two regions for a subset of 5551 bladder cancer cases and 10 242 controls. Analyses at the 13q34 region suggest a single signal marked by rs4907479. In contrast, we detected two signals in the 20p12.2 region-the first signal is marked by rs6104690, and the second signal is marked by two moderately correlated SNPs (r(2) = 0.53), rs6108803 and the previously reported rs62185668. The second 20p12.2 signal is more strongly associated with the risk of muscle-invasive (T2-T4 stage) compared with non-muscle-invasive (Ta, T1 stage) bladder cancer (case-case P ≤ 0.02 for both rs62185668 and rs6108803). Functional analyses are needed to explore the biological mechanisms underlying these novel genetic associations with risk for bladder cancer.
Genome-wide association studies (GWASs) have revealed increased breast cancer risk associated with multiple genetic variants at 5p12. Here, we report the fine mapping of this locus using data from 104,660 subjects from 50 case-control studies in the Breast Cancer Association Consortium (BCAC). With data for 3,365 genotyped and imputed SNPs across a 1 Mb region (positions 44,394,495-45,364,167; NCBI build 37), we found evidence for at least three independent signals: the strongest signal, consisting of a single SNP rs10941679, was associated with risk of estrogen-receptor-positive (ER<sup>+</sup>) breast cancer (per-g allele OR ER<sup>+</sup> = 1.15; 95% CI 1.13-1.18; p = 8.35 × 10<sup>-30</sup>). After adjustment for rs10941679, we detected signal 2, consisting of 38 SNPs more strongly associated with ER-negative (ER<sup>-</sup>) breast cancer (lead SNP rs6864776: per-a allele OR ER<sup>-</sup> = 1.10; 95% CI 1.05-1.14; p conditional = 1.44 × 10<sup>-12</sup>), and a single signal 3 SNP (rs200229088: per-t allele OR ER<sup>+</sup> = 1.12; 95% CI 1.09-1.15; p conditional = 1.12 × 10<sup>-05</sup>). Expression quantitative trait locus analysis in normal breast tissues and breast tumors showed that the g (risk) allele of rs10941679 was associated with increased expression of FGF10 and MRPS30. Functional assays demonstrated that SNP rs10941679 maps to an enhancer element that physically interacts with the FGF10 and MRPS30 promoter regions in breast cancer cell lines. FGF10 is an oncogene that binds to FGFR2 and is overexpressed in ∼10% of human breast cancers, whereas MRPS30 plays a key role in apoptosis. These data suggest that the strongest signal of association at 5p12 is mediated through coordinated activation of FGF10 and MRPS30, two candidate genes for breast cancer pathogenesis.
<h4>Background</h4>Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors.<h4>Methods</h4>We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC) (cases = 46,325, controls = 42,482). We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively.<h4>Results</h4>In the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR] = 0.65 per 5 kg/m2 increase, 95% confidence interval [CI]: 0.56-0.75, p = 3.32 × 10-10). The associations were similar for both premenopausal (OR = 0.44, 95% CI:0.31-0.62, p = 9.91 × 10-8) and postmenopausal breast cancer (OR = 0.57, 95% CI: 0.46-0.71, p = 1.88 × 10-8). This association was replicated in the data from the DRIVE consortium (OR = 0.72, 95% CI: 0.60-0.84, p = 1.64 × 10-7). Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs) in association with breast cancer risk at p < 0.05; for 16 of them, the allele associated with elevated BMI was associated with reduced breast cancer risk.<h4>Conclusions</h4>BMI predicted by genome-wide association studies (GWAS)-identified variants is inversely associated with the risk of both pre- and postmenopausal breast cancer. The reduced risk of postmenopausal breast cancer associated with genetically predicted BMI observed in this study differs from the positive association reported from studies using measured adult BMI. Understanding the reasons for this discrepancy may reveal insights into the complex relationship of genetic determinants of body weight in the etiology of breast cancer.
There are significant inter-individual differences in the levels of gene expression. Through modulation of gene expression, cis-acting variants represent an important source of phenotypic variation. Consequently, cis-regulatory SNPs associated with differential allelic expression are functional candidates for further investigation as disease-causing variants. To investigate whether common variants associated with differential allelic expression were involved in breast cancer susceptibility, a list of genes was established on the basis of their involvement in cancer related pathways and/or mechanisms. Thereafter, using data from a genome-wide map of allelic expression associated SNPs, 313 genetic variants were selected and their association with breast cancer risk was then evaluated in 46,451 breast cancer cases and 42,599 controls of European ancestry ascertained from 41 studies participating in the Breast Cancer Association Consortium. The associations were evaluated with overall breast cancer risk and with estrogen receptor negative and positive disease. One novel breast cancer susceptibility locus on 4q21 (rs11099601) was identified (OR = 1.05, P = 5.6x10-6). rs11099601 lies in a 135 kb linkage disequilibrium block containing several genes, including, HELQ, encoding the protein HEL308 a DNA dependant ATPase and DNA Helicase involved in DNA repair, MRPS18C encoding the Mitochondrial Ribosomal Protein S18C and FAM175A (ABRAXAS), encoding a BRCA1 BRCT domain-interacting protein involved in DNA damage response and double-strand break (DSB) repair. Expression QTL analysis in breast cancer tissue showed rs11099601 to be associated with HELQ (P = 8.28x10-14), MRPS18C (P = 1.94x10-27) and FAM175A (P = 3.83x10-3), explaining about 20%, 14% and 1%, respectively of the variance inexpression of these genes in breast carcinomas.
The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799-121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120,300,000-120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Per-allelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08-1.13, P = 1.49 x 10-21). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity P≤8.41 x 10-5). Additional analyses by other tumor characteristics showed stronger associations with moderately/well differentiated tumors and tumors of lobular histology. Although no significant eQTL associations were observed, in silico analyses showed that rs11249433 was located in a region that is likely a weak enhancer/promoter. Fine-mapping analysis of the 1p11.2 breast cancer susceptibility locus confirms this region to be limited to risk to cancers that are ER-positive.
<h4>Unlabelled</h4>Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis.<h4>Significance</h4>We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.
A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10(-20)), ER-negative BC (P=1.1 × 10(-13)), BRCA1-associated BC (P=7.7 × 10(-16)) and triple negative BC (P-diff=2 × 10(-5)). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10(-3)) and ABHD8 (P<2 × 10(-3)). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3'-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk.
Immunosuppression plays a pivotal role in assisting tumors to evade immune destruction and promoting tumor development. We hypothesized that genetic variation in the immunosuppression pathway genes may be implicated in breast cancer tumorigenesis. We included 42,510 female breast cancer cases and 40,577 controls of European ancestry from 37 studies in the Breast Cancer Association Consortium (2015) with available genotype data for 3595 single nucleotide polymorphisms (SNPs) in 133 candidate genes. Associations between genotyped SNPs and overall breast cancer risk, and secondarily according to estrogen receptor (ER) status, were assessed using multiple logistic regression models. Gene-level associations were assessed based on principal component analysis. Gene expression analyses were conducted using RNA sequencing level 3 data from The Cancer Genome Atlas for 989 breast tumor samples and 113 matched normal tissue samples. SNP rs1905339 (A>G) in the STAT3 region was associated with an increased breast cancer risk (per allele odds ratio 1.05, 95 % confidence interval 1.03-1.08; p value = 1.4 × 10(-6)). The association did not differ significantly by ER status. On the gene level, in addition to TGFBR2 and CCND1, IL5 and GM-CSF showed the strongest associations with overall breast cancer risk (p value = 1.0 × 10(-3) and 7.0 × 10(-3), respectively). Furthermore, STAT3 and IL5 but not GM-CSF were differentially expressed between breast tumor tissue and normal tissue (p value = 2.5 × 10(-3), 4.5 × 10(-4) and 0.63, respectively). Our data provide evidence that the immunosuppression pathway genes STAT3, IL5, and GM-CSF may be novel susceptibility loci for breast cancer in women of European ancestry.
NBS1, also known as NBN, plays an important role in maintaining genomic stability. Interestingly, rs2735383 G > C, located in a microRNA binding site in the 3'-untranslated region (UTR) of NBS1, was shown to be associated with increased susceptibility to lung and colorectal cancer. However, the relation between rs2735383 and susceptibility to breast cancer is not yet clear. Therefore, we genotyped rs2735383 in 1,170 familial non-BRCA1/2 breast cancer cases and 1,077 controls using PCR-based restriction fragment length polymorphism (RFLP-PCR) analysis, but found no association between rs2735383CC and breast cancer risk (OR = 1.214, 95% CI = 0.936-1.574, P = 0.144). Because we could not exclude a small effect size due to a limited sample size, we further analyzed imputed rs2735383 genotypes (r<sup>2</sup> > 0.999) of 47,640 breast cancer cases and 46,656 controls from the Breast Cancer Association Consortium (BCAC). However, rs2735383CC was not associated with overall breast cancer risk in European (OR = 1.014, 95% CI = 0.969-1.060, P = 0.556) nor in Asian women (OR = 0.998, 95% CI = 0.905-1.100, P = 0.961). Subgroup analyses by age, age at menarche, age at menopause, menopausal status, number of pregnancies, breast feeding, family history and receptor status also did not reveal a significant association. This study therefore does not support the involvement of the genotype at NBS1 rs2735383 in breast cancer susceptibility.
<h4>Background</h4>We adapted Bayesian statistical learning strategies to the prognosis field to investigate if genome-wide common SNP improve the prediction ability of clinico-pathological prognosticators and applied it to non-muscle invasive bladder cancer (NMIBC) patients.<h4>Methods</h4>Adapted Bayesian sequential threshold models in combination with LASSO were applied to consider the time-to-event and the censoring nature of data. We studied 822 NMIBC patients followed-up >10 years. The study outcomes were time-to-first-recurrence and time-to-progression. The predictive ability of the models including up to 171,304 SNP and/or 6 clinico-pathological prognosticators was evaluated using AUC-ROC and determination coefficient.<h4>Results</h4>Clinico-pathological prognosticators explained a larger proportion of the time-to-first-recurrence (3.1 %) and time-to-progression (5.4 %) phenotypic variances than SNPs (1 and 0.01 %, respectively). Adding SNPs to the clinico-pathological-parameters model slightly improved the prediction of time-to-first-recurrence (up to 4 %). The prediction of time-to-progression using both clinico-pathological prognosticators and SNP did not improve. Heritability (ĥ (2)) of both outcomes was <1 % in NMIBC.<h4>Conclusions</h4>We adapted a Bayesian statistical learning method to deal with a large number of parameters in prognostic studies. Common SNPs showed a limited role in predicting NMIBC outcomes yielding a very low heritability for both outcomes. We report for the first time a heritability estimate for a disease outcome. Our method can be extended to other disease models.
<h4>Importance</h4>An improved model for risk stratification can be useful for guiding public health strategies of breast cancer prevention.<h4>Objective</h4>To evaluate combined risk stratification utility of common low penetrant single nucleotide polymorphisms (SNPs) and epidemiologic risk factors.<h4>Design, setting, and participants</h4>Using a total of 17 171 cases and 19 862 controls sampled from the Breast and Prostate Cancer Cohort Consortium (BPC3) and 5879 women participating in the 2010 National Health Interview Survey, a model for predicting absolute risk of breast cancer was developed combining information on individual level data on epidemiologic risk factors and 24 genotyped SNPs from prospective cohort studies, published estimate of odds ratios for 68 additional SNPs, population incidence rate from the National Cancer Institute-Surveillance, Epidemiology, and End Results Program cancer registry and data on risk factor distribution from nationally representative health survey. The model is used to project the distribution of absolute risk for the population of white women in the United States after adjustment for competing cause of mortality.<h4>Exposures</h4>Single nucleotide polymorphisms, family history, anthropometric factors, menstrual and/or reproductive factors, and lifestyle factors.<h4>Main outcomes and measures</h4>Degree of stratification of absolute risk owing to nonmodifiable (SNPs, family history, height, and some components of menstrual and/or reproductive history) and modifiable factors (body mass index [BMI; calculated as weight in kilograms divided by height in meters squared], menopausal hormone therapy [MHT], alcohol, and smoking).<h4>Results</h4>The average absolute risk for a 30-year-old white woman in the United States developing invasive breast cancer by age 80 years is 11.3%. A model that includes all risk factors provided a range of average absolute risk from 4.4% to 23.5% for women in the bottom and top deciles of the risk distribution, respectively. For women who were at the lowest and highest deciles of nonmodifiable risks, the 5th and 95th percentile range of the risk distribution associated with 4 modifiable factors was 2.9% to 5.0% and 15.5% to 25.0%, respectively. For women in the highest decile of risk owing to nonmodifiable factors, those who had low BMI, did not drink or smoke, and did not use MHT had risks comparable to an average woman in the general population.<h4>Conclusions and relevance</h4>This model for absolute risk of breast cancer including SNPs can provide stratification for the population of white women in the United States. The model can also identify subsets of the population at an elevated risk that would benefit most from risk-reduction strategies based on altering modifiable factors. The effectiveness of this model for individual risk communication needs further investigation.
To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events >2 Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases.
<h4>Background</h4>Increasing evidence points to the role of tumor immunologic environment on urothelial bladder cancer prognosis. This effect might be partly dependent on the host genetic context. We evaluated the association of SNPs in inflammation-related genes with non-muscle-invasive bladder cancer (NMIBC) risk-of-recurrence and risk-of-progression.<h4>Methods</h4>We considered 822 NMIBC included in the SBC/EPICURO Study followed-up >10 years. We selected 1,679 SNPs belonging to 251 inflammatory genes. The association of SNPs with risk-of-recurrence and risk-of-progression was assessed using Cox regression single-marker (SMM) and multimarker methods (MMM) Bayes A and Bayesian LASSO. Discriminative abilities of the models were calculated using the c index and validated with bootstrap cross-validation procedures.<h4>Results</h4>While no SNP was found to be associated with risk-of-recurrence using SMM, three SNPs in TNIP1, CD5, and JAK3 showed very strong association with posterior probabilities >90% using MMM. Regarding risk-of-progression, one SNP in CD3G was significantly associated using SMM (HR, 2.69; P = 1.55 × 10(-5)) and two SNPs in MASP1 and AIRE, showed a posterior probability ≥80% with MMM. Validated discriminative abilities of the models without and with the SNPs were 58.4% versus 60.5% and 72.1% versus 72.8% for risk-of-recurrence and risk-of-progression, respectively.<h4>Conclusions</h4>Using innovative analytic approaches, we demonstrated that SNPs in inflammatory-related genes were associated with NMIBC prognosis and that they improve the discriminative ability of prognostic clinical models for NMIBC.<h4>Impact</h4>This study provides proof of concept for the joint effect of genetic variants in improving the discriminative ability of clinical prognostic models. The approach may be extended to other diseases. Cancer Epidemiol Biomarkers Prev; 25(7); 1144-50. ©2016 AACR.
<h4>Background</h4>The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers.<h4>Methods</h4>Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided.<h4>Results</h4>The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10(-) (6)) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10(-3)). These associations were stronger for serous ovarian cancer and for estrogen receptor-negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10(-5) and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10(-5), respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed.<h4>Conclusions</h4>Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations.
High rates of APOBEC-signature mutations are found in many tumors, but factors affecting this mutation pattern are not well understood. Here we explored the contribution of two common germline variants in the APOBEC3 region. SNP rs1014971 was associated with bladder cancer risk, increased APOBEC3B expression, and enrichment with APOBEC-signature mutations in bladder tumors. In contrast, a 30-kb deletion that eliminates APOBEC3B and creates an APOBEC3A-APOBEC3B chimera was not important in bladder cancer, whereas it was associated with breast cancer risk and enrichment with APOBEC-signature mutations in breast tumors. In vitro, APOBEC3B expression was predominantly induced by treatment with a DNA-damaging drug in bladder cancer cell lines, and APOBEC3A expression was induced as part of the antiviral interferon-stimulated response in breast cancer cell lines. These findings suggest a tissue-specific role of environmental oncogenic triggers, particularly in individuals with germline APOBEC3 risk variants.
<h4>Background</h4>P.I157T is a CHEK2 missense mutation associated with a modest increase in breast cancer risk. Previously, another CHEK2 mutation, the protein truncating c.1100delC has been associated with poor prognosis of breast cancer patients. Here, we have investigated patient survival and characteristics of breast tumors of germ line p.I157T carriers.<h4>Methods</h4>We included in the analyses 26,801 European female breast cancer patients from 15 studies participating in the Breast Cancer Association Consortium. We analyzed the association between p.I157T and the clinico-pathological breast cancer characteristics by comparing the p.I157T carrier tumors to non-carrier and c.1100delC carrier tumors. Similarly, we investigated the p.I157T associated risk of early death, breast cancer-associated death, distant metastasis, locoregional relapse and second breast cancer using Cox proportional hazards models. Additionally, we explored the p.I157T-associated genomic gene expression profile using data from breast tumors of 183 Finnish female breast cancer patients (ten p.I157T carriers) (GEO: GSE24450). Differential gene expression analysis was performed using a moderated t test. Functional enrichment was investigated using the DAVID functional annotation tool and gene set enrichment analysis (GSEA). The tumors were classified into molecular subtypes according to the St Gallen 2013 criteria and the PAM50 gene expression signature.<h4>Results</h4>P.I157T was not associated with increased risk of early death, breast cancer-associated death or distant metastasis relapse, and there was a significant difference in prognosis associated with the two CHEK2 mutations, p.I157T and c.1100delC. Furthermore, p.I157T was associated with lobular histological type and clinico-pathological markers of good prognosis, such as ER and PR expression, low TP53 expression and low grade. Gene expression analysis suggested luminal A to be the most common subtype for p.I157T carriers and CDH1 (cadherin 1) target genes to be significantly enriched among genes, whose expression differed between p.I157T and non-carrier tumors.<h4>Conclusions</h4>Our analyses suggest that there are fundamental differences in breast tumors of CHEK2:p.I157T and c.1100delC carriers. The poor prognosis associated with c.1100delC cannot be generalized to other CHEK2 mutations.
Reduced levels of terminal duct lobular unit (TDLU) involution, as reflected by higher numbers of TDLUs and acini per TDLU, have been associated with higher breast cancer risk. Younger age at menarche and older age at menopause have been previously related to lower levels of TDLU involution. To determine a possible genetic link, we examined whether single-nucleotide polymorphisms (SNPs) previously established in genome-wide association studies (GWAS) for ages at menarche and menopause are associated with TDLU involution. We conducted a pooled analysis of 862 women from two studies. H&E tissue sections were assessed for numbers of TDLUs and acini/TDLU. Poisson regression models were used to estimate associations of 36 menarche- and 21 menopause-SNPs with TDLU counts, acini counts/TDLU, and the product of these two measures, adjusting for age and study site. Fourteen percent of evaluated SNPs (eight SNPs) were associated with TDLU counts at p < 0.05, suggesting an enrichment of associations with TDLU counts. However, only menopause-SNPs had >50 % that were either significantly or nonsignificantly associated with TDLU measures in the directions consistent with their relationships shown in GWAS. Among ten SNPs that were statistically significantly associated with at least one TDLU involution measure (p < 0.05), seven SNPs (rs466639: RXRG; rs2243803: SLC14A2; rs2292573: GAB2; rs6438424: 3q13.32; rs7606918: METAP1D; rs11668344: TMEM150B; rs1635501: EXO1) were associated in the consistent directions. Our data suggest that the loci associated with ages at menarche and menopause may influence TDLU involution, suggesting some shared genetic mechanisms. However, larger studies are needed to confirm the results.
<h4>Objective</h4>Clinical genetic testing is commercially available for rs61764370, an inherited variant residing in a KRAS 3' UTR microRNA binding site, based on suggested associations with increased ovarian and breast cancer risk as well as with survival time. However, prior studies, emphasizing particular subgroups, were relatively small. Therefore, we comprehensively evaluated ovarian and breast cancer risks as well as clinical outcome associated with rs61764370.<h4>Methods</h4>Centralized genotyping and analysis were performed for 140,012 women enrolled in the Ovarian Cancer Association Consortium (15,357 ovarian cancer patients; 30,816 controls), the Breast Cancer Association Consortium (33,530 breast cancer patients; 37,640 controls), and the Consortium of Modifiers of BRCA1 and BRCA2 (14,765 BRCA1 and 7904 BRCA2 mutation carriers).<h4>Results</h4>We found no association with risk of ovarian cancer (OR=0.99, 95% CI 0.94-1.04, p=0.74) or breast cancer (OR=0.98, 95% CI 0.94-1.01, p=0.19) and results were consistent among mutation carriers (BRCA1, ovarian cancer HR=1.09, 95% CI 0.97-1.23, p=0.14, breast cancer HR=1.04, 95% CI 0.97-1.12, p=0.27; BRCA2, ovarian cancer HR=0.89, 95% CI 0.71-1.13, p=0.34, breast cancer HR=1.06, 95% CI 0.94-1.19, p=0.35). Null results were also obtained for associations with overall survival following ovarian cancer (HR=0.94, 95% CI 0.83-1.07, p=0.38), breast cancer (HR=0.96, 95% CI 0.87-1.06, p=0.38), and all other previously-reported associations.<h4>Conclusions</h4>rs61764370 is not associated with risk of ovarian or breast cancer nor with clinical outcome for patients with these cancers. Therefore, genotyping this variant has no clinical utility related to the prediction or management of these cancers.
Common variation on 14q24.1, close to RAD51B, has been associated with breast cancer: rs999737 and rs2588809 with the risk of female breast cancer and rs1314913 with the risk of male breast cancer. The aim of this study was to investigate the role of RAD51B variants in breast cancer predisposition, particularly in the context of familial breast cancer in Finland. We sequenced the coding region of RAD51B in 168 Finnish breast cancer patients from the Helsinki region for identification of possible recurrent founder mutations. In addition, we studied the known rs999737, rs2588809, and rs1314913 SNPs and RAD51B haplotypes in 44,791 breast cancer cases and 43,583 controls from 40 studies participating in the Breast Cancer Association Consortium (BCAC) that were genotyped on a custom chip (iCOGS). We identified one putatively pathogenic missense mutation c.541C>T among the Finnish cancer patients and subsequently genotyped the mutation in additional breast cancer cases (n = 5259) and population controls (n = 3586) from Finland and Belarus. No significant association with breast cancer risk was seen in the meta-analysis of the Finnish datasets or in the large BCAC dataset. The association with previously identified risk variants rs999737, rs2588809, and rs1314913 was replicated among all breast cancer cases and also among familial cases in the BCAC dataset. The most significant association was observed for the haplotype carrying the risk-alleles of all the three SNPs both among all cases (odds ratio (OR): 1.15, 95% confidence interval (CI): 1.11-1.19, P = 8.88 x 10-16) and among familial cases (OR: 1.24, 95% CI: 1.16-1.32, P = 6.19 x 10-11), compared to the haplotype with the respective protective alleles. Our results suggest that loss-of-function mutations in RAD51B are rare, but common variation at the RAD51B region is significantly associated with familial breast cancer risk.
<h4>Background</h4>Ductal carcinoma in situ (DCIS) is a non-invasive form of breast cancer. It is often associated with invasive ductal carcinoma (IDC), and is considered to be a non-obligate precursor of IDC. It is not clear to what extent these two forms of cancer share low-risk susceptibility loci, or whether there are differences in the strength of association for shared loci.<h4>Methods</h4>To identify genetic polymorphisms that predispose to DCIS, we pooled data from 38 studies comprising 5,067 cases of DCIS, 24,584 cases of IDC and 37,467 controls, all genotyped using the iCOGS chip.<h4>Results</h4>Most (67 %) of the 76 known breast cancer predisposition loci showed an association with DCIS in the same direction as previously reported for invasive breast cancer. Case-only analysis showed no evidence for differences between associations for IDC and DCIS after considering multiple testing. Analysis by estrogen receptor (ER) status confirmed that loci associated with ER positive IDC were also associated with ER positive DCIS. Analysis of DCIS by grade suggested that two independent SNPs at 11q13.3 near CCND1 were specific to low/intermediate grade DCIS (rs75915166, rs554219). These associations with grade remained after adjusting for ER status and were also found in IDC. We found no novel DCIS-specific loci at a genome wide significance level of P < 5.0x10(-8).<h4>Conclusion</h4>In conclusion, this study provides the strongest evidence to date of a shared genetic susceptibility for IDC and DCIS. Studies with larger numbers of DCIS are needed to determine if IDC or DCIS specific loci exist.
<h4>Purpose</h4>CHEK2*1100delC is a well-established breast cancer risk variant that is most prevalent in European populations; however, there are limited data on risk of breast cancer by age and tumor subtype, which limits its usefulness in breast cancer risk prediction. We aimed to generate tumor subtype- and age-specific risk estimates by using data from the Breast Cancer Association Consortium, including 44,777 patients with breast cancer and 42,997 controls from 33 studies genotyped for CHEK2*1100delC.<h4>Patients and methods</h4>CHEK2*1100delC genotyping was mostly done by a custom Taqman assay. Breast cancer odds ratios (ORs) for CHEK2*1100delC carriers versus noncarriers were estimated by using logistic regression and adjusted for study (categorical) and age. Main analyses included patients with invasive breast cancer from population- and hospital-based studies.<h4>Results</h4>Proportions of heterozygous CHEK2*1100delC carriers in controls, in patients with breast cancer from population- and hospital-based studies, and in patients with breast cancer from familial- and clinical genetics center-based studies were 0.5%, 1.3%, and 3.0%, respectively. The estimated OR for invasive breast cancer was 2.26 (95%CI, 1.90 to 2.69; P = 2.3 × 10(-20)). The OR was higher for estrogen receptor (ER)-positive disease (2.55 [95%CI, 2.10 to 3.10; P = 4.9 × 10(-21)]) than it was for ER-negative disease (1.32 [95%CI, 0.93 to 1.88; P = .12]; P interaction = 9.9 × 10(-4)). The OR significantly declined with attained age for breast cancer overall (P = .001) and for ER-positive tumors (P = .001). Estimated cumulative risks for development of ER-positive and ER-negative tumors by age 80 in CHEK2*1100delC carriers were 20% and 3%, respectively, compared with 9% and 2%, respectively, in the general population of the United Kingdom.<h4>Conclusion</h4>These CHEK2*1100delC breast cancer risk estimates provide a basis for incorporating CHEK2*1100delC into breast cancer risk prediction models and into guidelines for intensified screening and follow-up.
Recent heritability analyses have indicated that genome-wide association studies (GWAS) have the potential to improve genetic risk prediction for complex diseases based on polygenic risk score (PRS), a simple modelling technique that can be implemented using summary-level data from the discovery samples. We herein propose modifications to improve the performance of PRS. We introduce threshold-dependent winner's-curse adjustments for marginal association coefficients that are used to weight the single-nucleotide polymorphisms (SNPs) in PRS. Further, as a way to incorporate external functional/annotation knowledge that could identify subsets of SNPs highly enriched for associations, we propose variable thresholds for SNPs selection. We applied our methods to GWAS summary-level data of 14 complex diseases. Across all diseases, a simple winner's curse correction uniformly led to enhancement of performance of the models, whereas incorporation of functional SNPs was beneficial only for selected diseases. Compared to the standard PRS algorithm, the proposed methods in combination led to notable gain in efficiency (25-50% increase in the prediction R2) for 5 of 14 diseases. As an example, for GWAS of type 2 diabetes, winner's curse correction improved prediction R2 from 2.29% based on the standard PRS to 3.10% (P = 0.0017) and incorporating functional annotation data further improved R2 to 3.53% (P = 2×10-5). Our simulation studies illustrate why differential treatment of certain categories of functional SNPs, even when shown to be highly enriched for GWAS-heritability, does not lead to proportionate improvement in genetic risk-prediction because of non-uniform linkage disequilibrium structure.
Previous genome-wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. A fine-mapping study across 2.06 Mb (chr8:127,561,724-129,624,067, hg19) in 55,540 breast cancer cases and 51,168 controls within the Breast Cancer Association Consortium was conducted. Three additional independent association signals in women of European ancestry, represented by rs35961416 (OR = 0.95, 95% CI = 0.93-0.97, conditional p = 5.8 × 10(-6) ), rs7815245 (OR = 0.94, 95% CI = 0.91-0.96, conditional p = 1.1 × 10(-6) ) and rs2033101 (OR = 1.05, 95% CI = 1.02-1.07, conditional p = 1.1 × 10(-4) ) were found. Integrative analysis using functional genomic data from the Roadmap Epigenomics, the Encyclopedia of DNA Elements project, the Cancer Genome Atlas and other public resources implied that SNPs rs7815245 in Signal 3, and rs1121948 in Signal 5 (in linkage disequilibrium with rs11780156, r(2) = 0.77), were putatively functional variants for two of the five independent association signals. The results highlighted multiple 8q24 variants associated with breast cancer susceptibility in women of European ancestry.
<h4>Background</h4>The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study.<h4>Methods</h4>We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T>G and c.3113G>A, CHEK2 c.349A>G, c.538C>T, c.715G>A, c.1036C>T, c.1312G>T, and c.1343T>G and ATM c.7271T>G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant.<h4>Results</h4>For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10<sup>-5</sup>), PALB2 c.3113G>A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10<sup>-8</sup>) and ATM c.7271T>G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A>G OR 2.26 (95% CI 1.29 to 3.95), c.1036C>T OR 5.06 (95% CI 1.09 to 23.5) and c.538C>T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T>G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G>T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants.<h4>Conclusions</h4>This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.
<h4>Background</h4>Luminal A breast cancer defined as hormone receptor positive and human epidermal growth factor receptor 2 (HER2) negative is known to be heterogeneous. Previous study showed that luminal A tumours with the expression of basal markers ((cytokeratin (CK) 5 or CK5/6) or epidermal growth factor receptor (EGFR)) were associated with poorer prognosis compared with those that stained negative for basal markers. Prompted by this study, we assessed whether tumour characteristics and risk factors differed by basal marker status within luminal A tumours.<h4>Methods</h4>We pooled 5040 luminal A cases defined by immunohistochemistry (4490 basal-negative ((CK5 (or CK5/6))- and EGFR-) and 550 basal-positive ((CK5 (or CK5/6+)) or EGFR+)) from eight studies participating in the Breast Cancer Association Consortium. Case-case comparison was performed using unconditional logistic regression.<h4>Results</h4>Tumour characteristics and risk factors did not vary significantly by the expression of basal markers, although results suggested that basal-positive luminal tumours tended to be smaller and node negative, and were more common in women with a positive family history and lower body mass index.<h4>Conclusions</h4>Most established breast cancer risk factors were similar in basal-positive and basal-negative luminal A tumours. The non-significant but suggestive differences in tumour features and family history warrant further investigations.
<h4>Background</h4>Approximately 100 common breast cancer susceptibility alleles have been identified in genome-wide association studies (GWAS). The utility of these variants in breast cancer risk prediction models has not been evaluated adequately in women of Asian ancestry.<h4>Methods</h4>We evaluated 88 breast cancer risk variants that were identified previously by GWAS in 11,760 cases and 11,612 controls of Asian ancestry. SNPs confirmed to be associated with breast cancer risk in Asian women were used to construct a polygenic risk score (PRS). The relative and absolute risks of breast cancer by the PRS percentiles were estimated based on the PRS distribution, and were used to stratify women into different levels of breast cancer risk.<h4>Results</h4>We confirmed significant associations with breast cancer risk for SNPs in 44 of the 78 previously reported loci at P < 0.05. Compared with women in the middle quintile of the PRS, women in the top 1% group had a 2.70-fold elevated risk of breast cancer (95% CI: 2.15-3.40). The risk prediction model with the PRS had an area under the receiver operating characteristic curve of 0.606. The lifetime risk of breast cancer for Shanghai Chinese women in the lowest and highest 1% of the PRS was 1.35% and 10.06%, respectively.<h4>Conclusion</h4>Approximately one-half of GWAS-identified breast cancer risk variants can be directly replicated in East Asian women. Collectively, common genetic variants are important predictors for breast cancer risk. Using common genetic variants for breast cancer could help identify women at high risk of breast cancer.
Breast cancer is the most diagnosed malignancy and the second leading cause of cancer mortality in females. Previous association studies have identified variants on 2q35 associated with the risk of breast cancer. To identify functional susceptibility loci for breast cancer, we interrogated the 2q35 gene desert for chromatin architecture and functional variation correlated with gene expression. We report a novel intergenic breast cancer risk locus containing an enhancer copy number variation (enCNV; deletion) located approximately 400Kb upstream to IGFBP5, which overlaps an intergenic ERα-bound enhancer that loops to the IGFBP5 promoter. The enCNV is correlated with modified ERα binding and monoallelic-repression of IGFBP5 following oestrogen treatment. We investigated the association of enCNV genotype with breast cancer in 1,182 cases and 1,362 controls, and replicate our findings in an independent set of 62,533 cases and 60,966 controls from 41 case control studies and 11 GWAS. We report a dose-dependent inverse association of 2q35 enCNV genotype (percopy OR = 0.68 95%CI 0.55-0.83, P = 0.0002; replication OR = 0.77 95% CI 0.73-0.82, P = 2.1 × 10<sup>-19</sup>) and identify 13 additional linked variants (r<sup>2 </sup>><sup> </sup>0.8) in the 20Kb linkage block containing the enCNV (P = 3.2 × 10<sup>-15</sup> - 5.6 × 10<sup>-17</sup>). These associations were independent of previously reported 2q35 variants, rs13387042/rs4442975 and rs16857609, and were stronger for ER-positive than ER-negative disease. Together, these results suggest that 2q35 breast cancer risk loci may be mediating their effect through IGFBP5.
Previous studies have shown that a greater number of ovulatory cycles, cumulatively summed as lifetime number of ovulatory cycles (LOC), increases ovarian cancer risk, but there is no uniform algorithm with which to compute LOC. The association between LOC and endometrial cancer is less certain. Accordingly, we identified 14 different LOC algorithms in a literature review and calculated LOCs in the Polish Cancer Study (2001-2003). We evaluated the associations of LOC with ovarian and endometrial cancer risks using unconditional logistic regression, with and without adjustment for individual risk factors used in the LOC computations. Our analysis included 302 ovarian cancer cases with 1,356 controls and 532 endometrial cancer cases with 1,286 controls. We found a high correlation between LOC values among the combined controls (r ≥ 0.88) and identified 5 groups of similar LOC algorithms. A LOC value in the highest quartile was associated with ovarian cancer risk as computed by 2 algorithms (odds ratio (OR) = 2.22 (95% confidence interval (CI): 1.07, 4.62) and OR = 2.44 (95% CI: 1.22, 4.87)) and with endometrial cancer risk as computed by 1 algorithm (OR = 1.95, 95% CI: 1.11, 3.44). LOC algorithms using a core set of variables widely available in epidemiologic studies may be independently associated with risk of gynecological cancers beyond the contribution of the individual risk factors, such as ages at menopause and menarche.
<h4>Background</h4>Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk.<h4>Method</h4>We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation.<h4>Results</h4>Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05.<h4>Conclusion</h4>This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk.
<h4>Purpose</h4>Type 2 diabetes (T2D) has been reported to be associated with an elevated risk of breast cancer. It is unclear, however, whether this association is due to shared genetic factors.<h4>Methods</h4>We constructed a genetic risk score (GRS) using risk variants from 33 known independent T2D susceptibility loci and evaluated its relation to breast cancer risk using the data from two consortia, including 62,328 breast cancer patients and 83,817 controls of European ancestry. Unconditional logistic regression models were used to derive adjusted odds ratios (ORs) and 95 % confidence intervals (CIs) to measure the association of breast cancer risk with T2D GRS or T2D-associated genetic risk variants. Meta-analyses were conducted to obtain summary ORs across all studies.<h4>Results</h4>The T2D GRS was not found to be associated with breast cancer risk, overall, by menopausal status, or for estrogen receptor positive or negative breast cancer. Three T2D associated risk variants were individually associated with breast cancer risk after adjustment for multiple comparisons using the Bonferroni method (at p < 0.001), rs9939609 (FTO) (OR 0.94, 95 % CI = 0.92-0.95, p = 4.13E-13), rs7903146 (TCF7L2) (OR 1.04, 95 % CI = 1.02-1.06, p = 1.26E-05), and rs8042680 (PRC1) (OR 0.97, 95 % CI = 0.95-0.99, p = 8.05E-04).<h4>Conclusions</h4>We have shown that several genetic risk variants were associated with the risk of both T2D and breast cancer. However, overall genetic susceptibility to T2D may not be related to breast cancer risk.
Mosaic loss of chromosome Y (mLOY) leading to gonosomal XY/XO commonly occurs during aging, particularly in smokers. We investigated whether mLOY was associated with non-hematological cancer in three prospective cohorts (8,679 cancer cases and 5,110 cancer-free controls) and genetic susceptibility to mLOY. Overall, mLOY was observed in 7% of men, and its prevalence increased with age (per-year odds ratio (OR) = 1.13, 95% confidence interval (CI) = 1.12-1.15; P < 2 × 10(-16)), reaching 18.7% among men over 80 years old. mLOY was associated with current smoking (OR = 2.35, 95% CI = 1.82-3.03; P = 5.55 × 10(-11)), but the association weakened with years after cessation. mLOY was not consistently associated with overall or specific cancer risk (for example, bladder, lung or prostate cancer) nor with cancer survival after diagnosis (multivariate-adjusted hazard ratio = 0.87, 95% CI = 0.73-1.04; P = 0.12). In a genome-wide association study, we observed the first example of a common susceptibility locus for genetic mosaicism, specifically mLOY, which maps to TCL1A at 14q32.13, marked by rs2887399 (OR = 1.55, 95% CI = 1.36-1.78; P = 1.37 × 10(-10)).
<h4>Background</h4>Genome-wide association studies have reported nearly 100 common germline susceptibility loci associated with the risk for breast cancer. Tumour sequencing studies have characterised somatic mutation profiles in breast cancer patients. The relationship between breast cancer susceptibility loci and somatic mutation patterns in breast cancer remains largely unexplored.<h4>Methods</h4>We used single-nucleotide polymorphism (SNP) genotyping array data and tumour exome sequencing data available from 638 breast cancer patients of European ancestry from The Cancer Genome Atlas (TCGA) project. We analysed both genotype data and, when necessary, imputed genotypes for 90 known breast cancer susceptibility loci. We performed linear regression models to investigate possible associations between germline risk variants with total somatic mutation count (TSMC), as well as specific mutation types. We examined individual SNP genotypes, as well as a multi-SNP polygenic risk score (PRS). Models were statistically adjusted for age at diagnosis, stage, oestrogen-receptor (ER) and progesterone-receptor (PR) status of breast cancer. We also performed stratified analyses by ER and PR status.<h4>Results</h4>We observed a significant inverse association (P=8.75 × 10(-6); FDR=0.001) between the risk allele in rs2588809 of the gene RAD51B and TSMC across all breast cancer patients, for both ER(+) and ER(-) tumours. This association was also evident for different types of mutations. The PRS analysis for all patients, with or without rs2588809, showed a significant inverse association (P=0.01 and 0.04, respectively) with TSMC. This inverse association was significant in ER(+) patients with the ER(+)-specific PRS (P=0.02), but not among ER(-) patients for the ER(-)-specific PRS (P=0.39).<h4>Conclusions</h4>We observed an inverse association between common germline risk variants and TSMC, which, if confirmed, could provide new insights into how germline variation informs our understanding of somatic mutation patterns in breast cancer.
<h4>Background</h4>Citizen science, scientific research conducted by non-specialists, has the potential to facilitate biomedical research using available large-scale data, however validating the results is challenging. The Cell Slider is a citizen science project that intends to share images from tumors with the general public, enabling them to score tumor markers independently through an internet-based interface.<h4>Methods</h4>From October 2012 to June 2014, 98,293 Citizen Scientists accessed the Cell Slider web page and scored 180,172 sub-images derived from images of 12,326 tissue microarray cores labeled for estrogen receptor (ER). We evaluated the accuracy of Citizen Scientist's ER classification, and the association between ER status and prognosis by comparing their test performance against trained pathologists.<h4>Findings</h4>The area under ROC curve was 0.95 (95% CI 0.94 to 0.96) for cancer cell identification and 0.97 (95% CI 0.96 to 0.97) for ER status. ER positive tumors scored by Citizen Scientists were associated with survival in a similar way to that scored by trained pathologists. Survival probability at 15 years were 0.78 (95% CI 0.76 to 0.80) for ER-positive and 0.72 (95% CI 0.68 to 0.77) for ER-negative tumors based on Citizen Scientists classification. Based on pathologist classification, survival probability was 0.79 (95% CI 0.77 to 0.81) for ER-positive and 0.71 (95% CI 0.67 to 0.74) for ER-negative tumors. The hazard ratio for death was 0.26 (95% CI 0.18 to 0.37) at diagnosis and became greater than one after 6.5 years of follow-up for ER scored by Citizen Scientists, and 0.24 (95% CI 0.18 to 0.33) at diagnosis increasing thereafter to one after 6.7 (95% CI 4.1 to 10.9) years of follow-up for ER scored by pathologists.<h4>Interpretation</h4>Crowdsourcing of the general public to classify cancer pathology data for research is viable, engages the public and provides accurate ER data. Crowdsourced classification of research data may offer a valid solution to problems of throughput requiring human input.
Genome-wide association studies have identified SNPs near ZNF365 at 10q21.2 that are associated with both breast cancer risk and mammographic density. To identify the most likely causal SNPs, we fine mapped the association signal by genotyping 428 SNPs across the region in 89,050 European and 12,893 Asian case and control subjects from the Breast Cancer Association Consortium. We identified four independent sets of correlated, highly trait-associated variants (iCHAVs), three of which were located within ZNF365. The most strongly risk-associated SNP, rs10995201 in iCHAV1, showed clear evidence of association with both estrogen receptor (ER)-positive (OR = 0.85 [0.82-0.88]) and ER-negative (OR = 0.87 [0.82-0.91]) disease, and was also the SNP most strongly associated with percent mammographic density. iCHAV2 (lead SNP, chr10: 64,258,684:D) and iCHAV3 (lead SNP, rs7922449) were also associated with ER-positive (OR = 0.93 [0.91-0.95] and OR = 1.06 [1.03-1.09]) and ER-negative (OR = 0.95 [0.91-0.98] and OR = 1.08 [1.04-1.13]) disease. There was weaker evidence for iCHAV4, located 5' of ADO, associated only with ER-positive breast cancer (OR = 0.93 [0.90-0.96]). We found 12, 17, 18, and 2 candidate causal SNPs for breast cancer in iCHAVs 1-4, respectively. Chromosome conformation capture analysis showed that iCHAV2 interacts with the ZNF365 and NRBF2 (more than 600 kb away) promoters in normal and cancerous breast epithelial cells. Luciferase assays did not identify SNPs that affect transactivation of ZNF365, but identified a protective haplotype in iCHAV2, associated with silencing of the NRBF2 promoter, implicating this gene in the etiology of breast cancer.
Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ∼70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two regions harboring additional rare missense alleles of large effect. We found enrichment of signals in or near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses identified major association with DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal effect of later ANM on breast cancer risk (∼6% increase in risk per year; P = 3 × 10(-14)), likely mediated by prolonged sex hormone exposure rather than DDR mechanisms.
We have utilized a two-stage study design to search for SNPs associated with the survival of breast cancer patients treated with adjuvant chemotherapy. Our initial GWS data set consisted of 805 Finnish breast cancer cases (360 treated with adjuvant chemotherapy). The top 39 SNPs from this stage were analyzed in three independent data sets: iCOGS (n=6720 chemotherapy-treated cases), SUCCESS-A (n=3596), and POSH (n=518). Two SNPs were successfully validated: rs6500843 (any chemotherapy; per-allele HR 1.16, 95% C.I. 1.08-1.26, p=0.0001, p(adjusted)=0.0091), and rs11155012 (anthracycline therapy; per-allele HR 1.21, 95% C.I. 1.08-1.35, p=0.0010, p(adjusted)=0.0270). The SNP rs6500843 was found to specifically interact with adjuvant chemotherapy, independently of standard prognostic markers (p(interaction)=0.0009), with the rs6500843-GG genotype corresponding to the highest hazard among chemotherapy-treated cases (HR 1.47, 95% C.I. 1.20-1.80). Upon trans-eQTL analysis of public microarray data, the rs6500843 locus was found to associate with the expression of a group of genes involved in cell cycle control, notably AURKA, the expression of which also exhibited differential prognostic value between chemotherapy-treated and untreated cases in our analysis of microarray data. Based on previously published information, we propose that the eQTL genes may be connected to the rs6500843 locus via a RBFOX1-FOXM1 -mediated regulatory pathway.
Few studies have demonstrated gene/environment interactions in cancer research. Using data on high-risk occupations for 2258 case patients and 2410 control patients from two bladder cancer studies, we observed that three of 16 known or candidate bladder cancer susceptibility variants displayed statistically significant and consistent evidence of additive interactions; specifically, the GSTM1 deletion polymorphism (P interaction ≤ .001), rs11892031 (UGT1A, P interaction = .01), and rs798766 (TMEM129-TACC3-FGFR3, P interaction = .03). There was limited evidence for multiplicative interactions. When we examined detailed data on a prevalent occupational exposure associated with increased bladder cancer risk, straight metalworking fluids, we also observed statistically significant additive interaction for rs798766 (TMEM129-TACC3-FGFR3, P interaction = .02), with the interaction more apparent in patients with tumors positive for FGFR3 expression. All statistical tests were two-sided. The interaction we observed for rs798766 (TMEM129-TACC3-FGFR3) with specific exposure to straight metalworking fluids illustrates the value of integrating germline genetic variation, environmental exposures, and tumor marker data to provide insight into the mechanisms of bladder carcinogenesis.
Identification of prognostic gene expression signatures may enable improved decisions about management of breast cancer. To identify a prognostic signature for breast cancer, we performed DNA methylation profiling and identified methylation markers that were associated with expression of ER, PR, HER2, CK5/6, and EGFR proteins. Methylation markers that were correlated with corresponding mRNA expression levels were identified using 208 invasive tumors from a population-based case-control study conducted in Poland. Using this approach, we defined the methylation expression index (MEI) signature that was based on a weighted sum of mRNA levels of 57 genes. Classification of cases as low or high MEI scores was related to survival using Cox regression models. In the Polish study, women with ER-positive low MEI cancers had reduced survival at a median of 5.20 years of follow-up, HR = 2.85 95 % CI = 1.25-6.47. Low MEI was also related to decreased survival in four independent datasets totaling over 2500 ER-positive breast cancers. These results suggest that integrated analysis of tumor expression markers, DNA methylation, and mRNA data may be an important approach for identifying breast cancer prognostic signatures. Prospective assessment of MEI along with other prognostic signatures should be evaluated in future studies.
BACKGROUND: Epigenome-wide association studies (EWAS) using measurements of blood DNA methylation are performed to identify associations of methylation changes with environmental and lifestyle exposures and disease risk. However, little is known about the variation of methylation markers in the population and their stability over time, both important factors in the design and interpretation of EWAS. We aimed to identify stable variable methylated probes (VMP), i.e., markers that are variable in the population, yet stable over time. METHODS: We estimated the intraclass correlation coefficient (ICC) for each probe on the Illumina 450K methylation array in paired samples collected approximately 6 years apart from 92 participants in the Breakthrough Generations Study. We also evaluated relationships with age, reproductive and hormonal history, weight, alcohol intake, and smoking. RESULTS: Approximately 17% of probes had an ICC > 0.50 and were considered stable VMPs (stable-VMPs). Stable-VMPs were enriched for probes located in "shores" bordering CpG islands, and at approximately 1.3 kb downstream from the transcription start site in the transition between the unmethylated promoter and methylated gene body. Both cross-sectional and longitudinal data analyses provided strong evidence for associations between changes in methylation levels and aging. Smoking-related probes at 2q37.1 and AHRR were stable-VMPs and related to time since quitting. We also observed associations between methylation and weight changes. CONCLUSION: Our results provide support for the use of white blood cell DNA methylation as a biomarker of exposure in EWAS. IMPACT: Larger studies, preferably with repeated measures over time, will be required to establish associations between specific probes and exposures.
The role of lifestyle risk factors in prostate cancer risk remains elusive despite a large number of epidemiologic studies. In a pooled analysis of data from South and East Asian countries published in this issue, Fowke et al. (Am J Epidemiol. 2015;182(5):381-389) found no evidence for an association between prostate cancer mortality and obesity, alcohol, or smoking. Prostate cancer screening is very uncommon in these countries, and previous evidence for associations with lifestyle factors comes primarily from studies carried out in North America, where screening is very common. Fowke et al. concluded that screening biases are likely to explain the differences in study results. In this commentary, we discuss the potential influence of population-based cancer screening programs in estimates of association from epidemiologic studies. This highlights the importance of carefully considering the impact of screening in the analysis and interpretation of results, in order to advance our understanding of the etiology of cancers that can be detected by screening.
Genome-wide association studies (GWASs) have revealed SNP rs889312 on 5q11.2 to be associated with breast cancer risk in women of European ancestry. In an attempt to identify the biologically relevant variants, we analyzed 909 genetic variants across 5q11.2 in 103,991 breast cancer individuals and control individuals from 52 studies in the Breast Cancer Association Consortium. Multiple logistic regression analyses identified three independent risk signals: the strongest associations were with 15 correlated variants (iCHAV1), where the minor allele of the best candidate, rs62355902, associated with significantly increased risks of both estrogen-receptor-positive (ER(+): odds ratio [OR] = 1.24, 95% confidence interval [CI] = 1.21-1.27, ptrend = 5.7 × 10(-44)) and estrogen-receptor-negative (ER(-): OR = 1.10, 95% CI = 1.05-1.15, ptrend = 3.0 × 10(-4)) tumors. After adjustment for rs62355902, we found evidence of association of a further 173 variants (iCHAV2) containing three subsets with a range of effects (the strongest was rs113317823 [pcond = 1.61 × 10(-5)]) and five variants composing iCHAV3 (lead rs11949391; ER(+): OR = 0.90, 95% CI = 0.87-0.93, pcond = 1.4 × 10(-4)). Twenty-six percent of the prioritized candidate variants coincided with four putative regulatory elements that interact with the MAP3K1 promoter through chromatin looping and affect MAP3K1 promoter activity. Functional analysis indicated that the cancer risk alleles of four candidates (rs74345699 and rs62355900 [iCHAV1], rs16886397 [iCHAV2a], and rs17432750 [iCHAV3]) increased MAP3K1 transcriptional activity. Chromatin immunoprecipitation analysis revealed diminished GATA3 binding to the minor (cancer-protective) allele of rs17432750, indicating a mechanism for its action. We propose that the cancer risk alleles act to increase MAP3K1 expression in vivo and might promote breast cancer cell survival.
<h4>Background</h4>Survival after a diagnosis of breast cancer varies considerably between patients, and some of this variation may be because of germline genetic variation. We aimed to identify genetic markers associated with breast cancer-specific survival.<h4>Methods</h4>We conducted a large meta-analysis of studies in populations of European ancestry, including 37954 patients with 2900 deaths from breast cancer. Each study had been genotyped for between 200000 and 900000 single nucleotide polymorphisms (SNPs) across the genome; genotypes for nine million common variants were imputed using a common reference panel from the 1000 Genomes Project. We also carried out subtype-specific analyses based on 6881 estrogen receptor (ER)-negative patients (920 events) and 23059 ER-positive patients (1333 events). All statistical tests were two-sided.<h4>Results</h4>We identified one new locus (rs2059614 at 11q24.2) associated with survival in ER-negative breast cancer cases (hazard ratio [HR] = 1.95, 95% confidence interval [CI] = 1.55 to 2.47, P = 1.91 x 10(-8)). Genotyping a subset of 2113 case patients, of which 300 were ER negative, provided supporting evidence for the quality of the imputation. The association in this set of case patients was stronger for the observed genotypes than for the imputed genotypes. A second locus (rs148760487 at 2q24.2) was associated at genome-wide statistical significance in initial analyses; the association was similar in ER-positive and ER-negative case patients. Here the results of genotyping suggested that the finding was less robust.<h4>Conclusions</h4>This is currently the largest study investigating genetic variation associated with breast cancer survival. Our results have potential clinical implications, as they confirm that germline genotype can provide prognostic information in addition to standard tumor prognostic factors.
<h4>Background</h4>A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored.<h4>Methods</h4>We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium.<h4>Results</h4>Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10(-4); OR, 1.04; 95% confidence interval (CI), 1.02-1.07] and rs77928427 (P = 1.86 × 10(-4); OR, 1.04; 95% CI, 1.02-1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r(2) ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor-binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue.<h4>Conclusion</h4>Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2.<h4>Impact</h4>Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk.
Breast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large-scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65-70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose-response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96-98%), but yielded many false positives (positive predictive value = 30-32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large-scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker-specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results.
In breast cancer, constitutive activation of NF-κB has been reported, however, the impact of genetic variation of the pathway on patient prognosis has been little studied. Furthermore, a combination of genetic variants, rather than single polymorphisms, may affect disease prognosis. Here, in an extensive dataset (n = 30,431) from the Breast Cancer Association Consortium, we investigated the association of 917 SNPs in 75 genes in the NF-κB pathway with breast cancer prognosis. We explored SNP-SNP interactions on survival using the likelihood-ratio test comparing multivariate Cox' regression models of SNP pairs without and with an interaction term. We found two interacting pairs associating with prognosis: patients simultaneously homozygous for the rare alleles of rs5996080 and rs7973914 had worse survival (HRinteraction 6.98, 95% CI=3.3-14.4, P=1.42E-07), and patients carrying at least one rare allele for rs17243893 and rs57890595 had better survival (HRinteraction 0.51, 95% CI=0.3-0.6, P = 2.19E-05). Based on in silico functional analyses and literature, we speculate that the rs5996080 and rs7973914 loci may affect the BAFFR and TNFR1/TNFR3 receptors and breast cancer survival, possibly by disturbing both the canonical and non-canonical NF-κB pathways or their dynamics, whereas, rs17243893-rs57890595 interaction on survival may be mediated through TRAF2-TRAIL-R4 interplay. These results warrant further validation and functional analyses.
The chromosomal passenger complex (CPC) plays a pivotal role in the regulation of cell division. Therefore, inherited CPC variability could influence tumor development. The present candidate gene approach investigates the relationship between single nucleotide polymorphisms (SNPs) in genes encoding key CPC components and breast cancer risk. Fifteen SNPs in four CPC genes (INCENP, AURKB, BIRC5 and CDCA8) were genotyped in 88 911 European women from 39 case-control studies of the Breast Cancer Association Consortium. Possible associations were investigated in fixed-effects meta-analyses. The synonymous SNP rs1675126 in exon 7 of INCENP was associated with overall breast cancer risk [per A allele odds ratio (OR) 0.95, 95% confidence interval (CI) 0.92-0.98, P = 0.007] and particularly with estrogen receptor (ER)-negative breast tumors (per A allele OR 0.89, 95% CI 0.83-0.95, P = 0.0005). SNPs not directly genotyped were imputed based on 1000 Genomes. The SNPs rs1047739 in the 3' untranslated region and rs144045115 downstream of INCENP showed the strongest association signals for overall (per T allele OR 1.03, 95% CI 1.00-1.06, P = 0.0009) and ER-negative breast cancer risk (per A allele OR 1.06, 95% CI 1.02-1.10, P = 0.0002). Two genotyped SNPs in BIRC5 were associated with familial breast cancer risk (top SNP rs2071214: per G allele OR 1.12, 95% CI 1.04-1.21, P = 0.002). The data suggest that INCENP in the CPC pathway contributes to ER-negative breast cancer susceptibility in the European population. In spite of a modest contribution of CPC-inherited variants to the total burden of sporadic and familial breast cancer, their potential as novel targets for breast cancer treatment should be further investigated.
<h4>Introduction</h4>Tumor lymphocyte infiltration is associated with clinical response to chemotherapy in estrogen receptor (ER) negative breast cancer. To identify variants in immunosuppressive pathway genes associated with prognosis after adjuvant chemotherapy for ER-negative patients, we studied stage I-III invasive breast cancer patients of European ancestry, including 9,334 ER-positive (3,151 treated with chemotherapy) and 2,334 ER-negative patients (1,499 treated with chemotherapy).<h4>Methods</h4>We pooled data from sixteen studies from the Breast Cancer Association Consortium (BCAC), and employed two independent studies for replications. Overall 3,610 single nucleotide polymorphisms (SNPs) in 133 genes were genotyped as part of the Collaborative Oncological Gene-environment Study, in which phenotype and clinical data were collected and harmonized. Multivariable Cox proportional hazard regression was used to assess genetic associations with overall survival (OS) and breast cancer-specific survival (BCSS). Heterogeneity according to chemotherapy or ER status was evaluated with the log-likelihood ratio test.<h4>Results</h4>Three independent SNPs in TGFBR2 and IL12B were associated with OS (P <10⁻³) solely in ER-negative patients after chemotherapy (267 events). Poorer OS associated with TGFBR2 rs1367610 (G > C) (per allele hazard ratio (HR) 1.54 (95% confidence interval (CI) 1.22 to 1.95), P = 3.08 × 10⁻⁴) was not found in ER-negative patients without chemotherapy or ER-positive patients with chemotherapy (P for interaction <10-3). Two SNPs in IL12B (r² = 0.20) showed different associations with ER-negative disease after chemotherapy: rs2546892 (G > A) with poorer OS (HR 1.50 (95% CI 1.21 to 1.86), P = 1.81 × 10⁻⁴), and rs2853694 (A > C) with improved OS (HR 0.73 (95% CI 0.61 to 0.87), P = 3.67 × 10⁻⁴). Similar associations were observed with BCSS. Association with TGFBR2 rs1367610 but not IL12B variants replicated using BCAC Asian samples and the independent Prospective Study of Outcomes in Sporadic versus Hereditary Breast Cancer Study and yielded a combined HR of 1.57 ((95% CI 1.28 to 1.94), P = 2.05 × 10⁻⁵) without study heterogeneity.<h4>Conclusions</h4>TGFBR2 variants may have prognostic and predictive value in ER-negative breast cancer patients treated with adjuvant chemotherapy. Our findings provide further insights into the development of immunotherapeutic targets for ER-negative breast cancer.
Increased mitochondrial DNA (mtDNA) copy number in peripheral blood cells (PBC) has been associated with the risk of developing several tumor types. Here we evaluate sources of variation of this biomarker and its association with breast cancer risk in a prospective cohort study. mtDNA copy number was measured using quantitative real-time PCR on PBC DNA samples from participants in the UK-based Breakthrough Generations Study. Temporal and assay variation was evaluated in a serial study of 91 women, with two blood samples collected approximately 6-years apart. Then, associations with breast cancer risk factors and risk were evaluated in 1,108 cases and 1,099 controls using a nested case-control design. In the serial study, mtDNA copy number showed low assay variation but large temporal variation [assay intraclass correlation coefficient (ICC), 79.3%-87.9%; temporal ICC, 38.3%). Higher mtDNA copy number was significantly associated with younger age at blood collection, being premenopausal, having an older age at menopause, and never taking HRT, both in cases and controls. Based on measurements in a single blood sample taken on average 6 years before diagnosis, higher mtDNA copy number was associated with increased breast cancer risk [OR (95% CI) for highest versus lowest quartile, 1.37 (1.02-1.83); P trend = 0.007]. In conclusion, mtDNA copy number is associated with breast cancer risk and represents a promising biomarker for risk assessment. The relatively large temporal variation should be taken into account in future analyses.
Previous studies have suggested that polymorphisms in CASP8 on chromosome 2 are associated with breast cancer risk. To clarify the role of CASP8 in breast cancer susceptibility, we carried out dense genotyping of this region in the Breast Cancer Association Consortium (BCAC). Single-nucleotide polymorphisms (SNPs) spanning a 1 Mb region around CASP8 were genotyped in 46 450 breast cancer cases and 42 600 controls of European origin from 41 studies participating in the BCAC as part of a custom genotyping array experiment (iCOGS). Missing genotypes and SNPs were imputed and, after quality exclusions, 501 typed and 1232 imputed SNPs were included in logistic regression models adjusting for study and ancestry principal components. The SNPs retained in the final model were investigated further in data from nine genome-wide association studies (GWAS) comprising in total 10 052 case and 12 575 control subjects. The most significant association signal observed in European subjects was for the imputed intronic SNP rs1830298 in ALS2CR12 (telomeric to CASP8), with per allele odds ratio and 95% confidence interval [OR (95% confidence interval, CI)] for the minor allele of 1.05 (1.03-1.07), P = 1 × 10(-5). Three additional independent signals from intronic SNPs were identified, in CASP8 (rs36043647), ALS2CR11 (rs59278883) and CFLAR (rs7558475). The association with rs1830298 was replicated in the imputed results from the combined GWAS (P = 3 × 10(-6)), yielding a combined OR (95% CI) of 1.06 (1.04-1.08), P = 1 × 10(-9). Analyses of gene expression associations in peripheral blood and normal breast tissue indicate that CASP8 might be the target gene, suggesting a mechanism involving apoptosis.
Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 × 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population.
<h4>Background</h4>Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking.<h4>Methods</h4>We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates.<h4>Results</h4>There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer.<h4>Conclusions</h4>The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.
Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.
We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further 5795 cases and 6624 controls of Asian ancestry from nine studies. Single nucleotide polymorphism (SNP) rs676256 was most strongly associated with risk in Europeans (odds ratios [OR] = 0.90 [0.88-0.92]; P-value = 1.58 × 10(-25)). This SNP is one of a cluster of highly correlated variants, including rs865686, that spans ∼14.5 kb. We identified two additional independent association signals demarcated by SNPs rs10816625 (OR = 1.12 [1.08-1.17]; P-value = 7.89 × 10(-09)) and rs13294895 (OR = 1.09 [1.06-1.12]; P-value = 2.97 × 10(-11)). SNP rs10816625, but not rs13294895, was also associated with risk of breast cancer in Asian individuals (OR = 1.12 [1.06-1.18]; P-value = 2.77 × 10(-05)). Functional genomic annotation using data derived from breast cancer cell-line models indicates that these SNPs localise to putative enhancer elements that bind known drivers of hormone-dependent breast cancer, including ER-α, FOXA1 and GATA-3. In vitro analyses indicate that rs10816625 and rs13294895 have allele-specific effects on enhancer activity and suggest chromatin interactions with the KLF4 gene locus. These results demonstrate the power of dense genotyping in large studies to identify independent susceptibility variants. Analysis of associations using subjects with different ancestry, combined with bioinformatic and genomic characterisation, can provide strong evidence for the likely causative alleles and their functional basis.
<h4>Introduction</h4>Previous studies have identified common germline variants nominally associated with breast cancer survival. These associations have not been widely replicated in further studies. The purpose of this study was to evaluate the association of previously reported SNPs with breast cancer-specific survival using data from a pooled analysis of eight breast cancer survival genome-wide association studies (GWAS) from the Breast Cancer Association Consortium.<h4>Methods</h4>A literature review was conducted of all previously published associations between common germline variants and three survival outcomes: breast cancer-specific survival, overall survival and disease-free survival. All associations that reached the nominal significance level of P value <0.05 were included. Single nucleotide polymorphisms that had been previously reported as nominally associated with at least one survival outcome were evaluated in the pooled analysis of over 37,000 breast cancer cases for association with breast cancer-specific survival. Previous associations were evaluated using a one-sided test based on the reported direction of effect.<h4>Results</h4>Fifty-six variants from 45 previous publications were evaluated in the meta-analysis. Fifty-four of these were evaluated in the full set of 37,954 breast cancer cases with 2,900 events and the two additional variants were evaluated in a reduced sample size of 30,000 samples in order to ensure independence from the previously published studies. Five variants reached nominal significance (P <0.05) in the pooled GWAS data compared to 2.8 expected under the null hypothesis. Seven additional variants were associated (P <0.05) with ER-positive disease.<h4>Conclusions</h4>Although no variants reached genome-wide significance (P <5 x 10(-8)), these results suggest that there is some evidence of association between candidate common germline variants and breast cancer prognosis. Larger studies from multinational collaborations are necessary to increase the power to detect associations, between common variants and prognosis, at more stringent significance levels.
Genome-wide association studies (GWAS) have identified common variants that predispose individuals to a higher body mass index (BMI), an independent risk factor for endometrial cancer. Composite genotype risk scores (GRS) based on the joint effect of published BMI risk loci were used to explore whether endometrial cancer shares a genetic background with obesity. Genotype and risk factor data were available on 3,376 endometrial cancer case and 3,867 control participants of European ancestry from the Epidemiology of Endometrial Cancer Consortium GWAS. A BMI GRS was calculated by summing the number of BMI risk alleles at 97 independent loci. For exploratory analyses, additional GRSs were based on subsets of risk loci within putative etiologic BMI pathways. The BMI GRS was statistically significantly associated with endometrial cancer risk (P = 0.002). For every 10 BMI risk alleles a woman had a 13% increased endometrial cancer risk (95% CI: 4%, 22%). However, after adjusting for BMI, the BMI GRS was no longer associated with risk (per 10 BMI risk alleles OR = 0.99, 95% CI: 0.91, 1.07; P = 0.78). Heterogeneity by BMI did not reach statistical significance (P = 0.06), and no effect modification was noted by age, GWAS Stage, study design or between studies (P≥0.58). In exploratory analyses, the GRS defined by variants at loci containing monogenic obesity syndrome genes was associated with reduced endometrial cancer risk independent of BMI (per BMI risk allele OR = 0.92, 95% CI: 0.88, 0.96; P = 2.1 x 10-5). Possessing a large number of BMI risk alleles does not increase endometrial cancer risk above that conferred by excess body weight among women of European descent. Thus, the GRS based on all current established BMI loci does not provide added value independent of BMI. Future studies are required to validate the unexpected observed relation between monogenic obesity syndrome genetic variants and endometrial cancer risk.
A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes-type shrinkage estimator. Six SNPs showed interactions with associated p-values (pint ) <1.1 × 10(-3) . None of the observed interactions was significant after accounting for multiple testing. The Bayesian False Discovery Probability was used to rank the findings, which indicated three interactions as being noteworthy at 1% prior probability of interaction. SNP rs6828523 was associated with increased ER-negative BC risk in women ≥170 cm (OR = 1.22, p = 0.017), but inversely associated with ER-negative BC risk in women <160 cm (OR = 0.83, p = 0.039, pint = 1.9 × 10(-4) ). The inverse association between rs4808801 and overall BC risk was stronger for women who had had four or more pregnancies (OR = 0.85, p = 2.0 × 10(-4) ), and absent in women who had had just one (OR = 0.96, p = 0.19, pint = 6.1 × 10(-4) ). SNP rs11242675 was inversely associated with overall BC risk in never/former smokers (OR = 0.93, p = 2.8 × 10(-5) ), but no association was observed in current smokers (OR = 1.07, p = 0.14, pint = 3.4 × 10(-4) ). In conclusion, recently identified BC susceptibility loci are not strongly modified by established risk factors and the observed potential interactions require confirmation in independent studies.
<h4>Background</h4>Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites.<h4>Methods</h4>Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers.<h4>Results</h4>GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl (2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE =0.18), and bladder and lung (ρ = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures.<h4>Conclusion</h4>Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.
<h4>Background</h4>Annexin A1 (ANXA1) is a protein related with the carcinogenesis process and metastasis formation in many tumors. However, little is known about the prognostic value of ANXA1 in breast cancer. The purpose of this study is to evaluate the association between ANXA1 expression, BRCA1/2 germline carriership, specific tumor subtypes and survival in breast cancer patients.<h4>Methods</h4>Clinical-pathological information and follow-up data were collected from nine breast cancer studies from the Breast Cancer Association Consortium (BCAC) (n = 5,752) and from one study of familial breast cancer patients with BRCA1/2 mutations (n = 107). ANXA1 expression was scored based on the percentage of immunohistochemical staining in tumor cells. Survival analyses were performed using a multivariable Cox model.<h4>Results</h4>The frequency of ANXA1 positive tumors was higher in familial breast cancer patients with BRCA1/2 mutations than in BCAC patients, with 48.6 % versus 12.4 %, respectively; P <0.0001. ANXA1 was also highly expressed in BCAC tumors that were poorly differentiated, triple negative, EGFR-CK5/6 positive or had developed in patients at a young age. In the first 5 years of follow-up, patients with ANXA1 positive tumors had a worse breast cancer-specific survival (BCSS) than ANXA1 negative (HRadj = 1.35; 95 % CI = 1.05-1.73), but the association weakened after 10 years (HRadj = 1.13; 95 % CI = 0.91-1.40). ANXA1 was a significant independent predictor of survival in HER2+ patients (10-years BCSS: HRadj = 1.70; 95 % CI = 1.17-2.45).<h4>Conclusions</h4>ANXA1 is overexpressed in familial breast cancer patients with BRCA1/2 mutations and correlated with poor prognosis features: triple negative and poorly differentiated tumors. ANXA1 might be a biomarker candidate for breast cancer survival prediction in high risk groups such as HER2+ cases.
<h4>Background</h4>Interest in the potential of DNA methylation in peripheral blood as a biomarker of cancer risk is increasing. We aimed to assess whether epigenome-wide DNA methylation measured in peripheral blood samples obtained before onset of the disease is associated with increased risk of breast cancer. We report on three independent prospective nested case-control studies from the European Prospective Investigation into Cancer and Nutrition (EPIC-Italy; n = 162 matched case-control pairs), the Norwegian Women and Cancer study (NOWAC; n = 168 matched pairs), and the Breakthrough Generations Study (BGS; n = 548 matched pairs). We used the Illumina 450k array to measure methylation in the EPIC and NOWAC cohorts. Whole-genome bisulphite sequencing (WGBS) was performed on the BGS cohort using pooled DNA samples, combined to reach 50× coverage across ~16 million CpG sites in the genome including 450k array CpG sites. Mean β values over all probes were calculated as a measurement for epigenome-wide methylation.<h4>Results</h4>In EPIC, we found that high epigenome-wide methylation was associated with lower risk of breast cancer (odds ratio (OR) per 1 SD = 0.61, 95 % confidence interval (CI) 0.47-0.80; -0.2 % average difference in epigenome-wide methylation for cases and controls). Specifically, this was observed in gene bodies (OR = 0.51, 95 % CI 0.38-0.69) but not in gene promoters (OR = 0.92, 95 % CI 0.64-1.32). The association was not replicated in NOWAC (OR = 1.03 95 % CI 0.81-1.30). The reasons for heterogeneity across studies are unclear. However, data from the BGS cohort was consistent with epigenome-wide hypomethylation in breast cancer cases across the overlapping 450k probe sites (difference in average epigenome-wide methylation in case and control DNA pools = -0.2 %).<h4>Conclusions</h4>We conclude that epigenome-wide hypomethylation of DNA from pre-diagnostic blood samples may be predictive of breast cancer risk and may thus be useful as a clinical biomarker.
Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.
BACKGROUND: Nulliparity is an endometrial cancer risk factor, but whether or not this association is due to infertility is unclear. Although there are many underlying infertility causes, few studies have assessed risk relations by specific causes. METHODS: We conducted a pooled analysis of 8153 cases and 11 713 controls from 2 cohort and 12 case-control studies. All studies provided self-reported infertility and its causes, except for one study that relied on data from national registries. Logistic regression was used to estimate adjusted odds ratios (OR) and 95% confidence intervals (CI). RESULTS: Nulliparous women had an elevated endometrial cancer risk compared with parous women, even after adjusting for infertility (OR=1.76; 95% CI: 1.59-1.94). Women who reported infertility had an increased risk compared with those without infertility concerns, even after adjusting for nulliparity (OR=1.22; 95% CI: 1.13-1.33). Among women who reported infertility, none of the individual infertility causes were substantially related to endometrial cancer. CONCLUSIONS: Based on mainly self-reported infertility data that used study-specific definitions of infertility, nulliparity and infertility appeared to independently contribute to endometrial cancer risk. Understanding residual endometrial cancer risk related to infertility, its causes and its treatments may benefit from large studies involving detailed data on various infertility parameters.
<h4>Background</h4>Epidemiological studies have linked adult height with breast cancer risk in women. However, the magnitude of the association, particularly by subtypes of breast cancer, has not been established. Furthermore, the mechanisms of the association remain unclear.<h4>Methods</h4>We performed a meta-analysis to investigate associations between height and breast cancer risk using data from 159 prospective cohorts totaling 5216302 women, including 113178 events. In a consortium with individual-level data from 46325 case patients and 42482 control patients, we conducted a Mendelian randomization analysis using a genetic score that comprised 168 height-associated variants as an instrument. This association was further evaluated in a second consortium using summary statistics data from 16003 case patients and 41335 control patients.<h4>Results</h4>The pooled relative risk of breast cancer was 1.17 (95% confidence interval [CI] = 1.15 to 1.19) per 10cm increase in height in the meta-analysis of prospective studies. In Mendelian randomization analysis, the odds ratio of breast cancer per 10cm increase in genetically predicted height was 1.22 (95% CI = 1.13 to 1.32) in the first consortium and 1.21 (95% CI = 1.05 to 1.39) in the second consortium. The association was found in both premenopausal and postmenopausal women but restricted to hormone receptor-positive breast cancer. Analyses of height-associated variants identified eight new loci associated with breast cancer risk after adjusting for multiple comparisons, including three loci at 1q21.2, DNAJC27, and CCDC91 at genome-wide significance level P < 5×10(-8).<h4>Conclusions</h4>Our study provides strong evidence that adult height is a risk factor for breast cancer in women and certain genetic factors and biological pathways affecting adult height have an important role in the etiology of breast cancer.
BACKGROUND: Evidence for an association of alcohol consumption with prognosis after a diagnosis of breast cancer has been inconsistent. We have reviewed and summarized the published evidence and evaluated the association using individual patient data from multiple case cohorts. METHODS: A MEDLINE search to identify studies published up to January 2013 was performed. We combined published estimates of survival time for "moderate drinkers" versus nondrinkers. An analysis of individual participant data using Cox regression was carried out using data from 11 case cohorts. RESULTS: We identified 11 published studies suitable for inclusion in the meta-analysis. Moderate postdiagnosis alcohol consumption was not associated with overall survival [HR, 0.95; 95% confidence interval (CI), 0.85-1.05], but there was some evidence of better survival associated with prediagnosis consumption (HR, 0.80; 95% CI, 0.73-0.88). Individual data on alcohol consumption for 29,239 cases with 4,839 deaths were available from the 11 case cohorts, all of which had data on estrogen receptor (ER) status. For women with ER-positive disease, there was little evidence that pre- or postdiagnosis alcohol consumption is associated with breast cancer-specific mortality, with some evidence of a negative association with all-cause mortality. On the basis of a single study, moderate postdiagnosis alcohol intake was associated with a small reduction in breast cancer-specific mortality for women with ER-negative disease. There was no association with prediagnosis intake for women with ER-negative disease. CONCLUSION: There was little evidence that pre- or post-diagnosis alcohol consumption is associated with breast cancer-specific mortality for women with ER-positive disease. There was weak evidence that moderate post-diagnosis alcohol intake is associated with a small reduction in breast cancer-specific mortality in ER-negative disease. IMPACT: Considering the totality of the evidence, moderate postdiagnosis alcohol consumption is unlikely to have a major adverse effect on the survival of women with breast cancer.
Survival in epithelial ovarian cancer (EOC) is influenced by the host immune response, yet the key genetic determinants of inflammation and immunity that affect prognosis are not known. The nuclear factor-κB (NF-κB) transcription factor family plays an important role in many immune and inflammatory responses, including the response to cancer. We studied common inherited variation in 210 genes in the NF-κB family in 10,084 patients with invasive EOC (5,248 high-grade serous, 1,452 endometrioid, 795 clear cell, and 661 mucinous) from the Ovarian Cancer Association Consortium. Associations between genotype and overall survival were assessed using Cox regression for all patients and by major histology, adjusting for known prognostic factors and correcting for multiple testing (threshold for statistical significance, P < 2.5 × 10(-5)). Results were statistically significant when assessed for patients of a single histology. Key associations were with caspase recruitment domain family, member 11 (CARD11) rs41324349 in patients with mucinous EOC [HR, 1.82; 95% confidence interval (CI), 1.41-2.35; P = 4.13 × 10(-6)] and tumor necrosis factor receptor superfamily, member 13B (TNFRSF13B) rs7501462 in patients with endometrioid EOC (HR, 0.68; 95% CI, 0.56-0.82; P = 2.33 × 10(-5)). Other associations of note included TNF receptor-associated factor 2 (TRAF2) rs17250239 in patients with high-grade serous EOC (HR, 0.84; 95% CI, 0.77-0.92; P = 6.49 × 10(-5)) and phospholipase C, gamma 1 (PLCG1) rs11696662 in patients with clear cell EOC (HR, 0.43; 95% CI, 0.26-0.73; P = 4.56 × 10(-4)). These associations highlight the potential importance of genes associated with host inflammation and immunity in modulating clinical outcomes in distinct EOC histologies.
A missense single-nucleotide polymorphism (SNP) in the immune modulatory gene IL1A has been associated with ovarian cancer risk (rs17561). Although the exact mechanism through which this SNP alters risk of ovarian cancer is not clearly understood, rs17561 has also been associated with risk of endometriosis, an epidemiologic risk factor for ovarian cancer. Interleukin-1α (IL1A) is both regulated by and able to activate NF-κB, a transcription factor family that induces transcription of many proinflammatory genes and may be an important mediator in carcinogenesis. We therefore tagged SNPs in more than 200 genes in the NF-κB pathway for a total of 2,282 SNPs (including rs17561) for genotype analysis of 15,604 cases of ovarian cancer in patients of European descent, including 6,179 of high-grade serous (HGS), 2,100 endometrioid, 1,591 mucinous, 1,034 clear cell, and 1,016 low-grade serous, including 23,235 control cases spanning 40 studies in the Ovarian Cancer Association Consortium. In this large population, we confirmed the association between rs17561 and clear cell ovarian cancer [OR, 0.84; 95% confidence interval (CI), 0.76-0.93; P = 0.00075], which remained intact even after excluding participants in the prior study (OR, 0.85; 95% CI, 0.75-0.95; P = 0.006). Considering a multiple-testing-corrected significance threshold of P < 2.5 × 10(-5), only one other variant, the TNFSF10 SNP rs6785617, was associated significantly with a risk of ovarian cancer (low malignant potential tumors OR, 0.85; 95% CI, 0.79-0.91; P = 0.00002). Our results extend the evidence that borderline tumors may have a distinct genetic etiology. Further investigation of how these SNPs might modify ovarian cancer associations with other inflammation-related risk factors is warranted.
To build a predictive model for urothelial carcinoma of the bladder (UCB) risk combining both genomic and nongenomic data, 1,127 cases and 1,090 controls from the Spanish Bladder Cancer/EPICURO study were genotyped using the HumanHap 1M SNP array. After quality control filters, genotypes from 475,290 variants were available. Nongenomic information comprised age, gender, region, and smoking status. Three Bayesian threshold models were implemented including: (1) only genomic information, (2) only nongenomic data, and (3) both sources of information. The three models were applied to the whole population, to only nonsmokers, to male smokers, and to extreme phenotypes to potentiate the UCB genetic component. The area under the ROC curve allowed evaluating the predictive ability of each model in a 10-fold cross-validation scenario. Smoking status showed the highest predictive ability of UCB risk (AUCtest = 0.62). On the other hand, the AUC of all genetic variants was poorer (0.53). When the extreme phenotype approach was applied, the predictive ability of the genomic model improved 15%. This study represents a first attempt to build a predictive model for UCB risk combining both genomic and nongenomic data and applying state-of-the-art statistical approaches. However, the lack of genetic relatedness among individuals, the complexity of UCB etiology, as well as a relatively small statistical power, may explain the low predictive ability for UCB risk. The study confirms the difficulty of predicting complex diseases using genetic data, and suggests the limited translational potential of findings from this type of data into public health interventions.
Endometrial cancer (EC), a neoplasm of the uterine epithelial lining, is the most common gynecological malignancy in developed countries and the fourth most common cancer among US women. Women with a family history of EC have an increased risk for the disease, suggesting that inherited genetic factors play a role. We conducted a two-stage genome-wide association study of Type I EC. Stage 1 included 5,472 women (2,695 cases and 2,777 controls) of European ancestry from seven studies. We selected independent single-nucleotide polymorphisms (SNPs) that displayed the most significant associations with EC in Stage 1 for replication among 17,948 women (4,382 cases and 13,566 controls) in a multiethnic population (African America, Asian, Latina, Hawaiian and European ancestry), from nine studies. Although no novel variants reached genome-wide significance, we replicated previously identified associations with genetic markers near the HNF1B locus. Our findings suggest that larger studies with specific tumor classification are necessary to identify novel genetic polymorphisms associated with EC susceptibility.
Genome-wide association studies (GWAS) have identified hundreds of genetic susceptibility loci for cancers and other complex diseases. However, the public health and clinical relevance of these discoveries is unclear. Evaluating the combined associations of genetic and environmental risk factors, particularly those that can be modified, will be critical in assessing the utility of genetic information for risk stratified prevention. In this commentary, using breast cancer as a model, we show that genetic information in combination with other risk factors can provide levels of risk stratification that could be useful for individual decision-making or population-based prevention programs. Our projections are theoretical and rely on a number of assumptions, including multiplicative models for the combined associations of the different risk factors, which need confirmation. Thus, analyses of epidemiological studies with high-quality risk factor information, as well as prevention trials, are needed to empirically assess the impact of genetics in risk stratified prevention.
GWAS have identified a breast cancer susceptibility locus on 2q35. Here we report the fine mapping of this locus using data from 101,943 subjects from 50 case-control studies. We genotype 276 SNPs using the 'iCOGS' genotyping array and impute genotypes for a further 1,284 using 1000 Genomes Project data. All but two, strongly correlated SNPs (rs4442975 G/T and rs6721996 G/A) are excluded as candidate causal variants at odds against >100:1. The best functional candidate, rs4442975, is associated with oestrogen receptor positive (ER+) disease with an odds ratio (OR) in Europeans of 0.85 (95% confidence interval=0.84-0.87; P=1.7 × 10(-43)) per t-allele. This SNP flanks a transcriptional enhancer that physically interacts with the promoter of IGFBP5 (encoding insulin-like growth factor-binding protein 5) and displays allele-specific gene expression, FOXA1 binding and chromatin looping. Evidence suggests that the g-allele confers increased breast cancer susceptibility through relative downregulation of IGFBP5, a gene with known roles in breast cell biology.
BACKGROUND: The benefits and harms of population-wide mammography screening have been long debated. This study evaluated the impact of screening frequency and age range on breast cancer mortality reduction and overdiagnosis. METHODS: We developed a Markov simulation model for the evaluation of mammography screening in a cohort of British women born in 1935-40. RESULTS: For triennial screening in women aged 47-73, breast cancer mortality reduction and overdiagnosis was 18.1% (95% confidence interval: 17.3%, 19.0%) and 5.6% (5.1%, 6.1%), of all breast cancer deaths and diagnoses, respectively, from age 40 to 85 years. For annual screening in the same age range, estimates for both outcomes increased considerably to 35.0% (34.2%, 35.7%) and 7.6% (7.1%, 8.1%), respectively. For the age extension of triennial screening from 50-70 to 47-73, we estimated 5 (3, 7) incremental breast cancer deaths avoided and 14 (9, 19) incremental cases overdiagnosed per 10 000 women invited for screening. CONCLUSIONS: Estimates of mortality reduction and overdiagnosis were highly dependent on screening frequency, age range, and uptake, which may explain differences between some previous estimates obtained from randomised trials and from service screening.
<h4>Introduction</h4>We have previously shown that a tag single nucleotide polymorphism (rs10235235), which maps to the CYP3A locus (7q22.1), was associated with a reduction in premenopausal urinary estrone glucuronide levels and a modest reduction in risk of breast cancer in women age ≤50 years.<h4>Methods</h4>We further investigated the association of rs10235235 with breast cancer risk in a large case control study of 47,346 cases and 47,570 controls from 52 studies participating in the Breast Cancer Association Consortium. Genotyping of rs10235235 was conducted using a custom Illumina Infinium array. Stratified analyses were conducted to determine whether this association was modified by age at diagnosis, ethnicity, age at menarche or tumor characteristics.<h4>Results</h4>We confirmed the association of rs10235235 with breast cancer risk for women of European ancestry but found no evidence that this association differed with age at diagnosis. Heterozygote and homozygote odds ratios (ORs) were OR = 0.98 (95% CI 0.94, 1.01; P = 0.2) and OR = 0.80 (95% CI 0.69, 0.93; P = 0.004), respectively (P(trend) = 0.02). There was no evidence of effect modification by tumor characteristics. rs10235235 was, however, associated with age at menarche in controls (P(trend) = 0.005) but not cases (P(trend) = 0.97). Consequently the association between rs10235235 and breast cancer risk differed according to age at menarche (P(het) = 0.02); the rare allele of rs10235235 was associated with a reduction in breast cancer risk for women who had their menarche age ≥15 years (OR(het) = 0.84, 95% CI 0.75, 0.94; OR(hom) = 0.81, 95% CI 0.51, 1.30; P(trend) = 0.002) but not for those who had their menarche age ≤11 years (OR(het) = 1.06, 95% CI 0.95, 1.19, OR(hom) = 1.07, 95% CI 0.67, 1.72; P(trend) = 0.29).<h4>Conclusions</h4>To our knowledge rs10235235 is the first single nucleotide polymorphism to be associated with both breast cancer risk and age at menarche consistent with the well-documented association between later age at menarche and a reduction in breast cancer risk. These associations are likely mediated via an effect on circulating hormone levels.
Genetic variations, such as single nucleotide polymorphisms (SNPs) in microRNAs (miRNA) or in the miRNA binding sites may affect the miRNA dependent gene expression regulation, which has been implicated in various cancers, including breast cancer, and may alter individual susceptibility to cancer. We investigated associations between miRNA related SNPs and breast cancer risk. First we evaluated 2,196 SNPs in a case-control study combining nine genome wide association studies (GWAS). Second, we further investigated 42 SNPs with suggestive evidence for association using 41,785 cases and 41,880 controls from 41 studies included in the Breast Cancer Association Consortium (BCAC). Combining the GWAS and BCAC data within a meta-analysis, we estimated main effects on breast cancer risk as well as risks for estrogen receptor (ER) and age defined subgroups. Five miRNA binding site SNPs associated significantly with breast cancer risk: rs1045494 (odds ratio (OR) 0.92; 95% confidence interval (CI): 0.88-0.96), rs1052532 (OR 0.97; 95% CI: 0.95-0.99), rs10719 (OR 0.97; 95% CI: 0.94-0.99), rs4687554 (OR 0.97; 95% CI: 0.95-0.99, and rs3134615 (OR 1.03; 95% CI: 1.01-1.05) located in the 3' UTR of CASP8, HDDC3, DROSHA, MUSTN1, and MYCL1, respectively. DROSHA belongs to miRNA machinery genes and has a central role in initial miRNA processing. The remaining genes are involved in different molecular functions, including apoptosis and gene expression regulation. Further studies are warranted to elucidate whether the miRNA binding site SNPs are the causative variants for the observed risk effects.
Candidate variant association studies have been largely unsuccessful in identifying common breast cancer susceptibility variants, although most studies have been underpowered to detect associations of a realistic magnitude. We assessed 41 common non-synonymous single-nucleotide polymorphisms (nsSNPs) for which evidence of association with breast cancer risk had been previously reported. Case-control data were combined from 38 studies of white European women (46 450 cases and 42 600 controls) and analyzed using unconditional logistic regression. Strong evidence of association was observed for three nsSNPs: ATXN7-K264R at 3p21 [rs1053338, per allele OR = 1.07, 95% confidence interval (CI) = 1.04-1.10, P = 2.9 × 10(-6)], AKAP9-M463I at 7q21 (rs6964587, OR = 1.05, 95% CI = 1.03-1.07, P = 1.7 × 10(-6)) and NEK10-L513S at 3p24 (rs10510592, OR = 1.10, 95% CI = 1.07-1.12, P = 5.1 × 10(-17)). The first two associations reached genome-wide statistical significance in a combined analysis of available data, including independent data from nine genome-wide association studies (GWASs): for ATXN7-K264R, OR = 1.07 (95% CI = 1.05-1.10, P = 1.0 × 10(-8)); for AKAP9-M463I, OR = 1.05 (95% CI = 1.04-1.07, P = 2.0 × 10(-10)). Further analysis of other common variants in these two regions suggested that intronic SNPs nearby are more strongly associated with disease risk. We have thus identified a novel susceptibility locus at 3p21, and confirmed previous suggestive evidence that rs6964587 at 7q21 is associated with risk. The third locus, rs10510592, is located in an established breast cancer susceptibility region; the association was substantially attenuated after adjustment for the known GWAS hit. Thus, each of the associated nsSNPs is likely to be a marker for another, non-coding, variant causally related to breast cancer risk. Further fine-mapping and functional studies are required to identify the underlying risk-modifying variants and the genes through which they act.
Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70,917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46,450 breast cancer cases and 42,461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P < 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P < 10(-4)) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P < 10(-8). Results from the second analytic approach were consistent with those from the first (P > 10(-10)). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.
Age at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P < 5 × 10(-8)) for 123 signals at 106 genomic loci associated with age at menarche. Many loci were associated with other pubertal traits in both sexes, and there was substantial overlap with genes implicated in body mass index and various diseases, including rare disorders of puberty. Menarche signals were enriched in imprinted regions, with three loci (DLK1-WDR25, MKRN3-MAGEL2 and KCNK9) demonstrating parent-of-origin-specific associations concordant with known parental expression patterns. Pathway analyses implicated nuclear hormone receptors, particularly retinoic acid and γ-aminobutyric acid-B2 receptor signalling, among novel mechanisms that regulate pubertal timing in humans. Our findings suggest a genetic architecture involving at least hundreds of common variants in the coordinated timing of the pubertal transition.
The length of female reproductive lifespan is associated with multiple adverse outcomes, including breast cancer, cardiovascular disease and infertility. The biological processes that govern the timing of the beginning and end of reproductive life are not well understood. Genetic variants are known to contribute to ∼50% of the variation in both age at menarche and menopause, but to date the known genes explain <15% of the genetic component. We have used genome-wide association in a bivariate meta-analysis of both traits to identify genes involved in determining reproductive lifespan. We observed significant genetic correlation between the two traits using genome-wide complex trait analysis. However, we found no robust statistical evidence for individual variants with an effect on both traits. A novel association with age at menopause was detected for a variant rs1800932 in the mismatch repair gene MSH6 (P = 1.9 × 10(-9)), which was also associated with altered expression levels of MSH6 mRNA in multiple tissues. This study contributes to the growing evidence that DNA repair processes play a key role in ovarian ageing and could be an important therapeutic target for infertility.
<h4>Introduction</h4>Germline variants in TP63 have been consistently associated with several tumors, including bladder cancer, indicating the importance of TP53 pathway in cancer genetic susceptibility. However, variants in other related genes, including TP53 rs1042522 (Arg72Pro), still present controversial results. We carried out an in depth assessment of associations between common germline variants in the TP53 pathway and bladder cancer risk.<h4>Material and methods</h4>We investigated 184 tagSNPs from 18 genes in 1,058 cases and 1,138 controls from the Spanish Bladder Cancer/EPICURO Study. Cases were newly-diagnosed bladder cancer patients during 1998-2001. Hospital controls were age-gender, and area matched to cases. SNPs were genotyped in blood DNA using Illumina Golden Gate and TaqMan assays. Cases were subphenotyped according to stage/grade and tumor p53 expression. We applied classical tests to assess individual SNP associations and the Least Absolute Shrinkage and Selection Operator (LASSO)-penalized logistic regression analysis to assess multiple SNPs simultaneously.<h4>Results</h4>Based on classical analyses, SNPs in BAK1 (1), IGF1R (5), P53AIP1 (1), PMAIP1 (2), SERINPB5 (3), TP63 (3), and TP73 (1) showed significant associations at p-value≤0.05. However, no evidence of association, either with overall risk or with specific disease subtypes, was observed after correction for multiple testing (p-value≥0.8). LASSO selected the SNP rs6567355 in SERPINB5 with 83% of reproducibility. This SNP provided an OR = 1.21, 95%CI 1.05-1.38, p-value = 0.006, and a corrected p-value = 0.5 when controlling for over-estimation.<h4>Discussion</h4>We found no strong evidence that common variants in the TP53 pathway are associated with bladder cancer susceptibility. Our study suggests that it is unlikely that TP53 Arg72Pro is implicated in the UCB in white Europeans. SERPINB5 and TP63 variation deserve further exploration in extended studies.
Mitotic index is an important component of histologic grade and has an etiologic role in breast tumorigenesis. Several small candidate gene studies have reported associations between variation in mitotic genes and breast cancer risk. We measured associations between 2156 single nucleotide polymorphisms (SNPs) from 194 mitotic genes and breast cancer risk, overall and by histologic grade, in the Breast Cancer Association Consortium (BCAC) iCOGS study (n = 39 067 cases; n = 42 106 controls). SNPs in TACC2 [rs17550038: odds ratio (OR) = 1.24, 95% confidence interval (CI) 1.16-1.33, P = 4.2 × 10(-10)) and EIF3H (rs799890: OR = 1.07, 95% CI 1.04-1.11, P = 8.7 × 10(-6)) were significantly associated with risk of low-grade breast cancer. The TACC2 signal was retained (rs17550038: OR = 1.15, 95% CI 1.07-1.23, P = 7.9 × 10(-5)) after adjustment for breast cancer risk SNPs in the nearby FGFR2 gene, suggesting that TACC2 is a novel, independent genome-wide significant genetic risk locus for low-grade breast cancer. While no SNPs were individually associated with high-grade disease, a pathway-level gene set analysis showed that variation across the 194 mitotic genes was associated with high-grade breast cancer risk (P = 2.1 × 10(-3)). These observations will provide insight into the contribution of mitotic defects to histological grade and the etiology of breast cancer.
Invasive lobular breast cancer (ILC) accounts for 10-15% of all invasive breast carcinomas. It is generally ER positive (ER+) and often associated with lobular carcinoma in situ (LCIS). Genome-wide association studies have identified more than 70 common polymorphisms that predispose to breast cancer, but these studies included predominantly ductal (IDC) carcinomas. To identify novel common polymorphisms that predispose to ILC and LCIS, we pooled data from 6,023 cases (5,622 ILC, 401 pure LCIS) and 34,271 controls from 36 studies genotyped using the iCOGS chip. Six novel SNPs most strongly associated with ILC/LCIS in the pooled analysis were genotyped in a further 516 lobular cases (482 ILC, 36 LCIS) and 1,467 controls. These analyses identified a lobular-specific SNP at 7q34 (rs11977670, OR (95%CI) for ILC = 1.13 (1.09-1.18), P = 6.0 × 10(-10); P-het for ILC vs IDC ER+ tumors = 1.8 × 10(-4)). Of the 75 known breast cancer polymorphisms that were genotyped, 56 were associated with ILC and 15 with LCIS at P<0.05. Two SNPs showed significantly stronger associations for ILC than LCIS (rs2981579/10q26/FGFR2, P-het = 0.04 and rs889312/5q11/MAP3K1, P-het = 0.03); and two showed stronger associations for LCIS than ILC (rs6678914/1q32/LGR6, P-het = 0.001 and rs1752911/6q14, P-het = 0.04). In addition, seven of the 75 known loci showed significant differences between ER+ tumors with IDC and ILC histology, three of these showing stronger associations for ILC (rs11249433/1p11, rs2981579/10q26/FGFR2 and rs10995190/10q21/ZNF365) and four associated only with IDC (5p12/rs10941679; rs2588809/14q24/RAD51L1, rs6472903/8q21 and rs1550623/2q31/CDCA7). In conclusion, we have identified one novel lobular breast cancer specific predisposition polymorphism at 7q34, and shown for the first time that common breast cancer polymorphisms predispose to LCIS. We have shown that many of the ER+ breast cancer predisposition loci also predispose to ILC, although there is some heterogeneity between ER+ lobular and ER+ IDC tumors. These data provide evidence for overlapping, but distinct etiological pathways within ER+ breast cancer between morphological subtypes.
BACKGROUND: Aberrant global DNA methylation is shown to increase cancer risk. LINE-1 has been proven a measure of global DNA methylation. The objectives of this study were to assess the association between LINE-1 methylation level and bladder cancer risk and to evaluate effect modification by environmental and genetic factors. METHODS: Bisulphite-treated leukocyte DNA from 952 cases and 892 hospital controls was used to measure LINE-1 methylation level at four CpG sites by pyrosequencing. Logistic regression model was fitted to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs). Interactions between LINE-1 methylation levels and environmental and genetic factors were assessed. RESULTS: The risk of bladder cancer followed a nonlinear association with LINE-1 methylation. Compared with subjects in the middle tertile, the adjusted OR for subjects in the lower and the higher tertiles were 1.26 (95% CI 0.99-1.60, P=0.06) and 1.33 (95% CI 1.05-1.69, P=0.02), respectively. This association significantly increased among individuals homozygous for the major allele of five single-nucleotide polymorphisms located in the phosphatidylethanolamine N-methyltransferase gene (corrected P-interaction<0.05). CONCLUSIONS: The findings from this large-scale study suggest that both low and high levels of global DNA methylation are associated with the risk of bladder cancer.
Genome-wide association studies (GWAS) have mapped risk alleles for at least 10 distinct cancers to a small region of 63 000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (association analysis based on subsets) across six distinct cancers in 34 248 cases and 45 036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single-nucleotide polymorphisms: five in the TERT gene (Region 1: rs7726159, P = 2.10 × 10(-39); Region 3: rs2853677, P = 3.30 × 10(-36) and PConditional = 2.36 × 10(-8); Region 4: rs2736098, P = 3.87 × 10(-12) and PConditional = 5.19 × 10(-6), Region 5: rs13172201, P = 0.041 and PConditional = 2.04 × 10(-6); and Region 6: rs10069690, P = 7.49 × 10(-15) and PConditional = 5.35 × 10(-7)) and one in the neighboring CLPTM1L gene (Region 2: rs451360; P = 1.90 × 10(-18) and PConditional = 7.06 × 10(-16)). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele-specific effects on DNA methylation were seen for a subset of risk loci, indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci.
The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988 controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration with the widely used univariate logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold LASSO (BTL), a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs in 34 genes showing an association with bladder cancer. AUC-RF detected an optimal predictive subset of 56 SNPs. 13 SNPs were identified by both methods in the total population. Using resources from the Texas Bladder Cancer study we were able to replicate 30% of the SNPs assessed. The associations between inflammatory SNPs and bladder cancer were reexamined among non-smokers to eliminate the effect of tobacco, one of the strongest and most prevalent environmental risk factor for this tumor. A 9 SNP-signature was detected by BTL. Here we report, for the first time, a set of SNP in inflammatory genes jointly associated with bladder cancer risk. These results highlight the importance of the complex structure of genetic susceptibility associated with cancer risk.
<h4>Introduction</h4>Breast cancer remains a significant scientific, clinical and societal challenge. This gap analysis has reviewed and critically assessed enduring issues and new challenges emerging from recent research, and proposes strategies for translating solutions into practice.<h4>Methods</h4>More than 100 internationally recognised specialist breast cancer scientists, clinicians and healthcare professionals collaborated to address nine thematic areas: genetics, epigenetics and epidemiology; molecular pathology and cell biology; hormonal influences and endocrine therapy; imaging, detection and screening; current/novel therapies and biomarkers; drug resistance; metastasis, angiogenesis, circulating tumour cells, cancer 'stem' cells; risk and prevention; living with and managing breast cancer and its treatment. The groups developed summary papers through an iterative process which, following further appraisal from experts and patients, were melded into this summary account.<h4>Results</h4>The 10 major gaps identified were: (1) understanding the functions and contextual interactions of genetic and epigenetic changes in normal breast development and during malignant transformation; (2) how to implement sustainable lifestyle changes (diet, exercise and weight) and chemopreventive strategies; (3) the need for tailored screening approaches including clinically actionable tests; (4) enhancing knowledge of molecular drivers behind breast cancer subtypes, progression and metastasis; (5) understanding the molecular mechanisms of tumour heterogeneity, dormancy, de novo or acquired resistance and how to target key nodes in these dynamic processes; (6) developing validated markers for chemosensitivity and radiosensitivity; (7) understanding the optimal duration, sequencing and rational combinations of treatment for improved personalised therapy; (8) validating multimodality imaging biomarkers for minimally invasive diagnosis and monitoring of responses in primary and metastatic disease; (9) developing interventions and support to improve the survivorship experience; (10) a continuing need for clinical material for translational research derived from normal breast, blood, primary, relapsed, metastatic and drug-resistant cancers with expert bioinformatics support to maximise its utility. The proposed infrastructural enablers include enhanced resources to support clinically relevant in vitro and in vivo tumour models; improved access to appropriate, fully annotated clinical samples; extended biomarker discovery, validation and standardisation; and facilitated cross-discipline working.<h4>Conclusions</h4>With resources to conduct further high-quality targeted research focusing on the gaps identified, increased knowledge translating into improved clinical care should be achievable within five years.
Analysis of 4,405 variants in 89,050 European subjects from 41 case-control studies identified three independent association signals for estrogen-receptor-positive tumors at 11q13. The strongest signal maps to a transcriptional enhancer element in which the G allele of the best candidate causative variant rs554219 increases risk of breast cancer, reduces both binding of ELK4 transcription factor and luciferase activity in reporter assays, and may be associated with low cyclin D1 protein levels in tumors. Another candidate variant, rs78540526, lies in the same enhancer element. Risk association signal 2, rs75915166, creates a GATA3 binding site within a silencer element. Chromatin conformation studies demonstrate that these enhancer and silencer elements interact with each other and with their likely target gene, CCND1.
Estrogen receptor (ER)-negative tumors represent 20-30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry. The etiology and clinical behavior of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition. To identify susceptibility loci specific to ER-negative disease, we combined in a meta-analysis 3 genome-wide association studies of 4,193 ER-negative breast cancer cases and 35,194 controls with a series of 40 follow-up studies (6,514 cases and 41,455 controls), genotyped using a custom Illumina array, iCOGS, developed by the Collaborative Oncological Gene-environment Study (COGS). SNPs at four loci, 1q32.1 (MDM4, P = 2.1 × 10(-12) and LGR6, P = 1.4 × 10(-8)), 2p24.1 (P = 4.6 × 10(-8)) and 16q12.2 (FTO, P = 4.0 × 10(-8)), were associated with ER-negative but not ER-positive breast cancer (P > 0.05). These findings provide further evidence for distinct etiological pathways associated with invasive ER-positive and ER-negative breast cancers.
Background: Dietary and circulating carotenoids have been inversely associated with breast cancer risk, but observed associations may be due to confounding. Single-nucleotide polymorphisms (SNPs) in beta-carotene 15,15’-monooxygenase 1 (BCMO1), a gene encoding the enzyme involved in the first step of synthesizing vitamin A from dietary carotenoids, have been associated with circulating carotenoid concentrations and may serve as unconfounded surrogates for those biomarkers. We determined associations between variants in BCMO1 and breast cancer risk in a large cohort consortium. Methods: We used unconditional logistic regression to test four SNPs in BCMO1 for associations with breast cancer risk in 9,226 cases and 10,420 controls from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3). We also tested weighted multi-SNP scores composed of the two SNPs with strong, confirmed associations with circulating carotenoid concentrations. Results: Neither the individual SNPs nor the weighted multi-SNP scores were associated with breast cancer risk [OR (95% confidence interval) comparing extreme quintiles of weighted multi-SNP scores = 1.04 (0.94-1.16) for beta-carotene, 1.08 (0.98-1.20) for alpha-carotene, 1.04 (0.94-1.16) for beta-cryptoxanthin, 0.95 (0.87-1.05) for lutein/zeaxanthin, and 0.92 (0.83-1.02) for retinol]. Furthermore, no associations were observed when stratifying by estrogen receptor status, but power was limited. Conclusions: Our results do not support an association between SNPs associated with circulating carotenoid concentrations and breast cancer risk. Impact: Future studies will need additional genetic surrogates and/or sample sizes at least three times larger to contribute evidence of a causal link between carotenoids and breast cancer. (C) 2013 AACR.
<h4>Background</h4>Dietary and circulating carotenoids have been inversely associated with breast cancer risk, but observed associations may be due to confounding. Single-nucleotide polymorphisms (SNPs) in β-carotene 15,15'-monooxygenase 1 (BCMO1), a gene encoding the enzyme involved in the first step of synthesizing vitamin A from dietary carotenoids, have been associated with circulating carotenoid concentrations and may serve as unconfounded surrogates for those biomarkers. We determined associations between variants in BCMO1 and breast cancer risk in a large cohort consortium.<h4>Methods</h4>We used unconditional logistic regression to test four SNPs in BCMO1 for associations with breast cancer risk in 9,226 cases and 10,420 controls from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3). We also tested weighted multi-SNP scores composed of the two SNPs with strong, confirmed associations with circulating carotenoid concentrations.<h4>Results</h4>Neither the individual SNPs nor the weighted multi-SNP scores were associated with breast cancer risk [OR (95% confidence interval) comparing extreme quintiles of weighted multi-SNP scores = 1.04 (0.94-1.16) for β-carotene, 1.08 (0.98-1.20) for α-carotene, 1.04 (0.94-1.16) for β-cryptoxanthin, 0.95 (0.87-1.05) for lutein/zeaxanthin, and 0.92 (0.83-1.02) for retinol]. Furthermore, no associations were observed when stratifying by estrogen receptor status, but power was limited.<h4>Conclusions</h4>Our results do not support an association between SNPs associated with circulating carotenoid concentrations and breast cancer risk.<h4>Impact</h4>Future studies will need additional genetic surrogates and/or sample sizes at least three times larger to contribute evidence of a causal link between carotenoids and breast cancer.
The 10q26 locus in the second intron of FGFR2 is the locus most strongly associated with estrogen-receptor-positive breast cancer in genome-wide association studies. We conducted fine-scale mapping in case-control studies genotyped with a custom chip (iCOGS), comprising 41 studies (n = 89,050) of European ancestry, 9 Asian ancestry studies (n = 13,983), and 2 African ancestry studies (n = 2,028) from the Breast Cancer Association Consortium. We identified three statistically independent risk signals within the locus. Within risk signals 1 and 3, genetic analysis identified five and two variants, respectively, highly correlated with the most strongly associated SNPs. By using a combination of genetic fine mapping, data on DNase hypersensitivity, and electrophoretic mobility shift assays to study protein-DNA binding, we identified rs35054928, rs2981578, and rs45631563 as putative functional SNPs. Chromatin immunoprecipitation showed that FOXA1 preferentially bound to the risk-associated allele (C) of rs2981578 and was able to recruit ERα to this site in an allele-specific manner, whereas E2F1 preferentially bound the risk variant of rs35054928. The risk alleles were preferentially found in open chromatin and bound by Ser5 phosphorylated RNA polymerase II, suggesting that the risk alleles are associated with changes in transcription. Chromatin conformation capture demonstrated that the risk region was able to interact with the promoter of FGFR2, the likely target gene of this risk region. A role for FOXA1 in mediating breast cancer susceptibility at this locus is consistent with the finding that the FGFR2 risk locus primarily predisposes to estrogen-receptor-positive disease.
Whilst previous studies have reported that higher BMI increases a woman's risk of developing ovarian cancer, associations for the different histological subtypes have not been well defined. As the prevalence of obesity has increased dramatically, and classification of ovarian histology has improved in the last decade, we sought to examine the association in a pooled analysis of recent studies participating in the Ovarian Cancer Association Consortium. We evaluated the association between BMI (recent, maximum and in young adulthood) and ovarian cancer risk using original data from 15 case-control studies (13 548 cases and 17 913 controls). We combined study-specific adjusted odds ratios (ORs) using a random-effects model. We further examined the associations by histological subtype, menopausal status and post-menopausal hormone use. High BMI (all time-points) was associated with increased risk. This was most pronounced for borderline serous (recent BMI: pooled OR=1.24 per 5 kg/m(2); 95% CI 1.18-1.30), invasive endometrioid (1.17; 1.11-1.23) and invasive mucinous (1.19; 1.06-1.32) tumours. There was no association with serous invasive cancer overall (0.98; 0.94-1.02), but increased risks for low-grade serous invasive tumours (1.13, 1.03-1.25) and in pre-menopausal women (1.11; 1.04-1.18). Among post-menopausal women, the associations did not differ between hormone replacement therapy users and non-users. Whilst obesity appears to increase risk of the less common histological subtypes of ovarian cancer, it does not increase risk of high-grade invasive serous cancers, and reducing BMI is therefore unlikely to prevent the majority of ovarian cancer deaths. Other modifiable factors must be identified to control this disease.
Women using menopausal hormone therapy (MHT) are at increased risk of developing breast cancer (BC). To detect genetic modifiers of the association between current use of MHT and BC risk, we conducted a meta-analysis of four genome-wide case-only studies followed by replication in 11 case-control studies. We used a case-only design to assess interactions between single-nucleotide polymorphisms (SNPs) and current MHT use on risk of overall and lobular BC. The discovery stage included 2920 cases (541 lobular) from four genome-wide association studies. The top 1391 SNPs showing P values for interaction (Pint) <3.0 × 10(-3) were selected for replication using pooled case-control data from 11 studies of the Breast Cancer Association Consortium, including 7689 cases (676 lobular) and 9266 controls. Fixed-effects meta-analysis was used to derive combined Pint. No SNP reached genome-wide significance in either the discovery or combined stage. We observed effect modification of current MHT use on overall BC risk by two SNPs on chr13 near POMP (combined Pint≤8.9 × 10(-6)), two SNPs in SLC25A21 (combined Pint≤4.8 × 10(-5)), and three SNPs in PLCG2 (combined Pint≤4.5 × 10(-5)). The association between lobular BC risk was potentially modified by one SNP in TMEFF2 (combined Pint≤2.7 × 10(-5)), one SNP in CD80 (combined Pint≤8.2 × 10(-6)), three SNPs on chr17 near TMEM132E (combined Pint≤2.2×10(-6)), and two SNPs on chr18 near SLC25A52 (combined Pint≤4.6 × 10(-5)). In conclusion, polymorphisms in genes related to solute transportation in mitochondria, transmembrane signaling, and immune cell activation are potentially modifying BC risk associated with current use of MHT. These findings warrant replication in independent studies.
PURPOSE: Endometrial cancers have long been divided into estrogen-dependent type I and the less common clinically aggressive estrogen-independent type II. Little is known about risk factors for type II tumors because most studies lack sufficient cases to study these much less common tumors separately. We examined whether so-called classical endometrial cancer risk factors also influence the risk of type II tumors. PATIENTS AND METHODS: Individual-level data from 10 cohort and 14 case-control studies from the Epidemiology of Endometrial Cancer Consortium were pooled. A total of 14,069 endometrial cancer cases and 35,312 controls were included. We classified endometrioid (n = 7,246), adenocarcinoma not otherwise specified (n = 4,830), and adenocarcinoma with squamous differentiation (n = 777) as type I tumors and serous (n = 508) and mixed cell (n = 346) as type II tumors. RESULTS: Parity, oral contraceptive use, cigarette smoking, age at menarche, and diabetes were associated with type I and type II tumors to similar extents. Body mass index, however, had a greater effect on type I tumors than on type II tumors: odds ratio (OR) per 2 kg/m(2) increase was 1.20 (95% CI, 1.19 to 1.21) for type I and 1.12 (95% CI, 1.09 to 1.14) for type II tumors (P heterogeneity < .0001). Risk factor patterns for high-grade endometrioid tumors and type II tumors were similar. CONCLUSION: The results of this pooled analysis suggest that the two endometrial cancer types share many common etiologic factors. The etiology of type II tumors may, therefore, not be completely estrogen independent, as previously believed.
CONTEXT: Approximately 10% of women with invasive epithelial ovarian cancer (EOC) carry deleterious germline mutations in BRCA1 or BRCA2. A recent article suggested that BRCA2-related EOC was associated with an improved prognosis, but the effect of BRCA1 remains unclear. OBJECTIVE: To characterize the survival of BRCA carriers with EOC compared with noncarriers and to determine whether BRCA1 and BRCA2 carriers show similar survival patterns. DESIGN, SETTING, AND PARTICIPANTS: A pooled analysis of 26 observational studies on the survival of women with ovarian cancer, which included data from 1213 EOC cases with pathogenic germline mutations in BRCA1 (n = 909) or BRCA2 (n = 304) and from 2666 noncarriers recruited and followed up at variable times between 1987 and 2010 (the median year of diagnosis was 1998). MAIN OUTCOME MEASURE: Five-year overall mortality. RESULTS: The 5-year overall survival was 36% (95% CI, 34%-38%) for noncarriers, 44% (95% CI, 40%-48%) for BRCA1 carriers, and 52% (95% CI, 46%-58%) for BRCA2 carriers. After adjusting for study and year of diagnosis, BRCA1 and BRCA2 mutation carriers showed a more favorable survival than noncarriers (for BRCA1: hazard ratio [HR], 0.78; 95% CI, 0.68-0.89; P < .001; and for BRCA2: HR, 0.61; 95% CI, 0.50-0.76; P < .001). These survival differences remained after additional adjustment for stage, grade, histology, and age at diagnosis (for BRCA1: HR, 0.73; 95% CI, 0.64-0.84; P < .001; and for BRCA2: HR, 0.49; 95% CI, 0.39-0.61; P < .001). The BRCA1 HR estimate was significantly different from the HR estimated in the adjusted model (P for heterogeneity = .003). CONCLUSION: Among patients with invasive EOC, having a germline mutation in BRCA1 or BRCA2 was associated with improved 5-year overall survival. BRCA2 carriers had the best prognosis.
Few studies have evaluated the association between DNA methylation in white blood cells (WBC) and the risk of breast cancer. The evaluation of WBC DNA methylation as a biomarker of cancer risk is of particular importance as peripheral blood is often available in prospective cohorts and easier to obtain than tumor or normal tissues. Here, we used prediagnostic blood samples from three studies to analyze WBC DNA methylation of two ATM intragenic loci (ATMmvp2a and ATMmvp2b) and genome-wide DNA methylation in long interspersed nuclear element-1 (LINE1) repetitive elements. Samples were from a case-control study derived from a cohort of high-risk breast cancer families (KConFab) and nested case-control studies in two prospective cohorts: Breakthrough Generations Study (BGS) and European Prospective Investigation into Cancer and Nutrition (EPIC). Bisulfite pyrosequencing was used to quantify methylation from 640 incident cases of invasive breast cancer and 741 controls. Quintile analyses for ATMmvp2a showed an increased risk of breast cancer limited to women in the highest quintile [OR, 1.89; 95% confidence interval (CI), 1.36-2.64; P = 1.64 × 10(-4)]. We found no significant differences in estimates across studies or in analyses stratified by family history or menopausal status. However, a more consistent association was observed in younger than in older women and individually significant in KConFab and BGS, but not EPIC. We observed no differences in LINE1 or ATMmvp2b methylation between cases and controls. Together, our findings indicate that WBC DNA methylation levels at ATM could be a marker of breast cancer risk and further support the pursuit of epigenome-wide association studies of peripheral blood DNA methylation.
<h4>Context</h4>Endometrial cancer is associated with metabolic disturbances related to its underlying risk factors, including obesity and diabetes. Identifying metabolite biomarkers associated with endometrial cancer may have value for early detection, risk assessment, and understanding etiology.<h4>Objective</h4>The objective of the study was to evaluate the reliable measurement of metabolites in epidemiological studies with nonstandardized blood collection; confirm previously reported correlations of metabolites with body size; and assess differences in metabolite levels between cases and controls.<h4>Design</h4>This was the Polish Endometrial Cancer Study (2001-2003).<h4>Setting</h4>This study was a population-based case-control study.<h4>Patients</h4>Patients included 250 cases and 250 controls.<h4>Intervention</h4>The intervention included the measurement of serum metabolite levels of 15 amino acids, 45 acylcarnitines, and nine fatty acids.<h4>Main outcome measure</h4>The main outcome measure was endometrial cancer.<h4>Results</h4>Body mass index was correlated with levels of valine (r = 0.26, P = 3.4 × 10(-5)), octenoylcarnitine (r = 0.24, P = 1.5 × 10(-4)), palmitic acid (r = 0.26, P = 4.4 × 10(-5)), oleic acid (r = 0.28, P = 9.9 × 10(-6)), and stearic acid (r = 0.26, P = 2.9 × 10(-5)) among controls. Only stearic acid was inversely associated with endometrial cancer case status (quartile 4 vs. quartile 1: odds ratio 0.37, 95% confidence interval 0.20-0.69, P for trend = 1.2 × 10(-4)). Levels of the C5-acylcarnitines, octenoylcarnitine, decatrienoylcarnitine, and linoleic acid were significantly lower in cases than controls (odds ratios ranged from 0.21 to 0.38).<h4>Conclusions</h4>These data demonstrate that previously reported variations in metabolomic profiles with body mass index can be replicated in population-based studies with nonfasting blood collection protocols. We also provide preliminary evidence that large differences in metabolite levels exist between cases and controls, independent of body habitus. Our findings warrant assessment of metabolic profiles, including the candidate markers identified herein, in prospectively collected blood samples to define biomarkers and etiological factors related to endometrial cancer.
Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for ∼8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies (GWAS) in ∼70,000 cases and ∼68,000 controls from 41 case-control studies and 9 breast cancer GWAS. We identified three new breast cancer risk loci at 12p11 (rs10771399; P = 2.7 × 10(-35)), 12q24 (rs1292011; P = 4.3 × 10(-19)) and 21q21 (rs2823093; P = 1.1 × 10(-12)). rs10771399 was associated with similar relative risks for both estrogen receptor (ER)-negative and ER-positive breast cancer, whereas the other two loci were associated only with ER-positive disease. Two of the loci lie in regions that contain strong plausible candidate genes: PTHLH (12p11) has a crucial role in mammary gland development and the establishment of bone metastasis in breast cancer, and NRIP1 (21q21) encodes an ER cofactor and has a role in the regulation of breast cancer cell growth.
INTRODUCTION: Overdiagnosis of breast cancer due to mammography screening, defined as the diagnosis of screen-detected cancers that would not have presented clinically in a women's lifetime in the absence of screening, has emerged as a highly contentious issue, as harm caused may question the benefit of mammographic screening. Most studies included women over 50 years old and little information is available for younger women. METHODS: We estimated the overdiagnosis of breast cancer due to screening in women aged 40 to 49 years using data from a randomised trial of annual mammographic screening starting at age 40 conducted in the UK. A six-state Markov model was constructed to estimate the sensitivity of mammography for invasive and in situ breast cancer and the screen-detectable mean sojourn time for non-progressive in situ, progressive in situ, and invasive breast cancer. Then, a 10-state simulation model of cancer progression, screening, and death, was developed to estimate overdiagnosis attributable to screening. RESULTS: The sensitivity of mammography for invasive and in situ breast cancers was 90% (95% CI, 72 to 99) and 82% (43 to 99), respectively. The screen-detectable mean sojourn time of preclinical non-progressive and progressive in situ cancers was 1.3 (0.4 to 3.4) and 0.11 (0.05 to 0.19) years, respectively, and 0.8 years (0.6 to 1.2) for preclinical invasive breast cancer. The proportion of screen-detected in situ cancers that were non-progressive was 55% (25 to 77) for the first and 40% (22 to 60) for subsequent screens. In our main analysis, overdiagnosis was estimated as 0.7% of screen-detected cancers. A sensitivity analysis, covering a wide range of alternative scenarios, yielded a range of 0.5% to 2.9%. CONCLUSION: Although a high proportion of screen-detected in situ cancers were non-progressive, a majority of these would have presented clinically in the absence of screening. The extent of overdiagnosis due to screening in women aged 40 to 49 was small. Results also suggest annual screening is most suitable for women aged 40 to 49 in the United Kingdom due to short cancer sojourn times.
There has been a long-standing controversy in epidemiology with regard to an appropriate risk scale for testing interactions between genes (G) and environmental exposure (E ). Although interaction tests based on the logistic model-which approximates the multiplicative risk for rare diseases-have been more widely applied because of its convenience in statistical modeling, interactions under additive risk models have been regarded as closer to true biologic interactions and more useful in intervention-related decision-making processes in public health. It has been well known that exploiting a natural assumption of G-E independence for the underlying population can dramatically increase statistical power for detecting multiplicative interactions in case-control studies. However, the implication of the independence assumption for tests for additive interaction has not been previously investigated. In this article, the authors develop a likelihood ratio test for detecting additive interactions for case-control studies that incorporates the G-E independence assumption. Numerical investigation of power suggests that incorporation of the independence assumption can enhance the efficiency of the test for additive interaction by 2- to 2.5-fold. The authors illustrate their method by applying it to data from a bladder cancer study.
The 6q25.1 locus was first identified via a genome-wide association study (GWAS) in Chinese women and marked by single nucleotide polymorphism (SNP) rs2046210, approximately 180 Kb upstream of ESR1. There have been conflicting reports about the association of this locus with breast cancer in Europeans, and a GWAS in Europeans identified a different SNP, tagged here by rs12662670. We examined the associations of both SNPs in up to 61,689 cases and 58,822 controls from forty-four studies collaborating in the Breast Cancer Association Consortium, of which four studies were of Asian and 39 of European descent. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI). Case-only analyses were used to compare SNP effects in Estrogen Receptor positive (ER+) versus negative (ER-) tumours. Models including both SNPs were fitted to investigate whether the SNP effects were independent. Both SNPs are significantly associated with breast cancer risk in both ethnic groups. Per-allele ORs are higher in Asian than in European studies [rs2046210: OR (A/G) = 1.36 (95% CI 1.26-1.48), p = 7.6 × 10(-14) in Asians and 1.09 (95% CI 1.07-1.11), p = 6.8 × 10(-18) in Europeans. rs12662670: OR (G/T) = 1.29 (95% CI 1.19-1.41), p = 1.2 × 10(-9) in Asians and 1.12 (95% CI 1.08-1.17), p = 3.8 × 10(-9) in Europeans]. SNP rs2046210 is associated with a significantly greater risk of ER- than ER+ tumours in Europeans [OR (ER-) = 1.20 (95% CI 1.15-1.25), p = 1.8 × 10(-17) versus OR (ER+) = 1.07 (95% CI 1.04-1.1), p = 1.3 × 10(-7), p(heterogeneity) = 5.1 × 10(-6)]. In these Asian studies, by contrast, there is no clear evidence of a differential association by tumour receptor status. Each SNP is associated with risk after adjustment for the other SNP. These results suggest the presence of two variants at 6q25.1 each independently associated with breast cancer risk in Asians and in Europeans. Of these two, the one tagged by rs2046210 is associated with a greater risk of ER- tumours.
In the National Cancer Institute Cancer Genetic Markers of Susceptibility (CGEMS) genome-wide association study of breast cancer, a single nucleotide polymorphism (SNP) marker, rs999737, in the 14q24.1 interval, was associated with breast cancer risk. In order to fine map this region, we imputed a 3.93 MB region flanking rs999737 for Stages 1 and 2 of the CGEMS study (5,692 cases, 5,576 controls) using the combined reference panels of the HapMap 3 and the 1000 Genomes Project. Single-marker association testing and variable-sized sliding-window haplotype analysis were performed, and for both analyses the initial tagging SNP rs999737 retained the strongest association with breast cancer risk. Investigation of contiguous regions did not reveal evidence for an additional independent signal. Therefore, we conclude that rs999737 is an optimal tag SNP for common variants in the 14q24.1 region and thus narrow the candidate variants that should be investigated in follow-up laboratory evaluation.
<h4>Background</h4>Structural variations such as copy number variants (CNV) influence the expression of different phenotypic traits. Algorithms to identify CNVs through SNP-array platforms are available. The ability to evaluate well-characterized CNVs such as GSTM1 (1p13.3) deletion provides an important opportunity to assess their performance.<h4>Results</h4>773 cases and 759 controls from the SBC/EPICURO Study were genotyped in the GSTM1 region using TaqMan, Multiplex Ligation-dependent Probe Amplification (MLPA), and Illumina Infinium 1 M SNP-array platforms. CNV callings provided by TaqMan and MLPA were highly concordant and replicated the association between GSTM1 and bladder cancer. This was not the case when CNVs were called using Illumina 1 M data through available algorithms since no deletion was detected across the study samples. In contrast, when the Log R Ratio (LRR) was used as a continuous measure for the 5 probes contained in this locus, we were able to detect their association with bladder cancer using simple regression models or more sophisticated methods such as the ones implemented in the CNVtools package.<h4>Conclusions</h4>This study highlights an important limitation in the CNV calling from SNP-array data in regions of common aberrations and suggests that there may be added advantage for using LRR as a continuous measure in association tests rather than relying on calling algorithms.
We conducted a genome-wide association study of male breast cancer comprising 823 cases and 2,795 controls of European ancestry, with validation in independent sample sets totaling 438 cases and 474 controls. A SNP in RAD51B at 14q24.1 was significantly associated with male breast cancer risk (P = 3.02 x 10(-13); odds ratio (OR) = 1.57). We also refine association at 16q12.1 to a SNP within TOX3 (P = 3.87 x 10(-15); OR = 1.50).
The 19p13.1 breast cancer susceptibility locus is a modifier of breast cancer risk in BRCA1 mutation carriers and is also associated with the risk of ovarian cancer. Here, we investigated 19p13.1 variation and risk of breast cancer subtypes, defined by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) status, using 48,869 breast cancer cases and 49,787 controls from the Breast Cancer Association Consortium (BCAC). Variants from 19p13.1 were not associated with breast cancer overall or with ER-positive breast cancer but were significantly associated with ER-negative breast cancer risk [rs8170 OR, 1.10; 95% confidence interval (CI), 1.05-1.15; P = 3.49 × 10(-5)] and triple-negative (ER-, PR-, and HER2-negative) breast cancer (rs8170: OR, 1.22; 95% CI, 1.13-1.31; P = 2.22 × 10(-7)). However, rs8170 was no longer associated with ER-negative breast cancer risk when triple-negative cases were excluded (OR, 0.98; 95% CI, 0.89-1.07; P = 0.62). In addition, a combined analysis of triple-negative cases from BCAC and the Triple Negative Breast Cancer Consortium (TNBCC; N = 3,566) identified a genome-wide significant association between rs8170 and triple-negative breast cancer risk (OR, 1.25; 95% CI, 1.18-1.33; P = 3.31 × 10(-13)]. Thus, 19p13.1 is the first triple-negative-specific breast cancer risk locus and the first locus specific to a histologic subtype defined by ER, PR, and HER2 to be identified. These findings provide convincing evidence that genetic susceptibility to breast cancer varies by tumor subtype and that triple-negative tumors and other subtypes likely arise through distinct etiologic pathways.
<h4>Background</h4>Mammographic density adjusted for age and body mass index (BMI) is a heritable marker of breast cancer susceptibility. Little is known about the biologic mechanisms underlying the association between mammographic density and breast cancer risk. We examined whether common low-penetrance breast cancer susceptibility variants contribute to interindividual differences in mammographic density measures.<h4>Methods</h4>We established an international consortium (DENSNP) of 19 studies from 10 countries, comprising 16,895 Caucasian women, to conduct a pooled cross-sectional analysis of common breast cancer susceptibility variants in 14 independent loci and mammographic density measures. Dense and nondense areas, and percent density, were measured using interactive-thresholding techniques. Mixed linear models were used to assess the association between genetic variants and the square roots of mammographic density measures adjusted for study, age, case status, BMI, and menopausal status.<h4>Results</h4>Consistent with their breast cancer associations, the C-allele of rs3817198 in LSP1 was positively associated with both adjusted dense area (P = 0.00005) and adjusted percent density (P = 0.001), whereas the A-allele of rs10483813 in RAD51L1 was inversely associated with adjusted percent density (P = 0.003), but not with adjusted dense area (P = 0.07).<h4>Conclusion</h4>We identified two common breast cancer susceptibility variants associated with mammographic measures of radiodense tissue in the breast gland.<h4>Impact</h4>We examined the association of 14 established breast cancer susceptibility loci with mammographic density phenotypes within a large genetic consortium and identified two breast cancer susceptibility variants, LSP1-rs3817198 and RAD51L1-rs10483813, associated with mammographic measures and in the same direction as the breast cancer association.
The importance of inflammation pathways to the development of many human cancers prompted us to examine the associations between single-nucleotide polymorphisms (SNP) in inflammation-related genes and risk of ovarian cancer. In a multisite case-control study, we genotyped SNPs in a large panel of inflammatory genes in 930 epithelial ovarian cancer cases and 1,037 controls using a custom array and analyzed by logistic regression. SNPs with P < 0.10 were evaluated among 3,143 cases and 2,102 controls from the Follow-up of Ovarian Cancer Genetic Association and Interaction Studies (FOCI) post-GWAS collaboration. Combined analysis revealed association with SNPs rs17561 and rs4848300 in the interleukin gene IL1A which varied by histologic subtype (P(heterogeneity) = 0.03). For example, IL1A rs17561, which correlates with numerous inflammatory phenotypes, was associated with decreased risk of clear cell, mucinous, and endometrioid subtype, but not with the most common serous subtype. Genotype at rs1864414 in the arachidonate 5-lipoxygenase ALOX5 was also associated with decreased risk. Thus, inherited variation in IL1A and ALOX5 seems to affect ovarian cancer risk which, for IL1A, is limited to rarer subtypes. Given the importance of inflammation in tumorigenesis and growing evidence of subtype-specific features in ovarian cancer, functional investigations will be important to help clarify the importance of inherited variation related to inflammation in ovarian carcinogenesis.
Glucuronide conjugates of 4-aminobiphenyl and its N-hydroxy metabolite can be rapidly hydrolyzed in acidic urine to undergo further metabolic activation and form DNA adducts in the urothelium. We conducted a large multicenter case-control study in Spain to explore the etiology of bladder cancer and evaluated the association between urine pH and bladder cancer risk, alone and in combination with cigarette smoking. In total, 712 incident urothelial cell carcinoma cases and 611 hospital controls directly measured their urine pH with dipsticks twice a day (first void in the morning and early in the evening) during four consecutive days 2 weeks after hospital discharge. We found that a consistently acidic urine pH ≤6.0 was associated with an increased risk of bladder cancer [odds ratio (OR) = 1.5, 95% confidence interval (CI): 1.2-1.9] compared with all other subjects. Furthermore, risk estimates for smoking intensity and risk of bladder cancer among current smokers tended to be higher for those with a consistently acidic urine (OR = 8.8, 11.5 and 23.8) compared with those without (OR = 4.3, 7.7 and 5.8, respectively, for 1-19, 20-29 and 30+ cigarettes per day; P(interaction) for 30+ cigarettes per day = 0.024). These results suggest that urine pH, which is determined primarily by diet and body surface area, may be an important modifier of smoking and risk of bladder cancer.
BACKGROUND: We previously reported an association between rs2660753, a prostate cancer susceptibility polymorphism, and invasive epithelial ovarian cancer (EOC; OR = 1.2, 95% CI=1.0-1.4, P(trend) = 0.01) that showed a stronger association with the serous histological subtype (OR = 1.3, 95% CI = 1.1-1.5, P(trend) = 0.003). METHODS: We sought to replicate this association in 12 other studies comprising 4,482 cases and 6,894 controls of white non-Hispanic ancestry in the Ovarian Cancer Association Consortium. RESULTS: No evidence for an association with all cancers or serous cancers was observed in a combined analysis of data from the replication studies (all: OR = 1.0, 95% CI = 0.9-1.1, P(trend) = 0.61; serous: OR = 1.0, 95% CI = 0.9-1.1, P(trend) = 0.85) or from the combined analysis of discovery and replication studies (all: OR = 1.0, 95% CI = 1.0-1.1, P(trend) = 0.28; serous: OR = 1.1, 95% CI = 1.0-1.2, P(trend) = 0.11). There was no evidence for statistical heterogeneity in ORs across the studies. CONCLUSIONS: Although rs2660753 is a strong prostate cancer susceptibility polymorphism, the association with another hormonally related cancer, invasive EOC, is not supported by this replication study. IMPACT: Our findings, based on a larger sample size, emphasize the importance of replicating potentially promising genetic risk associations.
Breast cancers demonstrate substantial biological, clinical and etiological heterogeneity. We investigated breast cancer risk associations of eight susceptibility loci identified in GWAS and two putative susceptibility loci in candidate genes in relation to specific breast tumor subtypes. Subtypes were defined by five markers (ER, PR, HER2, CK5/6, EGFR) and other pathological and clinical features. Analyses included up to 30 040 invasive breast cancer cases and 53 692 controls from 31 studies within the Breast Cancer Association Consortium. We confirmed previous reports of stronger associations with ER+ than ER- tumors for six of the eight loci identified in GWAS: rs2981582 (10q26) (P-heterogeneity = 6.1 × 10(-18)), rs3803662 (16q12) (P = 3.7 × 10(-5)), rs13281615 (8q24) (P = 0.002), rs13387042 (2q35) (P = 0.006), rs4973768 (3p24) (P = 0.003) and rs6504950 (17q23) (P = 0.002). The two candidate loci, CASP8 (rs1045485, rs17468277) and TGFB1 (rs1982073), were most strongly related with the risk of PR negative tumors (P = 5.1 × 10(-6) and P = 4.1 × 10(-4), respectively), as previously suggested. Four of the eight loci identified in GWAS were associated with triple negative tumors (P ≤ 0.016): rs3803662 (16q12), rs889312 (5q11), rs3817198 (11p15) and rs13387042 (2q35); however, only two of them (16q12 and 2q35) were associated with tumors with the core basal phenotype (P ≤ 0.002). These analyses are consistent with different biological origins of breast cancers, and indicate that tumor stratification might help in the identification and characterization of novel risk factors for breast cancer subtypes. This may eventually result in further improvements in prevention, early detection and treatment.
We evaluated the generalizability of a single nucleotide polymorphism (SNP), rs2046210 (A/G allele), associated with breast cancer risk that was initially identified at 6q25.1 in a genome-wide association study conducted among Chinese women. In a pooled analysis of more than 31,000 women of East-Asian, European, and African ancestry, we found a positive association for rs2046210 and breast cancer risk in Chinese women [ORs (95% CI) = 1.30 (1.22-1.38) and 1.64 (1.50-1.80) for the AG and AA genotypes, respectively, P for trend = 1.54 × 10⁻³⁰], Japanese women [ORs (95% CI) = 1.31 (1.13-1.52) and 1.37 (1.06-1.76), P for trend = 2.51 × 10⁻⁴], and European-ancestry American women [ORs (95% CI) = 1.07 (0.99-1.16) and 1.18 (1.04-1.34), P for trend = 0.0069]. No association with this SNP, however, was observed in African American women [ORs (95% CI) = 0.81 (0.63-1.06) and 0.85 (0.65-1.11) for the AG and AA genotypes, respectively, P for trend = 0.4027]. In vitro functional genomic studies identified a putative functional variant, rs6913578. This SNP is 1,440 bp downstream of rs2046210 and is in high linkage disequilibrium with rs2046210 in Chinese (r(2) = 0.91) and European-ancestry (r² = 0.83) populations, but not in Africans (r² = 0.57). SNP rs6913578 was found to be associated with breast cancer risk in Chinese and European-ancestry American women. After adjusting for rs2046210, the association of rs6913578 with breast cancer risk in African Americans approached borderline significance. Results from this large consortium study confirmed the association of rs2046210 with breast cancer risk among women of Chinese, Japanese, and European ancestry. This association may be explained in part by a putatively functional variant (rs6913578) identified in the region.
A genome-wide association study (GWAS) identified single-nucleotide polymorphisms (SNPs) at 1p11.2 and 14q24.1 (RAD51L1) as breast cancer susceptibility loci. The initial GWAS suggested stronger effects for both loci for estrogen receptor (ER)-positive tumors. Using data from the Breast Cancer Association Consortium (BCAC), we sought to determine whether risks differ by ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), grade, node status, tumor size, and ductal or lobular morphology. We genotyped rs11249433 at 1p.11.2, and two highly correlated SNPs rs999737 and rs10483813 (r(2)= 0.98) at 14q24.1 (RAD51L1), for up to 46 036 invasive breast cancer cases and 46 930 controls from 39 studies. Analyses by tumor characteristics focused on subjects reporting to be white women of European ancestry and were based on 25 458 cases, of which 87% had ER data. The SNP at 1p11.2 showed significantly stronger associations with ER-positive tumors [per-allele odds ratio (OR) for ER-positive tumors was 1.13, 95% CI = 1.10-1.16 and, for ER-negative tumors, OR was 1.03, 95% CI = 0.98-1.07, case-only P-heterogeneity = 7.6 × 10(-5)]. The association with ER-positive tumors was stronger for tumors of lower grade (case-only P= 6.7 × 10(-3)) and lobular histology (case-only P= 0.01). SNPs at 14q24.1 were associated with risk for most tumor subtypes evaluated, including triple-negative breast cancers, which has not been described previously. Our results underscore the need for large pooling efforts with tumor pathology data to help refine risk estimates for SNP associations with susceptibility to different subtypes of breast cancer.
The arylamine N-acetyltransferase 2 (NAT2) slow acetylation phenotype is an established risk factor for urinary bladder cancer. We reported earlier on this risk association using NAT2 phenotypic categories inferred from NAT2 haplotypes based on seven single nucleotide polymorphisms (SNPs) in a study in Spain. In a subsequent genome-wide scan, we have identified a single common tag SNP (rs1495741) located in the 3' end of NAT2 that is also associated with bladder cancer risk. The aim of this report is to evaluate the agreement between the common tag SNP and the 7-SNP NAT2 inferred phenotype. The agreement between the 7-SNP NAT2 inferred phenotype and the tag SNP, rs1495741, was initially assessed in 2174 individuals from the Spanish Bladder Cancer Study (SBCS), and confirmed in a subset of individuals from the Main and Vermont component the New England Bladder Cancer Study (NEBCS). We also investigated the association of rs1495741 genotypes with NAT2 catalytic activity in cryopreserved hepatocytes from 154 individuals of European background. We observed very strong agreement between rs1495741 and the 7-SNP inferred NAT2 phenotype: sensitivity and specificity for the NAT2 slow phenotype was 99 and 95%, respectively. Our findings were replicated in an independent population from the NEBCS. Estimates for the association between NAT2 slow phenotype and bladder cancer risk in the SBCS and its interaction with cigarette smoking were comparable for the 7-SNP inferred NAT2 phenotype and rs1495741. In addition, rs1495741 genotypes were strongly related to NAT2 activity measured in hepatocytes (P<0.0001). A novel NAT2 tag SNP (rs1495741) predicts with high accuracy the 7-SNP inferred NAT2 phenotype, and thus can be used as a sole marker in pharmacogenetic or epidemiological studies of populations of European background. These findings illustrate the utility of tag SNPs, often used in genome-wide association studies (GWAS), to identify novel phenotypic markers. Further studies are required to determine the functional implications of rs1495741 and the structure and evolution of the haplotype on which it resides.
This chapter describes basic principles in study design, data analysis, and interpretation of epidemiological studies of genetic polymorphisms and disease risk, including the assessment of gene-environment interactions. The case-control design (hospital-based, population-based or nested within a prospective cohort) is frequently used to study common genetic variants and disease risk. Because of their widespread use, the analysis of case-control data will be the focus of this chapter. Two key considerations in the study design will be addressed: the selection of genetic markers to be evaluated, and sample size considerations to ensure adequate power to detect associations with disease risk. Single nucleotide polymorphisms (SNPs) are the most frequent form of common genetic variation, thus the discussion on data analysis will be based on the evaluation of associations between SNPs and disease risk. This chapter will begin with the evaluation of quality control of genotyping data, which is a critical first step in the analysis of genetic data. A description of statistical methods will follow, aimed at the discovery of genetic susceptibility loci, including analysis of candidate SNPs and genome-wide association studies, haplotype analyses, and the evaluation of gene-gene and gene-environment interactions.
This chapter will discuss design considerations for epidemiological studies that use biomarkers in the framework of etiologic investigations. The main focus will be on describing the incorporation of biomarkers into the main epidemiologic study designs, including cross-sectional or short-term longitudinal designs to characterize biomarkers, and prospective cohort and case-control studies to evaluate biomarker-disease associations. The advantages and limitations of each design will be presented, and the impact of study design on the feasibility of different approaches to exposure assessment and biospecimen collection and processing will be discussed.
Genome-wide and candidate-gene association studies of bladder cancer have identified 10 susceptibility loci thus far. We conducted a meta-analysis of two previously published genome-wide scans (4501 cases and 6076 controls of European background) and followed up the most significant association signals [17 single nucleotide polymorphisms (SNPs) in 10 genomic regions] in 1382 cases and 2201 controls from four studies. A combined analysis adjusted for study center, age, sex, and smoking status identified a novel susceptibility locus that mapped to a region of 18q12.3, marked by rs7238033 (P = 8.7 × 10(-9); allelic odds ratio 1.20 with 95% CI: 1.13-1.28) and two highly correlated SNPs, rs10775480/rs10853535 (r(2)= 1.00; P = 8.9 × 10(-9); allelic odds ratio 1.16 with 95% CI: 1.10-1.22). The signal localizes to the solute carrier family 14 member 1 gene, SLC14A1, a urea transporter that regulates cellular osmotic pressure. In the kidney, SLC14A1 regulates urine volume and concentration whereas in erythrocytes it determines the Kidd blood groups. Our findings suggest that genetic variation in SLC14A1 could provide new etiological insights into bladder carcinogenesis.
Identification of somatic mutations in cancer is a major goal for understanding and monitoring the events related to cancer initiation and progression. High resolution melting (HRM) curve analysis represents a fast, post-PCR high-throughput method for scanning somatic sequence alterations in target genes. The aim of this study was to assess the sensitivity and specificity of HRM analysis for tumor mutation screening in a range of tumor samples, which included 216 frozen pediatric small rounded blue-cell tumors as well as 180 paraffin-embedded tumors from breast, endometrial and ovarian cancers (60 of each). HRM analysis was performed in exons of the following candidate genes known to harbor established commonly observed mutations: PIK3CA, ERBB2, KRAS, TP53, EGFR, BRAF, GATA3, and FGFR3. Bi-directional sequencing analysis was used to determine the accuracy of the HRM analysis. For the 39 mutations observed in frozen samples, the sensitivity and specificity of HRM analysis were 97% and 87%, respectively. There were 67 mutation/variants in the paraffin-embedded samples, and the sensitivity and specificity for the HRM analysis were 88% and 80%, respectively. Paraffin-embedded samples require higher quantity of purified DNA for high performance. In summary, HRM analysis is a promising moderate-throughput screening test for mutations among known candidate genomic regions. Although the overall accuracy appears to be better in frozen specimens, somatic alterations were detected in DNA extracted from paraffin-embedded samples.
Recent large--scale association studies, both of genome-wide and candidate gene design, have revealed several single-nucleotide polymorphisms (SNPs) which are significantly associated with risk of developing breast cancer. As both breast and endometrial cancers are considered to be hormonally driven and share multiple risk factors, we investigated whether breast cancer risk alleles are also associated with endometrial cancer risk. We genotyped nine breast cancer risk SNPs in up to 4188 endometrial cases and 11,928 controls, from between three and seven Caucasian populations. None of the tested SNPs showed significant evidence of association with risk of endometrial cancer.
OBJECTIVE: We assessed whether common genetic variation in PTEN, PIK3CA, AKT1, MLH1, and MSH2-genes that reportedly are frequently altered in endometrial cancer-was associated with risk of endometrial cancer. METHODS: Using data from a population-based case-control study in Poland (PECS) of 417 cases and 407 matched controls, we genotyped 76 tagging single nucleotide polymorphisms (tagSNPs; located in or within 10 kb upstream or 5 kb downstream of the gene of interest, minor allele frequency >=5% among various ethnic groups, and not already represented by another tagSNP at a LD of r(2) >=0.80) on an Illumina Custom Infinium iSelect assay that included over 29,000 SNPs in 1316 genes. For individual SNPs, we used unconditional logistic regression models, adjusted for age and site, to generate odds ratios (ORs) and 95% confidence intervals (CIs). To replicate the one statistically significant association in PECS, we independently genotyped that tagSNP among 1141 endometrial cancer cases and 2275 controls from the SEARCH study in the UK. We assessed haplotypes via extended haplotype blocks and the sequential haplotype scan method. RESULTS: The rs2677764 tagSNP in PIK3CA was statistically significantly associated with endometrial cancer in PECS (OR=1.42, 95% CI, 1.03-1.95; P=0.03) but not SEARCH (OR=0.98, 95% CI=0.82-1.17). Of the 25 haplotypes observed in at least 5% of cases and controls in PECS, only 1, in PIK3CA, was statistically significantly associated with endometrial cancer (OR=1.39, 95% CI, 1.00-1.93). All haplotype global p-values were null. CONCLUSION: Common genetic variation in PTEN, PIK3CA, AKT1, MLH1, or MSH2 was not statistically significantly associated with endometrial cancer.
BACKGROUND: The XRCC2 gene is a key mediator in the homologous recombination repair of DNA double strand breaks. It is hypothesised that inherited variants in the XRCC2 gene might also affect susceptibility to, and survival from, breast cancer. METHODS: The study genotyped 12 XRCC2 tagging single nucleotide polymorphisms (SNPs) in 1131 breast cancer cases and 1148 controls from the Sheffield Breast Cancer Study (SBCS), and examined their associations with breast cancer risk and survival by estimating ORs and HRs, and their corresponding 95% CIs. Positive findings were further investigated in 860 cases and 869 controls from the Utah Breast Cancer Study (UBCS) and jointly analysed together with available published data for breast cancer risk. The survival findings were further confirmed in studies (8074 cases) from the Breast Cancer Association Consortium (BCAC). RESULTS: The most significant association with breast cancer risk in the SBCS dataset was the XRCC2 rs3218408 SNP (recessive model p=2.3×10(-4), minor allele frequency (MAF)=0.23). This SNP yielded an OR(rec) of 1.64 (95% CI 1.25 to 2.16) in a two-site analysis of SBCS and UBCS, and a meta-OR(rec) of 1.33 (95% CI 1.12 to 1.57) when all published data were included. This SNP may mark a rare risk haplotype carried by two in 1000 of the control population. Furthermore, the XRCC2 coding R188H SNP (rs3218536, MAF=0.08) was significantly associated with poor survival, with an increased per-allele HR of 1.58 (95% CI 1.01 to 2.49) in a multivariate analysis. This effect was still evident in a pooled meta-analysis of 8781 breast cancer patients from the BCAC (HR 1.19, 95% CI 1.05 to 1.36; p=0.01). CONCLUSIONS: These findings suggest that XRCC2 SNPs may influence breast cancer risk and survival.
Overweight and obesity are strongly associated with endometrial cancer. Several independent genome-wide association studies recently identified two common polymorphisms, FTO rs9939609 and MC4R rs17782313, that are linked to increased body weight and obesity. We examined the association of FTO rs9939609 and MC4R rs17782313 with endometrial cancer risk in a pooled analysis of nine case-control studies within the Epidemiology of Endometrial Cancer Consortium (E2C2). This analysis included 3601 non-Hispanic white women with histologically-confirmed endometrial carcinoma and 5275 frequency-matched controls. Unconditional logistic regression models were used to assess the relation of FTO rs9939609 and MC4R rs17782313 genotypes to the risk of endometrial cancer. Among control women, both the FTO rs9939609 A and MC4R rs17782313 C alleles were associated with a 16% increased risk of being overweight (p = 0.001 and p = 0.004, respectively). In case-control analyses, carriers of the FTO rs9939609 AA genotype were at increased risk of endometrial carcinoma compared to women with the TT genotype [odds ratio (OR) = 1.17; 95% confidence interval (CI): 1.03-1.32, p = 0.01]. However, this association was no longer apparent after adjusting for body mass index (BMI), suggesting mediation of the gene-disease effect through body weight. The MC4R rs17782313 polymorphism was not related to endometrial cancer risk (per allele OR = 0.98; 95% CI: 0.91-1.06; p = 0.68). FTO rs9939609 is a susceptibility marker for white non-Hispanic women at higher risk of endometrial cancer. Although FTO rs9939609 alone might have limited clinical or public health significance for identifying women at high risk for endometrial cancer beyond that of excess body weight, further investigation of obesity-related genetic markers might help to identify the pathways that influence endometrial carcinogenesis.
The association of ovarian carcinoma risk with the polymorphism rs1271572 in the estrogen receptor beta (ESR2) gene was examined in 4946 women with primary invasive ovarian carcinoma and 6582 controls in a pooled analysis of ten case-control studies within the Ovarian Cancer Association Consortium (OCAC). All participants were non-Hispanic white women. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using unconditional logistic regression adjusted for site and age. Women with the TT genotype were at increased risk of ovarian carcinoma compared to carriers of the G allele (OR = 1.10; 95%; CI: 1.01-1.21; p = 0.04); the OR was 1.09 (CI: 0.99-1.20; p = 0.07) after excluding data from the center (Hawaii) that nominated this SNP for OCAC genotyping A stronger association of rs1271572 TT versus GT/GG with risk was observed among women aged ≤50 years versus older women (OR = 1.35; CI: 1.12-1.62; p = 0.002; p for interaction = 0.02) that remained statistically significant after excluding Hawaii data (OR = 1.34; CI: 1.11-1.61; p = 0.009). No heterogeneity of the association was observed by study, menopausal status, gravidity, parity, use of contraceptive or menopausal hormones, tumor histological type, or stage at diagnosis. This pooled analysis suggests that rs1271572 might influence the risk of ovarian cancer, in particular among younger women.
High-throughput single nucleotide polymorphism (SNP)-array technologies allow to investigate copy number variants (CNVs) in genome-wide scans and specific calling algorithms have been developed to determine CNV location and copy number. We report the results of a reliability analysis comparing data from 96 pairs of samples processed with CNVpartition, PennCNV, and QuantiSNP for Infinium Illumina Human 1Million probe chip data. We also performed a validity assessment with multiplex ligation-dependent probe amplification (MLPA) as a reference standard. The number of CNVs per individual varied according to the calling algorithm. Higher numbers of CNVs were detected in saliva than in blood DNA samples regardless of the algorithm used. All algorithms presented low agreement with mean Kappa Index (KI) <66. PennCNV was the most reliable algorithm (KI(w=) 98.96) when assessing the number of copies. The agreement observed in detecting CNV was higher in blood than in saliva samples. When comparing to MLPA, all algorithms identified poorly known copy aberrations (sensitivity = 0.19-0.28). In contrast, specificity was very high (0.97-0.99). Once a CNV was detected, the number of copies was truly assessed (sensitivity >0.62). Our results indicate that the current calling algorithms should be improved for high performance CNV analysis in genome-wide scans. Further refinement is required to assess CNVs as risk factors in complex diseases.
BACKGROUND: The single-nucleotide polymorphism (SNP) 5p12-rs10941679 has been found to be associated with risk of breast cancer, particularly estrogen receptor (ER)-positive disease. We aimed to further explore this association overall, and by tumor histopathology, in the Breast Cancer Association Consortium. METHODS: Data were combined from 37 studies, including 40,972 invasive cases, 1,398 cases of ductal carcinoma in situ (DCIS), and 46,334 controls, all of white European ancestry, as well as 3,007 invasive cases and 2,337 controls of Asian ancestry. Associations overall and by tumor invasiveness and histopathology were assessed using logistic regression. RESULTS: For white Europeans, the per-allele OR associated with 5p12-rs10941679 was 1.11 (95% CI = 1.08-1.14, P = 7 × 10(-18)) for invasive breast cancer and 1.10 (95% CI = 1.01-1.21, P = 0.03) for DCIS. For Asian women, the estimated OR for invasive disease was similar (OR = 1.07, 95%CI = 0.99-1.15, P = 0.09). Further analyses suggested that the association in white Europeans was largely limited to progesterone receptor (PR)-positive disease (per-allele OR = 1.16, 95% CI = 1.12-1.20, P = 1 × 10(-18) vs. OR = 1.03, 95% CI = 0.99-1.07, P = 0.2 for PR-negative disease; P(heterogeneity) = 2 × 10(-7)); heterogeneity by ER status was not observed (P = 0.2) once PR status was accounted for. The association was also stronger for lower grade tumors [per-allele OR (95% CI) = 1.20 (1.14-1.25), 1.13 (1.09-1.16), and 1.04 (0.99-1.08) for grade 1, 2, and 3/4, respectively; P(trend) = 5 × 10(-7)]. CONCLUSION: 5p12 is a breast cancer susceptibility locus for PR-positive, lower grade breast cancer. IMPACT: Multicenter fine-mapping studies of this region are needed as a first step to identifying the causal variant or variants.
Associations between bladder cancer risk and NAT2 and GSTM1 polymorphisms have emerged as some of the most consistent findings in the genetic epidemiology of common metabolic polymorphisms and cancer, but their interaction with tobacco use, intensity and duration remain unclear. In a New England population-based case-control study of urothelial carcinoma, we collected mouthwash samples from 1088 of 1171 cases (92.9%) and 1282 of 1418 controls (91.2%) for genotype analysis of GSTM1, GSTT1 and NAT2 polymorphisms. Odds ratios and 95% confidence intervals of bladder cancer among New England Bladder Cancer Study subjects with one or two inactive GSTM1 alleles (i.e. the 'null' genotype) were 1.26 (0.85-1.88) and 1.54 (1.05-2.25), respectively (P-trend = 0.008), compared with those with two active copies. GSTT1 inactive alleles were not associated with risk. NAT2 slow acetylation status was not associated with risk among never (1.04; 0.71-1.51), former (0.95; 0.75-1.20) or current smokers (1.33; 0.91-1.95); however, a relationship emerged when smoking intensity was evaluated. Among slow acetylators who ever smoked at least 40 cigarettes/day, risk was elevated among ever (1.82; 1.14-2.91, P-interaction = 0.07) and current heavy smokers (3.16; 1.22-8.19, P-interaction = 0.03) compared with rapid acetylators in each category; but was not observed at lower intensities. In contrast, the effect of GSTM1-null genotype was not greater among smokers, regardless of intensity. Meta-analysis of the NAT2 associations with bladder cancer showed a highly significant relationship. Findings from this large USA population-based study provided evidence that the NAT2 slow acetylation genotype interacts with tobacco smoking as a function of exposure intensity.
INTRODUCTION: Studies suggest that high circulating levels of prolactin increase breast cancer risk. It is unclear if genetic variations in prolactin (PRL) or prolactin receptor (PRLR) genes also play a role. Thus, we examined the relationship between single nucleotide polymorphisms (SNPs) in PRL and PRLR, serum prolactin levels and breast cancer risk in a population-based case-control study. METHODS: We genotyped 8 PRL and 20 PRLR tag SNPs in 1965 breast cancer cases and 2229 matched controls, aged 20-74, and living in Warsaw or Łódź, Poland. Serum prolactin levels were measured by immunoassay in a subset of 773 controls. Odds ratios (ORs) and 95% confidence intervals (CIs) for genotype associations with breast cancer risk were estimated using unconditional logistic regression, adjusted for age and study site. Geometric mean prolactin levels were estimated using linear regression models adjusted for age, study site, blood collection time, and menstrual cycle day (premenopausal women). RESULTS: Three SNPs were associated with breast cancer risk: in premenopausal women, PRLR rs249537 (T vs. C per-allele OR 1.39, 95% CI 1.07 - 1.80, P = 0.01); and in postmenopausal women, PRLR rs7718468 (C vs. T per-allele OR 1.16, 95% CI 1.03 - 1.30, P = 0.01) and PRLR rs13436213 (A vs. G per-allele OR 1.13 95% CI 1.01 - 1.26, P = 0.04). However, mean serum prolactin levels for these SNPs did not vary by genotype (P-trend > 0.05). Other SNPs were associated with serum prolactin levels: PRLR rs62355518 (P-trend = 0.01), PRLR rs10941235 (P-trend = 0.01), PRLR rs1610218 (P-trend = 0.01), PRLR rs34024951 (P-trend = 0.02), and PRLR rs9292575 (P-trend = 0.03) in premenopausal controls and PRL rs849872 (P-trend = 0.01) in postmenopausal controls. CONCLUSIONS: Our data provide limited support for an association between common variations in PRLR and breast cancer risk. Altered serum prolactin levels were not associated with breast cancer risk-associated variants, suggesting that common genetic variation is not a strong predictor of prolactin-associated breast cancer risk in this population.
Several single nucleotide polymorphisms (SNPs) in candidate genes of DNA repair and hormone pathways have been reported to be associated with endometrial cancer risk. We sought to confirm these associations in two endometrial cancer case-control sample sets and used additional data from an existing genome-wide association study to prioritize an additional SNP for further study. Five SNPs from the CHEK2, MGMT, SULT1E1 and SULT1A1 genes, genotyped in a total of 1597 cases and 1507 controls from two case-control studies, the Australian National Endometrial Cancer Study and the Polish Endometrial Cancer Study, were assessed for association with endometrial cancer risk using logistic regression analysis. Imputed data was drawn for CHEK2 rs8135424 for 666 cases from the Study of Epidemiology and Risk factors in Cancer Heredity study and 5190 controls from the Wellcome Trust Case Control Consortium. We observed no association between SNPs in the MGMT, SULT1E1 and SULT1A1 genes and endometrial cancer risk. The A allele of the rs8135424 CHEK2 SNP was associated with decreased risk of endometrial cancer (adjusted per-allele OR 0.83; 95%CI 0.70-0.98; p = .03) however this finding was opposite to that previously published. Imputed data for CHEK2 rs8135424 supported the direction of effect reported in this study (OR 0.85; 95% CI 0.65-1.10). Previously reported endometrial cancer risk associations with SNPs from in genes involved in estrogen metabolism and DNA repair were not replicated in our larger study population. This study highlights the need for replication of candidate gene SNP studies using large sample groups, to confirm risk associations and better prioritize downstream studies to assess the causal relationship between genetic variants and cancer risk. Our findings suggest that the CHEK2 SNP rs8135424 be prioritized for further study as a genetic factor associated with risk of endometrial cancer.
BACKGROUND: Single nucleotide polymorphisms (SNP) in microRNA-related genes have been associated with epithelial ovarian cancer (EOC) risk in two reports, yet associated alleles may be inconsistent across studies. METHODS: We conducted a pooled analysis of previously identified SNPs by combining genotype data from 3,973 invasive EOC cases and 3,276 controls from the Ovarian Cancer Association Consortium. We also conducted imputation to obtain dense coverage of genes and comparable genotype data for all studies. In total, 226 SNPs within 15 kb of 4 miRNA biogenesis genes (DDX20, DROSHA, GEMIN4, and XPO5) and 23 SNPs located within putative miRNA binding sites of 6 genes (CAV1, COL18A1, E2F2, IL1R1, KRAS, and UGT2A3) were genotyped or imputed and analyzed in the entire dataset. RESULTS: After adjustment for European ancestry, no overall association was observed between any of the analyzed SNPs and EOC risk. CONCLUSIONS: Common variants in these evaluated genes do not seem to be strongly associated with EOC risk. IMPACT: This analysis suggests earlier associations between EOC risk and SNPs in these genes may have been chance findings, possibly confounded by population admixture. To more adequately evaluate the relationship between genetic variants and cancer risk, large sample sizes are needed, adjustment for population stratification should be carried out, and use of imputed SNP data should be considered.
Defective microRNA (miRNA) biogenesis contributes to the development and progression of epithelial ovarian cancer (EOC). In this study, we examined the hypothesis that single nucleotide polymorphisms (SNP) in miRNA biogenesis genes may influence EOC risk. In an initial investigation, 318 SNPs in 18 genes were evaluated among 1,815 EOC cases and 1,900 controls, followed up by a replicative joint meta-analysis of data from an additional 2,172 cases and 3,052 controls. Of 23 SNPs from 9 genes associated with risk (empirical P < 0.05) in the initial investigation, the meta-analysis replicated 6 SNPs from the DROSHA, FMR1, LIN28, and LIN28B genes, including rs12194974 (G>A), an SNP in a putative transcription factor binding site in the LIN28B promoter region (summary OR = 0.90, 95% CI: 0.82-0.98; P = 0.015) which has been recently implicated in age of menarche and other phenotypes. Consistent with reports that LIN28B overexpression in EOC contributes to tumorigenesis by repressing tumor suppressor let-7 expression, we provide data from luciferase reporter assays and quantitative RT-PCR to suggest that the inverse association among rs12194974 A allele carriers may be because of reduced LIN28B expression. Our findings suggest that variants in LIN28B and possibly other miRNA biogenesis genes may influence EOC susceptibility.
BACKGROUND: TGF-β acts as a suppressor of primary tumor initiation but has been implicated as a promoter of the later malignant stages. Here associations with risk of invasive breast cancer are assessed for single-nucleotide polymorphisms (SNP) tagging 17 genes in the canonical TGF-β ALK5/SMADs 2&3 and ALK1/SMADs 1&5 signaling pathways: LTBP1, LTBP2, LTBP4, TGFB1, TGFB2, TGFB3, TGFBR1(ALK5), ALK1, TGFBR2, Endoglin, SMAD1, SMAD2, SMAD3, SMAD4, SMAD5, SMAD6, and SMAD7 [Approved Human Gene Nomenclature Committee gene names: ACVRL1 (for ALK1) and ENG (for Endoglin)]. METHODS: Three-hundred-fifty-four tag SNPs (minor allele frequency > 0.05) were selected for genotyping in a staged study design using 6,703 cases and 6,840 controls from the Studies of Epidemiology and Risk Factors in Cancer Heredity (SEARCH) study. Significant associations were meta-analyzed with data from the NCI Polish Breast Cancer Study (PBCS; 1,966 cases and 2,347 controls) and published data from the Breast Cancer Association Consortium (BCAC). RESULTS: Associations of three SNPs, tagging TGFB1 (rs1982073), TGFBR1 (rs10512263), and TGFBR2 (rs4522809), were detected in SEARCH; however, associations became weaker in meta-analyses including data from PBCS and BCAC. Tumor subtype analyses indicated that the TGFB1 rs1982073 association may be confined to increased risk of developing progesterone receptor negative (PR(-)) tumors [1.18 (95% CI: 1.09-1.28), 4.1 × 10(-5) (P value for heterogeneity of ORs by PR status = 2.3 × 10(-4))]. There was no evidence for breast cancer risk associations with SNPs in the endothelial-specific pathway utilizing ALK1/SMADs 1&5 that promotes angiogenesis. CONCLUSION: Common variation in the TGF-β ALK5/SMADs 2&3 signaling pathway, which initiates signaling at the cell surface to inhibit cell proliferation, might be related to risk of specific tumor subtypes. IMPACT: The subtype specific associations require very large studies to be confirmed.
Endometrial cancer is the most common malignancy of the female genital tract in developed countries. To identify genetic variants associated with endometrial cancer risk, we performed a genome-wide association study involving 1,265 individuals with endometrial cancer (cases) from Australia and the UK and 5,190 controls from the Wellcome Trust Case Control Consortium. We compared genotype frequencies in cases and controls for 519,655 SNPs. Forty seven SNPs that showed evidence of association with endometrial cancer in stage 1 were genotyped in 3,957 additional cases and 6,886 controls. We identified an endometrial cancer susceptibility locus close to HNF1B at 17q12 (rs4430796, P = 7.1 × 10(-10)) that is also associated with risk of prostate cancer and is inversely associated with risk of type 2 diabetes.
BACKGROUND: Previous studies have suggested that breast cancer risk factors are associated with estrogen receptor (ER) and progesterone receptor (PR) expression status of the tumors. METHODS: We pooled tumor marker and epidemiological risk factor data from 35,568 invasive breast cancer case patients from 34 studies participating in the Breast Cancer Association Consortium. Logistic regression models were used in case-case analyses to estimate associations between epidemiological risk factors and tumor subtypes, and case-control analyses to estimate associations between epidemiological risk factors and the risk of developing specific tumor subtypes in 12 population-based studies. All statistical tests were two-sided. RESULTS: In case-case analyses, of the epidemiological risk factors examined, early age at menarche (≤12 years) was less frequent in case patients with PR(-) than PR(+) tumors (P = .001). Nulliparity (P = 3 × 10(-6)) and increasing age at first birth (P = 2 × 10(-9)) were less frequent in ER(-) than in ER(+) tumors. Obesity (body mass index [BMI] ≥ 30 kg/m(2)) in younger women (≤50 years) was more frequent in ER(-)/PR(-) than in ER(+)/PR(+) tumors (P = 1 × 10(-7)), whereas obesity in older women (>50 years) was less frequent in PR(-) than in PR(+) tumors (P = 6 × 10(-4)). The triple-negative (ER(-)/PR(-)/HER2(-)) or core basal phenotype (CBP; triple-negative and cytokeratins [CK]5/6(+) and/or epidermal growth factor receptor [EGFR](+)) accounted for much of the heterogeneity in parity-related variables and BMI in younger women. Case-control analyses showed that nulliparity, increasing age at first birth, and obesity in younger women showed the expected associations with the risk of ER(+) or PR(+) tumors but not triple-negative (nulliparity vs parity, odds ratio [OR] = 0.94, 95% confidence interval [CI] = 0.75 to 1.19, P = .61; 5-year increase in age at first full-term birth, OR = 0.95, 95% CI = 0.86 to 1.05, P = .34; obesity in younger women, OR = 1.36, 95% CI = 0.95 to 1.94, P = .09) or CBP tumors. CONCLUSIONS: This study shows that reproductive factors and BMI are most clearly associated with hormone receptor-positive tumors and suggest that triple-negative or CBP tumors may have distinct etiology.
BACKGROUND: Traditional prognostic factors for survival and treatment response of patients with breast cancer do not fully account for observed survival variation. We used available genotype data from a previously conducted two-stage, breast cancer susceptibility genome-wide association study (ie, Studies of Epidemiology and Risk factors in Cancer Heredity [SEARCH]) to investigate associations between variation in germline DNA and overall survival. METHODS: We evaluated possible associations between overall survival after a breast cancer diagnosis and 10 621 germline single-nucleotide polymorphisms (SNPs) from up to 3761 patients with invasive breast cancer (including 647 deaths and 26 978 person-years at risk) that were genotyped previously in the SEARCH study with high-density oligonucleotide microarrays (ie, hypothesis-generating set). Associations with all-cause mortality were assessed for each SNP by use of Cox regression analysis, generating a per rare allele hazard ratio (HR). To validate putative associations, we used patient genotype information that had been obtained with 5' nuclease assay or mass spectrometry and overall survival information for up to 14 096 patients with invasive breast cancer (including 2303 deaths and 70 019 person-years at risk) from 15 international case-control studies (ie, validation set). Fixed-effects meta-analysis was used to generate an overall effect estimate in the validation dataset and in combined SEARCH and validation datasets. All statistical tests were two-sided. RESULTS: In the hypothesis-generating dataset, SNP rs4778137 (C>G) of the OCA2 gene at 15q13.1 was statistically significantly associated with overall survival among patients with estrogen receptor-negative tumors, with the rare G allele being associated with increased overall survival (HR of death per rare allele carried = 0.56, 95% confidence interval [CI] = 0.41 to 0.75, P = 9.2 x 10(-5)). This association was also observed in the validation dataset (HR of death per rare allele carried = 0.88, 95% CI = 0.78 to 0.99, P = .03) and in the combined dataset (HR of death per rare allele carried = 0.82, 95% CI = 0.73 to 0.92, P = 5 x 10(-4)). CONCLUSION: The rare G allele of the OCA2 polymorphism, rs4778137, may be associated with improved overall survival among patients with estrogen receptor-negative breast cancer.
BACKGROUND: Immunohistochemical markers are often used to classify breast cancer into subtypes that are biologically distinct and behave differently. The aim of this study was to estimate mortality for patients with the major subtypes of breast cancer as classified using five immunohistochemical markers, to investigate patterns of mortality over time, and to test for heterogeneity by subtype. METHODS AND FINDINGS: We pooled data from more than 10,000 cases of invasive breast cancer from 12 studies that had collected information on hormone receptor status, human epidermal growth factor receptor-2 (HER2) status, and at least one basal marker (cytokeratin [CK]5/6 or epidermal growth factor receptor [EGFR]) together with survival time data. Tumours were classified as luminal and nonluminal tumours according to hormone receptor expression. These two groups were further subdivided according to expression of HER2, and finally, the luminal and nonluminal HER2-negative tumours were categorised according to expression of basal markers. Changes in mortality rates over time differed by subtype. In women with luminal HER2-negative subtypes, mortality rates were constant over time, whereas mortality rates associated with the luminal HER2-positive and nonluminal subtypes tended to peak within 5 y of diagnosis and then decline over time. In the first 5 y after diagnosis the nonluminal tumours were associated with a poorer prognosis, but over longer follow-up times the prognosis was poorer in the luminal subtypes, with the worst prognosis at 15 y being in the luminal HER2-positive tumours. Basal marker expression distinguished the HER2-negative luminal and nonluminal tumours into different subtypes. These patterns were independent of any systemic adjuvant therapy. CONCLUSIONS: The six subtypes of breast cancer defined by expression of five markers show distinct behaviours with important differences in short term and long term prognosis. Application of these markers in the clinical setting could have the potential to improve the targeting of adjuvant chemotherapy to those most likely to benefit. The different patterns of mortality over time also suggest important biological differences between the subtypes that may result in differences in response to specific therapies, and that stratification of breast cancers by clinically relevant subtypes in clinical trials is urgently required.
BACKGROUND: A major challenge in studies of etiologic heterogeneity in breast cancer has been the limited throughput, accuracy, and reproducibility of measuring tissue markers. Computerized image analysis systems may help address these concerns, but published reports of their use are limited. We assessed agreement between automated and pathologist scores of a diverse set of immunohistochemical assays done on breast cancer tissue microarrays (TMA). METHODS: TMAs of 440 breast cancers previously stained for estrogen receptor (ER)-alpha, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), ER-beta, and aromatase were independently scored by two pathologists and three automated systems (TMALab II, TMAx, and Ariol). Agreement between automated and pathologist scores of negative/positive was measured using the area under the receiver operating characteristics curve (AUC) and weighted kappa statistics for categorical scores. We also investigated the correlation between immunohistochemical scores and mRNA expression levels. RESULTS: Agreement between pathologist and automated negative/positive and categorical scores was excellent for ER-alpha and PR (AUC range = 0.98-0.99; kappa range = 0.86-0.91). Lower levels of agreement were seen for ER-beta categorical scores (AUC = 0.99-1.0; kappa = 0.80-0.86) and both negative/positive and categorical scores for aromatase (AUC = 0.85-0.96; kappa = 0.41-0.67) and HER2 (AUC = 0.94-0.97; kappa = 0.53-0.72). For ER-alpha and PR, there was a strong correlation between mRNA levels and automated (rho = 0.67-0.74) and pathologist immunohistochemical scores (rho = 0.67-0.77). HER2 mRNA levels were more strongly correlated with pathologist (rho = 0.63) than automated immunohistochemical scores (rho = 0.41-0.49). CONCLUSIONS: Automated analysis of immunohistochemical markers is a promising approach for scoring large numbers of breast cancer tissues in epidemiologic investigations. This would facilitate studies of etiologic heterogeneity, which ultimately may allow improved risk prediction and better prevention approaches.
BACKGROUND: Bladder cancer has been linked with long-term exposure to disinfection by-products (DBPs) in drinking water. OBJECTIVES: In this study we investigated the combined influence of DBP exposure and polymorphisms in glutathione S-transferase (GSTT1, GSTZ1) and cytochrome P450 (CYP2E1) genes in the metabolic pathways of selected by-products on bladder cancer in a hospital-based case-control study in Spain. METHODS: Average exposures to trihalomethanes (THMs; a surrogate for DBPs) from 15 years of age were estimated for each subject based on residential history and information on municipal water sources among 680 cases and 714 controls. We estimated effects of THMs and GSTT1, GSTZ1, and CYP2E1 polymorphisms on bladder cancer using adjusted logistic regression models with and without interaction terms. RESULTS: THM exposure was positively associated with bladder cancer: adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were 1.2 (0.8-1.8), 1.8 (1.1-2.9), and 1.8 (0.9-3.5) for THM quartiles 2, 3, and 4, respectively, relative to quartile 1. Associations between THMs and bladder cancer were stronger among subjects who were GSTT1 +/+ or +/- versus GSTT1 null (P(interaction) = 0.021), GSTZ1 rs1046428 CT/TT versus CC (P(interaction) = 0.018), or CYP2E1 rs2031920 CC versus CT/TT (P(interaction) = 0.035). Among the 195 cases and 192 controls with high-risk forms of GSTT1 and GSTZ1, the ORs for quartiles 2, 3, and 4 of THMs were 1.5 (0.7-3.5), 3.4 (1.4-8.2), and 5.9 (1.8-19.0), respectively. CONCLUSIONS: Polymorphisms in key metabolizing enzymes modified DBP-associated bladder cancer risk. The consistency of these findings with experimental observations of GSTT1, GSTZ1, and CYP2E1 activity strengthens the hypothesis that DBPs cause bladder cancer and suggests possible mechanisms as well as the classes of compounds likely to be implicated.
Sonic hedgehog (Shh) pathway genetic variations may affect bladder cancer risk and clinical outcomes. Therefore, we genotyped 177 single-nucleotide polymorphisms (SNP) in 11 Shh pathway genes in a study including 803 bladder cancer cases and 803 controls. We assessed SNP associations with cancer risk and clinical outcomes in 419 cases of non-muscle-invasive bladder cancer (NMIBC) and 318 cases of muscle-invasive and metastatic bladder cancer (MiMBC). Only three SNPs (GLI3 rs3823720, rs3735361, and rs10951671) reached nominal significance in association with risk (P ≤ 0.05), which became nonsignificant after adjusting for multiple comparisons. Nine SNPs reached a nominally significant individual association with recurrence of NMIBC in patients who received transurethral resection (TUR) only (P ≤ 0.05), of which two (SHH rs1233560 and GLI2 rs11685068) were replicated independently in 356 TUR-only NMIBC patients, with P values of 1.0 × 10(-3) (SHH rs1233560) and 1.3 × 10(-3) (GLI2 rs11685068). Nine SNPs also reached a nominally significant individual association with clinical outcome of NMIBC patients who received Bacillus Calmette-Guérin (BCG; P ≤ 0.05), of which two, the independent GLI3 variants rs6463089 and rs3801192, remained significant after adjusting for multiple comparisons (P = 2 × 10(-4) and 9 × 10(-4), respectively). The wild-type genotype of either of these SNPs was associated with a lower recurrence rate and longer recurrence-free survival (versus the variants). Although three SNPs (GLI2 rs735557, GLI2 rs4848632, and SHH rs208684) showed nominal significance in association with overall survival in MiMBC patients (P ≤ 0.05), none remained significant after multiple-comparison adjustments. Germ-line genetic variations in the Shh pathway predicted clinical outcomes of TUR and BCG for NMIBC patients.
We genotyped 13 single nucleotide polymorphisms (SNPs) in the estrogen receptor alpha gene (ESR1) region in three population-based case-control studies of epithelial ovarian cancer conducted in the United States, comprising a total of 1,128 and 1,866 non-Hispanic white invasive cases and controls, respectively. A SNP 19 kb downstream of ESR1 (rs2295190, G-to-T change) was associated with invasive ovarian cancer risk, with a per-T-allele odds ratio (OR) of 1.24 [95% confidence interval (CI), 1.06-1.44, P = 0.006]. rs2295190 is a nonsynonymous coding SNP in a neighboring gene called spectrin repeat containing, nuclear envelope 1 (SYNE1), which is involved in nuclear organization and structural integrity, function of the Golgi apparatus, and cytokinesis. An isoform encoded by SYNE1 has been reported to be downregulated in ovarian and other cancers. rs2295190 was genotyped in an additional 12 studies through the Ovarian Cancer Association Consortium, with 5,279 invasive epithelial cases and 7,450 controls. The per-T-allele OR for this 12-study set was 1.09 (95% CI, 1.02-1.17; P = 0.017). Results for the serous subtype in the 15 combined studies were similar to those overall (n = 3,545; OR, 1.09; 95% CI, 1.01-1.18; P = 0.025), and our findings were strongest for the mucinous subtype (n = 447; OR, 1.32; 95% CI, 1.11-1.58; P = 0.002). No association was observed for the endometrioid subtype. In an additional analysis of 1,459 borderline ovarian cancer cases and 7,370 controls, rs2295190 was not associated with risk. These data provide suggestive evidence that the rs2295190 T allele, or another allele in linkage disequilibrium with it, may be associated with increased risk of invasive ovarian cancer.
BACKGROUND: Previous prospective studies have found an association between prolactin (PRL) levels and increased risk of breast cancer. Using data from a population-based breast cancer case-control study conducted in two cities in Poland (2000-2003), we examined the association of PRL levels with breast cancer risk factors among controls and with tumour characteristics among the cases. METHODS: We analysed PRL serum levels among 773 controls without breast cancer matched on age and residence to 776 invasive breast cancer cases with available pretreatment serum. Tumours were centrally reviewed and prepared as tissue microarrays for immunohistochemical analysis. Breast cancer risk factors, assessed by interview, were related to serum PRL levels among controls using analysis of variance. Mean serum PRL levels by tumour characteristics are reported. These associations also were evaluated using polytomous logistic regression. RESULTS: Prolactin levels were associated with nulliparity in premenopausal (P=0.05) but not in postmenopausal women. Associations in postmenopausal women included an inverse association with increasing body mass index (P=0.0008) and direct association with use of recent/current hormone therapy (P=0.0006). In case-only analyses, higher PRL levels were more strongly associated with lobular compared with ductal carcinoma among postmenopausal women (P=0.02). Levels were not different by tumour size, grade, node involvement or oestrogen receptor, progesterone receptor, or human epidermal growth factor receptor 2 status. CONCLUSIONS: Our analysis demonstrates that PRL levels are higher among premenopausal nulliparous as compared with parous women. Among postmenopausal women, levels were higher among hormone users and lower among obese women. These results may have value in understanding the mechanisms underlying several breast cancer risk factor associations.
The transforming growth factor beta (TGF-beta) pathway can play either a tumor-suppressing or a tumor-promoting role in human breast carcinogenesis. In order to determine whether expression of TGF-beta signaling factors varies by age at onset and breast tumor characteristics that have prognostic significance, we undertook a study of 623 women with invasive breast carcinoma enrolled in a population-based case-control study conducted in Poland from 2000 to 2003. TGF-beta signaling factors were analyzed by immunohistochemistry in tumor tissue microarrays. We found that most tumors expressed extracellular-TGF-beta1 (78%), TGF-beta2 (91%), TGF-beta3 (93%), TGF-betaR2 (72%), and phospho-SMAD2 (61%), whereas intracellular-TGF-beta1 was expressed in 32% of tumors. Expression of TGF-beta ligands (beta1, beta2, and beta3) was associated with prognostically favorable pathological features including small size, and low grade, and these associations were similar for ER-positive and negative tumors. On the contrary, expression of the receptor TGF-betaR2 was primarily associated with small tumor size among ER-negative tumors, while expression of the transcription factor phospho-SMAD2 was associated with positive nodal status among ER-negative tumors. The greater frequency of expression of phospho-SMAD2 in cancers associated with lymph node metastases is consistent with a pro-progression role for TGF-beta. In addition, expression of extracellular-TGF-beta1 (P = 0.005), TGF-betaR2 (P = 8.2E-11), and phospho-SMAD2 (P = 1.3E-8) was strongly associated with earlier age at onset, independent of ER status. Our data provide evidence that TGF-beta signaling patterns vary by age and pathologic features of prognostic significance including ER expression. These results warrant analysis in studies of clinical outcomes accounting for age, ER status and treatment.
INTRODUCTION: Obesity and diabetes are known risk factors for endometrial cancer; thus, the genetic risk factors of these phenotypes might also be associated with endometrial cancer risk. To evaluate this hypothesis, we genotyped tag-single nucleotide polymorphisms (SNP) and candidate SNPs in FTO and HHEX in a primary set of 417 endometrial cancer cases and 406 population-based controls, and validated significant findings in a replication set of approximately 2,347 cases and 3,140 controls from three additional studies. METHODS: We genotyped 189 tagSNPs in FTO (including rs8050136) and five tagSNPs in HHEX (including rs1111875) in the primary set and one SNP each in FTO (rs12927155) and HHEX (rs1111875) in the validation set. Per allele odds ratios (OR) and 95% confidence intervals (CI) were calculated to estimate the association between the genotypes of each SNPs (as an ordinal variable) and endometrial cancer risk using unconditional logistic regression models, controlling for age and site. RESULTS: In the primary study, the most significant finding in FTO was rs12927155 (OR, 1.56; 95% CI, 1.21-2.01; P = 5.8 x 10(-4)), and in HHEX, it was rs1111875 (OR, 0.80; 95% CI, 0.66-0.97; P = 0.026). In the validation studies, the pooled per allele OR, adjusted for age and study for FTO, was rs12927155 (OR, 0.94; 95% CI, 0.83-1.06; P = 0.29), whereas for HHEX, it was rs1111875 (OR, 1.00; 95% CI, 0.92-1.10; P = 0.96). CONCLUSION: Our data indicate that common genetic variants in two genes previously related to obesity (FTO) and diabetes (HHEX) by genome-wide association scans were not associated with endometrial cancer risk. IMPACT: Polymorphisms in FTO and HHEX are unlikely to have large effects on endometrial cancer risk but may have weaker effects.
Ovarian cancer accounts for more deaths than all other gynecological cancers combined. To identify common low-penetrance ovarian cancer susceptibility genes, we conducted a genome-wide association study of 507,094 SNPs in 1,768 individuals with ovarian cancer (cases) and 2,354 controls, with follow up of 21,955 SNPs in 4,162 cases and 4,810 controls, leading to the identification of a confirmed susceptibility locus at 9p22 (in BNC2). Here, we report on nine additional candidate loci (defined as having P ≤ 10⁻⁴) identified after stratifying cases by histology, which we genotyped in an additional 4,353 cases and 6,021 controls. We confirmed two new susceptibility loci with P ≤ 5 × 10⁻⁸ (8q24, P = 8.0 × 10⁻¹⁵ and 2q31, P = 3.8 × 10⁻¹⁴) and identified two additional loci that approached genome-wide significance (3q25, P = 7.1 × 10⁻⁸ and 17q21, P = 1.4 × 10⁻⁷). The associations of these loci with serous ovarian cancer were generally stronger than with other cancer subtypes. Analysis of HOXD1, MYC, TIPARP and SKAP1 at these loci and of BNC2 at 9p22 supports a functional role for these genes in ovarian cancer development.
BACKGROUND: Clinical, pathologic, and molecular evidence indicate that bladder cancer is heterogeneous with pathologic/molecular features that define distinct subphenotypes with different prognoses. It is conceivable that specific patterns of genetic susceptibility are associated with particular subphenotypes. OBJECTIVE: To examine evidence for the contribution of germline genetic variation to bladder cancer heterogeneity. DESIGN, SETTING, AND PARTICIPANTS: The Spanish Bladder Cancer/EPICURO Study is a case-control study based in 18 hospitals located in five areas in Spain. Cases were patients with a newly diagnosed, histologically confirmed, urothelial cell carcinoma of the bladder from 1998 to 2001. Case diagnoses were reviewed and uniformly classified by pathologists following the World Health Organisation/International Society of Urological Pathology 1999 criteria. Controls were hospital-matched patients (n=1149). MEASUREMENTS: A total of 1526 candidate variants in 423 candidate genes were analysed. Three distinct subphenotypes were defined according to stage and grade: low-grade nonmuscle invasive (n=586), high-grade nonmuscle invasive (n=219), and muscle invasive (n=246). The association between each variant and subphenotype was assessed by polytomous risk models adjusting for potential confounders. Heterogeneity in genetic susceptibility among subphenotypes was also tested. RESULTS AND LIMITATIONS: Two established bladder cancer susceptibility genotypes, NAT2 slow-acetylation and GSTM1-null, exhibited similar associations among the subphenotypes, as did VEGF-rs25648, which was previously identified in our study. Other variants conferred risks for specific tumour subphenotypes such as PMS2-rs6463524 and CD4-rs3213427 (respective heterogeneity p values of 0.006 and 0.004), which were associated with muscle-invasive tumours (per-allele odds ratios [95% confidence interval] of 0.56 [0.41-0.77] and 0.71 [0.57-0.88], respectively) but not with non-muscle-invasive tumours. Heterogeneity p values were not robust in multiple testing according to their false-discovery rate. CONCLUSIONS: These exploratory analyses suggest that genetic susceptibility loci might be related to the molecular/pathologic diversity of bladder cancer. Validation through large-scale replication studies and the study of additional genes and single nucleotide polymorphisms are required.
We hypothesized that variants in genes expressed as a consequence of interactions between ovarian cancer cells and the host micro-environment could contribute to cancer susceptibility. We therefore used a two-stage approach to evaluate common single nucleotide polymorphisms (SNPs) in 173 genes involved in stromal epithelial interactions in the Ovarian Cancer Association Consortium (OCAC). In the discovery stage, cases with epithelial ovarian cancer (n=675) and controls (n=1,162) were genotyped at 1,536 SNPs using an Illumina GoldenGate assay. Based on Positive Predictive Value estimates, three SNPs-PODXL rs1013368, ITGA6 rs13027811, and MMP3 rs522616-were selected for replication using TaqMan genotyping in up to 3,059 serous invasive cases and 8,905 controls from 16 OCAC case-control studies. An additional 18 SNPs with Pper-allele<0.05 in the discovery stage were selected for replication in a subset of five OCAC studies (n=1,233 serous invasive cases; n=3,364 controls). The discovery stage associations in PODXL, ITGA6, and MMP3 were attenuated in the larger replication set (adj. Pper-allele>or=0.5). However genotypes at TERT rs7726159 were associated with ovarian cancer risk in the smaller, five-study replication study (Pper-allele=0.03). Combined analysis of the discovery and replication sets for this TERT SNP showed an increased risk of serous ovarian cancer among non-Hispanic whites [adj. ORper-allele 1.14 (1.04-1.24) p=0.003]. Our study adds to the growing evidence that, like the 8q24 locus, the telomerase reverse transcriptase locus at 5p15.33, is a general cancer susceptibility locus.
Genetic and lifestyle/environmental factors are implicated in the aetiology of breast cancer. This review summarizes the current state of knowledge on rare high penetrance mutations, as well as moderate and low-penetrance genetic variants implicated in breast cancer aetiology. We summarize recent discoveries from large collaborative efforts to combine data from candidate gene studies, and to conduct genome-wide association studies (GWAS), primarily in breast cancers in the general population. These findings are compared with results from collaborative efforts aiming to identify genetic modifiers in BRCA1 and BRCA2 carriers. Breast cancer is a heterogeneous disease, and tumours from BRCA1 and BRCA2 carriers display distinct pathological characteristics when compared with tumours unselected for family history. The relationship between genetic variants and pathological subtypes of breast cancer, and the implication of discoveries of novel genetic variants to risk prediction in BRCA1/2 mutation carriers and in populations unselected for mutation carrier status, are discussed.
Genome-wide association studies (GWAS) focus on relatively few highly significant loci, whereas less attention is given to other genotyped markers. Using pathway analysis to study existing GWAS data may shed light on relevant biological processes and illuminate new candidate genes. We applied a pathway-based approach to the breast cancer GWAS data of the National Cancer Institute (NCI) Cancer Genetic Markers of Susceptibility project that includes 1,145 cases and 1,142 controls. Pathways were retrieved from three databases: KEGG, BioCarta, and NCI Protein Interaction Database. Genes were represented by their most strongly associated SNP, and an enrichment score reflecting the overrepresentation of gene-based association signals in each pathway was calculated by using a weighted Kolmogorov-Smirnov procedure. Finally, hierarchical clustering was used to identify pathways with overlapping genes, and clusters with an excess of association signals were determined by the adaptive rank-truncated product (ARTP) method. A total of 421 pathways containing 3,962 genes was included in our study. Of these, three pathways (syndecan-1-mediated signaling, signaling of hepatocyte growth factor receptor, and growth hormone signaling) were highly enriched with association signals [P(ES) < 0.001, false discovery rate (FDR) = 0.118]. Our clustering analysis revealed that pathways containing key components of the RAS/RAF/mitogen-activated protein kinase canonical signaling cascade were significantly more likely to have an excess of association signals than expected by chance (P(ARTP) = 0.0051, FDR = 0.07). These results suggest that genetic alterations associated with these three pathways and one canonical signaling cascade may contribute to breast cancer susceptibility.
INTRODUCTION: Several common breast cancer genetic susceptibility variants have recently been identified. We aimed to determine how these variants combine with a subset of other known risk factors to influence breast cancer risk in white women of European ancestry using case-control studies participating in the Breast Cancer Association Consortium. METHODS: We evaluated two-way interactions between each of age at menarche, ever having had a live birth, number of live births, age at first birth and body mass index (BMI) and each of 12 single nucleotide polymorphisms (SNPs) (10q26-rs2981582 (FGFR2), 8q24-rs13281615, 11p15-rs3817198 (LSP1), 5q11-rs889312 (MAP3K1), 16q12-rs3803662 (TOX3), 2q35-rs13387042, 5p12-rs10941679 (MRPS30), 17q23-rs6504950 (COX11), 3p24-rs4973768 (SLC4A7), CASP8-rs17468277, TGFB1-rs1982073 and ESR1-rs3020314). Interactions were tested for by fitting logistic regression models including per-allele and linear trend main effects for SNPs and risk factors, respectively, and single-parameter interaction terms for linear departure from independent multiplicative effects. RESULTS: These analyses were applied to data for up to 26,349 invasive breast cancer cases and up to 32,208 controls from 21 case-control studies. No statistical evidence of interaction was observed beyond that expected by chance. Analyses were repeated using data from 11 population-based studies, and results were very similar. CONCLUSIONS: The relative risks for breast cancer associated with the common susceptibility variants identified to date do not appear to vary across women with different reproductive histories or body mass index (BMI). The assumption of multiplicative combined effects for these established genetic and other risk factors in risk prediction models appears justified.
OBJECTIVES: Telomeres are structures at chromosome ends that contribute to maintaining genomic integrity. Telomere shortening with repeated cell divisions may lead to genomic instability and carcinogenesis. Studies suggest that shorter telomeres in constitutional DNA are associated with bladder, breast, lung, and renal cancer. Ovarian cancer tissues also have shortened telomeres and increased telomerase activity, suggesting that telomere abnormalities may be related to ovarian cancer. METHODS: We investigated leukocyte telomere length in 99 women with serous ovarian adenocarcinoma and 100 age-matched cancer-free controls enrolled in a population-based case-control study. RESULTS: Cases tended to have shorter telomeres than controls (P (wilcoxon) = 0.002). Compared to subjects with telomere lengths in the longest tertile, those in the middle and shortest tertiles showed respective age-adjusted odds ratios (95% confidence intervals) of 2.69 (1.23-5.88) and 3.39 (1.54-7.46) (P (trend) = 0.002). Strongest associations were found for subjects with poorly differentiated carcinomas (OR = 4.89, 95% CI 1.93-12.34). CONCLUSIONS: This study shows that short leukocyte telomeres are associated with serous ovarian adenocarcinoma. These findings should be confirmed in large, prospective studies.
BACKGROUND: Although studies in rodents suggest possible associations between exposure to organic solvents and breast cancer, the evidence in humans is limited. METHODS: We evaluated job histories of 2383 incident breast cancer cases diagnosed during 2000-2003, and 2502 controls who participated in a large population-based case-control study in Poland. Industrial hygienists reviewed occupational histories and developed exposure metrics for total organic solvents and benzene. Unconditional logistic regression analyses estimated ORs and 95% CIs as the measure of association with breast cancer, controlling for breast cancer risk factors. Stratified analyses examined the potential modification by known breast cancer risk factors. Associations were also evaluated by oestrogen and progesterone receptor status and by other clinical characteristics of the tumours using polytomous regression analyses. RESULTS: Women who ever worked at jobs with organic solvents exposure had a small, non-significant increase in breast cancer risk (OR=1.16; 95% CI 0.99 to 1.4). A significant association was present for oestrogen receptor- and progesterone receptor-negative tumours (OR 1.40; 95% CI 1.1 to 1.8), but there was no association with tumours with both positive receptors (OR 0.97; 95% CI 0.8 to 1.2 (p heterogeneity: 0.008)). We did not observe trends with increasing level of exposure. Known breast cancer risk factors did not modify the association between organic solvents and breast cancer risk. No association with breast cancer was found for benzene exposure (OR 1.00; 95% CI 0.8 to 1.3). CONCLUSION: Our study provides weak evidence for a possible association between occupational exposure to organic solvents as a class and breast cancer risk. The association might be limited to hormone receptor-negative tumours.
Catechol-O-methyl transferase (COMT) is an important estrogen-metabolizing enzyme, and common genetic variants in this gene could affect breast cancer risk. We conducted a large population-based case control study in Massachusetts, New Hampshire, and Wisconsin to examine six strategically selected COMT haplotype-tagging (ht) single nucleotide polymorphism (SNPs), including the val158met polymorphism (rs4680), in relation to breast cancer risk. Analyses were based on 1,655 Caucasian women with invasive breast cancer and 1,470 Caucasian controls. None of the six individual SNPs were associated with breast cancer risk. The global test for haplotype associations was nonsignificant (p-value=0.097), although two uncommon haplotypes present in 6% of the study population showed statistically significant inverse associations with risk. These results suggest that genetic variation in COMT has no significant association with breast cancer risk among Caucasian women.
Aberrant glycosylation is a well-described hallmark of cancer. In a previous ovarian cancer case control study that examined polymorphisms in 26 glycosylation-associated genes, we found strong statistical evidence (P = 0.00017) that women who inherited two copies of a single-nucleotide polymorphism in the UDP-N-acetylgalactosamine:polypeptide N-acetylgalactosaminyltransferase, GALNT1, had decreased ovarian cancer risk. The current study attempted to replicate this observation. The GALNT1 single-nucleotide polymorphism rs17647532 was genotyped in 6,965 cases and 8,377 controls from 14 studies forming the Ovarian Cancer Association Consortium. The fixed effects estimate per rs17647532 allele was null (odds ratio, 0.99; 95% confidence interval, 0.92-1.07). When a recessive model was fit, the results were unchanged. Test for heterogeneity of the odds ratios revealed consistency across the 14 replication sites but significant differences compared with the original study population (P = 0.03). This study underscores the need for replication of putative findings in genetic association studies.
Mosaicism is defined as the coexistence of cells with different genetic composition within an individual, caused by postzygotic somatic mutation. Although somatic mosaicism for chromosomal abnormalities is a well-established cause of developmental and somatic disorders and has also been detected in different tissues, its frequency and extent in the adult normal population are still unknown. We provide here a genome-wide survey of mosaic genomic variation obtained by analyzing Illumina 1M SNP array data from blood or buccal DNA samples of 1991 adult individuals from the Spanish Bladder Cancer/EPICURO genome-wide association study. We found mosaic abnormalities in autosomes in 1.7% of samples, including 23 segmental uniparental disomies, 8 complete trisomies, and 11 large (1.5-37 Mb) copy-number variants. Alterations were observed across the different autosomes with recurrent events in chromosomes 9 and 20. No case-control differences were found in the frequency of events or the percentage of cells affected, thus indicating that most rearrangements found are not central to the development of bladder cancer. However, five out of six events tested were detected in both blood and bladder tissue from the same individual, indicating an early developmental origin. The high cellular frequency of the anomalies detected and their presence in normal adult individuals suggest that this type of mosaicism is a widespread phenomenon in the human genome. Somatic mosaicism should be considered in the expanding repertoire of inter- and intraindividual genetic variation, some of which may cause somatic human diseases but also contribute to modifying inherited disorders and/or late-onset multifactorial traits.
We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis.
The development of molecular pathologic components in epidemiologic studies offers opportunities to relate etiologic factors to specific tumor types, which in turn may allow the development of better overall risk prediction and provide clues about mechanisms that mediate risk factors. In addition, this research may help identify or validate tissue biomarkers related to prognosis and prediction of treatment responses. In this mini review, we highlight specific considerations related to the incorporation of pathology in epidemiologic studies, using breast cancer research as a model. Issues related to ensuring the representativeness of cases for which research tissue is available and understanding limitations resulting from variable procedures for tissue collection, fixation, and processing are discussed. The growing importance of molecular pathology in clinical medicine has led to increased emphasis on optimized tissue preparation, which should enhance this type of research. In addition, the availability of new technologies including tissue microarrays, image scanning, and automated analysis to achieve high-throughput standardized assessment of immunohistochemical markers, and potentially other assays, is enabling consistent scoring of a growing list of markers in large studies. Concurrently, methodologic research to extend the range of assays that can be done on fixed tissues is expanding possibilities for molecular pathologic studies in epidemiologic research.
BACKGROUND: Genomewide association studies have identified multiple genetic variants associated with breast cancer. The extent to which these variants add to existing risk-assessment models is unknown. METHODS: We used information on traditional risk factors and 10 common genetic variants associated with breast cancer in 5590 case subjects and 5998 control subjects, 50 to 79 years of age, from four U.S. cohort studies and one case-control study from Poland to fit models of the absolute risk of breast cancer. With the use of receiver-operating-characteristic curve analysis, we calculated the area under the curve (AUC) as a measure of discrimination. By definition, random classification of case and control subjects provides an AUC of 50%; perfect classification provides an AUC of 100%. We calculated the fraction of case subjects in quintiles of estimated absolute risk after the addition of genetic variants to the traditional risk model. RESULTS: The AUC for a risk model with age, study and entry year, and four traditional risk factors was 58.0%; with the addition of 10 genetic variants, the AUC was 61.8%. About half the case subjects (47.2%) were in the same quintile of risk as in a model without genetic variants; 32.5% were in a higher quintile, and 20.4% were in a lower quintile. CONCLUSIONS: The inclusion of newly discovered genetic factors modestly improved the performance of risk models for breast cancer. The level of predicted breast-cancer risk among most women changed little after the addition of currently available genetic information.
BACKGROUND: Epidemiological studies have consistently reported that active cigarette smoking is inversely associated with endometrial cancer risk. However, dose-response relationships with quantitative measures of active smoking or passive smoking remain less clear. METHODS: Data on lifetime active and passive smoking were collected for 551 endometrial cancer cases and 1925 controls in a population-based case-control study conducted during 2001-2003 in Poland (Warsaw and Łódz). RESULTS: Compared with never active smokers, active current (Odds Ratio (OR)=0.51, 95% Confidence Interval (CI): 0.39, 0.68) and former smokers (OR=0.60, 95% CI: 0.45, 0.80) were at a statistically significantly decreased risk. We did not observe statistically significant inverse dose-response relationships with increasing exposure with duration and cumulative measures. However, there was some indication that the highest category of number of years (OR=0.35, 95% CI: 0.23-0.55), intensity (OR=0.41, 95% CI: 0.24-0.69), and dose (OR=0.38, 95% CI: 0.24-0.60) of smoking among current smokers had the greatest inverse association compared to never smokers. Our data did not support the presence of an inverse association with passive smoking among never active smokers (OR=0.92; 95% CI: 0.65, 1.29). CONCLUSION: Our results support that long-term and heavy smoking among current smokers strongly influence endometrial cancer risk.
BACKGROUND: Estrogen plays a major role in endometrial carcinogenesis, suggesting that common variants of genes in the sex hormone metabolic pathway may be related to endometrial cancer risk. In support of this view, variants in CYP19A1 [cytochrome P450 (CYP), family 19, subfamily A, polypeptide 1] have been associated with both circulating estrogen levels and endometrial cancer risk. Associations with variants in other genes have been suggested, but findings have been inconsistent. METHODS: We examined 36 sex hormone-related genes using a tagging approach in a population-based case-control study of 417 endometrial cancer cases and 407 controls conducted in Poland. We evaluated common variation in these genes in relation to endometrial cancer risk using sequential haplotype scan, variable-sized sliding window and adaptive rank-truncated product (ARTP) methods. RESULTS: In our case-control study, the strongest association with endometrial cancer risk was for AR (androgen receptor; ARTP P = 0.006). Multilocus analyses also identified boundaries for a region of interest in AR and in CYP19A1 around a previously identified susceptibility loci. We did not find evidence for consistent associations between previously reported candidate single-nucleotide polymorphisms in this pathway and endometrial cancer risk. DISCUSSION: In summary, we identified regions in AR and CYP19A1 that are of interest for further evaluation in relation to endometrial cancer risk in future haplotype and subsequent fine mapping studies in larger study populations.
BACKGROUND: In 2001, the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) program established Residual Tissue Repositories (RTR) in the Hawaii, Iowa, and Los Angeles Tumor Registries to collect discarded tissue blocks from pathologic laboratories within their catchment areas. To validate the utility of the RTR for supplementing SEER's central database, we assessed human epidermal growth factor receptor-2 (HER2) and estrogen receptor expression (ER) in a demonstration project. MATERIALS: Using a prepared set of tissue microarrays (TMAs) residing in the Hawaii Tumor Registry (HTR), we performed standard immunohistochemistry. Breast cancers in the TMA were diagnosed in 1995, followed through 2006, and linked to SEER's main database. RESULTS: The TMA included 354 cases, representing 51% of 687 breast cancers in the HTR (1995). The HTR and TMA cases were similar with respect to patient demographics and tumor characteristics. Seventy-six percent (76%, 268 of 354) of TMA cases were HER2+ and/or ER+, i.e., 28 HER2+ER-, 12 HER2+ER+, and 228 HER2-ER+. There were 67 HER2-ER- cases and 19 were unclassified. Age distributions at diagnosis were bimodal with dominant early-onset modes for HER2+ER- tumors and dominant late-onset modes for HER2-ER+ breast cancers. Epidemiologic patterns for concordant HER2+ER+ (double-positive) and HER2-ER- (double-negative) were intermediate to discordant HER2+ER- and HER2-ER+. CONCLUSION: Results showed contrasting incidence patterns for HER2+ (HER2+ER-) and ER+ (HER2-ER+) breast cancers, diagnosed in 1995. Though sample sizes were small, this demonstration project validates the potential utility of the RTR for supplementing the SEER program.
The transforming growth factor-beta (TGF-beta) signalling pathway plays an important role in tumor development and progression. We aimed at analyzing whether 7 different common variants in genes coding for 2 key members of the TGF-beta signalling pathway (TGFB1 and TGFBR1) are associated with bladder cancer risk and prognosis. A total of 1,157 cases with urothelial cell carcinoma of the bladder and 1,157 matched controls where genotyped for 3 single nucleotide polymorphisms (SNPs) in TGFB1 (rs1982073, rs1800472, rs1800471) and an additional 3 SNPs and 1 indel polymorphism in TGFBR1 (rs868, rs928180, rs334358 and rs11466445, respectively). In the case-control study, we estimated odds ratios and 95% confidence intervals for each individual genetic variant using unconditional logistic regression adjusting for age, gender, study area and smoking status. Survival analysis was performed using the Kaplan-Meier method and Cox models. The endpoints of interest were tumor relapse, progression and death from bladder cancer. All the SNPs analyzed showed a similar distribution among cases and controls. The distribution of the TGFBR1*6A allele (rs11466445) was also similar among cases and controls, indicating no association with bladder cancer risk. Similarly, none of the haplotypes was significantly associated with bladder cancer risk. Among patients with muscle-invasive tumors, we found a significant association between TGFBR1-rs868 and disease-specific mortality with an allele dosage effect (p-trend=0.003). In conclusion, the genetic variants analyzed were not associated with an increased risk of bladder cancer. The association of TGFBR1-rs868 with outcome should be validated in independent patient series.
We have conducted a three-stage, comprehensive single nucleotide polymorphism (SNP)-tagging association study of ESR1 gene variants (SNPs) in more than 55,000 breast cancer cases and controls from studies within the Breast Cancer Association Consortium (BCAC). No large risks or highly significant associations were revealed. SNP rs3020314, tagging a region of ESR1 intron 4, is associated with an increase in breast cancer susceptibility with a dominant mode of action in European populations. Carriers of the c-allele have an odds ratio (OR) of 1.05 [95% Confidence Intervals (CI) 1.02-1.09] relative to t-allele homozygotes, P = 0.004. There is significant heterogeneity between studies, P = 0.002. The increased risk appears largely confined to oestrogen receptor-positive tumour risk. The region tagged by SNP rs3020314 contains sequence that is more highly conserved across mammalian species than the rest of intron 4, and it may subtly alter the ratio of two mRNA splice forms.
Improved understanding of the etiology of estrogen receptor-alpha (ERalpha)-negative and progesterone receptor (PR)-negative breast cancers may permit improved risk prediction. In vitro studies implicate DNA hypermethylation of the ERalpha and PR promoters in the pathogenesis of ERalpha-negative and PR-negative tumors, but results are not definitive. We evaluated 200 invasive breast cancers selected from a population-based case-control study. DNA extracted from fixed tumor tissue cores was tested using MethyLight to assess DNA methylation at four CpG islands: ESR1 promoters A and B; PGR promoters A and B; and a CpG shore, ESR1 promoter C. DNA methylation results were compared with levels of ERalpha and PR, tumor characteristics, and breast cancer risk factors. We observed mild to moderate DNA methylation levels in most tumors for ESR1 promoters A and B and PGR promoter B, and a few tumors showed mild methylation in PGR promoter A. In contrast, ESR1 promoter C showed a wide range of methylation and was weakly correlated with lower expression levels of ERalpha (beta = -0.26; P < 0.0001) and PR (beta = -0.25; P < 0.0001). The percentage of tumors with methylated PGR promoters A and B was significantly higher for tumors with low ERalpha (A, Fisher's test P = 0.0001; B, P = 0.033) and PR levels (A, P = 0.0006; B, P = 0.001). Our data suggest that the relationships between DNA methylation of ESR1 and PGR promoters and protein expression are weak and unlikely to represent a predominant mechanism of receptor silencing. In contrast to CpG islands, ESR1 promoter C showed a wider range of methylation levels and inverse associations with ERalpha and PR expression.
Genetic variation in SIPA1, signal-induced proliferation-associated gene 1, has been proposed to be associated with aggressive breast tumor characteristics related to metastasis and worse prognosis in humans and rodents. To test this hypothesis, we genotyped 3 single nucleotide polymorphisms (SNP) located at -3092 (A<G, rs931127), exon 3-135 (C>T, rs3741378), and exon 14 + 14 (C>T, rs746429), and examined them in relation to breast cancer risk and overall survival, stratified by tumor characteristics in 2 independent case-control studies conducted in Poland (1,995 cases, 2,296 controls) and in Britain (2,142 cases, 2,257 controls). Vital status (n = 396 deaths) was available for 911 Polish and 1,919 British breast cancer cases with an average follow-up time of 5.5 years. Overall, we found no significant associations between genetic variants of SIPA1 SNPs and breast cancer risk (per allele odds ratios, 95% confidence intervals (CI): rs931127-0.99, 0.93-1.06; rs3741378-1.03, 0.94-1.13; and, rs74642-0.98, 0.92-1.04). In both studies, SIPA1 polymorphisms were not related to overall mortality (per allele hazard ratios, 95% CI: 1.02, 0.88-1.17; 0.90, 0.72-1.11; 1.04, 0.90-1.21, respectively). Our results do not support a relationship between SIPA1 polymorphisms and breast cancer risk or subsequent survival.
Previous studies have suggested that minor alleles for ERCC4 rs744154, TNF rs361525, CASP10 rs13010627, PGR rs1042838, and BID rs8190315 may influence breast cancer risk, but the evidence is inconclusive due to their small sample size. These polymorphisms were genotyped in more than 30,000 breast cancer cases and 30,000 controls, primarily of European descent, from 30 studies in the Breast Cancer Association Consortium. We calculated odds ratios (OR) and 95% confidence intervals (95% CI) as a measure of association. We found that the minor alleles for these polymorphisms were not related to invasive breast cancer risk overall in women of European descent: ECCR4 per-allele OR (95% CI) = 0.99 (0.97-1.02), minor allele frequency = 27.5%; TNF 1.00 (0.95-1.06), 5.0%; CASP10 1.02 (0.98-1.07), 6.5%; PGR 1.02 (0.99-1.06), 15.3%; and BID 0.98 (0.86-1.12), 1.7%. However, we observed significant between-study heterogeneity for associations with risk for single-nucleotide polymorphisms (SNP) in CASP10, PGR, and BID. Estimates were imprecise for women of Asian and African descent due to small numbers and lower minor allele frequencies (with the exception of BID SNP). The ORs for each copy of the minor allele were not significantly different by estrogen or progesterone receptor status, nor were any significant interactions found between the polymorphisms and age or family history of breast cancer. In conclusion, our data provide persuasive evidence against an overall association between invasive breast cancer risk and ERCC4 rs744154, TNF rs361525, CASP10 rs13010627, PGR rs1042838, and BID rs8190315 genotypes among women of European descent.
CYP1B1 is a key enzyme involved in estrogen metabolism and may play an important role in the development and progression of breast cancer. In a population-based case-control study, we examined eight CYP1B1 haplotype-tagging single nucleotide polymorphisms in relation to invasive breast cancer risk. Analyses were based on 1,655 cases and 1,470 controls; all women were Caucasian. Among the individual single nucleotide polymorphisms, one (rs9341266) was associated with increased risk of breast cancer (P(trend) = 0.021), although the association was no longer significant after adjusting for multiple tests. A marginally significant haplotype effect was identified (P(global) = 0.015), with significant associations identified for 2 uncommon haplotypes comprising 4% of the controls. Results suggest that genetic variation in CYP1B1 has at most a minor influence on breast cancer susceptibility among Caucasian women.
Genome-wide association studies (GWAS) have led to a rapid increase in available data on common genetic variants and phenotypes and numerous discoveries of new loci associated with susceptibility to common complex diseases. Integrating the evidence from GWAS and candidate gene studies depends on concerted efforts in data production, online publication, database development, and continuously updated data synthesis. Here the authors summarize current experience and challenges on these fronts, which were discussed at a 2008 multidisciplinary workshop sponsored by the Human Genome Epidemiology Network. Comprehensive field synopses that integrate many reported gene-disease associations have been systematically developed for several fields, including Alzheimer's disease, schizophrenia, bladder cancer, coronary heart disease, preterm birth, and DNA repair genes in various cancers. The authors summarize insights from these field synopses and discuss remaining unresolved issues -- especially in the light of evidence from GWAS, for which they summarize empirical P-value and effect-size data on 223 discovered associations for binary outcomes (142 with P < 10(-7)). They also present a vision of collaboration that builds reliable cumulative evidence for genetic associations with common complex diseases and a transparent, distributed, authoritative knowledge base on genetic variation and human health. As a next step in the evolution of Human Genome Epidemiology reviews, the authors invite investigators to submit field synopses for possible publication in the American Journal of Epidemiology.
The p53 protein is critical for multiple cellular functions including cell growth and DNA repair. We assessed whether polymorphisms in the region encoding TP53 were associated with risk of invasive ovarian cancer. The study population includes a total of 5,206 invasive ovarian cancer cases (2,829 of which were serous) and 8,790 controls from 13 case-control or nested case-control studies participating in the Ovarian Cancer Association Consortium (OCAC). Three of the studies performed independent discovery investigations involving genotyping of up to 23 single nucleotide polymorphisms (SNP) in the TP53 region. Significant findings from this discovery phase were followed up for replication in the other OCAC studies. Mixed effects logistic regression was used to generate posterior median per allele odds ratios (OR), 95% probability intervals (PI), and Bayes factors (BF) for genotype associations. Five SNPs showed significant associations with risk in one or more of the discovery investigations and were followed up by OCAC. Mixed effects analysis confirmed associations with serous invasive cancers for two correlated (r(2) = 0.62) SNPs: rs2287498 (median per allele OR, 1.30; 95% PI, 1.07-1.57) and rs12951053 (median per allele OR, 1.19; 95% PI, 1.01-1.38). Analyses of other histologic subtypes suggested similar associations with endometrioid but not with mucinous or clear cell cancers. This large study provides statistical evidence for a small increase in risk of ovarian cancer associated with common variants in the TP53 region.
Common variants in CYP19A1 (the A alleles of rs749292 and rs727479) have been associated with a 10% to 20% increase in circulating estrogen levels in postmenopausal women. We hypothesized that the presence of one or both A alleles in these single nucleotide polymorphisms (SNP) is associated with increased endometrial cancer risk. We tested this hypothesis in a large pooled analysis of 4,998 endometrial cancer cases and 8,285 controls from 10 studies in the Epidemiology of Endometrial Cancer Consortium. The majority of women (>66%) were whites, with smaller proportions of other races and ethnic groups (blacks, Asians, and Latinas) also included in this pooled analysis. Unconditional logistic regression was used to model the association between SNPs/haplotypes and endometrial cancer risk. Carrying the A allele of either of these SNPs was associated with an increased risk of endometrial cancer, with pooled odds ratios per allele of 1.14, 95% confidence interval of 1.09-1.21, and P = 7.1 x 10(-7) for rs749292, and odds ratio per allele of 1.08, 95% confidence interval of 1.02-1.14, and P = 0.009 for rs727479. For rs749292, these associations were generally stronger among women age >or=55 years. For both SNPs, risk increased with increasing body mass index, and for rs727479, this pattern seemed stronger among women age >or=55 years (P interaction = 0.007). The combination of A alleles in the two SNPs, either by direct count or by haplotype analysis, did not increase risk above that observed for the individual SNPs. Our study provides evidence that CYP19A1 genetic variation influences susceptibility to endometrial cancer, particularly among older and obese women.
Because both ovarian and breast cancer are hormone-related and are known to have some predisposition genes in common, we evaluated 11 of the most significant hits (six with confirmed associations with breast cancer) from the breast cancer genome-wide association study for association with invasive ovarian cancer. Eleven SNPs were initially genotyped in 2927 invasive ovarian cancer cases and 4143 controls from six ovarian cancer case-control studies. Genotype frequencies in cases and controls were compared using a likelihood ratio test in a logistic regression model stratified by study. Initially, three SNPs (rs2107425 in MRPL23, rs7313833 in PTHLH, rs3803662 in TNRC9) were weakly associated with ovarian cancer risk and one SNP (rs4954956 in NXPH2) was associated with serous ovarian cancer in non-Hispanic white subjects (P-trend < 0.1). These four SNPs were then genotyped in an additional 4060 cases and 6308 controls from eight independent studies. Only rs4954956 was significantly associated with ovarian cancer risk both in the replication study and in combined analyses. This association was stronger for the serous histological subtype [per minor allele odds ratio (OR) 1.07 95% CI 1.01-1.13, P-trend = 0.02 for all types of ovarian cancer and OR 1.14 95% CI 1.07-1.22, P-trend = 0.00017 for serous ovarian cancer]. In conclusion, we found that rs4954956 was associated with increased ovarian cancer risk, particularly for serous ovarian cancer. However, none of the six confirmed breast cancer susceptibility variants we tested was associated with ovarian cancer risk. Further work will be needed to identify the causal variant associated with rs4954956 or elucidate its function.
Epithelial ovarian cancer has a major heritable component, but the known susceptibility genes explain less than half the excess familial risk. We performed a genome-wide association study (GWAS) to identify common ovarian cancer susceptibility alleles. We evaluated 507,094 SNPs genotyped in 1,817 cases and 2,353 controls from the UK and approximately 2 million imputed SNPs. We genotyped the 22,790 top ranked SNPs in 4,274 cases and 4,809 controls of European ancestry from Europe, USA and Australia. We identified 12 SNPs at 9p22 associated with disease risk (P < 10(-8)). The most significant SNP (rs3814113; P = 2.5 x 10(-17)) was genotyped in a further 2,670 ovarian cancer cases and 4,668 controls, confirming its association (combined data odds ratio (OR) = 0.82, 95% confidence interval (CI) 0.79-0.86, P(trend) = 5.1 x 10(-19)). The association differs by histological subtype, being strongest for serous ovarian cancers (OR 0.77, 95% CI 0.73-0.81, P(trend) = 4.1 x 10(-21)).
Tobacco smoking is the most important and well-established bladder cancer risk factor and a rich source of chemical carcinogens and reactive oxygen species that can induce damage to DNA in urothelial cells. Therefore, common variation in DNA repair genes might modify bladder cancer risk. In this study, we present results from meta-analyses and pooled analyses conducted as part of the International Consortium of Bladder Cancer. We included data on 10 single nucleotide polymorphisms corresponding to seven DNA repair genes from 13 studies. Pooled analyses and meta-analyses included 5,282 cases and 5,954 controls of non-Latino white origin. We found evidence for weak but consistent associations with ERCC2 D312N [rs1799793; per-allele odds ratio (OR), 1.10; 95% confidence interval (95% CI), 1.01-1.19; P = 0.021], NBN E185Q (rs1805794; per-allele OR, 1.09; 95% CI, 1.01-1.18; P = 0.028), and XPC A499V (rs2228000; per-allele OR, 1.10; 95% CI, 1.00-1.21; P = 0.044). The association with NBN E185Q was limited to ever smokers (interaction P = 0.002) and was strongest for the highest levels of smoking dose and smoking duration. Overall, our study provides the strongest evidence to date for a role of common variants in DNA repair genes in bladder carcinogenesis.
We conducted a three-stage genome-wide association study (GWAS) of breast cancer in 9,770 cases and 10,799 controls in the Cancer Genetic Markers of Susceptibility (CGEMS) initiative. In stage 1, we genotyped 528,173 SNPs in 1,145 cases of invasive breast cancer and 1,142 controls. In stage 2, we analyzed 24,909 top SNPs in 4,547 cases and 4,434 controls. In stage 3, we investigated 21 loci in 4,078 cases and 5,223 controls. Two new loci achieved genome-wide significance. A pericentromeric SNP on chromosome 1p11.2 (rs11249433; P = 6.74 x 10(-10) adjusted genotype test, 2 degrees of freedom) resides in a large linkage disequilibrium block neighboring NOTCH2 and FCGR1B; this signal was stronger for estrogen-receptor-positive tumors. A second SNP on chromosome 14q24.1 (rs999737; P = 1.74 x 10(-7)) localizes to RAD51L1, a gene in the homologous recombination DNA repair pathway. We also confirmed associations with loci on chromosomes 2q35, 5p12, 5q11.2, 8q24, 10q26 and 16q12.1.
OBJECTIVE: We evaluated the bladder cancer risk associated with coffee consumption in a case-control study in Spain and examined the gene-environment interactions for genetic variants of caffeine-metabolizing enzymes. METHODS: The analyses included 1,136 incident cases with urothelial carcinoma of the urinary bladder and 1,138 controls. Odds ratios (OR) and 95% confidence intervals (CI) were adjusted for area, age, gender, amount of cigarette smoking, and years since quitting among former smokers. RESULTS: The OR (95% CI) for ever consumed coffee was 1.25 (0.95-1.64). For consumers of 1, 2, 3, and 4 or more cups/day relative to never drinkers, OR were, respectively, 1.24 (0.92-1.66), 1.11 (95% CI 0.82-1.51), 1.57 (1.13-2.19), and 1.27 (0.88-1.81). Coffee consumption was higher in smokers compared to never smokers. The OR for drinking at least 4 cups/day was 1.13 (0.61-2.09) in current smokers, 1.57 (0.86-2.90) in former smokers, and 1.23 (0.55-2.76) in never smokers. Gene-coffee interactions evaluated in NAT2, CYP1A2, and CYP2E1-02 and CYP1A1 were not identified after adjusting for multiple testing. CONCLUSION: We observed a modest increased bladder cancer risk among coffee drinkers that may, in part, be explained by residual confounding by smoking. The findings from the gene-coffee interactions need replication in further studies.
Genetic variation in the androgen receptor (AR) gene may be associated with endometrial cancer risk based on the role of AR in regulating androgen levels. However, endometrial cancer studies reported inconsistent associations for a CAG repeat polymorphism in exon 1. Only one of these studies measured haplotype-tagging single nucleotide polymorphisms (htSNP) in AR and found statistically nonsignificant, decreased associations with endometrial cancer risk. In a population-based case-control study of 497 cases and 1,024 controls, we examined the CAG repeat polymorphism and six htSNPs (rs962458, rs6152, rs1204038, rs2361634, rs1337080, and rs1337082), which cover an estimated 80% of the known common variation in AR among Caucasian populations. CAG repeat length was not significantly associated with endometrial cancer [odds ratio per unit increase in the average number of repeats, 1.02 (95% confidence interval, 0.97-1.08); P(trend) = 0.29]. Minor alleles in three correlated htSNPs (rs6152, rs1204038, and rs1337082; r(2) >0.6) were associated with increased risk for endometrial cancer. The strongest association was observed for rs6152, with the odds ratios (95% confidence interval) being 1.13 (0.89-1.44) for heterozygous and 2.40 (1.28-4.51) for homozygous minor genotypes (P(trend) = 0.02) compared with homozygous major allele genotype. However, these associations were not statistically significant after permutation adjustment for multiple comparisons (P(trend) > 0.09). Haplotype analyses did not reveal any additional associations with endometrial cancer. Results from our study, taken together with previously published studies, provide little evidence of a consistent association between common genetic variation in AR and endometrial cancer risk.
Increases in the frequency of micronuclei (MN) in exposed cells can be used as a measure of genotoxicity. Hair dyes contain chemicals that are eliminated by urine and could be genotoxic to urothelial cells. To address this question, we evaluated whether hair dye use is associated with an increase in the frequency of MN in urothelial cells, and whether this association is modified by NAT1 (N-acetyltransferase 1), NAT2 (N-acetyltransferase 2) and GSTM1 (glutathione-S-transferase M1) genotypes. We included 92 women participating as controls in a bladder cancer case-control study in Spain. Of those, 72 had adequate number of cells to be included in the MN analysis. There were no significant differences in the mean MN frequency in women using hair dyes in the last month (9.88 MN/1000 cells), in comparison with the MN in unexposed women (9.50 MN/1000 cells). No statistically significant differences in MN frequency were observed by type of hair dye or color of the hair dye. Comparison of subjects in the highest quartile of MN frequency (> or = 12 MN/1000 cells) and those in the lowest quartile (< or = 4 MN/1000 cells) suggested an association between hair dye use and elevated MN frequency (OR 14.2 (95% CI 0.81-247.8; P=0.069)). None of the polymorphisms examined significantly modified association between hair dye use and frequency of MN. Findings of an increased frequency of MN in urothelial cells of hair dye users suggest a possible genotoxic effect of hair dye compounds and need confirmation in larger studies.
BACKGROUND: The lack of validated methods for measuring sex steroid hormones in breast tissue has limited our knowledge of their role in the development of breast cancer. We explored the feasibility of measuring hormones in breast adipocytes for epidemiologic and clinical studies by refining an existing assay procedure and assessing the reliability of hormone measurements using the modified assay. This report presents the reproducibility of measurements of androstenedione (A), testosterone (T), estrone (E(1)), and estradiol (E(2)), using breast adipose tissue samples obtained from women undergoing surgical resection for a variety of pathologic conditions. METHODS: Breast adipose tissues were obtained from 20 women. Measurements of the steroid hormones were carried out by harvesting oil from adipocytes following enzymatic digestion of the adipose tissue, extracting and chromatographing the steroids, and quantifying them by RIA. The study was conducted in three phases: first, samples from five women were used to assess the assay procedure; following this, tissues from an additional five women were assayed repeatedly to determine reproducibility of the hormone measurements. Finally, using samples from 10 women undergoing surgical resection of a breast tumor, we evaluated hormone concentrations in samples distal and proximal to the tumor. The assay coefficient of variation and intraclass correlation coefficient were used to assess hormone reproducibility. RESULTS: The within-batch coefficients of variation ranged from 5% to 17%, and between-batch estimates were between 2% and 10%, suggesting that E(1), E(2), A, and T can be reliably measured in breast adipocytes. Among samples obtained from women undergoing surgical resection of a breast tumor, hormone levels did not differ between adipose tissue fragments that were distal or proximal to the tumor, with the possible exception of E(1) in which levels were 10% higher in distal fragments. CONCLUSION: These data support the feasibility of measuring steroid hormone concentrations in breast adipocytes in epidemiologic studies. Future investigations that include the measurement of hormones in the breast microenvironment may have value in understanding breast carcinogenesis, developing prevention strategies, and assessing hormonal treatments.
Aromatic amines (AAs) and polycyclic aromatic hydrocarbons (PAHs) are carcinogens present in tobacco smoke and functional polymorphisms in NAT2 and GSTM1 metabolizing genes are associated with increased bladder cancer risk. We evaluated whether genetic variation in other candidate metabolizing genes are also associated with risk. Candidates included genes that control the transcription of metabolizing genes [aryl hydrocarbon receptor (AHR), AHRR and aryl hydrocarbon nuclear translocator (ARNT)] and genes that activate/detoxify AA or PAH (AKR1C3, CYP1A1, CYP1A2, CYP1B1, CYP3A4, EPHX1, EPHX2, NQO1, MPO, UGT1A4, SULT1A1 and SULT1A2). Using genotype data from 1150 cases of urothelial carcinomas and 1149 controls from the Spanish Bladder Cancer Study, we estimated odds ratios (ORs) and 95% confidence intervals (CIs) adjusting for age, gender, region and smoking status. Based on a test for trend, we observed 10 non-redundant single-nucleotide polymorphisms (SNPs) in five genes (AKR1C3, ARNT, CYP1A1, CYP1B1 and SULT1A2) significantly associated with bladder cancer risk. We observed an inverse association with risk for the AKR1C3 promoter SNP rs1937845 [OR (95% CI) for heterozygote and homozygote variant compared with common homozygote genotype were 0.86 (0.70-1.06) and 0.74 (0.57-0.96), respectively; P for trend = 0.02]. Interestingly, genetic variation in this region has been associated with lung, non-Hodgkin lymphoma and prostate cancer risk. Analysis of additional SNPs to capture most (approximately 90%) of common genetic variation in AKR1C3 and haplotype walking analyses based on all AKR1C3 SNPs (n = 25) suggest two separate regions associated with bladder cancer risk. These results indicate that genetic variation in carcinogen-metabolizing genes, particularly AKR1C3, could be associated with bladder cancer risk.
Breast cancer is a heterogeneous disease, and risk factors could be differentially associated with the development of distinct tumor subtypes that manifest different biological behavior and progression. In support of this view, there is growing evidence that known breast cancer risk factors vary by hormone receptor status and perhaps other pathologic characteristics of disease. Recent work from large consortial studies has led to the discovery of novel breast cancer susceptibility loci in genic (CASP8, FGFR2, TNRC9, MAP3K1, LSP1) and nongenic regions (8q24, 2q35, 5p12) of the genome, and to the finding of substantial heterogeneity by tumor characteristics. In particular, susceptibility loci in FGFR2, TNRC9, 8q24, 2q35, and 5p12 have stronger associations for estrogen receptor-positive (ER+) disease than estrogen receptor-negative (ER -) disease. These findings suggest that common genetic variants can influence the pathologic subtype of breast cancer, and provide further support for the hypothesis that ER+ and ER(-) disease result from different etiologic pathways. Current studies had limited power to detect susceptibility loci for less common tumor subtypes, such as ER(-) disease including triple-negative and basal-like tumors. Ongoing work targeting uncommon subtypes is likely to identify additional tumor-specific susceptibility loci in the near future. Characterization of etiologic heterogeneity of breast cancer may lead to improvements in the understanding of the biological mechanisms for breast cancer, and ultimately result in improvements in prevention, early detection, and treatment.
A three-stage genome-wide association study recently identified single nucleotide polymorphisms (SNPs) in five loci (fibroblast growth receptor 2 (FGFR2), trinucleotide repeat containing 9 (TNRC9), mitogen-activated protein kinase 3 K1 (MAP3K1), 8q24, and lymphocyte-specific protein 1 (LSP1)) associated with breast cancer risk. We investigated whether the associations between these SNPs and breast cancer risk varied by clinically important tumor characteristics in up to 23,039 invasive breast cancer cases and 26,273 controls from 20 studies. We also evaluated their influence on overall survival in 13,527 cases from 13 studies. All participants were of European or Asian origin. rs2981582 in FGFR2 was more strongly related to ER-positive (per-allele OR (95%CI) = 1.31 (1.27-1.36)) than ER-negative (1.08 (1.03-1.14)) disease (P for heterogeneity = 10(-13)). This SNP was also more strongly related to PR-positive, low grade and node positive tumors (P = 10(-5), 10(-8), 0.013, respectively). The association for rs13281615 in 8q24 was stronger for ER-positive, PR-positive, and low grade tumors (P = 0.001, 0.011 and 10(-4), respectively). The differences in the associations between SNPs in FGFR2 and 8q24 and risk by ER and grade remained significant after permutation adjustment for multiple comparisons and after adjustment for other tumor characteristics. Three SNPs (rs2981582, rs3803662, and rs889312) showed weak but significant associations with ER-negative disease, the strongest association being for rs3803662 in TNRC9 (1.14 (1.09-1.21)). rs13281615 in 8q24 was associated with an improvement in survival after diagnosis (per-allele HR = 0.90 (0.83-0.97). The association was attenuated and non-significant after adjusting for known prognostic factors. Our findings show that common genetic variants influence the pathological subtype of breast cancer and provide further support for the hypothesis that ER-positive and ER-negative disease are biologically distinct. Understanding the etiologic heterogeneity of breast cancer may ultimately result in improvements in prevention, early detection, and treatment.
HSD17B1 is an important candidate gene in breast cancer via its role in converting estrone to estradiol. A nonsynonymous G-to-A transition (rs605059) and an intronic C-to-A (rs676387) single-nucleotide polymorphism, which captured most common variation in HSD17B1, were evaluated in several breast cancer studies with inconclusive results. We followed up these findings in the Polish Breast Cancer Study (1,995 cases; 2,296 controls) and the British Studies of Epidemiology and Risk Factors in Cancer Heredity study (4,470 cases; 4,560 controls). Meta-analyses of published data and our own were also conducted among Caucasian women. Consistent with previous reports, we found little to no association with overall risk for heterozygotes and minor allele homozygotes compared with major allele homozygotes for rs605059 [summary odds ratios (95% confidence intervals), 0.93 (0.87-0.99) for GA and 0.96 (0.85-1.08), based on 11,762 cases and 14,329 controls from 10 studies] and for rs676387 [summary odds ratios (95% confidence intervals), 1.04 (0.97-1.12) and 1.12 (0.99-1.27), based on analyses of 11,074 cases and 13,605 controls from 8 studies]. Data from the Polish [n=586 estrogen receptor-negative (ER-) cases] and British (n=407) studies did not support the previous findings that ER- tumors were inversely associated with rs676387 AA genotype and positively associated with rs605059 GG genotype, based on subanalyses in 5 prospective cohorts with 354 ER- cases. In conclusion, it is unlikely that common genetic variation in HSD17B1 is associated with a moderate modulation in breast cancer risk overall; however, we cannot exclude the possibility of a very weak effect. Associations between HSD17B1 genotypes and risk for ER- breast cancer were inconsistent across studies and should be studied further.
Genetic variation in CYP17 is suspected to be related to endometrial cancer risk based on its role in the regulation of steroid and non-steroid hormone biosynthesis. Reported associations between CYP17 and higher levels of estradiol in some studies suggest that the C allele of a T-to-C single nucleotide polymorphism (SNP) in the 5'UTR of CYP17 (rs743572) may be associated with an increased risk of hormone-related cancers. However, five relatively small epidemiologic studies of endometrial cancer have reported that women with the rs743572 C allele have a decreased risk of endometrial cancer. To examine this association, we genotyped rs743572 and eight other haplotype-tagging SNPs (htSNPs), which are estimated to capture >80% of the variation in CYP17 in a population-based study of 497 endometrial cancer cases and 1,024 controls in Poland. Significant associations were not found for rs743572 (per C allele: OR = 1.12, 95%CI 0.96-1.30; P-trend = 0.15), for individual htSNPs, or for extended haplotypes (global P-value = 0.60). When we pooled data from previously published studies with our own (a total of 1,004 endometrial cases and 1,907 controls), we observed significant study heterogeneity in summary estimates of the association between rs743572 and endometrial cancer, as well as evidence of publication bias. In conclusion, our data are not consistent with a decreased endometrial cancer risk associated with rs743572, as previously reported, or with other haplotype-tagging polymorphisms. Further evaluation in consortia is necessary to confirm potential weak associations between common variation in CYP17 and endometrial cancer risk and to address the concern of publication bias.
The inconsistent associations between fruit and vegetable intake and breast cancer risk may be due to heterogeneity of associations by estrogen (ER) and progesterone receptor (PR) status of the tumors. We evaluated this hypothesis in a large (2,386 cases and 2,503 controls) population-based case-control study in Poland, conducted between 2000 and 2003. We observed significant associations between reduced overall risk of breast cancer and increasing levels of total fruit intake (odds ratio (OR) for highest versus lowest quartile = 0.76, 95%CI = 0.63-0.91; p-trend = 0.01), but not for total vegetable intake (1.13 (0.93-1.37), p-trend = 0.25), after controlling for age, energy intake and known risk factors for breast cancer. The inverse association with total fruit intake was stronger for risk of ER+ (0.69 (0.54-0.88), p-trend = 0.01) than ER- tumors (0.89 (0.67-1.19), p-trend = 0.57) (p-heterogeneity = 0.02). In conclusion, this study suggests that fruit intake might have differential associations for breast tumor subtypes defined by ER status.
In a multicenter case-control study of renal cell carcinoma (RCC) conducted in central and eastern Europe, we reported a strong inverse association with high vegetable intake and RCC risk. The odds ratio (OR) for high compared to the lowest tertile of vegetable intake was OR = 0.67; (95% confidence interval (CI): 0.53-0.83; p-trend < 0.001). We hypothesized that variation in key folate metabolism genes may modify this association. Common variation in 5 folate metabolism genes (CBS: Ex9+33C > T (rs234706), Ex13 +41C > T (rs1801181), Ex18 -391 G > A (rs12613); MTHFR: A222V Ex5+79C > T (rs1801133), Ex8-62A > C (rs1801131); MTR: Ex26 20A > G (rs1805087), MTRR: Ex5+136 T > C (rs161870), and TYMS:IVS2-405 C > T (rs502396), Ex8+157 C > T (rs699517), Ex8+227 A > G (rs2790)) were analyzed among 1,097 RCC cases and 1,555 controls genotyped in this study. Having at least 1 variant T allele of MTHFR A222V was associated with higher RCC risk compared to those with 2 common (CC) alleles (OR = 1.44; 95% CI: 1.17-1.77; p = 0.001). After stratification by tertile of vegetable intake, the higher risk associated with the variant genotype was only observed in the low and medium tertiles (p-trend = 0.001), but not among those in the highest tertile (p-interaction = 0.22). The association remained robust after calculation of the false discovery rate (FDR = 0.05). Of the 3 TYMS SNPs examined, only the TYMS IVS2 -405 C (rs502396) variant was associated with a significantly lower risk compared to the common genotype (OR = 0.73; 95% CI: 0.57-0.93). Vegetable intake modified the association between all 3 TYMS SNPs and RCC risk (p-interaction < 0.04 for all). In summary, these findings suggest that common variation in MTHFR and TYMS genes may be associated with RCC risk, particularly when vegetable intake is low.
BACKGROUND: DNA hypomethylation has been suggested to cause genomic instability and increase cancer risk. We aimed to test the hypothesis that DNA hypomethylation is associated with increased risk of bladder cancer. METHODS: We measured cytosine methylation (5-mC) content in genomic DNA from blood cells from patients with bladder cancer enrolled in a large case-control study in Spain between Jan 1, 1998, and Dec 31, 2001. Cases were men and women with newly diagnosed and histologically confirmed urothelial carcinoma of the bladder. Controls were selected from patients admitted to the same hospital for diseases or conditions unrelated to smoking or other known risk factors for bladder cancer. Controls were individually matched to cases on age (within 5 years), sex, race, and area of hospital referral. 5-mC content was measured in leucocyte DNA by use of a combination of high-performance capillary electrophoresis, Hpa II digestion, and densitometry. Data on demographics, 34 polymorphisms in nine folate metabolism genes, and nutritional intake of six B vitamins (including folate), alcohol, and smoking were assessed as potential confounders. Relative 5-mC content was expressed as a percentage (%5-mC) with respect to the total cytosine content (the sum of methylated and non-methylated cytosines). The primary endpoint was median %5-mC DNA content. FINDINGS: %5-mC was measured in leucocyte DNA from 775 cases and 397 controls. Median %5-mC DNA was significantly lower in cases (3.03% [IQR 2.17-3.56]) than in controls (3.19% [2.46-3.68], p=0.0002). All participants were subsequently categorised into quartiles by %5-mC content in controls. When the highest quartile of %5-mC content was used as the reference category (Q4), the following adjusted odds ratios (OR) and 95% CI were recorded for decreasing methylation quartiles: OR(Q3) 2.05 (95% CI 1.37-3.06); OR(Q2) 1.62 (1.07-2.44); and OR(Q1) 2.67 (1.77-4.03), p for trend <0.0001. The lowest cancer risk was noted in never smokers in the highest methylation quartile (never smokers in Q4). By comparison with never smokers in the highest quartile, current smokers in the lowest methylation quartile had the highest risk of bladder cancer (Q1: OR 25.51 [9.61-67.76], p for interaction 0.06). In analyses stratified by smoking, hypomethylation was a strong risk factor in never smokers (OR 6.39 [2.37-17.22]). Amount of methylation in controls were not associated with baseline characteristics, micronutrients, or selected genotypes in folate metabolism pathways. INTERPRETATION: For the first time, to our knowledge, we have shown in a large case-control study that leucocyte DNA hypomethylation is associated with increased risk of developing bladder cancer, and this association is independent of smoking and the other assessed risk factors. Amount of global methylation in genomic DNA could provide a useful biomarker of susceptibility to certain cancer types and further research is warranted.
INTRODUCTION: Various perinatal factors, including birth weight, birth order, maternal age, gestational age, twin status, and parental smoking, have been postulated to affect breast cancer risk in daughters by altering the hormonal environment of the developing fetal mammary glands. Despite ample biologic plausibility, epidemiologic studies to date have yielded conflicting results. We investigated the associations between perinatal factors and subsequent breast cancer risk through meta-analyses. METHODS: We reviewed breast cancer studies published from January 1966 to February 2007 that included data on birth weight, birth order, maternal age, gestational age, twin status, and maternal or paternal smoking. Meta-analyses using random effect models were employed to summarize the results. RESULTS: We found that heavier birth weights were associated with increased breast cancer risk, with studies involving five categories of birth weight identifying odds ratios (ORs) of 1.24 (95% confidence interval [CI] 1.04 to 1.48) for 4,000 g or more and 1.15 (95% CI 1.04 to 1.26) for 3,500 g to 3,999 g, relative to a birth weight of 2,500 to 2,599 g. These studies provided no support for a J-shaped relationship of birthweight to risk. Support for an association with birthweight was also derived from studies based on three birth weight categories (OR 1.15 [95% CI 1.01 to 1.31] for > or =4,000 g relative to <3,000 g) and two birth weight categories (OR 1.09 [95% CI 1.02 to 1.18] for > or =3,000 g relative to <3,000 g). Women born to older mothers and twins were also at some increased risk, but the results were heterogeneous across studies and publication years. Birth order, prematurity, and maternal smoking were unrelated to breast cancer risk. CONCLUSION: Our findings provide some support for the hypothesis that in utero exposures reflective of higher endogenous hormone levels could affect risk for development of breast cancer in adulthood.
There is evidence that progesterone plays a role in the aetiology of invasive epithelial ovarian cancer. Therefore, genes involved in pathways that regulate progesterone may be candidates for susceptibility to this disease. Previous studies have suggested that genetic variants in the progesterone receptor gene (PGR) may be associated with ovarian cancer risk, although results have been inconsistent. We have established an international consortium to pool resources and data from many ovarian cancer case-control studies in an effort to identify variants that influence risk. In this study, three PGR single nucleotide polymorphisms (SNPs), for which previous data have suggested they affect ovarian cancer risk, were examined. These were +331 C/T (rs10895068), PROGINS (rs1042838), and a 3' variant (rs608995). A total of 4788 ovarian cancer cases and 7614 controls from 12 case-control studies were included in this analysis. Unconditional logistic regression was used to model the association between each SNP and ovarian cancer risk and two-sided P-values are reported. Overall, risk of ovarian cancer was not associated with any of the three variants studied. However, in histopathological subtype analyses, we found a statistically significant association between risk of endometrioid ovarian cancer and the PROGINS allele (n=651, OR=1.17, 95% CI=1.01-1.36, P=0.036). We also observed borderline evidence of an association between risk of endometrioid ovarian cancer and the +331C/T variant (n=725 cases; OR=0.80, 95% CI 0.62-1.04, P=0.100). These data suggest that while these three variants in the PGR are not associated with ovarian cancer overall, the PROGINS variant may play a modest role in risk of endometrioid ovarian cancer.
BACKGROUND: Epidemiologic studies have shown that breast cancer risk is reduced 30% to 40% in highly physically active compared with inactive women. However, the effects of moderate activities, timing of activities, and intervening effects of other risk factors remain less clear. METHODS: We analyzed data on physical activity patterns in 2176 incident breast cancer cases and 2326 controls in a population-based breast cancer case-control study in Poland conducted in 2000-2003. Using unconditional logistic regression analyses, we calculated odds ratios (ORs) and 95% confidence intervals (CIs) associated with physical activity levels (measured by average metabolic equivalents of energy expenditure hours per week), controlling for potential confounders. RESULTS: Total adult lifetime activity reduced risk of breast cancer, with individuals in the highest quartile having an OR of 0.80 (CI = 0.67-0.96) compared with the lowest quartile. Reduced risks were most consistent for the highest quartiles of moderate-to-vigorous activities: moderate/vigorous recreational activities (OR = 0.74; CI = 0.62-0.89), outdoor activities (0.81; 0.68-0.97), heavy physical work (0.60; 0.42-0.87), and combined high intensity (metabolic equivalent >6.0) activities (0.75; 0.63-0.90). These relations were not modified by body mass index, menopausal status, or family history of breast cancer. Reductions in risk with moderate/vigorous recreational activities were stronger for larger tumors and those with nodal involvement. Women who increased their recreational activity in their 50s had significantly reduced risk, with those in the highest tertile of change being at a 27% lower risk. CONCLUSIONS: Leisure-time moderate-to-vigorous activities reduce breast cancer risk irrespective of underlying host characteristics.
The Ovarian Cancer Association Consortium selected 7 candidate single nucleotide polymorphisms (SNPs), for which there is evidence from previous studies of an association with variation in ovarian cancer or breast cancer risks. The SNPs selected for analysis were F31I (rs2273535) in AURKA, N372H (rs144848) in BRCA2, rs2854344 in intron 17 of RB1, rs2811712 5' flanking CDKN2A, rs523349 in the 3' UTR of SRD5A2, D302H (rs1045485) in CASP8 and L10P (rs1982073) in TGFB1. Fourteen studies genotyped 4,624 invasive epithelial ovarian cancer cases and 8,113 controls of white non-Hispanic origin. A marginally significant association was found for RB1 when all studies were included [ordinal odds ratio (OR) 0.88 (95% confidence interval (CI) 0.79-1.00) p = 0.041 and dominant OR 0.87 (95% CI 0.76-0.98) p = 0.025]; when the studies that originally suggested an association were excluded, the result was suggestive although no longer statistically significant (ordinal OR 0.92, 95% CI 0.79-1.06). This SNP has also been shown to have an association with decreased risk in breast cancer. There was a suggestion of an association for AURKA, when one study that caused significant study heterogeneity was excluded [ordinal OR 1.10 (95% CI 1.01-1.20) p = 0.027; dominant OR 1.12 (95% CI 1.01-1.24) p = 0.03]. The other 5 SNPs in BRCA2, CDKN2A, SRD5A2, CASP8 and TGFB1 showed no association with ovarian cancer risk; given the large sample size, these results can also be considered to be informative. These null results for SNPs identified from relatively large initial studies shows the importance of replicating associations by a consortium approach.
Experimental studies suggest that increased urination frequency may reduce bladder cancer risk if carcinogens are present in the urine. Only 2 small studies of the effect of increased urination frequency on bladder cancer risk in humans have been conducted with conflicting results. Our purpose was to evaluate the effect of urination frequency on risk of bladder cancer in a large, multicenter case-control study. We analyzed data based on interviews conducted with 884 patients with newly diagnosed, bladder cancer and 996 controls from 1998 to 2001 in Spain. We observed a consistent, inverse trend in risk with increasing nighttime voiding frequency in both men (p = 0.0003) and women (p = 0.07); voiding at least 2 times per night was associated with a significant, 40-50% risk reduction. The protective effect of nocturia was apparent among study participants with low, moderate and high water consumption. The risk associated with cigarette smoking was reduced by nocturia. Compared with nonsmokers who did not urinate at night, current smokers who did not urinate at night had an OR of 7.0 (95% CI = 4.7-10.2), whereas those who voided at least twice per night had an OR of 3.3 (95% CI = 1.9-5.8) (p value for trend = 0.0005). Our findings suggest a strong protective effect of nocturia on bladder cancer risk, providing evidence in humans that bladder cancer risk is related to the contact time of the urothelium with carcinogens in urine. Increased urination frequency, coupled with possible dilution of the urine from increased water intake, may diminish the effect of urinary carcinogens on bladder cancer risk.
Methods for efficiently identifying subjects with constantly acidic pH in epidemiological and clinical studies have not been assessed. We recruited 30 volunteers to estimate the minimum number of urine pH measurements using pH strips needed to identify subjects with "constantly acidic urine pH". Spearman's correlation coefficients between urine pH measured with a pH meter and with the four pH strips ranged from 0.94 to 0.95 (p < 0.001 for all four strips). Overall agreement within +/-0.5 pH units between the four strips and the pH meter ranged from 62.2% to 74.4%. When using a spot urine sample from a single morning to classify participants with respect to their urine pH, 80% of individuals fell into the acidic urine pH (pH equal to or lower than 6.0) group. When we required subjects to have urine pH equal to or lower than 6.0 in six consecutive AM spot urine samples and seven spot PM urine samples, only 20% of participants fulfilled this criterion. Measuring urine pH twice a day (early in the morning and early in the evening) during four consecutive days classified individuals in the same way as two daily measurements for one week. A single pH measurement from a spot urine sample is not reliable to identify individuals with constantly acidic pH. Morning and evening urine pH measurements with pH strips during four consecutive days identify individuals with constantly acidic urine pH individuals as well as one week of measurements, and thus might be useful to identify subjects with constantly acidic urine pH in epidemiological and clinical studies.
OBJECTIVE: Clarifying age-specific female breast cancer risks and interactions may provide important etiologic clues. METHOD: Using a population-based case-control study in Poland (2000-2003) of 2,386 incident breast cancer cases and 2,502 control subjects aged 25-74 years, we estimated age-specific breast cancer incidence rates according to risk factors. RESULTS: Breast cancer risks were elevated among women with positive family history (FH), younger age at menarche, older age at first full-term birth, nulliparity, exogenous hormonal usage, and reduced physical activity (PA). Notwithstanding overall risks, we observed statistically significant quantitative (non-crossover) and qualitative (crossover) age interactions for all risk factors except for FH and PA. For example, nulliparity compared to parity reduced breast cancer risk among women ages 25-39 years then rates crossed or reversed, after which nulliparity increased relative risks among women ages 40-74 years. CONCLUSION: Though quantitative age interactions could be expected, qualitative interactions were somewhat counterintuitive. If confirmed in other populations, qualitative interactions for a continuous covariate such as age will be difficult to reconcile in a sequential (multistep or monolithic) 'stochastic' breast cancer model. Alternatively, the reversal of relative risks among younger and older women suggests subgroup heterogeneity with different etiologic mechanisms for early-onset and late-onset breast cancer types.
We conducted a population-based case-control study of reproductive factors in Warsaw and Lódź, Poland, in 551 incident endometrial cancer cases and 1925 controls. The reproductive variable most strongly related to risk was multiparity, with subjects with three or more births having a 70% lower risk than the nulliparous women. The reduced risk was particularly strong below 55 years of age. Subjects with older ages at a first birth were also at reduced risk even after adjustment for number of births. Ages at last birth or intervals since last birth were not strongly related to risk. Spontaneous abortions were unrelated to risk, but induced abortions were associated with slight risk increases (odds ratios=1.28, 95% confidence intervals 0.8-2.1 for 3+ vs no abortions). The absence of effects on risk of later ages at, or short intervals since, a last birth fails to support the view that endometrial cancer is influenced by mechanical clearance of initiated cells. Alternative explanations for reproductive effects should be sought, including alterations in endogenous hormones.
Exposure to polycyclic aromatic hydrocarbons (PAHs) has been associated with risk of bladder cancer and with increased bulky DNA adduct levels in several studies, mainly in smokers. We investigated the relation between bulky PAH-DNA adducts in peripheral blood mononuclear cells and bladder cancer in nonsmoking subjects from a large hospital-based case-control study in Spain. Additionally, we examined the association between DNA adduct formation and several air pollution proxies. The study comprised 76 nonsmoking cases and 76 individually matched controls by sex, region of residence, age, and smoking status (never, former). To maximize the relevance of the DNA adduct measurement as a proxy of PAH exposure, subjects selected had not changed residence, occupation, and major lifestyle factors during the last 10 years. Bulky DNA adducts were measured using the (32)P-postlabeling technique, nuclease P1 treatment. The percentage of detectable adducts was higher in controls (41%) than in cases (32%) with an odds ratio of 0.75 (95% confidence interval, 0.36-1.58). In an analysis limited to controls, a higher percentage of DNA adducts was found among those whose last residence was in a big city (50%) compared with those living in villages (19%; P = 0.04). No consistent associations were found for other markers of air pollution. In this study, among nonsmokers with stable environmental and lifestyle factors, bulky DNA adducts were not associated with bladder cancer risk. Results do not support an association of bladder cancer risk with low-level exposure to PAHs as measured through the formation of bulky DNA adducts in peripheral mononuclear cells.
Genetic polymorphisms in DNA repair genes may impact individual variation in DNA repair capacity and alter cancer risk. In order to examine the association of common genetic variation in the base-excision repair (BER) pathway with bladder cancer risk, we analyzed 43 single nucleotide polymorphisms (SNPs) in 12 BER genes (OGG1, MUTYH, APEX1, PARP1, PARP3, PARP4, XRCC1, POLB, POLD1, PCNA, LIG1, and LIG3). Using genotype data from 1,150 cases of urinary bladder transitional cell carcinomas and 1,149 controls from the Spanish Bladder Cancer Study we estimated odds ratios (ORs) and 95% confidence intervals (CIs) adjusting for age, gender, region and smoking status. SNPs in three genes showed significant associations with bladder cancer risk: the 8-oxoG DNA glycosylase gene (OGG1), the Poly (ADP-ribose) polymerase family member 1 (PARP1) and the major gap filling polymerase-beta (POLB). Subjects who were heterozygous or homozygous variant for an OGG1 SNP in the promoter region (rs125701) had significantly decreased bladder cancer risk compared to common homozygous: OR (95%CI) 0.78 (0.63-0.96). Heterozygous or homozygous individuals for the functional SNP PARP1 rs1136410 (V762A) or for the intronic SNP POLB rs3136717 were at increased risk compared to those homozygous for the common alleles: 1.24 (1.02-1.51) and 1.30 (1.04-1.62), respectively. In summary, data from this large case-control study suggested bladder cancer risk associations with selected BER SNPs, which need to be confirmed in other study populations.
The double-strand break DNA repair (DSBR) pathway is implicated in maintaining genomic stability and therefore could affect bladder cancer risk. Here we present data evaluating 39 single-nucleotide polymorphisms (SNPs) in seven candidate genes whose products are involved in DNA break sensing (NBS1, BRCA1 interacting genes BRIP1 and ZNF350), non-homologous end-joining (NHEJ) DNA repair (XRCC4) and homologous recombination (HR) repair (RAD51, XRCC2 and XRCC3). SNPs for RAD51 and XRCC2 covered most of the common variation. Associations with bladder cancer risk were evaluated in 1,150 newly diagnosed cases of urinary bladder transitional cell carcinomas and 1,149 controls conducted in Spain during 1997-2001. We found that the genetic variants evaluated significantly contributed to bladder cancer risk (global likelihood ratio test P = 0.01). Subjects with the ZNF350 R501S (rs2,278,415) variant allele showed significantly reduced risk compared with common homozygote variants, odds ratio (OR) [95% confidence interval (95% CI)]: 0.76 (0.62-0.93) per variant allele. Carriers of a putative functional SNP in intron 7 of XRCC4 (rs1,805,377) had significantly increased bladder cancer risk compared with common homozygotes: 1.33 (1.08-1.64) per variant allele. Lastly, XRCC2 homozygote variants for three promoter SNPs (rs10,234,749, rs6,464,268, rs3,218,373) and one non-synonymous SNP (rs3,218,536, R188H) were associated with reduced bladder cancer risk (ORs ranging from 0.36 to 0.50 compared with common homozygotes). Meta-analysis for XRCC3 T241M (rs861,539) had a significant small increase in risk among homozygote variants: OR (95% CI) = 1.17 (1.00-1.36). Results from this study provide evidence for associations between variants in genes in the DSBR pathway and bladder cancers risk that warrant replication in other study populations.
BACKGROUND: The sex hormone-binding globulin (SHBG) is a carrier protein that modulates the bio-availability of serum sex steroid hormones, which may be involved in ovarian cancer. We evaluated whether common genetic variation in SHBG and its 3' neighbor ATP1B2, in linkage disequilibrium, is associated with the risk of epithelial ovarian cancer. METHODS: The study population included 264 women with ovarian carcinoma and 625 controls participating in a population-based case-control study in Poland. Five common single nucleotide polymorphisms (SNPs) in SHGB and five in ATP1B2 were selected to capture most common variation in this region. RESULTS: None of the SNPs evaluated was significantly associated with ovarian cancer risk, including the putative functional SNPs SHBG D356N (rs6259) and -67G>A 5'UTR (rs1799941). However, our data were consistent with a decreased ovarian cancer risk associated with the variant alleles for these two SNPs, which have been previously associated with increased circulating levels of SHBG. CONCLUSION: These data do not support a substantial association between common genetic variation in SHBG and ovarian cancer risk.
Germline mutations in the tumor suppressor gene TP53 are associated with high incidence of early-onset malignancies, and somatic mutations occur in 20-40% of all breast cancer cases. We investigated the association of common genetic variation in TP53 and its flanking genes, WDR79 and ATP1B2, with risk for breast cancer. Single nucleotide polymorphisms (SNPs) identified in a re-sequence analysis were genotyped in 2 large case-control studies including 731 cases and 1,124 controls from Norway, and 1,995 cases and 2,296 controls from Poland. Analyses of the pooled data showed no SNPs in TP53 to be significantly associated with risk for breast cancer. However, we found a significant and consistent association with risk for a SNP in exon 1 (R68G) of the 5' neighboring gene WDR79 (rs2287499, OR (95% CI) = 1.08 (0.95-1.23) for CG vs. CC and 1.60 (1.04-2.47) for GG vs. CC, p-trend = 0.01). Stratification by ER and PR status, showed these increases in risk to be limited to ER negative tumors (OR (95% CI) per variant allele: 1.42 (1.18-1.71) p-trend = 0.00009). In addition, 2 TP53 SNPs (rs17887200 3'of STP and rs12951053 in intron 7) showing weak and non-significant overall increases in risk, were also associated with ER negative tumors (1.48 (1.11-1.93) p-trend = 0.01 and 1.29 (1.06-1.58) p-trend = 0.009, respectively). In conclusion, this comprehensive evaluation of common genetic variation in TP53 and its flanking genes found no significant overall associations between SNPs in TP53 and breast cancer risk. However, data suggested that common variation in TP53 or WDR79 could be associated with ER negative breast cancers.
Common genetic variation could alter the risk for developing bladder cancer. We conducted a large-scale evaluation of single nucleotide polymorphisms (SNPs) in candidate genes for cancer to identify common variants that influence bladder cancer risk. An Illumina GoldenGate assay was used to genotype 1,433 SNPs within or near 386 genes in 1,086 cases and 1,033 controls in Spain. The most significant finding was in the 5' UTR of VEGF (rs25648, p for likelihood ratio test, 2 degrees of freedom = 1 x 10(-5)). To further investigate the region, we analyzed 29 additional SNPs in VEGF, selected to saturate the promoter and 5' UTR and to tag common genetic variation in this gene. Three additional SNPs in the promoter region (rs833052, rs1109324, and rs1547651) were associated with increased risk for bladder cancer: odds ratio (95% confidence interval): 2.52 (1.06-5.97), 2.74 (1.26-5.98), and 3.02 (1.36-6.63), respectively; and a polymorphism in intron 2 (rs3024994) was associated with reduced risk: 0.65 (0.46-0.91). Two of the promoter SNPs and the intron 2 SNP showed linkage disequilibrium with rs25648. Haplotype analyses revealed three blocks of linkage disequilibrium with significant associations for two blocks including the promoter and 5' UTR (global p = 0.02 and 0.009, respectively). These findings are biologically plausible since VEGF is critical in angiogenesis, which is important for tumor growth, its elevated expression in bladder tumors correlates with tumor progression, and specific 5' UTR haplotypes have been shown to influence promoter activity. Associations between bladder cancer risk and other genes in this report were not robust based on false discovery rate calculations. In conclusion, this large-scale evaluation of candidate cancer genes has identified common genetic variants in the regulatory regions of VEGF that could be associated with bladder cancer risk.
GATA-binding protein 3 (GATA3) is a transcription factor and a putative tumor suppressor that is highly expressed in normal breast luminal epithelium and estrogen receptor alpha (ER)-positive breast tumors. We hypothesized that common genetic variation in GATA3 could influence breast carcinogenesis. Four tag single-nucleotide polymorphisms (SNP) in GATA3 and its 3' flanking gene FLJ4598 were genotyped in two case control studies in Norway and Poland (2,726 cases and 3,420 controls). Analyses of pooled data suggested a reduced risk of breast cancer associated with two intronic variants in GATA3 in linkage disequilibrium (rs3802604 in intron 3 and rs570613 in intron 4). Odds ratio (95% confidence interval) for rs570613 heterozygous and rare homozygous versus common homozygous were 0.85 (0.75-1.95) and 0.82 (0.62-0.96), respectively (P(trend)=0.004). Stronger associations were observed for subjects with ER-negative, than ER-positive, tumors (P(heterogeneity)=0.01 for rs3802604; P(heterogeneity)=0.09 for rs570613). Although no individual SNPs were associated with ER-positive tumors, two haplotypes (GGTC in 2% of controls and AATT in 7% of controls) showed significant and consistent associations with increased risk for these tumors when compared with the common haplotype (GATT in 46% of controls): 1.71 (1.27-2.32) and 1.26 (1.03-1.54), respectively. In summary, data from two independent study populations showed two intronic variants in GATA3 associated with overall decreases in breast cancer risk and suggested heterogeneity of these associations by ER status. These differential associations are consistent with markedly different levels of GATA3 protein by ER status. Additional epidemiologic studies are needed to clarify these intriguing relationships.
Fruit and vegetable intake has been linked to bladder cancer risk; however, evidence for other foods or specific dietary factors is inconclusive. The association between diet and bladder cancer risk was evaluated among 912 incident bladder cancer cases and 873 controls in Spain. Data were consistent with a reduced bladder cancer risk associated with high fruit intake; however, the association was significant only among current smokers (OR (95% CI) for 5th versus 1st quintile: 0.5 (0.3-0.9), p trend=0.009). Evaluation of food subgroups showed significant inverse associations with high intakes of berries, Liliaceae vegetables and yellow-orange vegetables. The latter association was stronger among individuals with the GSTM1 present than the null genotype (0.4 (0.2, 0.7) and 0.9 (0.6, 1.3), respectively; p for interaction=0.04). Meat or fish intake, their cooking methods or level of doneness, or heterocyclic amine intakes were not significantly associated with risk. Intake of folate, other B-vitamins (B12, B6, B2) and retinol was also associated with a reduced risk, the strongest associations being for vitamin B6 (0.6 (0.4, 0.8) p trend=0.0006) and retinol (0.6 (0.4-0.9) p trend=0.004). Our findings indicate that fruit and vegetable intake, as well as B-vitamin and retinol intake might be associated with a reduced bladder cancer risk.
Tumor necrosis factor (TNF) is critical to regulation of inflammation. Genetic variation in the promoter region of TNF has been associated with expression differences, and a range of auto-immune, infectious, and oncologic diseases. We analyzed eight common single nucleotide polymorphisms (SNPs) (rs746868, rs909253, rs1799964, rs1800630, rs1800750, rs1800629, rs361525, and rs1800610) to capture most of the genetic variation in TNF in addition to SNPs in lymphotoxin-alpha (LTA), a pro-inflammatory cytokine in linkage disequilibrium with the TNF promoter region. SNPs were genotyped in a USA population-based case-control study (3,318 cases, 2,841 controls). Promising results were followed-up in an independent population-based case-control study in Poland (2,228 cases, 2,378 controls). In both studies, women carrying the variant allele of rs361525 were at elevated breast cancer risk compared to the GG genotype (per allele OR = 1.18, 95% CI 1.04-1.35; P for trend = 0.008). Other SNPs were not significantly associated with breast cancer risk. Haplotype analyses did not reveal any additional associations between TNF and breast cancer risk. Data from 5,269 cases and 4,982 controls suggested that the rs361525 A allele, located in the TNF promoter region, was associated with a modest increase in breast cancer risk. Additional studies are required to replicate these findings and to determine whether rs361525 is a causative SNP or is a marker of a causative SNP.
High-risk susceptibility genes explain <40% of the excess risk of familial ovarian cancer. Therefore, other ovarian cancer susceptibility genes are likely to exist. We have used a single nucleotide polymorphism (SNP)-tagging approach to evaluate common variants in 13 genes involved in cell cycle control-CCND1, CCND2, CCND3, CCNE1, CDK2, CDK4, CDK6, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CDKN2C, and CDKN2D-and risk of invasive epithelial ovarian cancer. We used a two-stage, multicenter, case-control study. In stage 1, 88 SNPs that tag common variation in these genes were genotyped in three studies from the United Kingdom, United States, and Denmark ( approximately 1,500 cases and 2,500 controls). Genotype frequencies in cases and controls were compared using logistic regression. In stage 2, eight other studies from Australia, Poland, and the United States ( approximately 2,000 cases and approximately 3,200 controls) were genotyped for the five most significant SNPs from stage 1. No SNP was significant in the stage 2 data alone. Using the combined stages 1 and 2 data set, CDKN2A rs3731257 and CDKN1B rs2066827 were associated with disease risk (unadjusted P trend = 0.008 and 0.036, respectively), but these were not significant after adjusting for multiple testing. Carrying the minor allele of these SNPs was found to be associated with reduced risk [OR, 0.91 (0.85-0.98) for rs3731257; and OR, 0.93 (0.87-0.995) for rs2066827]. In conclusion, we have found evidence that a single tagged SNP in both the CDKN2A and CDKN1B genes may be associated with reduced ovarian cancer risk. This study highlights the need for multicenter collaborations for genetic association studies.
Epidemiological evidence suggests that intake of folate and other B-vitamins and genetic variants in the one-carbon metabolism pathway could influence the risk of breast cancer. Previous studies have focused on 2 polymorphisms in the methylenetetrahydrofolate gene (MTHFR A222V and E429A); however, findings are inconclusive. In a large population-based case-control study in Poland (2,386 cases, 2,502 controls), we investigated the association between breast cancer risk and 13 polymorphisms in 6 one-carbon metabolism genes (MTHFR, MTR, MTRR, CBS, SHMT1 and SLC19A1). Data suggested an association between a nonsynonymous change in the gene coding for methionine synthase (MTR D919G) and reduced breast cancer risk: OR (95% CI) = 0.84 (0.73-0.96) and 0.85 (0.62-1.15) for heterozygous and homozygote variant genotypes, respectively, compared with common homozygotes; p-trend = 0.01, false discovery rate = 0.14. We found no significant associations between other variants and breast cancer risk, including MTHFR A222V or E429A. Meta-analyses including published studies of MTHFR A222V (8,330 cases and 10,825 controls) and E429A (6,521 cases and 8,515 controls) supported the lack of an overall association; however, studies suggested an increase in risk among premenopausal women. In conclusion, this report does not support a substantial overall association between the evaluated polymorphisms in the one-carbon metabolism pathway and breast cancer risk.
A recent analysis showed that the excess odds ratio (EOR) for lung cancer due to smoking can be modeled by a function which is linear in total pack-years and exponential in the logarithm of smoking intensity and its square. Below 15-20 cigarettes per day, the EOR/pack-year increased with intensity (direct exposure rate or enhanced potency effect), suggesting greater risk for a total exposure delivered at higher intensity (for a shorter duration) than for an equivalent exposure delivered at lower intensity. Above 20 cigarettes per day, the EOR/pack-year decreased with increasing intensity (inverse exposure rate or reduced potency effect), suggesting greater risk for a total exposure delivered at lower intensity (for a longer duration) than for an equivalent exposure delivered at higher intensity. The authors applied this model to data from 10 case-control studies of cancer, including cancers of the lung, bladder, oral cavity, pancreas, and esophagus. At lower intensities, there was enhanced potency for several cancer sites, but narrow ranges for pack-years increased uncertainty, precluding definitive conclusions. At higher intensities, there was a consistent reduced potency effect across studies. The intensity effects were statistically homogeneous, indicating that after accounting for risk from total pack-years, intensity patterns were comparable across the diverse cancer sites.
BACKGROUND: The N-acetyltransferase 2 (NAT2) enzyme detoxifies aromatic amines, an important class of carcinogens in tobacco smoke. Slow acetylation phenotype individuals have reduced detoxification capacity compared with those with a rapid/intermediate phenotype. Analysis of the Spanish Bladder Cancer Study found an odds ratio (OR) for slow acetylators relative to rapid/intermediate acetylators of 0.9 in never-smokers and 1.6 in ever-smokers, a 1.8-fold enhancement in smokers. Evidence indicates that acetylation is an exposure-dependent process, and thus the magnitude of the interaction may also depend on exposure level. METHODS: We extend a comprehensive three-parameter linear-exponential model for the excess odds ratio (EOR) for smoking to include effects of NAT2 status, and reanalyse smoking and NAT2 status for the bladder cancer data. RESULTS: We show that variations in smoking risk with NAT2 status result from interactions with smoking intensity (cigarettes per day) and not total pack-years of exposure. In addition, the relative increase in smoking risk in NAT2 slo acetylators increases with smoking intensity. CONCLUSIONS: Analyses reveal an enhanced effect for smoking intensity and bladder cancer in NAT2 slow acetylators which increases with intensity.
BACKGROUND: Findings on water and total fluid intake and bladder cancer are inconsistent; this may, in part, be due to different levels of carcinogens in drinking water. High levels of arsenic and chlorinated by-products in drinking water have been associated with elevated bladder cancer risk in most studies. A pooled analysis based on six case-control studies observed a positive association between tap water and bladder cancer but none for nontap fluid intake, suggesting that contaminants in tap water may be responsible for the excess risk. OBJECTIVES: We examined the association between total fluid and water consumption and bladder cancer risk, as well as the interaction between water intake and trihalomethane (THM) exposure, in a large case-control study in Spain. METHODS: A total of 397 bladder cancer cases and 664 matched controls were available for this analysis. Odds ratios (OR) were estimated using unconditional logistic regression, controlling for potential confounders. RESULTS: Total fluid intake was associated with a decrease in bladder cancer risk [OR = 0.62; 95% confidence interval (CI), 0.40-0.95 for highest vs. lowest quintile comparison]. A significant inverse association was observed for water intake (for > 1,399 vs. < 400 mL/day, OR = 0.47; 95% CI, 0.33-0.66; p for trend < 0.0001), but not for other individual beverages. The inverse association between water intake and bladder cancer persisted within each level of THM exposure; we found no statistical interaction (p for interaction = 0.13). CONCLUSION: Findings from this study suggest that water intake is inversely associated with bladder cancer risk, regardless of THM exposure level.
When cytobrush buccal cell samples have been collected as a genomic DNA (gDNA) source for an epidemiological study, whole genome amplification (WGA) can be critical to maintain sufficient DNA for genotyping. We evaluated REPLI-g WGA using gDNA from two paired cytobrushes (cytobush 'A' kept in a cell lysis buffer, and 'B' dried and kept at room temperature for 3 days, and frozen until DNA extraction) in a pilot study (n=21), and from 144 samples collected by mail in a breast cancer study. WGA success was assessed as the per cent completion/concordance of STR/SNP genotypes. Locus amplification bias was assessed using quantitative PCR of 23 human loci. The pilot study showed > 98% completion but low genotype concordance between cytobrush wgaDNA and paired blood gDNA (82% and 84% for cytobrushes A and B, respectively). Substantial amplification bias was observed with significantly lower human gDNA amplification from cytobrush B than A. Using cytobrush gDNA samples from the breast cancer study (n =20), an independent laboratory demonstrated that increasing template gDNA to the REPLI-g reaction improved genotype performance for 49 SNPs; however, average completion and concordance remained below 90%. To reduce genotype misclassification when cytobrush wgaDNA is used, inclusion of paired gDNA/wgaDNA and/or duplicate wgaDNA samples is critical to monitor data quality.
We have previously reported significant inverse associations between bladder cancer risk and dietary intake of vitamins B2, B6, B12, folate and protein in a hospital-based bladder cancer case-control study conducted in Spain (1,150 cases;1,149 controls). Because these dietary factors are involved in the one-carbon metabolism pathway, we evaluated associations between bladder cancer risk and 33 single nucleotide polymorphisms (SNPs) in 8 genes (CBS, CTH, MTHFR, MTR, MTRR, SHMT1, SLC19A1 and TYMS) and interactions with dietary variables involved in this pathway. Two SNPs in the CTH gene were significantly associated with bladder cancer risk. OR (95% CI) for heterozygous and the homozygous variants compared to homozygous wild-type individuals were: 1.37 (1.04-1.80) IVS3-66 A > C and 1.22 (1.02-1.45) IVS10-430 C > T. Because the CTH gene is important for glutathione synthesis, we examined interactions with the GSTM1 gene, which codes for glutathione S-transferase muu. Increased risk for individuals with the IVS10-430 CT or TT genotype was limited to those with the GSTM1 null genotype (p-interaction = 0.02). No other SNPs were associated with risk of bladder cancer. These findings suggest that common genetic variants in the one-carbon pathway may not play an important role in the etiology of bladder cancer. However, our results provide some evidence that variation in glutathione synthesis may contribute to risk, particularly among individuals who carry a deletion in GSTM1. Additional work is needed to comprehensively evaluate genomic variation in CTH and related genes in the trans-sulfuration pathway and bladder cancer risk.
The relationship between family history of cancer in first-degree relatives and risk of bladder cancer was examined in the Spanish Bladder Cancer Study. Information on family history of cancer was obtained for 1,158 newly diagnosed bladder cancer cases and 1,244 controls included in 18 hospitals between 1998 and 2001. A total of 464 (40.1%) cases and 436 (35.1%) controls reported a family history of cancer in >/=1 relative [odds ratio (OR), 1.32; 95% confidence interval (95% CI), 1.11-1.59]; the OR was 1.23 (95% CI, 1.01-1.50) among those with only one relative affected and 1.67 (95% CI, 1.23-2.29) among those with >/=2 affected relatives (P(trend) = 0.0004). A greater risk of bladder cancer was observed among those diagnosed at age </=45 years (OR, 2.67; 95% CI, 1.10-6.50) compared with those diagnosed over age 45 years (OR, 1.27; 95% CI, 1.06-1.52). The OR of bladder cancer among subjects reporting a family history of cancer of the bladder was 2.34 (95% CI, 0.95-5.77). Statistically significant associations emerged between bladder cancer risk and family history of cancer of the esophagus, lung, prostate, and brain. The OR of bladder cancer for those reporting family history of bladder cancer was 4.76 (95% CI, 1.25-18.09) among NAT2-slow acetylators and 1.17 (95% CI, 0.17-7.86) among NAT2-rapid/intermediate acetylators (P(interaction) = 0.609). Among individuals with GSTM1 null and present genotypes, the corresponding ORs were 2.91 (95% CI, 0.44-19.09) and 4.21 (95% CI, 1.26-14.14), respectively (P(interaction) = 0.712). Limitations of our study are small sample size in subgroup analyses, reliability of family history data, and possible residual confounding by shared environmental exposures. Overall, our findings support the hypothesis that genetic factors play a role in bladder cancer etiology. Whether these correspond to low-penetrance cancer-predisposing polymorphisms acting together and/or interacting with environmental factors warrants further research.
BACKGROUND: The etiology of breast cancer is not well understood and the role of occupational exposures in breast carcinogenesis is still uncertain. METHODS: The population-based case-control study included 2,386 incident breast cancer cases diagnosed in 2000-2003, and 2,502 controls. Lifetime occupational histories and information on other potential breast cancer risk factors were obtained through personal interviews. Conditional logistic regression analyses calculated odds ratios (ORs) associated with various occupations and industries after control for potential confounders. RESULTS: We found statistically significant excesses of breast cancer among engineers (OR=2.0; 95% CI: 1.0-3.8), economists (2.1; 1.1-3.8), sales occupations-retail (1.2; 1.0-1.5), and other sales occupations (1.2; 1.0-1.5). Industries showing significantly elevated risks included special trade contractors (2.2; 1.2-4.3), electronic and electric equipment manufacturers (1.7; 1.1-2.7); and public administration/general government n.e.c. (2.7; 1.3-5.7). Each of these findings was supported by a statistically significant positive trend for duration of employment (P<0.05). A decreased breast cancer risk was observed in janitors and cleaners (0.7; 0.5-0.8). CONCLUSIONS: In this study, we found few associations for breast cancer and occupations or industries. The suggestive findings for the electronic and electric equipment manufacturing industry and for the occupations with potential exposure to magnetic fields deserve further evaluation.
Telomeres, consisting of TTAGGG nucleotide repeats and a protein complex at chromosome ends, are critical for maintaining chromosomal stability. Genomic instability, following telomere crisis, may contribute to breast cancer pathogenesis. Many genes critical in telomere biology have limited nucleotide diversity, thus, single nucleotide polymorphisms (SNPs) in this pathway could contribute to breast cancer risk. In a population-based study of 1995 breast cancer cases and 2296 controls from Poland, 24 SNPs representing common variation in POT1, TEP1, TERF1, TERF2 and TERT were genotyped. We did not identify any significant associations between individual SNPs or haplotypes and breast cancer risk; however, data suggested that three correlated SNPs in TERT (-1381C>T, -244C>T, and Ex2-659G>A) may be associated with reduced risk of breast cancer among individuals with a family history of breast cancer (odds ratios 0.73, 0.66, and 0.57, 95% confidence intervals 0.53-1.00, 0.46-0.95 and 0.39-0.84, respectively). In conclusion, our data do not support substantial overall associations between SNPs in telomere pathway genes and breast cancer risk. Intriguing associations with variants in TERT among women with a family history of breast cancer warrant follow-up in independent studies.
OBJECTIVES: Data suggest that post-menopausal women with larger ovaries are at increased risk for endometrial carcinoma; however, analyses comparing ovarian volume to serum hormone levels are limited. Accordingly, we assessed ovarian volumes in relation to serum sex hormone levels among post-menopausal women with endometrial carcinoma who participated in a multi-center case-control study. METHODS: Data for established risk and protective factors for endometrial carcinoma were collected via in-person interviews. Ovarian volumes were estimated from pathology reports. Associations between exposures and age-adjusted ovarian volumes were analyzed for 175 cases with available data. For a subset of 135 cases, we analyzed relationships between ovarian volume, adjusted for age and body mass index (BMI), and serum hormone levels by analysis of variance. RESULTS: Ovarian volume declined progressively from 1.83 cm3 among women ages 55-59 years to 1.23 cm3 among women age 70 years or older (p-trend=0.02). Larger ovarian volume was associated with early menarche (p-trend=0.03), having given birth (p=0.01), and weakly with elevated BMI (p-trend=0.06). After adjustment, increased ovarian volume was associated with higher estradiol (p-trend=0.007); albumin-bound estradiol (p-trend=0.01); and free estradiol (p-trend=0.006) levels; androstenedione, estrone and estrone sulfate showed similar, though non-significant associations. CONCLUSIONS: Among women with endometrial carcinoma, larger ovaries were associated with higher serum levels of estrogens. Further studies examining the role of the ovaries in post-menopausal hormonal carcinogenesis are warranted.
Evidence suggests that breast cancer hormone receptor status varies by etiologic factors, but studies have been inconsistent. In a population-based case-control study in Poland that included 2,386 cases and 2,502 controls, we assessed ER-alpha and PR status of tumors based on clinical records according to etiologic exposure data collected via interview. For 842 cancers, we evaluated ER-alpha, ER-beta, PR and HER2 levels by semiquantitative microscopic scoring of immunostained tissue microarrays and a quantitative immunofluorescence method, automated quantitative analysis (AQUAtrade mark). We related marker levels in tumors to etiologic factors, using standard regression models and novel statistical methods, permitting adjustment for both correlated tumor features and exposures. Results obtained with different assays were generally consistent. Receptor levels varied most significantly with body mass index (BMI), a factor that was inversely related to risk among premenopausal women and directly related to risk among postmenopausal women with larger tumors. After adjustment for correlated markers, exposures and pathologic characteristics, PR and HER2 AQUA levels were inversely related to BMI among premenopausal women (p-trend = 0.01, both comparisons), whereas among postmenopausal women, PR levels were associated directly with BMI (p-trend = 0.002). Among postmenopausal women, analyses demonstrated that BMI was related to an interaction of PR and HER2: odds ratio (OR) = 0.86 (95% CI = 0.69-1.07) for low PR and HER2 expression vs. OR = 1.78 (95% CI = 1.25-2.55) for high expression (p-heterogeneity = 0.001). PR and HER2 levels in breast cancer vary by BMI, suggesting a heterogeneous etiology for tumors related to these markers.
Whereas germ line missense mutations in the tumor suppressor gene TP53 are associated with a marked predisposition to breast cancer, single-nucleotide polymorphisms (SNPs) may play a more modest role in breast cancer susceptibility. We examined genetic variation in TP53 in relation to breast cancer risk among women aged 20-74 years in a population-based case-control study in Wisconsin, Massachusetts and New Hampshire. Analyses were conducted separately for in situ (176 cases/581 controls) and invasive (1,490 cases/1,291 controls) breast cancer. Oral mucosal DNA samples were genotyped for the codon 72 polymorphism in exon 4 (rs1,042,522), seven intronic SNPs and three SNPs residing in the 3' untranslated region (UTR). Logistic regression was used to obtain age- and state-adjusted odds ratios for individual SNPs. Haplotypes were reconstructed using PHASE software, and the overall association with breast cancer risk was assessed using a global score test. None of the 11 individual SNPs or eight common haplotypes were significantly related to breast carcinoma in situ risk. Among all women, two linked SNPs (D' = 0.99, r(2) = 0.95) on intron 7 (rs12,951,053, rs12,947,788) were associated with modest increases in invasive breast cancer risk; however, associations were only significant for heterozygous carriers. The data suggested that additional variants in the 3' UTR (rs9,894,946), and in two correlated SNPs (D' = 0.94, r(2) = 0.81) in introns 6 (rs1,625,895) and 4 (rs2,909,430), were associated with reduced invasive breast cancer risk among women aged 50 and younger only (P(interaction) < 0.03). These results indicate that common variation in the TP53 gene could modify the risk of invasive breast cancer.
The objective of this study was to evaluate the coexpression patterns of hormonal markers in breast cancer tissue and their relationship with pathologic characteristics and epidemiologic risk factors. We evaluated the expression of 17 markers by immunohistochemistry in 842 invasive breast carcinomas collected in a population-based case-control study conducted in Poland. Based on marker correlations, factor analysis identified four major coexpression patterns (factors): "nuclear receptor factor" [estrogen receptor (ER)-alpha, progesterone receptor, androgen receptor, cyclin D1, and aromatase], "estrogen metabolism/ER-beta factor" (ER-beta, peroxisome proliferator-activated receptor-gamma, steroid sulfatase, estrogen sulfonotransferase, and cytochrome P450 1B1), "HER2 factor" (human epidermal growth factor receptor 2, E-cadherin, cyclooxygenase-2, aromatase, steroid sulfatase), and "proliferation factor" (cytokeratin 5, cytokeratin 5/6, epidermal growth factor receptor, P53). Three of these factors corresponded to molecular subtypes previously defined by expression profiling; however, the estrogen metabolism/ER-beta factor seemed to be distinctive. High scores for this factor were associated with high tumor grade (P heterogeneity = 0.02), younger age at menarche (P heterogeneity = 0.04), lower current body mass index among premenopausal women (P heterogeneity = 0.01), and older age at menopause (P heterogeneity = 0.04). High scores for the proliferation factor were also associated with early menarche (P heterogeneity < 0.0001), and in contrast to the estrogen metabolism/ER-beta factor, higher current body mass index among premenopausal women (P heterogeneity = 0.03). Our analysis of hormonal pathway markers independently confirmed several previously defined molecular subtypes identified by gene expression profiling and augmented these findings by suggesting the existence of additional relationships related to ER-beta and enzymes involved in hormone metabolism.
Analysis of gene expression data suggests that breast cancers are divisible into molecular subtypes which have distinct clinical features. This study evaluates whether pathologic features and etiologic associations differ among molecular subtypes. We evaluated 804 women with invasive breast cancers and 2,502 controls participating in a Polish Breast Cancer Study. Immunohistochemical stains for estrogen receptor alpha, progesterone receptor, human epidermal growth factor receptors (HER2 and HER1), and cytokeratin 5 were used to classify cases into five molecular subtypes: luminal A, luminal B, HER2-expresing, basal-like, and unclassified. Relative risks were estimated using adjusted odds ratios and 95% confidence intervals. We observed that compared with the predominant luminal A tumors (69%), other subtypes were associated with unfavorable clinical features at diagnosis, especially HER2-expressing (8%) and basal-like (12%) tumors. Increasing body mass index significantly reduced the risk of luminal A tumors among premenopausal women (odds ratios, 0.71; 95% confidence intervals, 0.57-0.88 per five-unit increase), whereas it did not reduce risk for basal-like tumors (1.18; 0.86-1.64; P(heterogeneity) = 0.003). On the other hand, reduced risk associated with increasing age at menarche was stronger for basal-like (0.78; 0.68-0.89 per 2-year increase) than luminal A tumors (0.90; 0.95-1.08; P(heterogeneity) = 0.0009). Although family history increased risk for all subtypes (except for unclassified tumors), the magnitude of the relative risk was highest for basal-like tumors. Results from this study have shown that breast cancer risk factors may vary by molecular subtypes identified in expression studies, suggesting etiologic, in addition to clinical, heterogeneity of breast cancer.
<h4>Background</h4>The Breast Cancer Association Consortium (BCAC) is an international collaboration that was established to provide large sample sizes for examining genetic associations. We conducted combined analyses on all single-nucleotide polymorphisms (SNPs) whose associations with breast cancer have been investigated by at least three participating groups.<h4>Methods</h4>Data from up to 12 studies were pooled for each SNP (ADH1C I350V, AURKA F31I, BRCA2 N372H, CASP8 D302H, ERCC2 D312N, IGFBP3 -202 c>a, LIG4 D501D, PGR V660L, SOD2 V16A, TGFB1 L10P, TP53 R72P, XRCC1 R399Q, XRCC2 R188H, XRCC3 T241M, XRCC3 5' UTR, and XRCC3 IVS7-14). Genotype frequencies in case and control subjects were compared, and genotype-specific odds ratios for the risk of breast cancer in heterozygotes and homozygotes for the rare allele compared with homozygotes for the common allele were estimated with logistic regression. Statistical tests were two-sided.<h4>Results</h4>The total number of subjects for analysis of each SNP ranged from 12,013 to 31,595. For five SNPs--CASP8 D302H, IGFBP3 -202 c>a, PGR V660L, SOD2 V16A, and TGFB1 L10P--the associations with breast cancer were of borderline statistical significance (P = .016, .060, .047, .056, and .0088 respectively). The remaining 11 SNPs were not associated with breast cancer risk; genotype-specific odds ratios were close to unity. There was some evidence for between-study heterogeneity (P<.05) for four of the 11 SNPs (ADH1C I350V, ERCC2 D312N, XRCC1 R399Q, and XRCC3 IVS5-14).<h4>Conclusion</h4>Pooling data within a large consortium has helped to clarify associations of SNPs with breast cancer. In the future, consortia such as the BCAC will be important in the analysis of rare polymorphisms and gene x gene or gene x environment interactions, for which individual studies have low power to identify associations, and in the validation of associations identified from genome-wide association studies.
BACKGROUND: We assessed use of nonaspirin nonsteroidal anti-inflammatory drugs (NSAID), aspirin, paracetamol (acetaminophen), phenacetin, and metamizol (dipyrone) and risk of bladder cancer and their interaction with polymorphisms in drug-metabolizing genes. METHODS: We analyzed personal interview data from 958 incident bladder cancer cases and 1,029 hospital controls from a multicenter case-control study in Spain. A drug matrix was developed to estimate cumulative lifetime dose of active ingredients. Polymorphisms in GSTP1, SULT1A1, CYP2E1, CYP2C9, and NAT2 were examined. RESULTS: A significant reduction in bladder cancer risk [adjusted odds ratio (OR), 0.4; 95% confidence interval (95% CI), 0.2-0.9] was observed for regular users of nonaspirin NSAIDs compared with never users. Regular users of aspirin experienced no reduction in risk (OR, 1.0; 95% CI, 0.7-1.5). Regular users of paracetamol had no overall increased risk of bladder cancer (OR, 0.8; 95% CI, 0.4-1.3), but our data suggested a qualitative interaction with the GSTP1 I105V genotype. Subjects with at least one copy of the 359L or 144C variant alleles in the NSAID-metabolizing gene CYP2C9 had a slightly decreased risk of bladder cancer (OR, 0.8; 95% CI, 0.7-1.0; P = 0.037); however, having at least one copy of the 359L or 144C variant alleles did not significantly modify the protective effect of nonaspirin NSAID use. CONCLUSION: Regular use of nonaspirin NSAIDs was associated with a reduced risk of bladder cancer, which was not modified by polymorphisms in the NSAID-metabolizing gene CYP2C9. We found no evidence of an overall effect for paracetamol or aspirin use.
Breast cancer is a morphologically and clinically heterogeneous disease; however, it is less clear how risk factors relate to tumour features. We evaluated risk factors by tumour characteristics (histopathologic type, grade, size, and nodal status) in a population-based case-control of 2386 breast cancers and 2502 controls in Poland. Use of a novel extension of the polytomous logistic regression permitted simultaneous modelling of multiple tumour characteristics. Late age at first full-term birth was associated with increased risk of large (> 2 cm) tumours (odds ratios (95% confidence intervals) 1.19 (1.07-1.33) for a 5-year increase in age), but not smaller tumours (P for heterogeneity adjusting for other tumour features (Phet) = 0.007). On the other hand, multiparity was associated with reduced risk for small tumours (0.76 (0.68-0.86) per additional birth; Phet = 0.004). Consideration of all tumour characteristics simultaneously revealed that current or recent use of combined hormone replacement therapy was associated with risk of small (2.29 (1.66-3.15)) and grade 1 (3.36 (2.22-5.08)) tumours (Phet = 0.05 for size and 0.0008 for grade 1 vs 3), rather than specific histopathologic types (Phet = 0.63 for ductal vs lobular). Finally, elevated body mass index was associated with larger tumour size among both pre- and postmenopausal women (Phet = 0.05 and 0.0001, respectively). None of these relationships were explained by hormone receptor status of the tumours. In conclusion, these data support distinctive risk factor relationships by tumour characteristics of prognostic relevance. These findings might be useful in developing targeted prevention efforts.
The double-strand break DNA repair pathway has been implicated in breast carcinogenesis. We evaluated the association between 19 polymorphisms in seven genes in this pathway (XRCC2, XRCC3, BRCA2, ZNF350, BRIP1, XRCC4, LIG4) and breast cancer risk in two population-based studies in USA (3,368 cases and 2,880 controls) and Poland (1,995 cases and 2,296 controls). These data suggested weak associations with breast cancer risk for XRCC3 T241M and IVS7-14A>G (pooled odds ratio (95% confidence interval): 1.18 (1.04-1.34) and 0.85 (0.73-0.98) for homozygous variant vs wild-type genotypes, respectively), and for an uncommon variant in ZNF350 S472P (1.24 (1.05-1.48)), with no evidence for study heterogeneity. The remaining variants examined had no significant relationships to breast cancer risk. Meta-analyses of studies in Caucasian populations, including ours, provided some support for a weak association for homozygous variants for XRCC3 T241M (1.16 (1.04-1.30); total of 10,979 cases and 10,423 controls) and BRCA2 N372H (1.13 (1.10-1.28); total of 13,032 cases and 13,314 controls), and no support for XRCC2 R188H (1.06 (0.59-1.91); total of 8,394 cases and 8,404 controls). In conclusion, the genetic variants evaluated are unlikely to have a substantial overall association with breast cancer risk; however, weak associations are possible for XRCC3 (T241M and IVS7-14A>G), BRCA2 N372H, and ZNF350 S472P. Evaluation of potential underlying gene-gene interactions or associations in population subgroups will require even larger sample sizes.
Nucleotide excision repair (NER) is critical for protecting against damage from carcinogens in tobacco smoke. We evaluated the influence of common genetic variation in the NER pathway on bladder cancer risk by analyzing 22 single nucleotide polymorphisms (SNP) in seven NER genes (XPC, RAD23B, ERCC1, ERCC2, ERCC4, ERCC5, and ERCC6). Our study population included 1,150 patients with transitional cell carcinoma of the urinary bladder and 1,149 control subjects from Spain. Odds ratios (OR) and 95% confidence intervals (95% CI) were adjusted for age, gender, region, and smoking status. Subjects with the variant genotypes for SNPs in four of the seven genes evaluated had small increases in bladder cancer risk compared to subjects with the homozygous wild-type genotypes: RAD23B IVS5-15A>G (OR, 1.3; 95% CI, 1.1-1.5; P = 0.01), ERCC2 R156R (OR, 1.3; 95% CI, 1.1-1.6; P = 0.006), ERCC1 IVS5+33A>C (OR, 1.2; 95% CI, 1.0-1.5; P = 0.06; P(trend) = 0.04), and ERCC5 M254V (OR, 1.4; 95% CI, 1.0-2.0; P = 0.04). A global test for pathway effects indicated that genetic variation in NER characterized by the 22 SNPs analyzed in this study significantly predicts bladder cancer risk (P = 0.04). Pairwise comparisons suggested that carrying variants in two genes could result in substantial increases in risk. Classification tree analyses suggested the presence of subgroups of individuals defined by smoking and NER genotypes that could have substantial increases in risk. In conclusion, these findings provide support for the influence of genetic variation in NER on bladder cancer risk. A detailed characterization of genetic variation in key NER genes is warranted and might ultimately help identify multiple susceptibility variants that could be responsible for substantial joint increases in risk.
Buccal cell samples are increasingly used in epidemiological studies as a source of genomic DNA. The accurate and precise quantitation of human DNA is critical for the optimal use of these samples. However, it is complicated by the presence of bacterial DNA and wide inter-individual variation in DNA concentration from buccal cell collections. The paper evaluated the use of ultraviolet light (UV) spectroscopy, Höechst (H33258) and PicoGreen as measures of total DNA, and real-time quantitative polymerase chain reaction (PCR) as a measure of human amplifiable DNA in buccal samples. Using serially diluted white blood cell DNA samples (at a concentration range of 300 to 0.5 ng microl-1), UV spectroscopy showed the largest bias, followed by Höechst, especially for low concentrations. PicoGreen and real-time PCR provided the most accurate and precise estimates across the range of concentrations evaluated, although an increase in bias with decreasing concentrations was observed. The ratio of real-time PCR to PicoGreen provided a reasonable estimate of the percentage of human DNA in samples containing known mixtures of human and bacterial DNA. Quantification of buccal DNA from samples collected in a breast cancer case-control study by PicoGreen and real-time PCR indicated that cytobrush and mouthwash DNA samples contain similar percentages of human amplifiable DNA. Real-time PCR is recommended for the quantification of buccal cell DNA in epidemiological studies since it provides precise estimates of human amplifiable DNA across the wide range of DNA concentrations commonly observed in buccal cell DNA samples.
Because catechol-O-methyltransferase (COMT) catalyzes the addition of methyl groups to stabilize catechol estrogens that may induce DNA damage, genetic variants could influence breast cancer risk. To comprehensively characterize genetic variation in this gene, we selected haplotype-tagging single nucleotide polymorphisms (htSNP) in COMT. A total of 11 htSNPs (including COMT Val(158)Met) were selected based on the resequencing and dense genotyping approach of the Breast and Prostate Cancer Cohort Consortium. htSNPs were genotyped in a population-based, case-control study in Poland (1,995 cases and 2,296 controls). Individual SNPs were not significantly associated with risk. Haplotypes were estimated using the expectation-maximization algorithm. Overall differences in the haplotype distribution between cases and controls were assessed using a global score test. The TGAG haplotype (frequent in 4.3% of controls), in a linkage disequilibrium (LD) block that included the 3' untranslated region (UTR) of COMT, was associated with breast cancer risk (odds ratio, 1.29; 95% confidence interval, 1.06-1.58) compared with the most common haplotype TGAA; however, the global test for haplotype associations was not significant (P = 0.09). Haplotypes in another LD block, which included COMT Val(158)Met, were not associated with breast cancer risk (global P = 0.76). Haplotype-breast cancer risk associations were not significantly modified by hormonally related risk factors, family history of breast cancer, or tumor characteristics. In summary, our data does not support a substantial overall association between COMT haplotypes and breast cancer. The suggestion of increased risk associated with a haplotype in the 3' UTR of COMT needs to be confirmed in independent study populations.
Four single nucleotide polymorphisms (SNPs) in CYP1B1 (Ex2 + 143 C > G, Ex2 + 356 G > T, Ex3 + 251 G > C, Ex3 + 315 A > G) cause amino acid changes (R48G, A119S, L432V and N453S, respectively) and are associated with increased formation of catechol estrogens; however, epidemiologic evidence only weakly supports an association between these variants and breast cancer risk. Because genetic variability conferring increased susceptibility could exist beyond these putative functional variants, we comprehensively examined the common genetic variability within CYP1B1. A total of eight haplotype-tagging (ht)SNPs (including Ex3 + 315 A > G), in addition to two putatively functional SNPs (Ex2 + 143 C > G and Ex3 + 251 G > C), were selected and genotyped in a large case-control study of Polish women (1995 cases and 2296 controls). Haplotypes were estimated using the expectation-maximization algorithm, and overall differences in the haplotype distribution between cases and controls were assessed using a global score test. We also evaluated levels of tumor CYP1B1 protein expression in a subset of 841 cases by immunohistochemistry, and their association with genetic variants. In the Polish population, we observed two linkage disequilibrium (LD)-defined blocks. Neither haplotypes (global P-value of 0.99 and 0.67 for each block of LD, respectively), nor individual SNPs (including three putatively functional SNPs) were associated with breast cancer risk. CYP1B1 was expressed in most tumor tissues (98%), and the level of expression was not related to the studied genetic variants. We found little evidence for modification of the estimated effect of haplotypes or individual SNPs by age, family history of breast cancer, or tumor hormone receptor status. The present study provides strong evidence against the existence of a substantial overall association between common genetic variation in CYP1B1 and breast cancer risk.
An increased bladder cancer risk has been suggested among users of hair dyes. We evaluated this association among females in a hospital-based case-control study in Spain (152 female incident cases, 166 female controls). The effect of hair dye use was also evaluated among potentially susceptible subgroups defined by NAT1, NAT2, CYP1A2, GSTM1, GSTT1 and GSTP1 genotypes. Use of any hair dye (OR=0.8, CI 0.5-1.4) or of permanent hair dyes (OR=0.8, CI 0.5-1.5) was not associated with increased risk. Small non-significant increases in risks were observed in a lagged analysis that ignores exposures within ten years of diagnosis (OR=1.3, CI 0.8-2.2). No trend in risk with increasing exposure was seen for duration of use, average use or cumulative use. None of the polymorphisms examined significantly modified the hair dye associated risk. Overall, this study does not support an association between hair dye use and bladder cancer.
The role of active and passive cigarette smoking in breast cancer etiology remains controversial. Using data from a large population-based case-control study in Poland (2386 cases, 2502 controls) conducted during 2000-2003, we examined the associations between active and passive smoking overall and for different age categories. We also evaluated differences in risk by estrogen receptor (ER) and progesterone receptor (PR) status in tumors, and the potential modification of the smoking association by N-acetyl transferase 2 (NAT2) genotype. Women ever exposed to passive smoking at home or at work had a risk of breast cancer similar to those never exposed to active or passive smoking (OR (95%CI) = 1.11 (0.85-1.46), and no trends were observed with increasing hours/day-years of passive smoking exposure. Active smoking was associated with a significant increase in risk only among women younger than 45 years of age (OR (95%CI) = 1.95 (1.38-2.76); 1.15 (0.93-1.40); 0.91 (0.77-1.09) for < 45, 45-55 and > 55 years of age, respectively; p-heterogeneity < 0.001 for < 45 vs. > 55 years) and prevailed for both ER+ and ER- tumors. The smoking association among women < 45 years was stronger for current than former smokers, and a significant trend was observed with duration of smoking (p = 0.04). NAT2 slow vs. rapid/intermediate acetylation genotype was not related to breast cancer risk (0.99 (0.87-1.13)), and did not significantly modify the smoking relationships. In conclusion, our data indicate that passive smoking is not associated with breast cancer risk; however, active smoking might be associated with an increased risk for early onset breast cancers.
High estrogen exposure in utero may increase breast cancer risk later in life. However, studies of the associations between perinatal factors presumed to affect the fetal hormonal environment and breast cancer risk are inconsistent. We used data from a population-based case-control study of 2,386 incident breast cancers and 2,502 controls in Poland to evaluate risks associated with various perinatal characteristics. After adjusting for confounders, we found a significant trend (p = 0.01) of breast cancer risk with birth weight (OR = 1.54, 95% CI 1.08-2.19 for birth weights >4,000 g vs. <2,500 g). Subjects with a high birth order (> or =6) were at reduced risk (OR = 0.81, 0.61-1.06) when compared with first born subjects. Birth weight was somewhat a stronger risk predictor among subjects whose cancers were diagnosed at 50 years of age or older (OR = 1.84, 1.19-2.85) than among those with cancers diagnosed at younger ages (OR = 1.14, 0.61-2.12). Subjects whose mothers smoked during their pregnancies were at slightly higher risk than those who never smoked (OR = 1.21, 0.99-1.47), but the risk was similar to mothers who only smoked at other times (OR = 1.22, 0.81-1.84). Breast cancer risk was not related to paternal smoking, maternal age, gestational age or twin status. Our results add support to the growing evidence that some perinatal exposures may relate to breast cancer risk. Additional studies are needed to confirm associations and clarify the biologic mechanisms underlying these associations.
We examined the effects of dose, type of tobacco, cessation, inhalation, and environmental tobacco smoke exposure on bladder cancer risk among 1,219 patients with newly diagnosed bladder cancer and 1,271 controls recruited from 18 hospitals in Spain. We used unconditional logistic regression to estimate odds ratios (OR) and 95% confidence intervals (95% CI) for the association between bladder cancer risk and various characteristics of cigarette smoking. Current smokers (men: OR, 7.4; 95% CI, 5.3-10.4; women: OR, 5.1; 95% CI, 1.6-16.4) and former smokers (men: OR, 3.8; 95% CI, 2.8-5.3; women: OR, 1.8; 95% CI, 0.5-7.2) had significantly increased risks of bladder cancer compared with nonsmokers. We observed a significant positive trend in risk with increasing duration and amount smoked. After adjustment for duration, risk was only 40% higher in smokers of black tobacco than that in smokers of blond tobacco (OR, 1.4; 95% CI, 0.98-2.0). Compared with risk in current smokers, a significant inverse trend in risk with increasing time since quitting smoking blond tobacco was observed (> or =20 years cessation: OR, 0.2; 95% CI, 0.1-0.9). No trend in risk with cessation of smoking black tobacco was apparent. Compared with men who inhaled into the mouth, risk increased for men who inhaled into the throat (OR, 1.7; 95% CI, 1.1-2.6) and chest (OR, 1.5; 95% CI, 1.1-2.1). Cumulative occupational exposure to environmental tobacco smoke seemed to confer increased risk among female nonsmokers but not among male nonsmokers. After eliminating the effect of cigarette smoking on bladder cancer risk in our study population, the male-to-female incidence ratio decreased from 8.2 to 1.7, suggesting that nearly the entire male excess of bladder cancer observed in Spain is explained by cigarette smoking rather than occupational/environmental exposures to other bladder carcinogens.
Homozygous mutation in the ATM gene causes ataxia telangiectasia and heterozygous mutation carriers may be at increased risk of breast cancer. We studied a total of 22 ATM variants; 18 variants were analyzed in one of two large population-based studies from the U.S. and Poland, and four variants were analyzed in all 2,856 breast cancer cases and 3,344 controls from the two studies. The missense mutation Ser49Cys (c.146C>G, p.S49C), carried by approximately 2% of subjects, was more common in cases than controls in both study populations, combined odds ratio (OR) 1.69 (95% CI, 1.19-2.40; P=0.004). Another missense mutation at approximately 2% frequency, Phe858Leu (c.2572T>C, p.F858L), was associated with a significant increased risk in the U.S. study but not in Poland, and had a combined OR of 1.44 (95% CI, 0.98-2.11; P=0.06). These analyses provide the most convincing evidence thus far that missense mutations in ATM, particularly p.S49C, may be breast cancer susceptibility alleles. Because of their low frequency, even larger sample sizes are required to more firmly establish these associations.
BACKGROUND: Skewed X chromosome inactivation may be more common in women with epithelial ovarian cancer and early-onset breast cancer. We tested this hypothesis in a group of 235 breast cancer patients and 253 controls (mean age 45.8 years) from a larger population based case control study. METHODS: We measured X chromosome inactivation with the AR gene assay in lymphocyte DNA digested with the methylation specific enzyme HpaII. We judged skewness using an adjusted measure (relative to the undigested sample) with a cut point of 75%, and an unadjusted measure where skewed was defined as > 90% of the signal from one allele in the HpaII digested sample. RESULTS: There were no significant differences in any of the skewing measures between cases and controls. Using the adjusted skewing measure among pre-menopausal subjects under the age of 50, 14% of cases versus 11% of controls were skewed, OR = 1.2, 95% CI 0.6 to 2.3; using the unadjusted measure, OR = 0.9, 95% CI 0.4 to 2.0. CONCLUSIONS: While we cannot rule out a subtle difference of approximately twofold or less, we have failed to find a significant difference in the prevalence of skewed X chromosome inactivation in younger women with breast cancer compared to controls.
Construction of tissue microarrays (TMAs) to efficiently characterize large sets of noninvasive epithelial lesions in the breast by immunohistochemistry is an appealing investigative approach, but presents technical challenges. We report methodologic studies performed to optimize methods for building TMAs from noninvasive breast tissues collected in a large case-control study of breast cancer. Using a manual arraying technique with 2.0-mm diameter needles, we constructed TMAs from specimens obtained from 32 women with breast cancer containing the following targets: (1) 28 terminal duct lobular units (TDLUs); (2) 28 ductal carcinomas in situ, and (3) 23 invasive carcinomas. Using careful target selection, we achieved representation of approximately 80% of noninvasive targets with sustained preservation through section 30 of the TMAs. Immunohistochemical staining of TDLU targets demonstrated positive staining for estrogen receptor (ER) in 30.8% of tubules and for progesterone receptor (PR) in 50.0%. To establish an efficient method to evaluate staining results in TDLUs, we created a categorical scoring system to approximate the percentage of tubules containing positive stained cells (<10%, 10% to 50%, >or=50%), and compared the results with those obtained by tubule counting. Comparison between the two methods demonstrated exact agreement for 70.8% of ER and 79.2% of PR stains without two-category discrepancies. ER/PR expression levels in multiple (up to 4) noninvasive targets of the same tissue type (TDLU or DCIS) from a single block showed good correlation. These data suggest that it is feasible to produce TMAs of noninvasive breast structures, albeit with careful selection of targets, and that immunostains of such cores may permit efficient immunohistochemical characterization of peritumoral tissues. Additional exploration of this approach is needed.
Impaired base-excision repair (BER) function can give rise to the accumulation of DNA damage and initiation of cancer. We evaluated whether genetic variation in six BER pathway genes (XRCC1, ADPRT, APEX1, OGG1, LIG3, and MUTYH) is associated with breast cancer risk in two large population-based case-control studies in the United States (3,368 cases and 2,880 controls) and Poland (1,995 cases and 2,296 controls). A detailed evaluation was first done in a subset of 1,898 cases and 1,514 controls with mouthwash DNA samples in the U.S. study. Significant findings were followed up in the remainder of the U.S. study population that provided cytobrush DNA samples and in the Polish study. Using data from U.S. study participants with mouthwash DNA, we found no significant overall association between breast cancer risk and XRCC1 R280H and R194W, ADPRT V726W, APEX1 D148E, OGG1 S326C, LIG3 R780H, or MUTYH 5' untranslated region. These data suggested a decreased risk for XRCC1Q399R homozygous variants compared with homozygous wild-type in premenopausal women, but these findings were not confirmed when data from cytobrush DNA samples were added [combined odds ratio (OR), 0.8; 95% confidence interval (95% CI), 0.6-1.1] or in the Polish study (OR, 1.0; 95% CI, 0.7-1.5). Meta-analyses based on our data and published data from studies of two single nucleotide polymorphisms in XRCC1 showed no evidence of an overall association between breast cancer risk and homozygous variants versus wild-type for Q399R (OR, 1.1; 95% CI, 1.0-1.2) or R194W (OR, 1.0; 95% CI, 0.7-1.8), although there was a suggestion for an association in Asian populations for Q399R (OR, 1.6; 95% CI, 1.1-2.4; P = 0.02). In conclusion, our results do not support that the polymorphisms evaluated in six BER pathway genes play a major role in breast carcinogenesis, particularly in Caucasian populations.
The promise of whole genome amplification (WGA) is that genomic DNA (gDNA) quantity will not limit molecular genetic analyses. Multiple displacement amplification (MDA) and the OmniPlex PCR-based WGA protocols were evaluated using 4 and 5 ng of input gDNA from 60 gDNA samples from three tissue sources (mouthwash, buffy coat, and lymphoblast). WGA DNA (wgaDNA) yield and genotyping performance were evaluated using genotypes determined from gDNA and wgaDNA using the AmpFlSTR Identifiler assay and N = 49 TaqMan SNP assays. Short tandem repeat (STR) and SNP genotyping completion and concordance rates were significantly reduced with wgaDNA from all WGA methods compared with gDNA. OmniPlex wgaDNA exhibited a greater reduction in genotyping performance than MDA wgaDNA. Reduced wgaDNA genotyping performance was due to allelic (all protocols) and locus (OmniPlex) amplification bias leading to heterozygote and locus dropout, respectively, and %GC sequence content (%GC) was significantly correlated with TaqMan assay performance. Lymphoblast wgaDNA exhibited higher yield (OmniPlex), buffy coat wgaDNA exhibited higher STR genotyping completion (MDA), whereas mouthwash wgaDNA exhibited higher SNP genotyping discordance (MDA). Genotyping of wgaDNA generated from < or = 5 ng gDNA, e.g., from archaeological, forensic, prenatal diagnostic, or pathology samples, may require additional genotyping validation with gDNA and/or more sophisticated analysis of genotypes incorporating observed reductions in genotyping performance.
Electron-beam (E-beam) irradiation, currently being used to sterilize mail addressed to selected ZIP codes in the United States, has significant negative effects on the genomic integrity of DNA extracted from buccal-cell washes. We investigated the yield, composition, and genotyping performance of whole genome amplified DNA (wgaDNA) derived from 24 matched samples of E-beam-irradiated and nonirradiated genomic DNA (gDNA) as a model for the effects of degraded gDNA on the performance of whole genome amplification. gDNA was amplified using the Multiple Displacement Amplification method. Three methods of DNA quantification analysis were used to estimate the yield and composition of wgaDNA, and 65 short tandem repeat and single nucleotide polymorphism genotyping assays were used to evaluate the genotyping performance of irradiated and nonirradiated gDNA and wgaDNA. Compared with wgaDNA derived from nonirradiated gDNA, wgaDNA derived from irradiated gDNA exhibited a significantly reduced yield of wgaDNA and significantly reduced short tandem repeat and single nucleotide polymorphism genotyping completion and concordance rates (P < 0.0001). Increasing the amount of irradiated gDNA input into whole genome amplification improved genotyping performance of wgaDNA but not to the level of wgaDNA derived from nonirradiated gDNA. Multiple Displacement Amplification wgaDNA derived from E-beam-irradiated gDNA is not suitable for genotyping analysis.
BACKGROUND: Many reported associations between common genetic polymorphisms and complex diseases have not been confirmed in subsequent studies. An exception could be the association between NAT2 slow acetylation, GSTM1 null genotype, and bladder-cancer risk. However, current evidence is based on meta-analyses of relatively small studies (range 23-374 cases) with some evidence of publication bias and study heterogeneity. Associations between polymorphisms in other NAT and GST genes and bladder-cancer risk have been inconsistent. METHODS: We investigated polymorphisms in NAT2, GSTM1, NAT1, GSTT1, GSTM3, and GSTP1 in 1150 patients with transitional-cell carcinoma of the urinary bladder and 1149 controls in Spain; all the participants were white. We also carried out meta-analyses of NAT2, GSTM1, and bladder cancer that included more than twice as many cases as in previous reports. FINDINGS: In our study, the odds ratios for bladder cancer for individuals with deletion of one or two copies of the GSTM1 gene were 1.2 (95% CI 0.8-1.7) and 1.9 (1.4-2.7) respectively (p for trend <0.0001). Compared with NAT2 rapid or intermediate acetylators, NAT2 slow acetylators had an increased overall risk of bladder cancer (1.4 [1.2-1.7]) that was stronger for cigarette smokers than for never smokers (p for interaction 0.008). No significant associations were found with the other polymorphisms. Meta-analyses showed that the overall association for NAT2 was robust (p<0.0001), and case-only meta-analyses provided support for an interaction between NAT2 and smoking (p for interaction 0.009). The overall association for GSTM1 was also robust (p<0.0001) and was not modified by smoking status (p=0.86). INTERPRETATION: The GSTM1 null genotype increases the overall risk of bladder cancer, and the NAT2 slow-acetylator genotype increases risk particularly among cigarette smokers. These findings provide compelling evidence for the role of common polymorphisms in the aetiology of cancer. RELEVANCE TO PRACTICE: Although the relative risks are modest, these polymorphisms could account for up to 31% of bladder cancers because of their high prevalence.
Breast cancers classified by estrogen receptor (ER) and/or progesterone receptor (PR) expression have different clinical, pathologic, and molecular features. We examined existing evidence from the epidemiologic literature as to whether breast cancers stratified by hormone receptor status are also etiologically distinct diseases. Despite limited statistical power and nonstandardized receptor assays, in aggregate, the critically evaluated studies (n = 31) suggest that the etiology of hormone receptor-defined breast cancers may be heterogeneous. Reproduction-related exposures tended to be associated with increased risk of ER-positive but not ER-negative tumors. Nulliparity and delayed childbearing were more consistently associated with increased cancer risk for ER-positive than ER-negative tumors, and early menarche was more consistently associated with ER-positive/PR-positive than ER-negative/PR-negative tumors. Postmenopausal obesity was also more consistently associated with increased risk of hormone receptor-positive than hormone receptor-negative tumors, possibly reflecting increased estrogen synthesis in adipose stores and greater bioavailability. Published data are insufficient to suggest that exogenous estrogen use (oral contraceptives or hormone replacement therapy) increase risk of hormone-sensitive tumors. Risks associated with breast-feeding, alcohol consumption, cigarette smoking, family history of breast cancer, or premenopausal obesity did not differ by receptor status. Large population-based studies of determinants of hormone receptor-defined breast cancers defined using state-of-the-art quantitative immunostaining methods are needed to clarify the role of ER/PR expression in breast cancer etiology.
Errors in genotype determination can lead to bias in the estimation of genotype effects and gene-environment interactions and increases in the sample size required for molecular epidemiologic studies. We evaluated the effect of genotype misclassification on odds ratio estimates and sample size requirements for a study of NAT2 acetylation status, smoking, and bladder cancer risk. Errors in the assignment of NAT2 acetylation status by a commonly used 3-single nucleotide polymorphism (SNP) genotyping assay, compared with an 11-SNP assay, were relatively small (sensitivity of 94% and specificity of 100%) and resulted in only slight biases of the interaction parameters. However, use of the 11-SNP assay resulted in a substantial decrease in sample size needs to detect a previously reported NAT2-smoking interaction for bladder cancer: 1,121 cases instead of 1,444 cases, assuming a 1:1 case-control ratio. This example illustrates how reducing genotype misclassification can result in substantial decreases in sample size requirements and possibly substantial decreases in the cost of studies to evaluate interactions.
Immunohistochemical characterization of tumor tissues in epidemiological studies is a promising approach to identify breast cancer subtypes with distinct etiology. The recent development of the tissue microarray (TMA) technique allows for standardized, rapid, and cost-effective immunohistochemical characterization of many cases, which is critical in epidemiological studies. Sectioning paraffin blocks at different times results in loss of material, which can be reduced by preparing many sections each time a block is cut. However, data suggest that staining intensity declines in whole sections prepared from conventional paraffin blocks with storage time, resulting in false-negative results. This problem would be accentuated in TMAs because of the limited tissue representation of each case. To evaluate this concern, we prepared a single TMA block from 125 invasive breast carcinomas collected in a population-based case-control study conducted in Poland and compared estrogen receptor (ER-alpha), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression in sections cut and stored for 6 months at room temperature with sections cut from the same TMA block and stained on the same day. Percentage of positive cases for stored versus fresh sections was similar for ER (59.0%) but significantly higher in fresh sections for PR (56.3% versus 64.1%, P = 0.01) and HER2 (45.5% versus 64.4%, P < 0.001). Among cases positive in both stored and fresh sections, the median percentage of immunoreactive cells was significantly reduced and the staining intensity was consistently lower in stored compared with fresh sections. We conclude that loss of immunoreactivity is an important problem in TMAs of breast cancer. Improved methods for sectioning TMAs and storing tissue sections aimed at reducing loss of immunoreactivity are critical for the use of TMAs in epidemiological studies.
Too many reports of associations between genetic variants and common cancer sites and other complex diseases are false positives. A major reason for this unfortunate situation is the strategy of declaring statistical significance based on a P value alone, particularly, any P value below.05. The false positive report probability (FPRP), the probability of no true association between a genetic variant and disease given a statistically significant finding, depends not only on the observed P value but also on both the prior probability that the association between the genetic variant and the disease is real and the statistical power of the test. In this commentary, we show how to assess the FPRP and how to use it to decide whether a finding is deserving of attention or "noteworthy." We show how this approach can lead to improvements in the design, analysis, and interpretation of molecular epidemiology studies. Our proposal can help investigators, editors, and readers of research articles to protect themselves from overinterpreting statistically significant findings that are not likely to signify a true association. An FPRP-based criterion for deciding whether to call a finding noteworthy formalizes the process already used informally by investigators--that is, tempering enthusiasm for remarkable study findings with considerations of plausibility.
Buccal cells were collected from 29 participants, by use of mouthwash rinses, and were split into equal aliquots, with one aliquot irradiated by electron-beam (E-beam) irradiation equivalent to the sterilizing dosage used by the U.S. Postal Service and the other left untreated. Aliquots were extracted and tested for DNA yields (e.g., TaqMan assay for quantifying human genomic DNA), genomic integrity, and amplification-based analysis of genetic variants (e.g., single-nucleotide polymorphisms [SNPs] and single tandem repeats [STRs]). Irradiated aliquots had lower median DNA yields (3.7 microg/aliquot) than untreated aliquots (7.6 microg/aliquot) (P<.0005) and were more likely to have smaller maximum DNA fragment size, on the basis of genomic integrity gels, than untreated aliquots (P<.0005). Irradiated aliquots showed poorer PCR amplification of a 989-bp beta-globin target (97% for weak amplification and 3% for no amplification) than untreated aliquots (7% for weak amplification and 0% for no amplification) (P<.0005), but 536-bp and 268-bp beta-globin targets were amplified from all aliquots. There was no detectable irradiation effect on SNP assays, but there was a significant trend for decreased detection of longer STRs (P=.01) in irradiated versus untreated aliquots. We conclude that E-beam irradiation reduced the yield and quality of buccal-cell specimens, and, although irradiated buccal-cell specimens may retain sufficient DNA integrity for some amplified analyses of many common genomic targets, assays that target longer DNA fragments (>989 bp) or require whole-genome amplification may be compromised.
Smoking is a known risk factor for bladder cancer. The product of the GSTM1 gene, glutathione S-transferase M1 (GSTM1), is involved in the detoxification of polycyclic aromatic hydrocarbons found in tobacco smoke; a homozygous deletion of this gene in approximately 50% of Caucasians and Asians results in a lack of GSTM1 enzyme activity. Most studies examining the relation between bladder cancer and GSTM1 have reported an increased risk associated with a lack of GSTM1 activity. The authors performed meta- and pooled analyses of published and unpublished, case-control, genotype-based studies that examined this association (17 studies, 2,149 cases, 3,646 controls) and excluded studies conducted in populations with a high prevalence of exposure to known bladder cancer risk factors other than tobacco smoke. Using random effects models in the meta-analysis, the authors obtained a summary odds ratio of 1.44 (95% confidence interval (CI): 1.23, 1.68) for GSTM1 null status with all studies included. Results from studies with at least 100 cases and 100 controls produced a summary odds ratio of 1.42 (95% CI: 1.26, 1.60). Pooled analyses using original data sets from 10 studies (1,496 cases and 1,444 controls) and adjusting for age, sex, and race produced similar results. There was no evidence of multiplicative interaction between the GSTM1 null genotype and ever smoking in relation to bladder cancer, although there was a suggestion of additive interaction (additive interaction = 0.45, 95% CI: -0.03, 0.93). These results indicate that, among populations studied to date, GSTM1 null status is associated with a modest increase in the risk of bladder cancer.
Reproductive characteristics, alcohol intake and polymorphisms in genes encoding sex-steroid metabolizing enzymes might influence the risk of hormone-related cancers by changing circulating concentrations of sex hormones. The relationship between these factors and serum concentrations of estradiol, progesterone, androstenedione, testosterone and DHEA was evaluated in a cross-sectional study of 218 pre-menopausal women from Kaiser Permanente Health Plan in Portland, Oregon. Risk factor information was obtained from questionnaires and hormone serum concentrations were determined by radioimmunoassays. Genotypes for CYP11A 5'UTR(tttta)n, CYP17 5'-UTR -34 T>C, CYP19 IVS4(ttta)n, CYP1B1 (L432V and S453N) and COMT (V158M) were determined from genomic DNA samples. Increasing number of full-term pregnancies was associated with a significant decrease in late-follicular progesterone levels (p-trend = 0.03). Increasing alcohol consumption was associated with higher estradiol levels averaged through the menstrual cycle (p-trend = 0.009) and higher progesterone levels during luteal phase (p-trend = 0.04). Androstenedione and testosterone levels were higher among light to moderate drinkers compared to non-drinkers, although we only observe a significant trend with increasing levels of alcohol consumption for androstenedione. Women heterozygous or homozygous for the CYP1B1 L432V or the S453N polymorphisms had increased luteal estradiol levels (p-value = 0.04 for L432V and 0.04 for S453N). None of the other factors evaluated was significantly associated with serum concentration of hormones. In conclusion, results from this cross-sectional study of pre-menopausal women provide support for an association between light to moderate alcohol intake and elevated levels of estrogen and androgen levels. Our data suggest that circulating levels of progesterone might be related to parity and alcohol consumption, however the biological plausibility of the observed associations is unclear. We found little support for an influence of the evaluated genetic polymorphisms in the steroid synthesis and metabolism pathway on serum hormone levels, except for a possible effect of the CYP1B1 L432V and S453N polymorphisms on serum estradiol levels.
To study genetic risk factors for common diseases, researchers have begun collecting DNA specimens in large epidemiologic studies and surveys. However, little information is available to guide researchers in selecting the most appropriate specimens. In an effort to gather the best information for the selection of specimens for these studies, we convened a meeting of scientists engaged in DNA banking for large epidemiologic studies. In this discussion, we review the information presented at that meeting in the context of recent published information. Factors to be considered in choosing the appropriate specimens for epidemiologic studies include quality and quantity of DNA, convenience of collection and storage, cost, and ability to accommodate future needs for genotyping. We focus on four types of specimens that are stored in these banks: (1) whole blood preserved as dried blood spots; (2) whole blood from which genomic DNA is isolated, (3) immortalized lymphocytes from whole blood or separated lymphocytes, prepared immediately or subsequent to cryopreservation; and (4) buccal epithelial cells. Each of the specimens discussed is useful for epidemiologic studies according to specific needs, which we enumerate in our conclusions.
Blood samples are an excellent source of large amounts of genomic DNA. However, alternative sources are often needed in epidemiological studies because of difficulties in obtaining blood samples. This report evaluates the buccal cytobrush and alcohol-containing mouthwash protocols for collecting DNA by mail. Several DNA extraction techniques are also evaluated. The study was conducted in two phases. In phase 1, we compared cytobrush and mouthwash samples collected by mail in two different epidemiological studies: (a) cytobrush samples (n = 120) from a United States case-control study of breast cancer; and (b) mouthwash samples (n = 40) from a prospective cohort of male United States farmers. Findings from phase 1 were confirmed in phase 2, where we randomized cytobrush (n = 28) and mouthwash (n = 25) samples among participants in the breast cancer study to directly compare both collection methods. The median human DNA yield determined by hybridization with a human DNA probe from phenol-chloroform extracts was 1.0 and 1.6 microg/2 brushes for phases 1 and 2, respectively, and 27.5 and 16.6 microg/mouthwash sample for phases 1 and 2, respectively. Most (94-100%) mouthwash extracts contained high molecular weight DNA (>23 kb), in contrast to 55-61% of the brush extracts. PCR success rates for amplification of beta-globin gene fragments (268, 536, and 989 bp) were similar for cytobrush and mouthwash phenol-chloroform extracts (range, 94.4-100%). Also, we obtained high success rates in determining the number of CAG repeats in the androgen receptor gene, characterizing tetranucleotide microsatellites in six gene loci, and screening for mutations in the BRCA1/2 genes in a subset of phenol-chloroform DNA extracts. Relative to DNA extracted by phenol-chloroform from cytobrush samples, DNA extracted by NaOH had lower molecular weight, decreased PCR success rates for most assays performed, and unreliably high spectrophotometer readings for DNA yields. In conclusion, although DNA isolated from either mouthwash or cytobrush samples collected by mail from adults is adequate for a wide range of PCR-based assays, a single mouthwash sample provides substantially larger amounts and higher molecular weight DNA than two cytobrush samples.
Experimental studies suggest that vitamin D and calcium protect against cancer by reducing proliferation and inducing differentiation. The effects of vitamin D and calcium may be mediated by the vitamin D receptor (VDR), which is encoded by the VDR gene. The present study investigated whether calcium intake and serum vitamin D, as an integrated measure of intake and endogenous production, were associated with risk of colorectal adenoma, known precursors of invasive colorectal cancer. In addition, the interrelation among vitamin D, calcium, and FokI polymorphism of the VDR gene was investigated. Persons (239) with histologically confirmed colorectal adenomas and 228 control individuals without colorectal adenomas confirmed by sigmoidoscopy were enrolled in this case control study conducted at the National Naval Medical Center, Bethesda, MD. We observed an inverse association of serum 25-OH vitamin D [25-(OH)D] with colorectal adenoma. With each 10 ng/ml increase of serum 25-(OH)D, the risk of colorectal adenoma decreased by 26% (odds ratio 0.74, 95% confidence interval 0.60-0.92). The results provided limited evidence for a weak association between calcium intake and colorectal adenoma (odds ratio 0.97, 95% confidence interval 0.93-1.01 per each 100-mg calcium intake). However, the inverse association of serum 25-(OH)D with colorectal adenoma is suggested to be stronger in subjects with calcium intake above the median (P for multiplicative interaction 0.13). The VDR FokI polymorphism was not significantly associated with colorectal adenoma and did not modify the effect of vitamin D or calcium. In conclusion, the study results suggested a protective effect for vitamin D on colorectal adenoma.
Overwhelming evidence indicates that environmental exposures, broadly defined, are responsible for most cancer. There is reason to believe, however, that relatively common polymorphisms in a wide spectrum of genes may modify the effect of these exposures. We discuss the rationale for using common polymorphisms to enhance our understanding of how environmental exposures cause cancer and comment on epidemiologic strategies to assess these effects, including study design, genetic and statistical analysis, and sample size requirements. Special attention is given to sources of potential bias in population studies of gene--environment interactions, including exposure and genotype misclassification and population stratification (i.e., confounding by ethnicity). Nevertheless, by merging epidemiologic and molecular approaches in the twenty-first century, there will be enormous opportunities for unraveling the environmental determinants of cancer. In particular, studies of genetically susceptible subgroups may enable the detection of low levels of risk due to certain common exposures that have eluded traditional epidemiologic methods. Further, by identifying susceptibility genes and their pathways of action, it may be possible to identify previously unsuspected carcinogens. Finally, by gaining a more comprehensive understanding of environmental and genetic risk factors, there should emerge new clinical and public health strategies aimed at preventing and controlling cancer.
The results obtained from experimental studies of estrogen carcinogenesis need validation in epidemiologic studies. Such studies present additional challenges, however, because variations in human populations are much greater than those in experimental systems and in animal models. Because epidemiologic studies are often used to evaluate modest differences in risk factors, it is essential to minimize sources of errors and to maximize sensitivity, reproducibility, and specificity. In the first part of this chapter, critical factors in designing and executing epidemiologic studies, as well as the influence of sample collection, processing, and storage on data reliability, are discussed. One of the most important requirements is attaining sufficient statistical power to assess small genetic effects and to evaluate interactions between genetic and environmental factors. The second part of this chapter describes innovative technology, namely, Fourier transform-infrared (FT-IR) spectra of DNA that reveal major structural differences at various stages of the progression from normal to cancer tissue. The structural differences become evident from wavenumber-by-wavenumber statistical comparisons of the mean FT-IR spectra of DNA from normal to cancer tissues. This analysis has allowed distinguishing benign tissues from cancer and metastatic tissues in human breast, prostate, and ovarian cancers. This analysis, which requires less than 1 microg of DNA, is predicted to be used for detecting early cancer-related changes at the level of DNA, rather than at the cellular level.
We devised a simple, noninvasive, cost-efficient technique for collecting buccal cell DNA for molecular epidemiology studies. Subjects (n = 52) brushed their oral mucosa and expectorated the fluid in their mouths, which was applied to "Guthrie" cards pretreated to retard bacterial growth and inhibit nuclease activity (IsoCode, Schleicher and Schuell, Keene, NH). The cards are well-suited for transport and storage because they dry quickly, need no processing, and are compact and lightweight. We stored the samples at room temperature for 5 days to mimic a field situation and then divided them into portions from which DNA was extracted either immediately or after storage for 9 months at room temperature, -20 degrees C, or -70 degrees C. The fresh samples had a median yield of 2.3 microg of human DNA (range, 0.2-53.8 microg), which was adequate for at least 550 PCR reactions. More than 90% of the samples were amplified in all three beta-globin gene fragment assays attempted. DNA extract frozen for 1 week at -20 degrees C also performed well. Stored samples had reduced DNA yields, which achieved statistical significance for room temperature and -70 degrees C, but not -20 degrees C, storage. However, because all of the stored samples tested were successfully amplified, the observed reduction may represent tighter DNA fixation to the card over time rather than loss of genetic material. We conclude that treated cards are an alternative to brushes/swabs and mouth rinses for the collection of buccal cell DNA and offer some advantages over these methods, particularly for large-scale or large-scale or long-term studies involving stored samples and studies in which samples are collected off-site and transported. Future studies that enable direct comparisons of the various buccal cell collection methods are needed.
Tobacco use is an established cause of bladder cancer. The ability to detoxify aromatic amines, which are present in tobacco and are potent bladder carcinogens, is compromised in persons with the N-acetyltransferase 2 slow acetylation polymorphism. The relationship of cigarette smoking with bladder cancer risk therefore has been hypothesized to be stronger among slow acetylators. The few studies to formally explore such a possibility have produced inconsistent results, however. To assess this potential gene-environment interaction in as many bladder cancer studies as possible and to summarize results, we conducted a meta-analysis using data from 16 bladder cancer studies conducted in the general population (n = 1999 cases), Most had been conducted in European countries. Because control subjects were unavailable for a number of these studies, we used a case-series design, which can be used to assess multiplicative gene-environment interaction without inclusion of control subjects. A case-series interaction odds ratio (OR) > 1.0 indicates that the relationship of cigarette smoking and bladder cancer risk is stronger among slow acetylators as compared with rapid acetylators. We observed an interaction between smoking and N-acetyltransferase 2 slow acetylation (OR, 1.3; 95% confidence interval, 1.0-1.6) that was somewhat stronger when analyses were restricted to studies conducted in Europe (OR, 1.5; confidence interval, 1.1-1.9), a pooling that included nearly 80% of the collected data. Using the predominantly male European study population and assuming a 2.5-fold elevation in bladder cancer risk from smoking, we estimated that the population attributable risk percent was 35% for slow acetylators who had ever smoked and 13% for rapid acetylators who had ever smoked. These results suggest that the relationship of smoking and bladder cancer is stronger among slow acetylators than among rapid acetylators.
OBJECTIVES: This study was undertaken to evaluate the relationship between vaginal pH and factors related to cervical cancer. STUDY DESIGN: In a population-based sample of 9161 women from Guanacaste Province in Costa Rica women were categorized into 2 groups, those with vaginal pH in the reference range (4.0-4.5) and those with elevated vaginal pH (5.0-5.5). Odds ratios were used to estimate the relationship between elevated pH and its potential determinants. RESULTS: Aging was strongly associated with increasing vaginal pH, starting at around 45 years of age and continuing into old age. Menopause was responsible for an additional 1.7-fold increase in the odds of having an elevated pH (odds ratio 1.7, 95% confidence interval 1.4-2.0). Human papillomavirus infection and cervical intraepithelial neoplasia were not associated with changes in pH. CONCLUSIONS: Our data indicate that vaginal pH is strongly related to age and to menopausal status and thus could be a marker of age-related hormonal changes. Elevated pH does not appear to be associated with risk of high-grade intraepithelial neoplasia among women infected with human papillomavirus.
BACKGROUND: The enzymes encoded by the glutathione S-transferase mu 1 (GSTM1) and theta 1 (GSTT1) genes are involved in the metabolism (mainly inactivation, but activation is possible) of a wide range of carcinogens that are ubiquitous in the environment; the enzyme encoded by the GSTT1 gene may also be active in endogenous mutagenic processes. Homozygous deletions of the GSTM1 and GSTT1 genes are commonly found in the population and result in a lack of enzyme activity. This study was undertaken to evaluate the association between GSTM1 and GSTT1 gene polymorphisms and breast cancer risk. METHODS: Our study included 466 women with incident cases of breast cancer occurring from May 1989 through May 1994 and 466 matched control subjects. These individuals were part of a prospective cohort of U.S. women (i.e., the Nurses' Health Study). Odds ratios (ORs) and 95% confidence intervals (CIs) from conditional logistic regression models were used to estimate the association between genetic polymorphisms and breast cancer risk. RESULTS: The GSTM1 and GSTT1 null genotypes were not associated with an increased risk of breast cancer (OR = 1.05 [95% CI = 0.80-1.37] for GSTM1 null; OR = 0. 86 [95% CI = 0.61-1.21] for GSTT1 null). On the contrary, a suggestion of a decreased risk of breast cancer associated with the GSTT1 null genotype was observed among premenopausal women. When considered together, no combination of the GSTM1 and GSTT1 genotypes was associated with an increased risk of breast cancer. The relationship between GSTM1 and GSTT1 gene deletions and breast cancer risk was not substantially modified by cigarette smoking. CONCLUSIONS: Our data provide evidence against a substantially increased risk of breast cancer associated with GSTM1 and/or GSTT1 homozygous gene deletions.
Power and sample size considerations are critical for the design of epidemiologic studies of gene-environment interactions. Hwang et al. (Am J Epidemiol 1994;140:1029-37) and Foppa and Spiegelman (Am J Epidemiol 1997;146:596-604) have presented power and sample size calculations for case-control studies of gene-environment interactions. Comparisons of calculations using these approaches and an approach for general multivariate regression models for the odds ratio previously published by Lubin and Gail (Am J Epidemiol 1990; 131:552-66) have revealed substantial differences under some scenarios. These differences are the result of a highly restrictive characterization of the null hypothesis in Hwang et al. and Foppa and Spiegelman, which results in an underestimation of sample size and overestimation of power for the test of a gene-environment interaction. A computer program to perform sample size and power calculations to detect additive or multiplicative models of gene-environment interactions using the Lubin and Gail approach will be available free of charge in the near future from the National Cancer Institute.
In studies of gene-environment interactions, exposure misclassification can lead to bias in the estimation of an interaction effect and increased sample size. The magnitude of the bias and the consequent increase in sample size for fixed misclassification probabilities are highly dependent on the prevalence of the misclassified factor and on the interaction model. This paper describes a relatively simple approach to assess the impact of misclassification on bias in the estimation of multiplicative or additive interactions and on sample size requirements. Applications of this method illustrate that even small errors in the assessment of environmental or genetic factors can result in biased interaction parameters and substantially increased sample size requirements that can compromise the feasibility of the study. Also, an example is provided where nondifferential misclassification biases an additive interaction parameter away from the null value, even under conditions where a multiplicative interaction parameter will always be biased toward the null value. Efforts to improve the accuracy in measuring both genetic and environmental factors are critical for the valid assessment of gene-environment interactions in case-control studies.
In this chapter we describe the impact of risk factor misclassification in case-control studies designed to estimate gene-environment interactions. We show that under certain scenarios even small amounts of exposure or genotype misclassification can substantially attenuate the interaction effect and, as a consequence, dramatically increase the sample size required to study these interactions. A consideration of how sample size is affected by exposure and genotype misclassification in the study design phase should help to identify situations where obtaining better risk factor information is crucial for the feasibility of studies.
Red meat or meat-cooking methods such as frying and doneness level have been associated with an increased risk of colorectal and other cancers. It is unclear whether it is red meat intake or the way it is cooked that is involved in the etiology of colorectal cancer. To address this issue, we developed an extensive food frequency questionnaire module that collects information on meat-cooking techniques as well as the level of doneness for individual meat items and used it in a study of colorectal adenomas, known precursors of colorectal cancer. A case-control study of colorectal adenomas was conducted at the National Naval Medical Center (Bethesda, MD) between April 1994 and September 1996. All cases (n = 146) were diagnosed with colorectal adenomas at sigmoidoscopy or colonoscopy and histologically confirmed. Controls (n = 228) were screened with sigmoidoscopy and found not to have colorectal adenomas. The subjects completed a food frequency questionnaire and answered detailed questions on meat-cooking practices. We used frequency and portion size to estimate grams of meat consumed per day for total meat as well as for meat subgroups defined by cooking methods and doneness levels. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using logistic regression, adjusted for age, gender, total caloric intake, reason for screening (routine or other), and several established risk factors for colorectal adenomas or cancer, including the use of nonsteroidal anti-inflammatory drugs, physical activity, and pack-years of cigarette smoking. There was an increased risk of 11% per 10 g/day (or 2.5 oz/week) of reported red meat consumption (OR, 1.11; CI, 1.03-1.19). The increased risk was mainly associated with well-done/very well-done red meat, with an excess risk of 29% per 10 g/day (OR, 1.29; CI, 1.08-1.54) versus an excess of 10% per 10 g/day (OR, 1.10; CI, 0.96-1.26) for consumption of rare/medium red meat. High-temperature cooking methods were also associated with increased risk; 26% per 10 g/day (OR, 1.26; CI, 1.06-1.50) of grilled red meat and 15% per 10 g/day (OR, 1.15; CI, 0.97-1.36) of pan-fried red meat consumption. There was an increased risk of colorectal adenomas associated with higher intake of red meat, most of which was due to the subgroup of red meat that was cooked until well done/very well done and/or by high-temperature cooking techniques, such as grilling. These results are consistent with the hypothesis that carcinogenic compounds formed by high-temperature cooking techniques, such as heterocyclic amines and polycyclic aromatic hydrocarbons, may contribute to the risk of developing colorectal tumors.
Carcinogenic heterocyclic amines are activated by N-acetyltransferase (NAT) enzymes, encoded by NAT1 and NAT2, to genotoxic compounds that can form DNA adducts in the colon epithelium. We have examined the relation of polymorphisms in the genes coding for both enzymes to risk of colorectal cancer and the gene-environment interaction with red meat intake among participants in the prospective Physicians' Health Study. Baseline blood samples from 212 men subsequently diagnosed with colorectal cancer during 13 years of follow-up were genotyped, along with 221 controls. NAT genotypes were analyzed by a PCR-restriction fragment length polymorphism method. Effect modification of the relation of red meat intake and risk of colorectal cancer by NAT genotype was assessed using conditional logistic regression. There was no overall independent association of NAT acetylation genotypes and colorectal cancer risk. The relative risks for the rapid acetylation genotype were 0.93 [95% confidence interval (CI), 0.61-1.42] for NAT1, 0.80 (95% CI, 0.53-1.19) for NAT2, and 0.81 (95% CI, 0.52-1.27) for NAT1/NAT2 combined. We observed a stronger association of red meat intake with cancer risk among NAT rapid acetylators, especially among men 60 years old or older. Among those men who were rapid acetylators for both NAT1 and NAT2, consumption of >1 serving of red meat per day was associated with a relative risk of 5.82 (95% CI, 1.11-30.6) compared with consumption of < or = 0.5 serving per day (P, trend = 0.02). These prospective data, which need to be confirmed in other studies, suggest that polymorphisms in the NAT genes confer differential susceptibility to the effect of red meat consumption on colorectal cancer risk.
In case-control studies of interactions between genetic and environmental exposures, differential misclassification of the environmental exposure with respect to disease status can introduce spurious heterogeneity of the stratum-specific odds ratios. In this paper, the authors identify conditions under which differential misclassification does not introduce bias in the interaction parameter when no multiplicative interaction is present, and it biases the interaction parameter toward the null value when a multiplicative interaction is present. The conditions are that (i) conditional on potential confounders, the environmental exposure is independent of the genotype among the controls, and (ii) misclassification of the environmental exposure is nondifferential with respect to the genotype. These conditions can be tested from the misclassified data in the control group, since a test of the independence of the genotype and the misclassified environmental exposure among the controls is a test of the joint hypothesis that conditions (i) and (ii) are both true. Therefore, the authors propose a two-step test for interaction which first tests conditions (i) and (ii) and then goes on to test for interaction, provided the first step hypothesis is not rejected. A summary test procedure to test for gene-environment interactions in the presence of misclassification, based on both a conventional test for interaction and the two-step test, is recommended, and is illustrated with data from a case-control study of the role of diet as a modifier of the association between a metabolic polymorphism and lung cancer.
Cytochrome P450 1A1 (CYP1A1) and glutathione S-transferase M1 (GSTM1) genetic polymorphisms are involved in the activation and detoxification of chemical carcinogens found in tobacco smoke; thus they may influence host susceptibility to lung cancer. In this study at Massachusetts General Hospital (Boston, MA, USA) of 416 cases and 446 controls (mostly White) we evaluated the association between the CYP1A1 MspI and GSTM1 polymorphisms and lung cancer risk, and their interaction with cigarette smoke. The CYP1A1 MspI heterozygous genotype was present in 18 percent of cases and 16 percent of controls, and one percent of cases and controls were CYP1A1 MspI homozygous variant. The GSTM1 null genotype was detected in 54 percent of cases and 52 percent of controls. After adjusting for age, gender, pack-years of smoking, and years since quitting smoking, while neither the CYP1A1 MspI heterozygous genotype alone nor the GSTM1 null genotype alone were associated with a significant increase in lung cancer risk, having both genetic traits was associated with a twofold increase in risk (95 percent confidence interval [CI] = 1.0-3.4). Our data did not provide enough evidence for a substantial modification of the effect of pack-years on lung cancer risk by the CYP1A1 MspI and GSTM1 genotypes. However, limitations of our study preclude a conclusion about this potential interaction.
In this cross-sectional study of 236 schoolchildren living in Manresa, Spain, we evaluated the association between prevalence of dental caries and frequency of consumption of various food groups, including sweetened baked goods and similar foods (rich in starch and sugars) and confectionery (rich in sugars but not starch), using a food-frequency questionnaire. Because Streptococcus mutans is associated with the cariogenicity of carbohydrates, we also evaluated the modification of these associations by salivary counts of this microorganism. Odds ratios (ORs) were used to measure the association between caries and tertiles of consumption. Sex, age, use of fluorides, tooth-brushing frequency, frequency of dental visits, socioeconomic status, and intake of other potentially cariogenic food groups were considered as potential confounders. We did not find a significant association between any of the food groups evaluated and caries prevalence. Failure to detect an association could have been due to the low prevalence of caries in our population (decayed, missing, or filled permanent teeth = 1.3 at age 10.6 y) or to underestimation of the association due to diet misclassification. In this population, the association between consumption of sweetened baked goods and caries appeared to be modified by the numbers of S. mutans [OR = 6.1 (95% CI: 1.6, 23.0) for low compared with high intake in children with moderate-to-high S. mutans counts and OR = 0.3 (95% CI: 0.1, 1.6) for low compared with high intake in children with low S. mutans counts]. These results suggest that a high intake of sweetened baked goods may be a determinant of caries prevalence in children with moderate-to-high salivary counts of S. mutans.
Polymorphisms in the N-acetyltransferase 2 (NAT2) gene are determinants of the rate of metabolic activation of carcinogenic compounds such as aryl aromatic amines. Homozygosity for any combination of three variant alleles in Caucasians defines 'slow' acetylators; presence of one or two wild-type alleles characterizes 'rapid' acetylators. Although most previous studies have not observed an overall elevation in risk of breast cancer among slow acetylators, a recent study observed that cigarette smoking was associated with a large increase in risk of breast cancer among slow acetylators. We assessed the relation between NAT2 acetylation status and breast cancer risk, and its interaction with smoking, in a prospective study of mainly Caucasian US women. Four hundred and sixty-six incident cases who were diagnosed with breast cancer after giving a blood specimen in 1989-90 were matched to 466 controls in a nested case-control study. NAT2 genotype was determined using PCR-RFLP assays. The multivariate relative risk (RR) comparing slow with rapid acetylators was 0.9 (95% CI 0.7-1.2). Among slow acetylators, current smoking immediately prior to diagnosis was not associated with a significant elevation in risk compared with never smoking rapid acetylators (RR = 1.4, 95% CI 0.7-2.6). No significant association was seen between pack-years of smoking and risk of breast cancer among either slow or fast acetylators. A non-significant elevation in risk was observed among women who smoked for > or = 5 years prior to first pregnancy and were rapid acetylators, compared with never smoking rapid acetylators (RR = 1.5, 95% CI 0.9-2.6). In analyses limited to 706 post-menopausal women, the elevated risks for current smokers immediately prior to diagnosis who were slow acetylators compared with never smokers who were fast acetylators were slightly stronger but still not statistically significant. In summary, we observed little evidence of an association between NAT2 genotype and breast cancer. In this prospective study, cigarette smoking was not appreciably associated with breast cancer among either slow or fast NAT2 acetylators.
A common deletion polymorphism in the gene coding for the glutathione S-transferase class mu (the GSTM1 gene) results in a decreased ability to detoxify carcinogenic epoxide intermediates and has been associated with increased breast cancer risk in some small studies. We studied the GSTM1 gene deletion polymorphism (conferring the null genotype) in 243 women who had prevalent breast cancer and 245 women without breast cancer, who were among the 32,826 women in the Nurses' Health Study who gave a blood sample in 1989-1990. In the prevalent case series, the null genotype was slightly more common among cases (58%) than among controls (51%; age-adjusted odds ratio = 1.30; 95% confidence interval, 0.91-1.86). Among cases, the prevalence of the GSTM1 deletion increased with duration of survival [68% for > or = 8 years since diagnosis; 57% for 4-8 years; 51% for < 4 years; P (trend) = 0.04]. In an incident case series of 240 women who were diagnosed with breast cancer following blood collection and prior to June of 1992 and compared with age-matched controls, the GSTM1 deletion was not associated with an elevation in risk (relative risk, 1.08; 95% confidence interval, 0.74-1.57). No significant interaction with cigarette smoking was evident. Thus, there was no significant increase in risk of incident breast cancer associated with the GSTM1 null genotype; however, the gene deletion polymorphism appeared to confer improved survival. These data suggest that odds ratios based upon prevalent cases in molecular epidemiologic studies may be biased due to differential survival. Further studies are required to determine whether this polymorphism is associated with improved breast cancer prognosis.
To assess the association of minimal parenchymal fibrosis and pleural plaques with respiratory functional impairment, we conducted a survey of 631 asbestos-exposed construction carpenters. This population had a relatively low prevalence of radiographic abnormalities and lung function impairment. Pleural plaques was the asbestos-related disease most prevalent, followed by interstitial fibrosis with predominantly low profusion scores. The most frequent functional impairment was the obstructive pattern, followed by restrictive and mixed patterns. After adjusting for potential confounders, the presence of pleural plaques was significantly associated with a mixed respiratory pattern of impairment (OR = 3.7, 95% CI 1.4-12.3). Furthermore, our data were consistent with a weak association between pleural plaques and a predominantly restrictive defect (OR-1.3, 95% CI 0.4-3.9). This study also suggested an association between minimally detectable profusions and both obstructive (OR = 1.9, 95% CI 0.6-6.3) and mixed (OR = 1.6, 95% CI 0.3-7.1) defects. Although only 631 of a potential 7,649 active and retired union members participated in this first-time survey and were relatively young, these findings add new evidence to the functional importance of pleural fibrosis and minimal parenchymal fibrosis.
Recent studies have utilized nasal lavage to study the inflammatory cells of the nasal epithelium. In unexposed subjects, investigators have reported wide interindividual variability in lavage cell counts. The intraindividual variability of cell counts in sequential lavages has been less well described. Investigators have also reported that nasal lavage may washout cells, resulting in lower cell counts on subsequent lavages. The present study was designed to characterize both the variability in cell counts in unexposed volunteers and the kinetics of cell washout. Twenty-one subjects participated in two nasal lavage trials. In Trial 1, a baseline lavage was followed by a lavage 72 h later; in Trial 2, the baseline lavage was followed by a lavage 48 h later. Intraclass correlation coefficients of reliability (R) were calculated for each trial. In Trial 1, the R was 0.88, with a one-sided confidence interval > or = 0.75, whereas in Trial 2 R was 0.67, with a confidence interval > or = 0.40. The smaller R in Trial 2 may suggest that washout was more evident at 48 h than at 72 h after the baseline lavage. Furthermore, these R values suggest that within-subject variability is smaller than between-subject variability, supporting the utility of nasal lavage as a reliable technique for investigating the nasal cavity response to air pollutants.