Dr Maggie Cheang
Group Leader: ICR-CTSU Integrative Genomic Analysis in Clinical Trials
Biography
Dr Maggie Cheang have extensive multidisciplinary experience in cutting-edge fields including biomedical sciences, cancer genomics (bioinformatics), pathology and clinical trials. Her main research focus is in the molecular classification of tumours and the development of multi-parametric (multi-modal) genomics assays by integrative analyses and to identify clinically relevant biomarkers that can be used as intermediate biological endpoints for phase II (platform) trials for targeted therapies. Dr Cheang currently leads a multidisciplinary research group of statistical, computational and translational scientists, strategically within the Clinical Trials and Statistics Unit at The Institute of Cancer Research, to develop novel and efficient computational analytical methods for the application of high-dimensional multi-omics data generated from bio-specimens collected in clinical trials.
Dr Cheang grew up in Vancouver, Canada and obtained her PhD in Pathology and Laboratory Medicine under the supervision of Professor Torsten Nielsen from the University of British Columbia in Canada. She then received a prestigious Canadian Cancer Society/Terry Fox Foundation Postdoctoral Fellowship to train with Professor Charles Perou, a pioneer in identifying subtypes of breast cancer, at the Lineberger Comprehensive Cancer Center at the University of North Carolina, US.
She has co-invented several biomarkers which inform the design of biomarker driven trials. Her longstanding research interest is also to determine the clinical utility of new biomarkers to predict sensitivity of therapeutic agents in Phase III clinical trials. She co-invented the 50 genes-based classifier for the intrinsic subtypes of breast cancer, commonly known as PAM50 and is currently licensed by Veracyte as Prosigna®, an assay integrated into multiple international clinical practice guidelines.
Her research achievements have been internationally recognised by numerous awards, grants and memberships. She was a Merit Award recipient at the American Society of Clinical Oncology Meeting in 2011 and received a Clinical Science Scholar Scholarship at the CTRC-AACR San Antonio Breast Cancer Symposium in 2011. Dr Cheang was also a recipient of a Career Development Award for Junior Faculty funded by ReThink Breast Cancer Canada in 2011–12; two Novartis Oncology Young Canadian Investigator Awards (2011, 2008); and a National Cancer Institute of Canada Traveling Award for senior graduate students (2007–08).
She consults on several trial management and translational research committees for phase II and III trials. As a mark of her standing in the field, she currently serves as an Associate Editor of BMC Cancer and npj Breast cancer, member of Breast Cancer Now Scientific and UKRI/MRC Clinical Academic Research Partnerships grant panels.
She serves as Chair of the National Cancer Research Institute (NCRI) CM-Path Clinical Trials Pathology Advisory Group (CT-PAG), chairs the NCRI Next-generation Pathology Working Group. She is a member of the International Breast Cancer Research Foundation Immuno-oncology Biomarker working group and Roche’s imCORE Advanced Analytics Network.
Outside of work, she enjoys playing piano and snowboarding.
Types of Publications
Journal articles
The identification of early-stage breast cancer patients at high risk of relapse would allow tailoring of adjuvant therapy approaches. We assessed whether analysis of circulating tumor DNA (ctDNA) in plasma can be used to monitor for minimal residual disease (MRD) in breast cancer. In a prospective cohort of 55 early breast cancer patients receiving neoadjuvant chemotherapy, detection of ctDNA in plasma after completion of apparently curative treatment-either at a single postsurgical time point or with serial follow-up plasma samples-predicted metastatic relapse with high accuracy [hazard ratio, 25.1 (confidence interval, 4.08 to 130.5; log-rank P < 0.0001) or 12.0 (confidence interval, 3.36 to 43.07; log-rank P < 0.0001), respectively]. Mutation tracking in serial samples increased sensitivity for the prediction of relapse, with a median lead time of 7.9 months over clinical relapse. We further demonstrated that targeted capture sequencing analysis of ctDNA could define the genetic events of MRD, and that MRD sequencing predicted the genetic events of the subsequent metastatic relapse more accurately than sequencing of the primary cancer. Mutation tracking can therefore identify early breast cancer patients at high risk of relapse. Subsequent adjuvant therapeutic interventions could be tailored to the genetic events present in the MRD, a therapeutic approach that could in part combat the challenge posed by intratumor genetic heterogeneity.
Germline mutations in BRCA1/2 predispose individuals to breast cancer (termed germline-mutated BRCA1/2 breast cancer, gBRCA-BC) by impairing homologous recombination (HR) and causing genomic instability. HR also repairs DNA lesions caused by platinum agents and PARP inhibitors. Triple-negative breast cancers (TNBCs) harbor subpopulations with BRCA1/2 mutations, hypothesized to be especially platinum-sensitive. Cancers in putative 'BRCAness' subgroups-tumors with BRCA1 methylation; low levels of BRCA1 mRNA (BRCA1 mRNA-low); or mutational signatures for HR deficiency and those with basal phenotypes-may also be sensitive to platinum. We assessed the efficacy of carboplatin and another mechanistically distinct therapy, docetaxel, in a phase 3 trial in subjects with unselected advanced TNBC. A prespecified protocol enabled biomarker-treatment interaction analyses in gBRCA-BC and BRCAness subgroups. The primary endpoint was objective response rate (ORR). In the unselected population (376 subjects; 188 carboplatin, 188 docetaxel), carboplatin was not more active than docetaxel (ORR, 31.4% versus 34.0%, respectively; P = 0.66). In contrast, in subjects with gBRCA-BC, carboplatin had double the ORR of docetaxel (68% versus 33%, respectively; biomarker, treatment interaction P = 0.01). Such benefit was not observed for subjects with BRCA1 methylation, BRCA1 mRNA-low tumors or a high score in a Myriad HRD assay. Significant interaction between treatment and the basal-like subtype was driven by high docetaxel response in the nonbasal subgroup. We conclude that patients with advanced TNBC benefit from characterization of BRCA1/2 mutations, but not BRCA1 methylation or Myriad HRD analyses, to inform choices on platinum-based chemotherapy. Additionally, gene expression analysis of basal-like cancers may also influence treatment selection.
Background: Genomic data from human epidermal growth factor receptor 2-positive (HER2+) tumors were analyzed to assess the association between intrinsic subtype and clinical outcome in a large, well-annotated patient cohort. Methods: Samples from the NCCTG (Alliance) N9831 trial were analyzed using the Prosigna algorithm on the NanoString platform to define intrinsic subtype, risk of recurrence scores, and risk categories for 1392 HER2+ tumors. Subtypes were evaluated for recurrence-free survival (RFS) using Kaplan-Meier and Cox model analysis following adjuvant chemotherapy (n = 484) or chemotherapy plus trastuzumab (n = 908). All statistical tests were two-sided. Results: Patients with HER2+ tumors from N9831 were primarily scored as HER2-enriched (72.1%). These individuals received statistically significant benefit from trastuzumab (hazard ratio [HR] = 0.68, 95% confidence interval [CI] = 0.52 to 0.89, P = .005), as did the patients (291 of 1392) with luminal-type tumors (HR = 0.52, 95% CI = 0.32 to 0.85, P = .01). Patients with basal-like tumors (97 of 1392) did not have statistically significantly better RFS when treated with trastuzumab and chemotherapy compared with chemotherapy alone (HR = 1.06, 95% CI = 0.53 to 2.13, P = .87). Conclusions: The majority of clinically defined HER2-positive tumors were classified as HER2-enriched or luminal using the Prosigna algorithm. Intrinsic subtype alone cannot replace conventional histopathological evaluation of HER2 status because many tumors that are classified as luminal A or luminal B will benefit from adjuvant trastuzumab if that subtype is accompanied by HER2 overexpression. However, among tumors that overexpress HER2, we speculate that assessment of intrinsic subtype may influence treatment, particularly with respect to evaluating alternative therapeutic approaches for that subset of HER2-positive tumors of the basal-like subtype.
BACKGROUND: Retrospective analyses of NSABP B20 and SWOG 8814 showed a large benefit of chemotherapy in patients with ER-positive tumors and high OncotypeDX Recurrence Score (RS≥31). However, it might be possible that both studies may be contaminated by non-luminal tumors, especially in high-risk RS group. METHODS: We conducted simulations in order to obtain a better understanding of how the NSABP B20 and SWOG 8814 results would have been if non-luminal breast cancer would have been excluded. Simulations were done separately for the node-negative and node-positive cohorts. RESULTS AND CONCLUSION: The results of the simulations suggest that the non-luminal tumors are augmenting the apparent benefit of chemotherapy, but do not appear to be responsible for the entire effect. These simulations could provide information about the potential influence of contamination by unexpected tumor subtypes on the future results of TAILORx and RxPONDER clinical trials.
Importance: The value of the intrinsic subtypes of breast cancer (luminal A, luminal B, human epidermal growth factor receptor 2 [currently known as ERBB2, but referred to as HER2 in this study]-enriched, and basal-like) in the metastatic setting is currently unknown. Objective: To evaluate the association of the intrinsic subtypes of breast cancer with outcome and/or benefit in hormone receptor (HR)-positive metastatic breast cancer. Design, Setting, and Participants: Unplanned retrospective analysis of 821 tumor samples (85.7% primary and 14.3% metastatic) from the EGF30008 phase 3 clinical trial (NCT00073528), in which postmenopausal women with HR-positive invasive breast cancer and no prior therapy for advanced or metastatic disease were randomized to letrozole with or without lapatinib, an epidermal growth factor receptor (EGFR)/HER2 tyrosine kinase inhibitor. Tumor samples were classified into each subtype using the research-based PAM50 classifier. Prior neoadjuvant/adjuvant antiestrogen therapy was allowed. Patients with extensive symptomatic visceral disease were excluded. Treatment effects were evaluated using interaction tests. Main Outcomes and Measures: Primary and secondary end points were progression-free survival and overall survival. Results: The median (range) age was 62 (31-94) years. Intrinsic subtype was the strongest prognostic factor independently associated with progression-free survival and overall survival in all patients, and in patients with HER2-negative (n = 644) or HER2-positive (n = 157) diseases. Median progression-free survival differed across the intrinsic subtypes of clinically HER2-negative disease: luminal A (16.9 [95% CI, 14.1-19.9] months), luminal B (11.0 [95% CI, 9.6-13.6] months), HER2-enriched (4.7 [95% CI, 2.7-10.8] months), and basal-like (4.1 [95% CI, 2.5-13.8] months). Median OS also differed across the intrinsic subtypes: luminal A (45 [95% CI, 41-not applicable {NA}] months), luminal B (37 [95% CI, 31-42] months), HER2-enriched (16 [95% CI, 10-NA] months), and basal-like (23 [95% CI, 12-NA] months). Patients with HER2-negative/HER2-enriched disease benefited from lapatinib therapy (median PFS, 6.49 vs 2.60 months; progression-free survival hazard ratio, 0.238 [95% CI, 0.066-0.863]; interaction P = .02). Conclusions and Relevance: This is the first study to reveal an association between intrinsic subtype and outcome in first-line HR-positive metastatic breast cancer. Patients with HR-positive/HER2-negative disease with a HER2-enriched profile may benefit from lapatinib in combination with endocrine therapy. The clinical value of intrinsic subtyping in hormone receptor-positive metastatic breast cancer warrants further investigation, but patients with luminal A/HER2-negative metastatic breast cancer might be good candidates for letrozole monotherapy in the first-line setting regardless of visceral disease and number of metastases.
<h4>Purpose</h4>To determine intrinsic breast cancer subtypes represented within categories defined by quantitative hormone receptor (HR) and HER2 expression.<h4>Methods</h4>We merged 1,557 cases from three randomized phase III trials into a single data set. These breast tumors were centrally reviewed in each trial for quantitative ER, PR, and HER2 expression by immunohistochemistry (IHC) stain and by reverse transcription-quantitative polymerase chain reaction (RT-qPCR), with intrinsic subtyping by research-based PAM50 RT-qPCR assay.<h4>Results</h4>Among 283 HER2-negative tumors with <1% HR expression by IHC, 207 (73%) were basal-like; other subtypes, particularly HER2-enriched (48, 17%), were present. Among the 1,298 HER2-negative tumors, borderline HR (1%-9% staining) was uncommon (n = 39), and these tumors were heterogeneous: 17 (44%) luminal A/B, 12 (31%) HER2-enriched, and only 7 (18%) basal-like. Including them in the definition of triple-negative breast cancer significantly diminished enrichment for basal-like cancer (p < .05). Among 106 HER2-positive tumors with <1% HR expression by IHC, the HER2-enriched subtype was the most frequent (87, 82%), whereas among 127 HER2-positive tumors with strong HR (>10%) expression, only 69 (54%) were HER2-enriched and 55 (43%) were luminal (39 luminal B, 16 luminal A). Quantitative HR expression by RT-qPCR gave similar results. Regardless of methodology, basal-like cases seldom expressed ER/ESR1 or PR/PGR and were associated with the lowest expression level of HER2/ERBB2 relative to other subtypes.<h4>Conclusion</h4>Significant discordance remains between clinical assay-defined subsets and intrinsic subtype. For identifying basal-like breast cancer, the optimal HR IHC cut point was <1%, matching the American Society of Clinical Oncology and College of American Pathologists guidelines. Tumors with borderline HR staining are molecularly diverse and may require additional assays to clarify underlying biology.
<h4>Background/objectives</h4>The molecular chaperone αB-crystallin is expressed in estrogen receptor, progesterone receptor and human epidermal growth factor receptor-2 "triple-negative" breast carcinomas and promotes brain and lung metastasis. We examined αB-crystallin expression in primary breast carcinomas with metastatic data to evaluate its association with prognosis and site-specific metastases.<h4>Methods</h4>αB-crystallin gene (<i>CRYAB</i>) expression was examined using publically available global-gene expression data (n=855 breast tumors) with first site of distant metastasis information ("855Met"). αB-crystallin protein expression was determined by immunohistochemistry using the clinically annotated tissue microarray (n=3987 breast tumors) from British Columbia Cancer Agency (BCCA). Kaplan-Meier and multivariable Cox regression analyses were used to evaluate the prognostic value of αB-crystallin. Multivariable logistic regression analysis was used to evaluate risks of αB-crystallin and other markers for site of metastasis.<h4>Results</h4>In the 855Met dataset, αB-crystallin gene (<i>CRYAB)</i> expression was an independent predictor of brain as the first distant site of relapse (HR = 1.2, (95% CI 1.0-1.4), <i>P</i> = 0.021). In the BCCA series, αB-crystallin protein expression was an independent prognostic marker of poor breast cancer specific survival (HR = 1.3, (95% CI 1.1-1.6), <i>P</i> = 0.014). Among patients with metastases, αB-crystallin was the strongest independent predictor of brain metastasis (OR = 2.99 (95% CI 1.83-4.89), <i>P</i> < 0.0001) and the only independent predictor of brain as the first site of distant metastasis (OR = 3.15 (95% CI1.43-6.95), <i>P</i> = 0.005). αB-crystallin was also associated with worse survival (3.0 versus 4.7 months, <i>P</i> = 0.007).<h4>Conclusions</h4>αB-crystallin is a promising biomarker to identify breast cancer patients at high risk for early relapse in the brain, independent of ER and HER2 status.
<h4>Background</h4>Oestrogen receptor positive/ human epidermal growth factor receptor positive (ER+/HER2+) breast cancers (BCs) are less responsive to endocrine therapy than ER+/HER2- tumours. Mechanisms underpinning the differential behaviour of ER+HER2+ tumours are poorly characterised. Our aim was to identify biomarkers of response to 2 weeks' presurgical AI treatment in ER+/HER2+ BCs.<h4>Methods</h4>All available ER+/HER2+ BC baseline tumours (n=342) in the POETIC trial were gene expression profiled using BC360™ (NanoString) covering intrinsic subtypes and 46 key biological signatures. Early response to AI was assessed by changes in Ki67 expression and residual Ki67 at 2 weeks (Ki67<sub>2wk</sub>). Time-To-Recurrence (TTR) was estimated using Kaplan-Meier methods and Cox models adjusted for standard clinicopathological variables. New molecular subgroups (MS) were identified using consensus clustering.<h4>Findings</h4>HER2-enriched (HER2-E) subtype BCs (44.7% of the total) showed poorer Ki67 response and higher Ki67<sub>2wk</sub> (p<0.0001) than non-HER2-E BCs. High expression of ERBB2 expression, homologous recombination deficiency (HRD) and TP53 mutational score were associated with poor response and immune-related signatures with High Ki67<sub>2wk</sub>. Five new MS that were associated with differential response to AI were identified. HER2-E had significantly poorer TTR compared to Luminal BCs (HR 2.55, 95% CI 1.14-5.69; p=0.0222). The new MS were independent predictors of TTR, adding significant value beyond intrinsic subtypes.<h4>Interpretation</h4>Our results show HER2-E as a standardised biomarker associated with poor response to AI and worse outcome in ER+/HER2+. HRD, TP53 mutational score and immune-tumour tolerance are predictive biomarkers for poor response to AI. Lastly, novel MS identify additional non-HER2-E tumours not responding to AI with an increased risk of relapse.<h4>Funding</h4>Cancer Research UK (CRUK/07/015).
<h4>Purpose</h4>Aromatase inhibitor (AI) treatment is the standard of care for postmenopausal women with primary estrogen receptor-positive breast cancer. The impact of duration of neoadjuvant endocrine therapy (NET) on molecular characteristics is still unknown. We evaluated and compared changes of gene expression profiles under short-term (2-week) versus longer-term neoadjuvant AIs.<h4>Experimental design</h4>Global gene expression profiles from the PeriOperative Endocrine Therapy for Individualised Care (POETIC) trial (137 received 2 weeks of AIs and 47 received no treatment) and targeted gene expression from 80 patients with breast cancer treated with NET for more than 1 month (NeoAI) were assessed. Intrinsic subtyping, module scores covering different cancer pathways and immune-related genes were calculated for pretreated and posttreated tumors.<h4>Results</h4>The differences in intrinsic subtypes after NET were comparable between the two cohorts, with most Luminal B (90.0% in the POETIC trial and 76.3% in NeoAI) and 50.0% of HER2 enriched at baseline reclassified as Luminal A or normal-like after NET. Downregulation of proliferative-related pathways was observed after 2 weeks of AIs. However, more changes in genes from cancer-signaling pathways such as MAPK and PI3K/AKT/mTOR and immune response/immune-checkpoint components that were associated with AI-resistant tumors and differential outcome were observed in the NeoAI study.<h4>Conclusions</h4>Tumor transcriptional profiles undergo bigger changes in response to longer NET. Changes in HER2-enriched and Luminal B subtypes are similar between the two cohorts, thus AI-sensitive intrinsic subtype tumors associated with good survival might be identified after 2 weeks of AI. The changes of immune-checkpoint component expression in early AI resistance and its impact on survival outcome warrants careful investigation in clinical trials.
<h4>Purpose</h4>To determine (i) the relationship between candidate biomarkers of the antiproliferative (Ki67) response to letrozole and palbociclib alone and combined in ER<sup>+</sup>/HER2<sup>-</sup> breast cancer; and (ii) the pharmacodynamic effect of the agents on the biomarkers.<h4>Experimental design</h4>307 postmenopausal women with ER<sup>+</sup>/HER2<sup>-</sup> primary breast cancer were randomly assigned to neoadjuvant treatment with letrozole for 14 weeks; letrozole for 2 weeks, then letrozole+palbociclib to 14 weeks; palbociclib for 2 weeks, then letrozole+palbociclib to 14 weeks; or letrozole+palbociclib for 14 weeks. Biopsies were taken at baseline, 2 and 14 weeks and surgery at varying times after stopping palbociclib. Immunohistochemical analyses were conducted for Ki67, c-PARP, ER, PgR, RB1, CCNE1, and CCND1.<h4>Results</h4>Higher baselines ER and PgR were significantly associated with a greater chance of complete cell-cycle arrest (CCCA: Ki67 <2.7%) at 14 weeks and higher baseline Ki67, c-PARP, and CCNE1 with a lower chance. The interaction with treatment was significant only for c-PARP. CCND1 levels were decreased c.20% by letrozole at 2 and 14 weeks but showed a tendency to increase with palbociclib. CCNE1 levels fell 82% (median) in tumors showing CCCA but were unchanged in those with no CCCA. Only 2/9 tumors showed CCCA 3-9 days after stopping palbociclib. <i>ESR1</i> mutations were found in 2/4 tumors for which surgery took place ≥6 months after starting treatment.<h4>Conclusions</h4>High CCNE1 levels were confirmed as a biomarker of resistance to letrozole+palbociclib. Ki67 recovery within 3-9 days of discontinuing palbociclib indicates incomplete suppression of proliferation during the "off" week of its schedule.
<jats:p>Breast cancer is a heterogenous disease with variability in tumor cells and in the surrounding tumor microenvironment (TME). Understanding the molecular diversity in breast cancer is critical for improving prediction of therapeutic response and prognostication. High-plex spatial profiling of tumors enables characterization of heterogeneity in the breast TME, which can holistically illuminate the biology of tumor growth, dissemination and, ultimately, response to therapy. The GeoMx Digital Spatial Profiler (DSP) enables researchers to spatially resolve and quantify proteins and RNA transcripts from tissue sections. The platform is compatible with both formalin-fixed paraffin-embedded and frozen tissues. RNA profiling was developed at the whole transcriptome level for human and mouse samples and protein profiling of 100-plex for human samples. Tissue can be optically segmented for analysis of regions of interest or cell populations to study biology-directed tissue characterization. The GeoMx Breast Cancer Consortium (GBCC) is composed of breast cancer researchers who are developing innovative approaches for spatial profiling to accelerate biomarker discovery. Here, the GBCC presents best practices for GeoMx profiling to promote the collection of high-quality data, optimization of data analysis and integration of datasets to advance collaboration and meta-analyses. Although the capabilities of the platform are presented in the context of breast cancer research, they can be generalized to a variety of other tumor types that are characterized by high heterogeneity.</jats:p>
Multi-gene prognostic signatures including the Oncotype® DX Recurrence Score (RS), EndoPredict® (EP) and Prosigna® (Risk Of Recurrence, ROR) are widely used to predict the likelihood of distant recurrence in patients with oestrogen-receptor-positive (ER+), HER2-negative breast cancer. Here, we describe the development and validation of methods to recapitulate RS, EP and ROR scores from NanoString expression data. RNA was available from 107 tumours from postmenopausal women with early-stage, ER+, HER2- breast cancer from the translational Arimidex, Tamoxifen, Alone or in Combination study (TransATAC) where previously these signatures had been assessed with commercial methodology. Gene expression was measured using NanoString nCounter. For RS and EP, conversion factors to adjust for cross-platform variation were estimated using linear regression. For ROR, the steps to perform subgroup-specific normalisation of the gene expression data and calibration factors to calculate the 46-gene ROR score were assessed and verified. Training with bootstrapping (n = 59) was followed by validation (n = 48) using adjusted, research use only (RUO) NanoString-based algorithms. In the validation set, there was excellent concordance between the RUO scores and their commercial counterparts (r<sub>c</sub>(RS) = 0.96, 95% CI 0.93-0.97 with level of agreement (LoA) of -7.69 to 8.12; r<sub>c</sub>(EP) = 0.97, 95% CI 0.96-0.98 with LoA of -0.64 to 1.26 and r<sub>c</sub>(ROR) = 0.97 (95% CI 0.94-0.98) with LoA of -8.65 to 10.54). There was also a strong agreement in risk stratification: (RS: κ = 0.86, p < 0.0001; EP: κ = 0.87, p < 0.0001; ROR: κ = 0.92, p < 0.001). In conclusion, the calibrated algorithms recapitulate the commercial RS and EP scores on individual biopsies and ROR scores on samples based on subgroup-centreing method using NanoString expression data.
The rapidly evolving landscape of immuno-oncology (IO) is redefining the treatment of a number of cancer types. IO treatments are becoming increasingly complex, with different types of drugs emerging beyond checkpoint inhibitors. However, many of the new drugs either do not progress from phase I-II clinical trials or even fail in late-phase trials. We have identified at least five areas in the development of promising IO treatments that should be redefined for more efficient designs and accelerated approvals. Here we review those critical aspects of IO drug development that could be optimized for more successful outcome rates in all cancer types. It is important to focus our efforts on the mechanisms of action, types of response and adverse events of these novel agents. The use of appropriate clinical trial designs with robust biomarkers of response and surrogate endpoints will undoubtedly facilitate the development and subsequent approval of these drugs. Further research is also needed to establish biomarker-driven strategies to select which patients may benefit from immunotherapy and identify potential mechanisms of resistance.
The concept of precision medicine has been around for many years and recent advances in high-throughput sequencing techniques are enabling this to become reality. Within the field of breast cancer, a number of signatures have been developed to molecularly sub-classify tumours. Notable examples recently approved by National Institute for Health and Care Excellence in the UK to guide treatment decisions for oestrogen receptors (ER)+ human epidermal growth factor receptor 2 (HER2)- patients include Prosigna test, EndoPredict, and Oncotype DX. However, a population of still unmet need are those with triple negative breast cancer (TNBC). Accounting for 15-20% of patients, this population has comparatively poor prognosis and as yet no targeted treatment options. Studies have shown that some patients with TNBC respond favourably to DNA damaging drugs (carboplatin) or agents which inhibit DNA damage response (poly ADP ribose polymerase (PARP) inhibitors). Known to be a heterogeneous population, there is a need to identify further TNBC patients who may benefit from these treatments. A number of signatures have been identified based on association with treatment response or specific genetic features/pathways however many of these were not restricted to TNBC patients and as of yet are not common practice in the clinic.
Breast cancer is a highly heterogeneous disease. Although differences between intrinsic breast cancer subtypes have been well studied, heterogeneity within each subtype, especially luminal-A cancers, requires further interrogation to personalize disease management. Here, we applied well-characterized and cancer-associated heterocellular signatures representing stem, mesenchymal, stromal, immune, and epithelial cell types to breast cancer. This analysis stratified the luminal-A breast cancer samples into five subtypes with a majority of them enriched for a subtype (stem-like) that has increased stem and stromal cell gene signatures, representing potential luminal progenitor origin. The enrichment of immune checkpoint genes and other immune cell types in two (including stem-like) of the five heterocellular subtypes of luminal-A tumors suggest their potential response to immunotherapy. These immune-enriched subtypes of luminal-A tumors (containing only estrogen receptor positive samples) showed good or intermediate prognosis along with the two other differentiated subtypes as assessed using recurrence-free and distant metastasis-free patient survival outcomes. On the other hand, a partially differentiated subtype of luminal-A breast cancer with transit-amplifying colon-crypt characteristics showed poor prognosis. Furthermore, published luminal-A subtypes associated with specific somatic copy number alterations and mutations shared similar cellular and mutational characteristics to colorectal cancer subtypes where the heterocellular signatures were derived. These heterocellular subtypes reveal transcriptome and cell-type based heterogeneity of luminal-A and other breast cancer subtypes that may be useful for additional understanding of the cancer type and potential patient stratification and personalized medicine.
<h4>Purpose</h4>CDK4/6 inhibitors are used to treat estrogen receptor (ER)-positive metastatic breast cancer (BC) in combination with endocrine therapy. PALLET is a phase II randomized trial that evaluated the effects of combination palbociclib plus letrozole as neoadjuvant therapy.<h4>Patients and methods</h4>Postmenopausal women with ER-positive primary BC and tumors greater than or equal to 2.0 cm were randomly assigned 3:2:2:2 to letrozole (2.5 mg/d) for 14 weeks (A); letrozole for 2 weeks, then palbociclib plus letrozole to 14 weeks (B); palbociclib for 2 weeks, then palbociclib plus letrozole to 14 weeks (C); or palbociclib plus letrozole for 14 weeks. Palbociclib 125 mg/d was administered orally on a 21-days-on, 7-days-off schedule. Core-cut biopsies were taken at baseline and 2 and 14 weeks. Coprimary end points for letrozole versus palbociclib plus letrozole groups (A v B + C + D) were change in Ki-67 (protein encoded by the MKI67 gene; immunohistochemistry) between baseline and 14 weeks and clinical response (ordinal and ultrasound) after 14 weeks. Complete cell-cycle arrest was defined as Ki-67 less than or equal to 2.7%. Apoptosis was characterized by cleaved poly (ADP-ribose) polymerase.<h4>Results</h4>Three hundred seven patients were recruited. Clinical response was not significantly different between palbociclib plus letrozole and letrozole groups ( P = .20; complete response + partial response, 54.3% v 49.5%), and progressive disease was 3.2% versus 5.4%, respectively. Median log-fold change in Ki-67 was greater with palbociclib plus letrozole compared with letrozole (-4.1 v -2.2; P < .001) in the 190 evaluable patients (61.9%), corresponding to a geometric mean change of -97.4% versus -88.5%. More patients on palbociclib plus letrozole achieved complete cell-cycle arrest (90% v 59%; P < .001). Median log-fold change (suppression) of cleaved poly (ADP-ribose) polymerase was greater with palbociclib plus letrozole versus letrozole (-0.80 v -0.42; P < .001). More patients had grade 3 or greater toxicity on palbociclib plus letrozole (49.8% v 17.0%; P < .001) mainly because of asymptomatic neutropenia.<h4>Conclusion</h4>Adding palbociclib to letrozole significantly enhanced the suppression of malignant cell proliferation (Ki-67) in primary ER-positive BC, but did not increase the clinical response rate over 14 weeks, which was possibly related to a concurrent reduction in apoptosis.
BACKGROUND: Preoperative and perioperative aromatase inhibitor (POAI) therapy has the potential to improve outcomes in women with operable oestrogen receptor-positive primary breast cancer. It has also been suggested that tumour Ki67 values after 2 weeks (Ki672W) of POAI predicts individual patient outcome better than baseline Ki67 (Ki67B). The POETIC trial aimed to test these two hypotheses. METHODS: POETIC was an open-label, multicentre, parallel-group, randomised, phase 3 trial (done in 130 UK hospitals) in which postmenopausal women aged at least 50 years with WHO performance status 0-1 and hormone receptor-positive, operable breast cancer were randomly assigned (2:1) to POAI (letrozole 2·5 mg per day orally or anastrozole 1 mg per day orally) for 14 days before and following surgery or no POAI (control). Adjuvant treatment was given as per UK standard local practice. Randomisation was done centrally by computer-generated permuted block method (variable block size of six or nine) and was stratified by hospital. Treatment allocation was not masked. The primary endpoint was time to recurrence. A key second objective explored association between Ki67 (dichotomised at 10%) and disease outcomes. The primary analysis for clinical endpoints was by modified intention to treat (excluding patients who withdrew consent). For Ki67 biomarker association and endpoint analysis, the evaluable population included all randomly assigned patients who had paired Ki67 values available. This study is registered with ClinicalTrials.gov, NCT02338310; the European Clinical Trials database, EudraCT2007-003877-21; and the ISRCTN registry, ISRCTN63882543. Recruitment is complete and long-term follow-up is ongoing. FINDINGS: Between Oct 13, 2008, and April 16, 2014, 4480 women were recruited and randomly assigned to POAI (n=2976) or control (n=1504). On Feb 6, 2018, median follow-up was 62·9 months (IQR 58·1-74·1). 434 (10%) of 4480 women had a breast cancer recurrence (280 [9%] POAI; 154 [10%] control), hazard ratio 0·92 (95% CI 0·75-1·12); p=0·40 with the proportion free from breast cancer recurrence at 5 years of 91·0% (95% CI 89·9-92·0) for patients in the POAI group and 90·4% (88·7-91·9) in the control group. Within the POAI-treated HER2-negative subpopulation, 5-year recurrence risk in women with low Ki67B and Ki672W (low-low) was 4·3% (95% CI 2·9-6·3), 8·4% (6·8-10·5) with high Ki67B and low Ki672W (high-low) and 21·5% (17·1-27·0) with high Ki67B and Ki672W (high-high). Within the POAI-treated HER2-positive subpopulation, 5-year recurrence risk in the low-low group was 10·1% (95% CI 3·2-31·3), 7·7% (3·4-17·5) in the high-low group, and 15·7% (10·1-24·4) in the high-high group. The most commonly reported grade 3 adverse events were hot flushes (20 [1%] of 2801 patients in the POAI group vs six [<1%] of 1400 in the control group) and musculoskeletal pain (29 [1%] vs 13 [1%]). No treatment-related deaths were reported. INTERPRETATION: POAI has not been shown to improve treatment outcome, but can be used without detriment to help select appropriate adjuvant therapy based on tumour Ki67. Most patients with low Ki67B or low POAI-induced Ki672W do well with adjuvant standard endocrine therapy (giving consideration to clinical-pathological factors), whereas those whose POAI-induced Ki672W remains high might benefit from further adjuvant treatment or trials of new therapies. FUNDING: Cancer Research UK.
Types of Publications
Journal articles
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.
The identification of early-stage breast cancer patients at high risk of relapse would allow tailoring of adjuvant therapy approaches. We assessed whether analysis of circulating tumor DNA (ctDNA) in plasma can be used to monitor for minimal residual disease (MRD) in breast cancer. In a prospective cohort of 55 early breast cancer patients receiving neoadjuvant chemotherapy, detection of ctDNA in plasma after completion of apparently curative treatment-either at a single postsurgical time point or with serial follow-up plasma samples-predicted metastatic relapse with high accuracy [hazard ratio, 25.1 (confidence interval, 4.08 to 130.5; log-rank P < 0.0001) or 12.0 (confidence interval, 3.36 to 43.07; log-rank P < 0.0001), respectively]. Mutation tracking in serial samples increased sensitivity for the prediction of relapse, with a median lead time of 7.9 months over clinical relapse. We further demonstrated that targeted capture sequencing analysis of ctDNA could define the genetic events of MRD, and that MRD sequencing predicted the genetic events of the subsequent metastatic relapse more accurately than sequencing of the primary cancer. Mutation tracking can therefore identify early breast cancer patients at high risk of relapse. Subsequent adjuvant therapeutic interventions could be tailored to the genetic events present in the MRD, a therapeutic approach that could in part combat the challenge posed by intratumor genetic heterogeneity.
<h4>Unlabelled</h4>Triple-negative breast cancers (TNBC) are characterized by a wide spectrum of genomic alterations, some of which might be caused by defects in DNA repair processes such as homologous recombination (HR). Despite this understanding, associating particular patterns of genomic instability with response to therapy has been challenging. Here, we show that allelic-imbalanced copy-number aberrations (AiCNA) are more prevalent in TNBCs that respond to platinum-based chemotherapy, thus providing a candidate predictive biomarker for this disease. Furthermore, we show that a high level of AiCNA is linked with elevated expression of a meiosis-associated gene, HORMAD1. Elevated HORMAD1 expression suppresses RAD51-dependent HR and drives the use of alternative forms of DNA repair, the generation of AiCNAs, as well as sensitizing cancer cells to HR-targeting therapies. Our data therefore provide a mechanistic association between HORMAD1 expression, a specific pattern of genomic instability, and an association with response to platinum-based chemotherapy in TNBC.<h4>Significance</h4>Previous studies have shown correlation between mutational "scars" and sensitivity to platinums extending beyond associations with BRCA1/2 mutation, but do not elucidate the mechanism. Here, a novel allele-specific copy-number characterization of genome instability identifies and functionally validates the inappropriate expression of the meiotic gene HORMAD1 as a driver of HR deficiency in TNBC, acting to induce allelic imbalance and moderate platinum and PARP inhibitor sensitivity with implications for the use of such "scars" and expression of meiotic genes as predictive biomarkers.
<h4>Background</h4>Intergroup Exemestane Study (IES) was a randomised study that showed a survival benefit of switching adjuvant endocrine therapy after 2-3 years from tamoxifen to exemestane. PathIES aimed to assess the potential prognostic and predictive value of ERβ1 and ERβ2 expression in primary tumours in order to determine benefit in the two treatment arms.<h4>Patients and methods</h4>Primary tumour samples were available for 1256 patients (27% IES population). ERβ1 and ERβ2 expression was dichotomised at the median IHC score (high if ERβ1 ≥ 191, ERβ2 ≥ 164). Hazard ratios (HRs) were estimated by multivariable Cox proportional hazards models adjusting for clinicopathological factors. Treatment effects with biomarker expressions were determined by interaction tests. Analysis explored effects of markers both as a continuous variable and with dichotomised cut-offs.<h4>Results</h4>Neither ERβ1 nor ERβ2 were associated with disease-free survival (DFS) or overall survival (OS) in the whole cohort. In patients treated with continued tamoxifen, high ERβ1 expression compared with low was associated with better DFS [HR = 0.38:95% confidence interval (CI) 0.21-0.68, P = 0.001]. DFS benefit of exemestane over tamoxifen (HR = 0.40:95% CI 0.22-0.70) was found in the low ERβ1 subgroup (interaction P = 0.01). No significant difference with treatment was observed for ERβ2 expression in either DFS or OS.<h4>Conclusion</h4>In the PathIES population, exemestane appeared to be superior to tamoxifen among patients with low ERβ1 expression but not in those with high ERβ1 expression. This is the first trial of its kind to report a parameter potentially predicting benefit of an aromatase inhibitor when compared with tamoxifen and an independent validation is warranted.
Neoadjuvant endocrine therapy is an alternative to chemotherapy for women with oestrogen receptor (ER)-positive early breast cancer (BC). We aimed to assess feasibility of recruiting patients to a study comparing chemotherapy versus endocrine therapy in postmenopausal women with ER-rich primary BC, and response as well as translational endpoints were assessed. Patients requiring neoadjuvant therapy were randomised to chemotherapy: 6 × 3-weekly cycles FE₁₀₀C or endocrine therapy: letrozole 2.5 mg, daily for 18-23 weeks. Primary endpoints were recruitment feasibility and tissue collection. Secondary endpoints included clinical, radiological and pathological response rates, quality of life and translational endpoints. 63/80 patients approached were eligible, of those 44 (70, 95% CI 57-81) were randomised. 12 (54.5, 95% CI 32.2-75.6) chemotherapy patients showed radiological objective response compared with 13 (59.1, 95% CI 36.4-79.3) letrozole patients. Compared with baseline, mean Ki-67 levels fell in both groups at days 2-4 and at surgery [fold change: 0.24 (95% CI 0.12-0.51) and 0.24; (95% CI 0.15-0.37), respectively]. Plasma total cfDNA levels rose from baseline to week 8 [fold change: chemotherapy 2.10 (95% CI 1.47-3.00), letrozole 1.47(95% CI 0.98-2.20)], and were maintained at surgery in the chemotherapy group [chemotherapy 2.63; 95% CI 1.56-4.41), letrozole 0.95 (95% CI 0.71-1.26)]. An increase in plasma let-7a miRNA was seen at surgery for patients with objective radiological response to chemotherapy. Recruitment and tissue collection endpoints were met; however, a larger trial was deemed unfeasible due to slow accrual. Both regimens were equally efficacious. Dynamic changes were seen in Ki-67 and circulating biomarkers in both groups with increases in cfDNA and let-7a miRNA persisting until surgery for chemotherapy patients.
<h4>Background</h4>Gene expression is widely used for the characterisation of breast cancers. Variability due to tissue heterogeneity or measurement error or systematic change due to peri-surgical procedures can affect measurements but is poorly documented. We studied the variability of global gene expression between core-cuts of primary ER+ breast cancers and the impact of delays to tissue stabilisation due to sample X-ray and of diagnostic core cutting.<h4>Methods</h4>Twenty-six paired core-cuts were taken immediately after tumour excision and up to 90 minutes delay due to sample X-ray; 57 paired core-cuts were taken at diagnosis and 2 weeks later at surgical excision. Whole genome expression analysis was conducted on extracted RNA. Correlations and differences were assessed between the expression of individual genes, gene sets/signatures and intrinsic subtypes.<h4>Results</h4>Twenty-three and 56 sample pairs, respectively, were suitable for analysis. The range of correlations for both sample sets were similar with the majority being >0.97 in both. Correlations between pairs for 18 commonly studied genes were also similar between the studies and mainly with Pearson correlation coefficients >0.6 except for a small number of genes, which had a narrow-dynamic range (e.g. MKI67, SNAI2). There was no systematic difference in intrinsic subtyping between the first and second sample of either set but there was c.15 % discordance between the subtype assignments between the pairs, mainly where the subtyping of individual samples was less certain. Increases in the expression of several stress/early-response genes (e.g. FOS, FOSB, JUN) were found in both studies and confirmed findings in earlier smaller studies. Increased expression of IL6, IGFBP2 and MYC (by 17 %, 14 % and 44 %, respectively) occurred between the samples taken 2 weeks apart and again confirmed findings from an earlier study.<h4>Conclusions</h4>There is generally good correlation in gene expression between pairs of core-cuts except where genes have a narrow dynamic range. Similar correlation coefficients to the average gene expression profiles of intrinsic subtype, particularly LumA and LumB, can lead to discordances between assigned subtypes. Substantial changes in expression of early-response genes occur within an hour after surgery and in IL6, IGFB2 and MYC as a result of diagnostic core-cut biopsy.<h4>Trial registration</h4>Trial number CRUK/07/015 . Study start date September 2008.
<h4>Purpose</h4>The primary aim was to derive evidence for or against the clinical importance of several biologic processes in patients treated with neoadjuvant chemotherapy (NAC) by assessing expression of selected genes with prior implications in prognosis or treatment resistance. The secondary aim was to determine the prognostic impact in residual disease of the genes' expression.<h4>Experimental design</h4>Expression levels of 24 genes were quantified by NanoString nCounter on formalin-fixed paraffin-embedded residual tumors from 126 patients treated with NAC and 56 paired presurgical biopsies. The paired t test was used for testing changes in gene expression, and Cox regression and penalized elastic-net Cox Regression for estimating HRs.<h4>Results</h4>After NAC, 12 genes were significantly up- and 8 downregulated. Fourteen genes were significantly associated with time to recurrence in univariable analysis in residual disease. In a multivariable model, ACACB, CD3D, MKI67, and TOP2A added prognostic value independent of clinical ER(-), PgR(-), and HER2(-) status. In ER(+)/HER2(-) patients, ACACB, PAWR, and ERBB2 predicted outcome, whereas CD3D and PAWR were prognostic in ER(-)/HER2(-) patients. By use of elastic-net analysis, a 6-gene signature (ACACB, CD3D, DECORIN, ESR1, MKI67, PLAU) was identified adding prognostic value independent of ER, PgR, and HER2.<h4>Conclusions</h4>Most of the tested genes were significantly enriched or depleted in response to NAC. Expression levels of genes representing proliferation, stromal activation, metabolism, apoptosis, stemcellness, immunologic response, and Ras-ERK activation predicted outcome in residual disease. The multivariable gene models identified could, if validated, be used to identify patients needing additional post-neoadjuvant treatment to improve prognosis. Clin Cancer Res; 22(10); 2405-16. ©2016 AACR.
Triple-negative breast cancers (TNBCs) have poor prognosis and lack targeted therapies. Here we identified increased copy number and expression of the PIM1 proto-oncogene in genomic data sets of patients with TNBC. TNBC cells, but not nonmalignant mammary epithelial cells, were dependent on PIM1 for proliferation and protection from apoptosis. PIM1 knockdown reduced expression of the anti-apoptotic factor BCL2, and dynamic BH3 profiling of apoptotic priming revealed that PIM1 prevents mitochondrial-mediated apoptosis in TNBC cell lines. In TNBC tumors and their cellular models, PIM1 expression was associated with several transcriptional signatures involving the transcription factor MYC, and PIM1 depletion in TNBC cell lines decreased, in a MYC-dependent manner, cell population growth and expression of the MYC target gene MCL1. Treatment with the pan-PIM kinase inhibitor AZD1208 impaired the growth of both cell line and patient-derived xenografts and sensitized them to standard-of-care chemotherapy. This work identifies PIM1 as a malignant-cell-selective target in TNBC and the potential use of PIM1 inhibitors for sensitizing TNBC to chemotherapy-induced apoptotic cell death.
<h4>Background</h4>Intergroup Exemestane Study (IES) was a randomised study that showed a survival benefit of switching adjuvant endocrine therapy after 2-3 years from tamoxifen to exemestane. This PathIES aimed to assess the role of immunohistochemical (IHC)4 score in determining the relative sensitivity to either tamoxifen or sequential treatment with tamoxifen and exemestane.<h4>Patients and methods</h4>Primary tumour samples were available for 1274 patients (27% of IES population). Only patients for whom the IHC4 score could be calculated (based on oestrogen receptor, progesterone receptor, HER2 and Ki67) were included in this analysis (N = 430 patients). The clinical score (C) was based on age, grade, tumour size and nodal status. The association of clinicopathological parameters, IHC4(+C) scores and treatment effect with time to distant recurrence-free survival (TTDR) was assessed in univariable and multivariable Cox regression analyses. A modified clinical score (PathIEscore) (N = 350) was also estimated.<h4>Results</h4>Our results confirm the prognostic importance of the original IHC4, alone and in conjunction with clinical scores, but no significant difference with treatment effects was observed. The combined IHC4 + Clinical PathIES score was prognostic for TTDR (P < 0.001) with a hazard ratio (HR) of 5.54 (95% CI 1.29-23.70) for a change from 1st quartile (Q1) to Q1-Q3 and HR of 15.54 (95% CI 3.70-65.24) for a change from Q1 to Q4.<h4>Conclusion</h4>In the PathIES population, the IHC4 score is useful in predicting long-term relapse in patients who remain disease-free after 2-3 years. This is a first trial to suggest the extending use of IHC4+C score for prognostic indication for patients who have switched endocrine therapies at 2-3 years and who remain disease-free after 2-3 years.
<h4>Background</h4>The study of the intrinsic molecular subtypes of breast cancer has revealed differences among them in terms of prognosis and response to chemotherapy and endocrine therapy. However, the ability of intrinsic subtypes to predict benefit from adjuvant radiotherapy has only been examined in few studies.<h4>Methods</h4>Gene expression-based intrinsic subtyping was performed in 228 breast tumors collected from two independent post-mastectomy clinical trials (British Columbia and the Danish Breast Cancer Cooperative Group 82b trials), where pre-menopausal patients with node-positive disease were randomized to adjuvant radiotherapy or not. All patients received adjuvant chemotherapy and a subgroup of patients underwent ovarian ablation. Tumors were classified into intrinsic subtypes: Luminal A, Luminal B, HER2-enriched, Basal-like and Normal-like using the research-based PAM50 classifier.<h4>Results</h4>In the British Columbia study, patients treated with radiation had an overall significant lower incidence of locoregional recurrence compared to the controls. For Luminal A tumors the risk of loco-regional recurrence was low and was further lowered by adjuvant radiation. These findings were validated in the DBCG 82b study. The individual data from the two cohorts were merged, the hazard ratio (HR) for loco-regional recurrence associated with giving radiation was 0.34 (0.19 to 0.61) overall and 0.12 (0.03 to 0.52) for Luminal A tumors.<h4>Conclusions</h4>In both postmastectomy trials, patients with Luminal A tumors turned out to have a significant lower incidence of loco-regional recurrence when randomized to adjuvant radiotherapy, leaving no indication to omit postmastectomy adjuvant radiation in pre-menopausal high-risk patients with Luminal A tumors. It was not possible to evaluate the effect of radiotherapy among the other subtypes because of limited sample sizes.
Germline mutations in BRCA1/2 predispose individuals to breast cancer (termed germline-mutated BRCA1/2 breast cancer, gBRCA-BC) by impairing homologous recombination (HR) and causing genomic instability. HR also repairs DNA lesions caused by platinum agents and PARP inhibitors. Triple-negative breast cancers (TNBCs) harbor subpopulations with BRCA1/2 mutations, hypothesized to be especially platinum-sensitive. Cancers in putative 'BRCAness' subgroups-tumors with BRCA1 methylation; low levels of BRCA1 mRNA (BRCA1 mRNA-low); or mutational signatures for HR deficiency and those with basal phenotypes-may also be sensitive to platinum. We assessed the efficacy of carboplatin and another mechanistically distinct therapy, docetaxel, in a phase 3 trial in subjects with unselected advanced TNBC. A prespecified protocol enabled biomarker-treatment interaction analyses in gBRCA-BC and BRCAness subgroups. The primary endpoint was objective response rate (ORR). In the unselected population (376 subjects; 188 carboplatin, 188 docetaxel), carboplatin was not more active than docetaxel (ORR, 31.4% versus 34.0%, respectively; P = 0.66). In contrast, in subjects with gBRCA-BC, carboplatin had double the ORR of docetaxel (68% versus 33%, respectively; biomarker, treatment interaction P = 0.01). Such benefit was not observed for subjects with BRCA1 methylation, BRCA1 mRNA-low tumors or a high score in a Myriad HRD assay. Significant interaction between treatment and the basal-like subtype was driven by high docetaxel response in the nonbasal subgroup. We conclude that patients with advanced TNBC benefit from characterization of BRCA1/2 mutations, but not BRCA1 methylation or Myriad HRD analyses, to inform choices on platinum-based chemotherapy. Additionally, gene expression analysis of basal-like cancers may also influence treatment selection.
The molecular complexity of triple-negative breast cancers (TNBCs) provides a challenge for patient management. We set out to characterize this heterogeneous disease by combining transcriptomics and genomics data, with the aim of revealing convergent pathway dependencies with the potential for treatment intervention. A Bayesian algorithm was used to integrate molecular profiles in two TNBC cohorts, followed by validation using five independent cohorts (<i>n</i> = 1,168), including three clinical trials. A four-gene decision tree signature was identified, which robustly classified TNBCs into six subtypes. All four genes in the signature (<i>EXO1, TP53BP2, FOXM1</i>, and <i>RSU1</i>) are associated with either genomic instability, malignant growth, or treatment response. One of the six subtypes, MC6, encompassed the largest proportion of tumors (∼50%) in early diagnosed TNBCs. In TNBC patients with metastatic disease, the MC6 proportion was reduced to 25%, and was independently associated with a higher response rate to platinum-based chemotherapy. In TNBC cell line data, platinum sensitivity was recapitulated, and a sensitivity to the inhibition of the phosphatase PPM1D was revealed. Molecularly, MC6-TNBCs displayed high levels of telomeric allelic imbalances, enrichment of CD4<sup>+</sup> and CD8<sup>+</sup> immune signatures, and reduced expression of genes negatively regulating the MAPK signaling pathway. These observations suggest that our integrative classification approach may identify TNBC patients with discernible and theoretically pharmacologically tractable features that merit further studies in prospective trials.
While pathologists have always played a pivotal role in clinical trials ensuring accurate diagnosis and staging, pathology data from prognostic and predictive tests are increasingly being used to enrol, stratify and randomise patients to experimental treatments. The use of pathological parameters as primary and secondary outcome measures, either as standalone classifiers or in combination with clinical data, is also becoming more common. Moreover, reporting of estimates of residual disease, termed 'pathological complete response', have been incorporated into neoadjuvant clinical trials. Pathologists have the expertise to deliver this essential information and they also understand the requirements and limitations of laboratory testing. Quality assurance of pathology-derived data builds confidence around trial-specific findings and is necessarily focused on the reproducibility of pathological data, including 'estimates of uncertainty of measurement', emphasising the importance of pathologist education, training, calibration and demonstration of satisfactory inter-observer agreement. There are also opportunities to validate objective image analysis tools alongside conventional histological assessments. The ever-expanding portfolio of clinical trials will demand more pathologist engagement to deliver the reliable evidence-base required for new treatments. We provide guidance for quality assurance of pathology scoring and reporting in clinical trials.
<h4>Purpose</h4>The prognostic and predictive values of the MAPK/AKT/ERα phosphorylation axis (pT202/T204MAPK, pT308AKT, pS473AKT, pS118ERα and pS167ERα) in primary tumours were assessed to determine whether these markers can differentiate between patient responses for switching adjuvant endocrine therapy after 2-3 years from tamoxifen to exemestane and continued tamoxifen monotherapy in the Intergroup Exemestane Study (IES).<h4>Methods</h4>Of the 4724 patients in IES, 1506 were managed in a subset of centres (N = 89) participating in PathIES. These centres recruited 1282 (85%, 1282/1506) women into PathIES of whom 1036 had phospho-marker data. All phospho-markers were analysed by immunohistochemistry staining. Multivariable Cox proportional hazards models of the phospho-markers for disease-free survival (DFS) and overall survival (OS) were adjusted for clinicopathological factors. Treatment effects on the biomarker expression were determined by interaction tests. Benjamini-Hochberg adjustment for multiple testing with a false discovery rate of 10% was applied (p<sub>BH</sub>).<h4>Results</h4>Phospho-T202/T204MAPK, pS118ERα and pS167ERα were all found to be correlated (p<sub>BH</sub> = 0.0002). These markers were not associated with either DFS or OS when controlling for the established clinicopathological factors. Interaction terms between the phospho-markers and treatment strategies for either DFS or OS were not statistically significant (p<sub>BH</sub> > 0.05 for all).<h4>Conclusions</h4>This PathIES study confirmed previously described associations between the phosphorylation site markers of AKT, MAPK and ERα activity in postmenopausal breast cancer patients. No prognostic correlations between the phosphorylation markers and clinical outcome were found, nor were they predictive for clinical outcomes among patients who switched therapy over those treated with tamoxifen alone.
<h4>Purpose</h4>Although aromatase inhibitor (AI) treatment is effective in estrogen receptor-positive postmenopausal breast cancer, resistance is common and incompletely explained. Genomic instability, as measured by somatic copy number alterations (SCNAs), is important in breast cancer development and prognosis. SCNAs to specific genes may drive intrinsic resistance, or high genomic instability may drive tumor heterogeneity, which allows differential response across tumors and surviving cells to evolve resistance to treatment rapidly. We therefore evaluated the relationship between SCNAs and intrinsic resistance to treatment as measured by a poor antiproliferative response.<h4>Patients and methods</h4>SCNAs were determined by single nucleotide polymorphism array in baseline and surgery core-cuts from 73 postmenopausal patients randomly assigned to receive 2 weeks of preoperative AI or no AI in the Perioperative Endocrine Therapy-Individualizing Care (POETIC) trial. Fifty-six samples from the AI group included 28 poor responders (PrRs, less than 60% reduction in protein encoded by the <i>MKI67</i> gene [Ki-67]) and 28 good responders (GdRs, greater than 75% reduction in Ki-67). Exome sequencing was available for 72 pairs of samples.<h4>Results</h4>Genomic instability correlated with Ki-67 expression at both baseline (<i>P</i> < .001) and surgery (<i>P</i> < .001) and was higher in PrRs (<i>P</i> = .048). The SCNA with the largest difference between GdRs and PrRs was loss of heterozygosity observed at 17p (false discovery rate, 0.08), which includes <i>TP53.</i> Nine of 28 PrRs had loss of wild-type <i>TP53</i> as a result of mutations and loss of heterozygosity compared with three of 28 GdRs. In PrRs, somatic alterations of <i>TP53</i> were associated with higher genomic instability, higher baseline Ki-67, and greater resistance to AI treatment compared with wild-type <i>TP53</i>.<h4>Conclusion</h4>We observed that primary tumors with high genomic instability have an intrinsic resistance to AI treatment and do not require additional evolution to develop resistance to estrogen deprivation therapy.
<h4>Purpose</h4>To investigate the presence of <i>ESR1</i> mutations in primary estrogen-receptor-positive (ER<sup>+</sup>) breast cancer treated with extended (>4 weeks) neoadjuvant (presurgical) aromatase inhibitor (NAI) therapy and to identify patients who may gain less benefit from aromatase inhibition (AI) alone based upon on-treatment changes in gene expression.<h4>Experimental design</h4>We evaluated ER, progesterone receptor, and Ki67 by immunostaining, <i>ESR1</i> mutations by droplet-digital PCR and expression of over 800 key breast cancer genes in paired pre- and post-NAI tumor samples from 87 ER<sup>+</sup> breast cancer patients.<h4>Results</h4>Cell proliferation and estrogen-regulated genes (ERG) remained suppressed in most tumors indicative of persistent response to NAI. Enrichment of <i>ESR1</i> mutations was found in five tumors and predominantly in patients receiving therapy for >6 months. <i>ESR1</i>-mutant tumors showed increased expression of <i>ESR1</i> transcript and limited suppression of ERGs and proliferation-associated genes in response to NAI. <i>ESR1</i> wild-type tumors with high residual proliferation (Ki67r ≥10%; 15/87 tumors) showed lower <i>ESR1</i>/ER expression pre- and post-therapy and lower ERGs. Tumors with <i>ESR1</i> mutations or Ki67r ≥10% showed less inhibition of estrogen response, cell cycle, and E2F-target genes.<h4>Conclusions</h4>Ligand-independent ER signaling, as a result of <i>ESR1</i> mutation or reduced ER dependence, identified after extended NAI therapy, can guide early selection of patients who would benefit from combination therapy.
<h4>Background</h4>Endocrine therapy reduces breast cancer mortality by 40%, but resistance remains a major clinical problem. In this study, we sought to investigate the impact of aromatase inhibitor (AI) therapy on gene expression and identify gene modules representing key biological pathways that relate to early AI therapy resistance.<h4>Methods</h4>Global gene expression was measured on pairs of core-cut biopsies taken at baseline and at surgery from 254 patients with ER-positive primary breast cancer randomised to receive 2-week presurgical AI (n = 198) or no presurgical treatment (control n = 56) from the POETIC trial. Data from the AI group was adjusted to eliminate artefactual process-related changes identified in the control group. The response was assessed by changes in the proliferation marker, Ki67.<h4>Results</h4>High baseline ESR1 expression associated with better AI response in HER2+ tumours but not HER2- tumours. In HER2- tumours, baseline expression of 48 genes associated with poor antiproliferative response (p < 0.005) including PERP and YWHAQ, the two most significant, and the transcription co-regulators (SAP130, HDAC4, and NCOA7) which were among the top 16 most significant. Baseline gene signature scores measuring cell proliferation, growth factor signalling (ERBB2-GS, RET/GDNF-GS, and IGF-1-GS), and immune activity (STAT1-GS) were significantly higher in poor AI responders. Two weeks of AI caused downregulation of genes involved in cell proliferation and ER signalling, as expected. Signature scores of E2F activation and TP53 dysfunction after 2-week AI were associated with poor AI response in both HER2- and HER2+ patients.<h4>Conclusions</h4>There is a high degree of heterogeneity in adaptive mechanisms after as little as 2-week AI therapy; however, all appear to converge on cell cycle regulation. Our data support the evaluation of whether an E2F signatures after short-term exposure to AI may identify those patients most likely to benefit from the early addition of CDK4/6 inhibitors.<h4>Trial registration</h4>ISRCTN, ISRCTN63882543, registered on 18 December 2007.
Clinical trials rely on multidisciplinary teams for successful delivery. Pathologists should be involved in clinical trial design from the outset to ensure that protocols are optimised to deliver maximum data collection and translational research opportunities. Clinical trials must be performed according to the principles of Good Clinical Practice (GCP) and the trial sponsor has an obligation to ensure that all of the personnel involved in the trial have undergone training relevant to their role. Pathologists who are involved in the delivery of clinical trials are often required to undergo formal GCP training and may additionally undergo Good Clinical Laboratory Practice training if they are involved in the laboratory analysis of trials samples. Further training can be provided via trial-specific investigator meetings, which may be either multidisciplinary or discipline-specific events. Pathologists should also ensure that they undertake External Quality Assurance schemes relevant to the area of diagnostic practice required in the trial. The level of engagement of pathologists in academia and clinical trials research has declined in the United Kingdom over recent years. This paper recommends the optimal training and accreditation for pathologists undertaking clinical trials activities with the aim of facilitating increased engagement. Clinical trials training should ideally be provided to all pathologists through centrally organised educational events, with additional training provided to pathologists in training through local postgraduate teaching. Pathologists in training should also be strongly encouraged to undertake GCP training. It is hoped that these recommendations will increase the number of pathologists who take part in clinical trials research in order to ensure a high level and standard of data collection and to maximise the translational research opportunities.
Digital pathology and image analysis potentially provide greater accuracy, reproducibility and standardisation of pathology-based trial entry criteria and endpoints, alongside extracting new insights from both existing and novel features. Image analysis has great potential to identify, extract and quantify features in greater detail in comparison to pathologist assessment, which may produce improved prediction models or perform tasks beyond manual capability. In this article, we provide an overview of the utility of such technologies in clinical trials and provide a discussion of the potential applications, current challenges, limitations and remaining unanswered questions that require addressing prior to routine adoption in such studies. We reiterate the value of central review of pathology in clinical trials, and discuss inherent logistical, cost and performance advantages of using a digital approach. The current and emerging regulatory landscape is outlined. The role of digital platforms and remote learning to improve the training and performance of clinical trial pathologists is discussed. The impact of image analysis on quantitative tissue morphometrics in key areas such as standardisation of immunohistochemical stain interpretation, assessment of tumour cellularity prior to molecular analytical applications and the assessment of novel histological features is described. The standardisation of digital image production, establishment of criteria for digital pathology use in pre-clinical and clinical studies, establishment of performance criteria for image analysis algorithms and liaison with regulatory bodies to facilitate incorporation of image analysis applications into clinical practice are key issues to be addressed to improve digital pathology incorporation into clinical trials.
<h4>Purpose</h4>The recent publication of the ACOSOG Z1031 trial results demonstrated that Ki-67 proliferation marker-based neoadjuvant endocrine therapy response monitoring could be used for tailoring the use of adjuvant chemotherapy in ER+HER2-negative breast cancer patients. In this paper, we describe the development of the Ki-67 clinical trial assay used for this study.<h4>Methods</h4>Ki-67 assay assessment focused on reproducing a 2.7% Ki-67 cut-point (CP) required for calculating the Preoperative Endocrine Prognostic Index and a 10% CP for poor endocrine therapy response identification within the first month of neoadjuvant endocrine treatment. Image analysis was assessed to increase the efficiency of the scoring process. Clinical outcome concordance for two independent Ki-67 scores was the primary performance metric.<h4>Results</h4>Discordant scores led to a triage approach where cases with complex histological features that software algorithms could not resolve were flagged for visual point counting (17%). The final Ki-67 scoring approach was run on T1/2 N0 cases from the P024 and POL trials (N = 58). The percent positive agreement for the 2.7% CP was 87.5% (95% CI 61.7-98.5%); percent negative agreement 88.9% (95% CI: 65.3-98.6%). Minor discordance did not affect the ability to predict similar relapse-free outcomes (Log-Rank P = 0.044 and P = 0.055). The data for the 10% early triage CP in the POL trial were similar (N = 66), the percentage positive agreement was 100%, and percent negative agreement 93.55% (95% CI: 78.58-99.21%). The independent survival predictions were concordant (Log-rank P = 0.0001 and P = 0.01).<h4>Conclusions</h4>We have developed an efficient and reproducible Ki-67 scoring system that was approved by the Clinical Trials Evaluation Program for NCI-supported neoadjuvant endocrine therapy trials. Using the methodology described here, investigators are able to identify a subgroup of patients with ER+HER2-negative breast cancer that can be safely managed without the need of adjuvant chemotherapy.
To investigate the impact of sampling methodology on gene expression data from primary estrogen receptor-positive (ER+) breast cancer biopsies, global gene expression was measured in core-cut biopsies at baseline and surgery from patients randomly assigned to receive either two weeks of presurgical aromatase inhibitor (AI; n = 157) or no presurgical treatment (n = 56). Those genes most markedly altered in the AI group (eg, <i>FOS</i>, <i>DUSP1</i>, <i>RGS1</i>, <i>FOSB</i>) were similarly altered in the no treatment group; some widely investigated genes that were apparently unaffected in the AI group (eg, <i>MYC</i>) were counter-altered in the control group, masking actual AI-dependent changes. In the absence of a control group, these artefactual changes would likely lead to the most affected genes being the erroneous focus of research. The findings are likely relevant to all archival collections of ER+ breast cancer.
A prospective study was conducted to identify biomarkers associated with resistance to panitumumab monotherapy in patients with metastatic colorectal cancer (mCRC). Patients with previously treated, codon 12/13 KRAS wt, mCRC were prospectively administered panitumumab 6 mg/kg IV q2weeks. Of 34 panitumumab-treated patients, 11 (32%) had progressive disease at 8 weeks and were classified as non-responders. A Nanostring nCounter-based assay identified a 5-gene expression signature (ERBB2, MLPH, IRX3, MYRF, and KLK6) associated with panitumumab resistance (P = 0.001). Immunohistochemistry and in situ hybridization determined that the HER2 (ERBB2) protein was overexpressed in 4/11 non-responding and 0/21 responding cases (P = 0.035). Two non-responding tumors had ERBB2 gene amplification only, and one demonstrated both ERBB2 amplification and mutation. A non-codon 12/13 KRAS mutation occurred in one panitumumab-resistant patient and was mutually exclusive with ERBB2/HER2 abnormalities. This study identifies a 5-gene signature associated with non-response to single agent panitumumab, including a subgroup of non-responders with evidence of aberrant ERBB2/HER2 signaling. KRAS wt tumors resistant to EGFRi may be identified by gene signature analysis, and the HER2 pathway plays an important role in resistance to therapy.
The classification of endometrial carcinomas is based on pathological assessment of tumour cell type; the different cell types (endometrioid, serous, carcinosarcoma, mixed, undifferentiated, and clear cell) are associated with distinct molecular alterations. This current classification system for high-grade subtypes, in particular the distinction between high-grade endometrioid (EEC-3) and serous carcinomas (ESC), is limited in its reproducibility and prognostic abilities. Therefore, a search for specific molecular classifiers to improve endometrial carcinoma subclassification is warranted. We performed target enrichment sequencing on 393 endometrial carcinomas from two large cohorts, sequencing exons from the following nine genes: ARID1A, PPP2R1A, PTEN, PIK3CA, KRAS, CTNNB1, TP53, BRAF, and PPP2R5C. Based on this gene panel, each endometrial carcinoma subtype shows a distinct mutation profile. EEC-3s have significantly different frequencies of PTEN and TP53 mutations when compared to low-grade endometrioid carcinomas. ESCs and EEC-3s are distinct subtypes with significantly different frequencies of mutations in PTEN, ARID1A, PPP2R1A, TP53, and CTNNB1. From the mutation profiles, we were able to identify subtype outliers, ie cases diagnosed morphologically as one subtype but with a mutation profile suggestive of a different subtype. Careful review of these diagnostically challenging cases suggested that the original morphological classification was incorrect in most instances. The molecular profile of carcinosarcomas suggests two distinct mutation profiles for these tumours: endometrioid-type (PTEN, PIK3CA, ARID1A, KRAS mutations) and serous-type (TP53 and PPP2R1A mutations). While this nine-gene panel does not allow for a purely molecularly based classification of endometrial carcinoma, it may prove useful as an adjunct to morphological classification and serve as an aid in the classification of problematic cases. If used in practice, it may lead to improved diagnostic reproducibility and may also serve to stratify patients for targeted therapeutics.
Background: Genomic data from human epidermal growth factor receptor 2-positive (HER2+) tumors were analyzed to assess the association between intrinsic subtype and clinical outcome in a large, well-annotated patient cohort. Methods: Samples from the NCCTG (Alliance) N9831 trial were analyzed using the Prosigna algorithm on the NanoString platform to define intrinsic subtype, risk of recurrence scores, and risk categories for 1392 HER2+ tumors. Subtypes were evaluated for recurrence-free survival (RFS) using Kaplan-Meier and Cox model analysis following adjuvant chemotherapy (n = 484) or chemotherapy plus trastuzumab (n = 908). All statistical tests were two-sided. Results: Patients with HER2+ tumors from N9831 were primarily scored as HER2-enriched (72.1%). These individuals received statistically significant benefit from trastuzumab (hazard ratio [HR] = 0.68, 95% confidence interval [CI] = 0.52 to 0.89, P = .005), as did the patients (291 of 1392) with luminal-type tumors (HR = 0.52, 95% CI = 0.32 to 0.85, P = .01). Patients with basal-like tumors (97 of 1392) did not have statistically significantly better RFS when treated with trastuzumab and chemotherapy compared with chemotherapy alone (HR = 1.06, 95% CI = 0.53 to 2.13, P = .87). Conclusions: The majority of clinically defined HER2-positive tumors were classified as HER2-enriched or luminal using the Prosigna algorithm. Intrinsic subtype alone cannot replace conventional histopathological evaluation of HER2 status because many tumors that are classified as luminal A or luminal B will benefit from adjuvant trastuzumab if that subtype is accompanied by HER2 overexpression. However, among tumors that overexpress HER2, we speculate that assessment of intrinsic subtype may influence treatment, particularly with respect to evaluating alternative therapeutic approaches for that subset of HER2-positive tumors of the basal-like subtype.
<h4>Purpose</h4>Dual human epidermal growth factor receptor 2 (HER2) targeting can increase pathologic complete response rates (pCRs) to neoadjuvant therapy and improve progression-free survival in metastatic disease. CALGB 40601 examined the impact of dual HER2 blockade consisting of trastuzumab and lapatinib added to paclitaxel, considering tumor and microenvironment molecular features.<h4>Patients and methods</h4>Patients with stage II to III HER2-positive breast cancer underwent tumor biopsy followed by random assignment to paclitaxel plus trastuzumab alone (TH) or with the addition of lapatinib (THL) for 16 weeks before surgery. An investigational arm of paclitaxel plus lapatinib (TL) was closed early. The primary end point was pCR in the breast; correlative end points focused on molecular features identified by gene expression-based assays.<h4>Results</h4>Among 305 randomly assigned patients (THL, n = 118; TH, n = 120; TL, n = 67), the pCR rate was 56% (95% CI, 47% to 65%) with THL and 46% (95% CI, 37% to 55%) with TH (P = .13), with no effect of dual therapy in the hormone receptor-positive subset but a significant increase in pCR with dual therapy in those with hormone receptor-negative disease (P = .01). The tumors were molecularly heterogeneous by gene expression analysis using mRNA sequencing (mRNAseq). pCR rates significantly differed by intrinsic subtype (HER2 enriched, 70%; luminal A, 34%; luminal B, 36%; P < .001). In multivariable analysis treatment arm, intrinsic subtype, HER2 amplicon gene expression, p53 mutation signature, and immune cell signatures were independently associated with pCR. Post-treatment residual disease was largely luminal A (69%).<h4>Conclusion</h4>pCR to dual HER2-targeted therapy was not significantly higher than single HER2 targeting. Tissue analysis demonstrated a high degree of intertumoral heterogeneity with respect to both tumor genomics and tumor microenvironment that significantly affected pCR rates. These factors should be considered when interpreting and designing trials in HER2-positive disease.
BACKGROUND: Retrospective analyses of NSABP B20 and SWOG 8814 showed a large benefit of chemotherapy in patients with ER-positive tumors and high OncotypeDX Recurrence Score (RS≥31). However, it might be possible that both studies may be contaminated by non-luminal tumors, especially in high-risk RS group. METHODS: We conducted simulations in order to obtain a better understanding of how the NSABP B20 and SWOG 8814 results would have been if non-luminal breast cancer would have been excluded. Simulations were done separately for the node-negative and node-positive cohorts. RESULTS AND CONCLUSION: The results of the simulations suggest that the non-luminal tumors are augmenting the apparent benefit of chemotherapy, but do not appear to be responsible for the entire effect. These simulations could provide information about the potential influence of contamination by unexpected tumor subtypes on the future results of TAILORx and RxPONDER clinical trials.
Importance: The value of the intrinsic subtypes of breast cancer (luminal A, luminal B, human epidermal growth factor receptor 2 [currently known as ERBB2, but referred to as HER2 in this study]-enriched, and basal-like) in the metastatic setting is currently unknown. Objective: To evaluate the association of the intrinsic subtypes of breast cancer with outcome and/or benefit in hormone receptor (HR)-positive metastatic breast cancer. Design, Setting, and Participants: Unplanned retrospective analysis of 821 tumor samples (85.7% primary and 14.3% metastatic) from the EGF30008 phase 3 clinical trial (NCT00073528), in which postmenopausal women with HR-positive invasive breast cancer and no prior therapy for advanced or metastatic disease were randomized to letrozole with or without lapatinib, an epidermal growth factor receptor (EGFR)/HER2 tyrosine kinase inhibitor. Tumor samples were classified into each subtype using the research-based PAM50 classifier. Prior neoadjuvant/adjuvant antiestrogen therapy was allowed. Patients with extensive symptomatic visceral disease were excluded. Treatment effects were evaluated using interaction tests. Main Outcomes and Measures: Primary and secondary end points were progression-free survival and overall survival. Results: The median (range) age was 62 (31-94) years. Intrinsic subtype was the strongest prognostic factor independently associated with progression-free survival and overall survival in all patients, and in patients with HER2-negative (n = 644) or HER2-positive (n = 157) diseases. Median progression-free survival differed across the intrinsic subtypes of clinically HER2-negative disease: luminal A (16.9 [95% CI, 14.1-19.9] months), luminal B (11.0 [95% CI, 9.6-13.6] months), HER2-enriched (4.7 [95% CI, 2.7-10.8] months), and basal-like (4.1 [95% CI, 2.5-13.8] months). Median OS also differed across the intrinsic subtypes: luminal A (45 [95% CI, 41-not applicable {NA}] months), luminal B (37 [95% CI, 31-42] months), HER2-enriched (16 [95% CI, 10-NA] months), and basal-like (23 [95% CI, 12-NA] months). Patients with HER2-negative/HER2-enriched disease benefited from lapatinib therapy (median PFS, 6.49 vs 2.60 months; progression-free survival hazard ratio, 0.238 [95% CI, 0.066-0.863]; interaction P = .02). Conclusions and Relevance: This is the first study to reveal an association between intrinsic subtype and outcome in first-line HR-positive metastatic breast cancer. Patients with HR-positive/HER2-negative disease with a HER2-enriched profile may benefit from lapatinib in combination with endocrine therapy. The clinical value of intrinsic subtyping in hormone receptor-positive metastatic breast cancer warrants further investigation, but patients with luminal A/HER2-negative metastatic breast cancer might be good candidates for letrozole monotherapy in the first-line setting regardless of visceral disease and number of metastases.
<h4>Background</h4>Predicting treatment benefit and/or outcome before any therapeutic intervention has taken place would be clinically very useful. Herein, we evaluate the ability of the intrinsic subtypes and the risk of relapse score at diagnosis to predict survival and response following neoadjuvant chemotherapy. In addition, we evaluated the ability of the Claudin-low and 7-TNBCtype classifications to predict response within triple-negative breast cancer (TNBC).<h4>Methods</h4>Gene expression and clinical-pathological data were evaluated in a combined dataset of 957 breast cancer patients, including 350 with TNBC, treated with sequential anthracycline and anti-microtubule-based neoadjuvant regimens. Intrinsic subtype, risk of relapse score based on subtype and proliferation (ROR-P), the Claudin-low subtype and the 7-TNBCtype subtype classification were evaluated. Logistic regression models for pathological complete response (pCR) and Cox models for distant relapse-free survival (DRFS) were used.<h4>Results</h4>Basal-like, Luminal A, Luminal B, and HER2-enriched subtypes represented 32.7%, 30.6%, 18.2%, and 10.3% of cases, respectively. Intrinsic subtype was independently associated with pCR in all patients, in hormone receptor-positive/HER2-negative disease, in HER2-positive disease, and in TNBC. The pCR rate of Basal-like disease was >35% across all clinical cohorts. Neither the Claudin-low nor the 7-TNBCtype subtype classifications predicted pCR within TNBCs after accounting for intrinsic subtype. Finally, intrinsic subtype and ROR-P provided independent prognostic information beyond clinicopathological variables and type of pathological response. A 5-year DRFS of 97.5% (92.8-100.0%) was observed in these neoadjuvant-treated and clinically node-negative patients predicted to be low risk by ROR-P (i.e. 57.4% of Luminal A tumors with clinically node-negative disease).<h4>Conclusions</h4>Intrinsic subtyping at diagnosis provides prognostic and predictive information for patients receiving neoadjuvant chemotherapy. Although we could not exclude a survival benefit of neoadjuvant chemotherapy in patients with early breast cancer with clinically node-negative and ROR-low disease at diagnosis, the absolute benefit of cytotoxic therapy in this group might be rather small (if any).
<h4>Purpose</h4>To determine intrinsic breast cancer subtypes represented within categories defined by quantitative hormone receptor (HR) and HER2 expression.<h4>Methods</h4>We merged 1,557 cases from three randomized phase III trials into a single data set. These breast tumors were centrally reviewed in each trial for quantitative ER, PR, and HER2 expression by immunohistochemistry (IHC) stain and by reverse transcription-quantitative polymerase chain reaction (RT-qPCR), with intrinsic subtyping by research-based PAM50 RT-qPCR assay.<h4>Results</h4>Among 283 HER2-negative tumors with <1% HR expression by IHC, 207 (73%) were basal-like; other subtypes, particularly HER2-enriched (48, 17%), were present. Among the 1,298 HER2-negative tumors, borderline HR (1%-9% staining) was uncommon (n = 39), and these tumors were heterogeneous: 17 (44%) luminal A/B, 12 (31%) HER2-enriched, and only 7 (18%) basal-like. Including them in the definition of triple-negative breast cancer significantly diminished enrichment for basal-like cancer (p < .05). Among 106 HER2-positive tumors with <1% HR expression by IHC, the HER2-enriched subtype was the most frequent (87, 82%), whereas among 127 HER2-positive tumors with strong HR (>10%) expression, only 69 (54%) were HER2-enriched and 55 (43%) were luminal (39 luminal B, 16 luminal A). Quantitative HR expression by RT-qPCR gave similar results. Regardless of methodology, basal-like cases seldom expressed ER/ESR1 or PR/PGR and were associated with the lowest expression level of HER2/ERBB2 relative to other subtypes.<h4>Conclusion</h4>Significant discordance remains between clinical assay-defined subsets and intrinsic subtype. For identifying basal-like breast cancer, the optimal HR IHC cut point was <1%, matching the American Society of Clinical Oncology and College of American Pathologists guidelines. Tumors with borderline HR staining are molecularly diverse and may require additional assays to clarify underlying biology.
BACKGROUND: In this study, we evaluated the ability of gene expression profiles to predict chemotherapy response and survival in triple-negative breast cancer (TNBC). METHODS: Gene expression and clinical-pathological data were evaluated in five independent cohorts, including three randomised clinical trials for a total of 1055 patients with TNBC, basal-like disease (BLBC) or both. Previously defined intrinsic molecular subtype and a proliferation signature were determined and tested. Each signature was tested using multivariable logistic regression models (for pCR (pathological complete response)) and Cox models (for survival). Within TNBC, interactions between each signature and the basal-like subtype (vs other subtypes) for predicting either pCR or survival were investigated. RESULTS: Within TNBC, all intrinsic subtypes were identified but BLBC predominated (55-81%). Significant associations between genomic signatures and response and survival after chemotherapy were only identified within BLBC and not within TNBC as a whole. In particular, high expression of a previously identified proliferation signature, or low expression of the luminal A signature, was found independently associated with pCR and improved survival following chemotherapy across different cohorts. Significant interaction tests were only obtained between each signature and the BLBC subtype for prediction of chemotherapy response or survival. CONCLUSIONS: The proliferation signature predicts response and improved survival after chemotherapy, but only within BLBC. This highlights the clinical implications of TNBC heterogeneity, and suggests that future clinical trials focused on this phenotypic subtype should consider stratifying patients as having BLBC or not.
<h4>Purpose</h4>We report a retrospective exploratory analysis of the association of the research-based prediction analysis of microarray 50 (PAM50) subtype predictor with pathologic complete response (pCR) and event-free survival (EFS) in women enrolled in the NeOAdjuvant Herceptin (NOAH) trial.<h4>Experimental design</h4>Gene expression profiling was performed using RNA from formalin-fixed paraffin-embedded core biopsies from 114 pretreated patients with HER2-positive (HER2(+)) tumors randomized to receive neoadjuvant doxorubicin/paclitaxel (AT) followed by cyclophosphamide/methotrexate/fluorouracil (CMF), or the same regimen in combination with trastuzumab for one year. A control cohort of 42 patients with HER2-negative tumors treated with AT-CMF was also included. The PAM50 subtypes, the PAM50 proliferation score, and the PAM50 risk of relapse score based on subtype (RORS) and subtype and proliferation (RORP) were evaluated.<h4>Results</h4>HER2-enriched (HER2-E) tumors predominated within HER2(+) disease, although all PAM50 intrinsic subtypes were identified across the three cohorts. The OR for achieving pCR with trastuzumab-based chemotherapy for HER2(+)/HER2-E and HER2(+)/RORP-high were 5.117 (P = 0.009) and 8.469 (P = 0.025), respectively, compared with chemotherapy only. The pCR rates of HER2(+)/HER2-E and HER2(+)/RORP-high after trastuzumab-based chemotherapy were 52.9% and 75.0%, respectively. A statistically nonsignificant trend was observed for more pronounced survival benefit with trastuzumab in patients with HER2(+)/HER2-E and HER2(+)/RORP-high tumors compared with patients with HER2(+)/non-HER2-E and HER2(+)/non-RORP-high tumors, respectively.<h4>Conclusions</h4>As determined by EFS and pCR, patients with HER2(+)/HER2-E tumors, or HER2(+)/RORP-high tumors, benefit substantially from trastuzumab-based chemotherapy. The clinical value of this genomic test within HER2(+) disease warrants further investigation.
PURPOSE: To use genetically engineered mouse models (GEMM) and orthotopic syngeneic murine transplants (OST) to develop gene expression-based predictors of response to anticancer drugs in human tumors. These mouse models offer advantages including precise genetics and an intact microenvironment/immune system. EXPERIMENTAL DESIGN: We examined the efficacy of 4 chemotherapeutic or targeted anticancer drugs, alone and in combination, using mouse models representing 3 distinct breast cancer subtypes: Basal-like (C3(1)-T-antigen GEMM), Luminal B (MMTV-Neu GEMM), and Claudin-low (T11/TP53-/- OST). We expression-profiled tumors to develop signatures that corresponded to treatment and response, and then tested their predictive potential using human patient data. RESULTS: Although a single agent exhibited exceptional efficacy (i.e., lapatinib in the Neu-driven model), generally single-agent activity was modest, whereas some combination therapies were more active and life prolonging. Through analysis of RNA expression in this large set of chemotherapy-treated murine tumors, we identified a pair of gene expression signatures that predicted pathologic complete response to neoadjuvant anthracycline/taxane therapy in human patients with breast cancer. CONCLUSIONS: These results show that murine-derived gene signatures can predict response even after accounting for common clinical variables and other predictive genomic signatures, suggesting that mice can be used to identify new biomarkers for human patients with cancer.
<h4>Background/objectives</h4>The molecular chaperone αB-crystallin is expressed in estrogen receptor, progesterone receptor and human epidermal growth factor receptor-2 "triple-negative" breast carcinomas and promotes brain and lung metastasis. We examined αB-crystallin expression in primary breast carcinomas with metastatic data to evaluate its association with prognosis and site-specific metastases.<h4>Methods</h4>αB-crystallin gene (<i>CRYAB</i>) expression was examined using publically available global-gene expression data (n=855 breast tumors) with first site of distant metastasis information ("855Met"). αB-crystallin protein expression was determined by immunohistochemistry using the clinically annotated tissue microarray (n=3987 breast tumors) from British Columbia Cancer Agency (BCCA). Kaplan-Meier and multivariable Cox regression analyses were used to evaluate the prognostic value of αB-crystallin. Multivariable logistic regression analysis was used to evaluate risks of αB-crystallin and other markers for site of metastasis.<h4>Results</h4>In the 855Met dataset, αB-crystallin gene (<i>CRYAB)</i> expression was an independent predictor of brain as the first distant site of relapse (HR = 1.2, (95% CI 1.0-1.4), <i>P</i> = 0.021). In the BCCA series, αB-crystallin protein expression was an independent prognostic marker of poor breast cancer specific survival (HR = 1.3, (95% CI 1.1-1.6), <i>P</i> = 0.014). Among patients with metastases, αB-crystallin was the strongest independent predictor of brain metastasis (OR = 2.99 (95% CI 1.83-4.89), <i>P</i> < 0.0001) and the only independent predictor of brain as the first site of distant metastasis (OR = 3.15 (95% CI1.43-6.95), <i>P</i> = 0.005). αB-crystallin was also associated with worse survival (3.0 versus 4.7 months, <i>P</i> = 0.007).<h4>Conclusions</h4>αB-crystallin is a promising biomarker to identify breast cancer patients at high risk for early relapse in the brain, independent of ER and HER2 status.
<h4>Purpose</h4>Metastatic colorectal cancers (mCRCs) assigned to the transit-amplifying (TA) CRCAssigner subtype are more sensitive to anti-epidermal growth factor receptor (EGFR) therapy. We evaluated the association between the intratumoral presence of TA signature (TA-high/TA-low, dubbed as TA-ness classification) and outcomes in CRCs treated with anti-EGFR therapy.<h4>Patients and methods</h4>The TA-ness classes were defined in a discovery cohort (n = 84) and independently validated in a clinical trial (CO.20; cetuximab monotherapy arm; n = 121) and other samples using an established NanoString-based gene expression assay. Progression-free survival (PFS), overall survival (OS), and disease control rate (DCR) according to TA-ness classification were assessed by univariate and multivariate analyses.<h4>Results</h4>The TA-ness was measured in 772 samples from 712 patients. Patients (treated with anti-EGFR therapy) with TA-high tumors had significantly longer PFS (discovery hazard ratio [HR], 0.40; 95% CI, 0.25 to 0.64; <i>P</i> < .001; validation HR, 0.65; 95% CI, 0.45 to 0.93; <i>P</i> = .018), longer OS (discovery HR, 0.48; 95% CI, 0.29 to 0.78; <i>P</i> = .003; validation HR, 0.67; 95% CI, 0.46 to 0.98; <i>P</i> = .04), and higher DCR (discovery odds ratio [OR]; 14.8; 95% CI, 4.30 to 59.54; <i>P</i> < .001; validation OR, 4.35; 95% CI, 2.00 to 9.09; <i>P</i> < .001). TA-ness classification and its association with anti-EGFR therapy outcomes were further confirmed using publicly available data (n = 80) from metastatic samples (PFS <i>P</i> < .001) and patient-derived xenografts (<i>P</i> = .042). In an exploratory analysis of 55 patients with <i>RAS/BRAF</i> wild-type and left-sided tumors, TA-high class was significantly associated with longer PFS and trend toward higher response rate (PFS HR, 0.53; 95% CI, 0.28 to 1.00; <i>P</i> = .049; OR, 5.88; 95% CI, 0.71 to 4.55; <i>P</i> = .09; response rate 33% in TA-high and 7.7% in TA-low).<h4>Conclusion</h4>TA-ness classification is associated with prognosis in patients with mCRC treated with anti-EGFR therapy and may further help understanding the value of sidedness in patients with <i>RAS/BRAF</i> wild-type tumors.
<h4>Background</h4>In the TNT trial of triple negative breast cancer (NCT00532727), germline BRCA1/2 mutations were present in 28% of carboplatin responders. We assessed quantitative measures of structural chromosomal instability (CIN) to identify a wider patient subgroup within TNT with preferential benefit from carboplatin over docetaxel.<h4>Patients and methods</h4>Copy number aberrations (CNAs) were established from 135 formalin-fixed paraffin-embedded primary carcinomas using Illumina OmniExpress SNP-arrays. Seven published [allelic imbalanced CNA (AiCNA); allelic balanced CNA (AbCNA); copy number neutral loss of heterozygosity (CnLOH); number of telomeric allelic imbalances (NtAI); BRCA1-like status; percentage of genome altered (PGA); homologous recombination deficiency (HRD) scores] and two novel [Shannon diversity index (SI); high-level amplifications (HLAMP)] CIN-measurements were derived. HLAMP was defined based on the presence of at least one of the top 5% amplified cytobands located on 1q, 8q and 10p. Continuous CIN-measurements were divided into tertiles. All nine CIN-measurements were used to analyse objective response rate (ORR) and progression-free survival (PFS).<h4>Results</h4>Patients with tumours without HLAMP had a numerically higher ORR and significantly longer PFS in the carboplatin (C) than in the docetaxel (D) arm [56% (C) versus 29% (D), P<sub>HLAMP,quiet</sub> = 0.085; PFS 6.1 months (C) versus 4.1 months (D), P<sub>interaction/HLAMP</sub> = 0.047]. In the carboplatin arm, patients with tumours showing intermediate telomeric NtAI and AiCNA had higher ORR [54% (C) versus 20% (D), P<sub>NtAI,intermediate</sub> = 0.03; 62% (C) versus 33% (D), P<sub>AiCNA,intermediate</sub> = 0.076]. Patients with high AiCNA and PGA had shorter PFS in the carboplatin arm [3.4 months (high) versus 5.7 months (low/intermediate); and 3.8 months (high) versus 5.6 months (low/intermediate), respectively; P<sub>interaction/AiCNA</sub> = 0.027, P<sub>adj.interaction/AiCNA</sub> = 0.125 and P<sub>interaction/PGA</sub> = 0.053, P<sub>adj.interaction/PGA</sub> = 0.176], whilst no difference was observed in the docetaxel arm.<h4>Conclusions</h4>Patients with tumours lacking HLAMP and demonstrating intermediate CIN-measurements formed a subgroup benefitting from carboplatin relative to docetaxel treatment within the TNT trial. This suggests a complex and paradoxical relationship between the extent of genomic instability in primary tumours and treatment response in the metastatic setting.
Triple-negative breast cancers (TNBC) are resistant to standard-of-care chemotherapy and lack known targetable driver gene alterations. Identification of novel drivers could aid the discovery of new treatment strategies for this hard-to-treat patient population, yet studies using high-throughput and accurate models to define the functions of driver genes in TNBC to date have been limited. Here, we employed unbiased functional genomics screening of the 200 most frequently mutated genes in breast cancer, using spheroid cultures to model <i>in vivo</i>-like conditions, and identified the histone acetyltransferase CREBBP as a novel tumor suppressor in TNBC. CREBBP protein expression in patient tumor samples was absent in 8% of TNBCs and at a high frequency in other tumors, including squamous lung cancer, where CREBBP-inactivating mutations are common. In TNBC, CREBBP alterations were associated with higher genomic heterogeneity and poorer patient survival and resulted in upregulation and dependency on a FOXM1 proliferative program. Targeting FOXM1-driven proliferation indirectly with clinical CDK4/6 inhibitors (CDK4/6i) selectively impaired growth in spheroids, cell line xenografts, and patient-derived models from multiple tumor types with CREBBP mutations or loss of protein expression. In conclusion, we have identified CREBBP as a novel driver in aggressive TNBC and identified an associated genetic vulnerability in tumor cells with alterations in CREBBP and provide a preclinical rationale for assessing CREBBP alterations as a biomarker of CDK4/6i response in a new patient population. SIGNIFICANCE: This study demonstrates that CREBBP genomic alterations drive aggressive TNBC, lung cancer, and lymphomas and may be selectively treated with clinical CDK4/6 inhibitors.
Soft tissue sarcomas (STS) are a group of rare and heterogeneous cancers. While large-scale genomic and epigenomic profiling of STS have been undertaken, proteomic analysis has thus far been limited. Here we utilise sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) for proteomic profiling of formalin fixed paraffin embedded (FFPE) specimens from a cohort of STS patients (n = 36) across four histological subtypes (leiomyosarcoma, synovial sarcoma, undifferentiated pleomorphic sarcoma and dedifferentiated liposarcoma). We quantified 2951 proteins across all cases and show that there is a significant enrichment of gene sets associated with smooth muscle contraction in leiomyosarcoma, RNA splicing regulation in synovial sarcoma and leukocyte activation in undifferentiated pleomorphic sarcoma. We further identified a subgroup of STS cases that have a distinct expression profile in a panel of proteins, with worse survival outcomes when compared to the rest of the cohort. Our study highlights the value of comprehensive proteomic characterisation as a means to identify histotype-specific STS profiles that describe key biological pathways of clinical and therapeutic relevance; as well as for discovering new prognostic biomarkers in this group of rare and difficult-to-treat diseases.
Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls .
Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting.
Acquired ESR1 mutations are a major mechanism of resistance to aromatase inhibitors (AIs). We developed ultra high-sensitivity multiplex digital polymerase chain reaction assays for ESR1 mutations in circulating tumor DNA (ctDNA) and investigated the clinical relevance and origin of ESR1 mutations in 171 women with advanced breast cancer. ESR1 mutation status in ctDNA showed high concordance with contemporaneous tumor biopsies and was accurately assessed in samples shipped at room temperature in preservative tubes. ESR1 mutations were found exclusively in estrogen receptor-positive breast cancer patients previously exposed to AI. Patients with ESR1 mutations had a substantially shorter progression-free survival on subsequent AI-based therapy [hazard ratio, 3.1; 95% confidence interval (CI), 1.9 to 23.1; P = 0.0041]. ESR1 mutation prevalence differed markedly between patients who were first exposed to AI during the adjuvant and metastatic settings [5.8% (3 of 52) versus 36.4% (16 of 44), respectively; P = 0.0002]. In an independent cohort, ESR1 mutations were identified in 0% (0 of 32; 95% CI, 0 to 10.9) tumor biopsies taken after progression on adjuvant AI. In a patient with serial sampling, ESR1 mutation was selected during metastatic AI therapy to become the dominant clone in the cancer. ESR1 mutations can be robustly identified with ctDNA analysis and predict for resistance to subsequent AI therapy. ESR1 mutations are rarely acquired during adjuvant AI but are commonly selected by therapy for metastatic disease, providing evidence that mechanisms of resistance to targeted therapy may be substantially different between the treatment of micrometastatic and overt metastatic cancer.
<h4>Purpose</h4>Changes occur in the expression of oestrogen-regulated and proliferation-associated genes in oestrogen receptor (ER)-positive breast tumours during the menstrual cycle. We investigated if Oncotype® DX recurrence score (RS), Prosigna® (ROR) and EndoPredict® (EP/EPclin) prognostic tests, which include some of these genes, vary according to the time in the menstrual cycle when they are measured.<h4>Methods</h4>Pairs of test scores were derived from 30 ER-positive/human epidermal growth factor receptor-2-negative tumours sampled at two different points of the menstrual cycle. Menstrual cycle windows were prospectively defined as either W1 (days 1-6 and 27-35; low oestrogen and low progesterone) or W2 (days 7-26; high oestrogen and high or low progesterone).<h4>Results</h4>The invasion module score of RS was lower (- 10.9%; p = 0.098), whereas the ER (+ 16.6%; p = 0.046) and proliferation (+ 7.3%; p = 0.13) module scores were higher in W2. PGR expression was significantly increased in W2 (+ 81.4%; p = 0.0029). Despite this, mean scores were not significantly different between W1 and W2 for any of the tests and the two measurements showed high correlation (r = 0.72-0.93). However, variability between the two measurements led to tumours being assigned to different risk categories in the following proportion of cases: RS 22.7%, ROR 27.3%, EP 13.6% and EPclin 13.6%.<h4>Conclusion</h4>There are significant changes during the menstrual cycle in the expression of some of the genes and gene module scores comprising the RS, ROR and EP/EPclin scores. These did not affect any of the prognostic scores in a systematic fashion, but there was substantial variability in paired measurements.
<h4>Importance</h4>Angiosarcoma is a rare sarcoma subtype with a poor outcome. Carotuximab plus pazopanib produced a median progression-free survival (PFS) of 7.8 months in pazopanib-naive patients with chemotherapy-refractory angiosarcoma in a phase 1/2 trial.<h4>Objective</h4>To determine whether carotuximab plus pazopanib improves PFS compared with pazopanib alone in patients with advanced angiosarcoma.<h4>Design, setting, and participants</h4>The TAPPAS Trial: An Adaptive Enrichment Phase 3 Trial of TRC105 and Pazopanib vs Pazopanib Alone in Patients With Advanced Angiosarcoma was a multinational, multicenter, open-label, parallel-group, phase 3 randomized clinical trial of 123 patients 18 years or older with advanced angiosarcoma that was conducted between February 16, 2017, and April 12, 2019, at 31 sites in the US and the European Union. Patients were randomized 1:1 to receive pazopanib alone or carotuximab plus pazopanib. The trial incorporated an adaptive enrichment design. Inclusion criteria were no more than 2 prior lines of systemic therapy and an Eastern Cooperative Oncology Group performance status of 0 or 1. The efficacy analysis used the intent-to-treat population; the safety analysis included all patients who received a dose of either study drug.<h4>Exposures</h4>Oral pazopanib, 800 mg/d, or intravenous carotuximab, 10 mg/kg, administered weekly, plus oral pazopanib, 800 mg/d, with dose modification allowed per patient tolerance or until disease progression.<h4>Main outcomes and measures</h4>The primary end point was PFS, assessed by blinded independent radiographic and cutaneous photographic review per Response Evaluation Criteria in Solid Tumors (RECIST) guidelines, version 1.1. Secondary end points included the objective response rate and overall survival. An interim analysis to determine the final sample size was conducted after enrollment of 123 patients. PFS in the group receiving pazopanib alone was compared with PFS in the group receiving carotuximab plus pazopanib using the log rank test.<h4>Results</h4>Of 114 patients with evaluable data (53 in the pazopanib arm and 61 in the carotuximab plus pazopanib arm), 69 (61%) were female and the median age was 68 years (range, 24-82 years); 57 (50%) had cutaneous disease and 32 (28%) had had no prior treatment. The primary end point (PFS) was not reached (hazard ratio [HR], 0.98; 95% CI, 0.52-1.84; P = .95), with a median of 4.3 months (95% CI, 2.9 months to not reached) for pazopanib and 4.2 months (95% CI, 2.8-8.3 months) for the combination arm. The most common all-grade adverse events in the single-agent pazopanib arm vs the combination arm were fatigue (29 patients [55%] vs 37 [61%]), headache (12 patients [23%] vs 39 [64%]), diarrhea (27 patients [51%] vs 35 [57%]), nausea (26 patients [49%] vs 29 [48%]), vomiting (12 patients [23%] vs 23 [38%]), anemia (5 patients [9%] vs 27 [44%]), epistaxis (2 patients [4%] vs 34 [56%]), and hypertension (29 patients [55%] vs 22 [36%]).<h4>Conclusions and relevance</h4>In this phase 3 randomized clinical trial, carotuximab plus pazopanib did not improve PFS compared with pazopanib alone in patients with advanced angiosarcoma.<h4>Trial registration</h4>ClinicalTrials.gov Identifier: NCT02979899.
<h4>Background</h4>In clinical practice, oestrogen receptor (ER) analysis is almost entirely by immunohistochemistry (IHC). ASCO/CAP recommends cut-offs of < 1% (negative) and 1-10% (low) cells positive. There is uncertainty whether patients with ER low tumours benefit from endocrine therapy. We aimed to assess IHC and mRNA cut-points for ER versus biological response of primary breast cancer to 2 weeks' aromatase inhibitor treatment as measured by change in Ki67.<h4>Methods</h4>Cases were selected from the aromatase inhibitor treatment group of POETIC. We selected the 15% with the poorest Ki67 response (PR, < 40% Ki67 suppression, n = 230) and a random 30% of the remainder categorised as intermediate (IR, 40-79% Ki67 suppression, n = 150) and good-responders (GR, ≥ 80% Ki67 suppression, n = 230) from HER2 - group. All HER2 + cases available were selected irrespective of their response category (n = 317). ER expression was measured by IHC and qPCR.<h4>Results</h4>ER IHC was available from 515 HER2 - and 186 HER2 + tumours and ER qPCR from 367 HER2 - and 171 HER2 + tumours. Ninety-one percentage of patients with ER IHC < 10% were PRs with similar rates in HER2 - and HER2 + cases. At or above ER IHC 10% substantial numbers of patients showed IR or GR. Similar proportions of patients were defined by cut-points of ER IHC < 10% and ER mRNA < 5 units. In addition, loss of PgR expression altered ER anti-proliferation response with 92% of PgR - cases with ER IHC < 40% being PRs.<h4>Conclusions</h4>There was little responsiveness at IHC < 10% and no distinction between < 1% and 1-10% cells positive. Similar separation of PRs from IR/GRs was achieved by IHC and mRNA.
<h4>Purpose</h4>Triple-negative breast cancer (TNBC) is a heterogeneous disease with a significant challenge to effectively manage in the clinic worldwide. Immunotherapy may be beneficial to TNBC patients if responders can be effectively identified. Here we sought to elucidate the immune landscape of TNBCs by stratifying patients into immune-specific subtypes (immunotypes) to decipher the molecular and cellular presentations and signaling events of this heterogeneous disease and associating them with their clinical outcomes and potential treatment options.<h4>Experimental design</h4>We profiled 730 immune genes in 88 retrospective Indian TNBC samples using the NanoString platform, established immunotypes using non-negative matrix factorization-based machine learning approach, and validated them using Western TNBCs (n=422; public datasets). Immunotype-specific gene signatures were associated with clinicopathological features, immune cell types, biological pathways, acute/chronic inflammatory responses, and immunogenic cell death processes. Responses to different immunotherapies associated with TNBC immunotypes were assessed using cross-cancer comparison to melanoma (n=504). Tumor-infiltrating lymphocytes (TILs) and pan-macrophage spatial marker expression were evaluated.<h4>Results</h4>We identified three robust transcriptome-based immunotypes in both Indian and Western TNBCs in similar proportions. Immunotype-1 tumors, mainly representing well-known claudin-low and immunomodulatory subgroups, harbored dense TIL infiltrates and T-helper-1 (Th1) response profiles associated with smaller tumors, pre-menopausal status, and a better prognosis. They displayed a cascade of events, including acute inflammation, damage-associated molecular patterns, T-cell receptor-related and chemokine-specific signaling, antigen presentation, and viral-mimicry pathways. On the other hand, immunotype-2 was enriched for Th2/Th17 responses, CD4<sup>+</sup> regulatory cells, basal-like/mesenchymal immunotypes, and an intermediate prognosis. In contrast to the two T-cell enriched immunotypes, immunotype-3 patients expressed innate immune genes/proteins, including those representing myeloid infiltrations (validated by spatial immunohistochemistry), and had poor survival. Remarkably, a cross-cancer comparison analysis revealed the association of immunotype-1 with responses to anti-PD-L1 and MAGEA3 immunotherapies.<h4>Conclusion</h4>Overall, the TNBC immunotypes identified in TNBCs reveal different prognoses, immune infiltrations, signaling, acute/chronic inflammation leading to immunogenic cell death of cancer cells, and potentially distinct responses to immunotherapies. The overlap in immune characteristics in Indian and Western TNBCs suggests similar efficiency of immunotherapy in both populations if strategies to select patients according to immunotypes can be further optimized and implemented.
<h4>Background</h4>Oestrogen receptor positive/ human epidermal growth factor receptor positive (ER+/HER2+) breast cancers (BCs) are less responsive to endocrine therapy than ER+/HER2- tumours. Mechanisms underpinning the differential behaviour of ER+HER2+ tumours are poorly characterised. Our aim was to identify biomarkers of response to 2 weeks' presurgical AI treatment in ER+/HER2+ BCs.<h4>Methods</h4>All available ER+/HER2+ BC baseline tumours (n=342) in the POETIC trial were gene expression profiled using BC360™ (NanoString) covering intrinsic subtypes and 46 key biological signatures. Early response to AI was assessed by changes in Ki67 expression and residual Ki67 at 2 weeks (Ki67<sub>2wk</sub>). Time-To-Recurrence (TTR) was estimated using Kaplan-Meier methods and Cox models adjusted for standard clinicopathological variables. New molecular subgroups (MS) were identified using consensus clustering.<h4>Findings</h4>HER2-enriched (HER2-E) subtype BCs (44.7% of the total) showed poorer Ki67 response and higher Ki67<sub>2wk</sub> (p<0.0001) than non-HER2-E BCs. High expression of ERBB2 expression, homologous recombination deficiency (HRD) and TP53 mutational score were associated with poor response and immune-related signatures with High Ki67<sub>2wk</sub>. Five new MS that were associated with differential response to AI were identified. HER2-E had significantly poorer TTR compared to Luminal BCs (HR 2.55, 95% CI 1.14-5.69; p=0.0222). The new MS were independent predictors of TTR, adding significant value beyond intrinsic subtypes.<h4>Interpretation</h4>Our results show HER2-E as a standardised biomarker associated with poor response to AI and worse outcome in ER+/HER2+. HRD, TP53 mutational score and immune-tumour tolerance are predictive biomarkers for poor response to AI. Lastly, novel MS identify additional non-HER2-E tumours not responding to AI with an increased risk of relapse.<h4>Funding</h4>Cancer Research UK (CRUK/07/015).
<h4>Purpose</h4>Aromatase inhibitor (AI) treatment is the standard of care for postmenopausal women with primary estrogen receptor-positive breast cancer. The impact of duration of neoadjuvant endocrine therapy (NET) on molecular characteristics is still unknown. We evaluated and compared changes of gene expression profiles under short-term (2-week) versus longer-term neoadjuvant AIs.<h4>Experimental design</h4>Global gene expression profiles from the PeriOperative Endocrine Therapy for Individualised Care (POETIC) trial (137 received 2 weeks of AIs and 47 received no treatment) and targeted gene expression from 80 patients with breast cancer treated with NET for more than 1 month (NeoAI) were assessed. Intrinsic subtyping, module scores covering different cancer pathways and immune-related genes were calculated for pretreated and posttreated tumors.<h4>Results</h4>The differences in intrinsic subtypes after NET were comparable between the two cohorts, with most Luminal B (90.0% in the POETIC trial and 76.3% in NeoAI) and 50.0% of HER2 enriched at baseline reclassified as Luminal A or normal-like after NET. Downregulation of proliferative-related pathways was observed after 2 weeks of AIs. However, more changes in genes from cancer-signaling pathways such as MAPK and PI3K/AKT/mTOR and immune response/immune-checkpoint components that were associated with AI-resistant tumors and differential outcome were observed in the NeoAI study.<h4>Conclusions</h4>Tumor transcriptional profiles undergo bigger changes in response to longer NET. Changes in HER2-enriched and Luminal B subtypes are similar between the two cohorts, thus AI-sensitive intrinsic subtype tumors associated with good survival might be identified after 2 weeks of AI. The changes of immune-checkpoint component expression in early AI resistance and its impact on survival outcome warrants careful investigation in clinical trials.
<h4>Purpose</h4>To determine (i) the relationship between candidate biomarkers of the antiproliferative (Ki67) response to letrozole and palbociclib alone and combined in ER<sup>+</sup>/HER2<sup>-</sup> breast cancer; and (ii) the pharmacodynamic effect of the agents on the biomarkers.<h4>Experimental design</h4>307 postmenopausal women with ER<sup>+</sup>/HER2<sup>-</sup> primary breast cancer were randomly assigned to neoadjuvant treatment with letrozole for 14 weeks; letrozole for 2 weeks, then letrozole+palbociclib to 14 weeks; palbociclib for 2 weeks, then letrozole+palbociclib to 14 weeks; or letrozole+palbociclib for 14 weeks. Biopsies were taken at baseline, 2 and 14 weeks and surgery at varying times after stopping palbociclib. Immunohistochemical analyses were conducted for Ki67, c-PARP, ER, PgR, RB1, CCNE1, and CCND1.<h4>Results</h4>Higher baselines ER and PgR were significantly associated with a greater chance of complete cell-cycle arrest (CCCA: Ki67 <2.7%) at 14 weeks and higher baseline Ki67, c-PARP, and CCNE1 with a lower chance. The interaction with treatment was significant only for c-PARP. CCND1 levels were decreased c.20% by letrozole at 2 and 14 weeks but showed a tendency to increase with palbociclib. CCNE1 levels fell 82% (median) in tumors showing CCCA but were unchanged in those with no CCCA. Only 2/9 tumors showed CCCA 3-9 days after stopping palbociclib. <i>ESR1</i> mutations were found in 2/4 tumors for which surgery took place ≥6 months after starting treatment.<h4>Conclusions</h4>High CCNE1 levels were confirmed as a biomarker of resistance to letrozole+palbociclib. Ki67 recovery within 3-9 days of discontinuing palbociclib indicates incomplete suppression of proliferation during the "off" week of its schedule.
<jats:p>Breast cancer is a heterogenous disease with variability in tumor cells and in the surrounding tumor microenvironment (TME). Understanding the molecular diversity in breast cancer is critical for improving prediction of therapeutic response and prognostication. High-plex spatial profiling of tumors enables characterization of heterogeneity in the breast TME, which can holistically illuminate the biology of tumor growth, dissemination and, ultimately, response to therapy. The GeoMx Digital Spatial Profiler (DSP) enables researchers to spatially resolve and quantify proteins and RNA transcripts from tissue sections. The platform is compatible with both formalin-fixed paraffin-embedded and frozen tissues. RNA profiling was developed at the whole transcriptome level for human and mouse samples and protein profiling of 100-plex for human samples. Tissue can be optically segmented for analysis of regions of interest or cell populations to study biology-directed tissue characterization. The GeoMx Breast Cancer Consortium (GBCC) is composed of breast cancer researchers who are developing innovative approaches for spatial profiling to accelerate biomarker discovery. Here, the GBCC presents best practices for GeoMx profiling to promote the collection of high-quality data, optimization of data analysis and integration of datasets to advance collaboration and meta-analyses. Although the capabilities of the platform are presented in the context of breast cancer research, they can be generalized to a variety of other tumor types that are characterized by high heterogeneity.</jats:p>
Multi-gene prognostic signatures including the Oncotype® DX Recurrence Score (RS), EndoPredict® (EP) and Prosigna® (Risk Of Recurrence, ROR) are widely used to predict the likelihood of distant recurrence in patients with oestrogen-receptor-positive (ER+), HER2-negative breast cancer. Here, we describe the development and validation of methods to recapitulate RS, EP and ROR scores from NanoString expression data. RNA was available from 107 tumours from postmenopausal women with early-stage, ER+, HER2- breast cancer from the translational Arimidex, Tamoxifen, Alone or in Combination study (TransATAC) where previously these signatures had been assessed with commercial methodology. Gene expression was measured using NanoString nCounter. For RS and EP, conversion factors to adjust for cross-platform variation were estimated using linear regression. For ROR, the steps to perform subgroup-specific normalisation of the gene expression data and calibration factors to calculate the 46-gene ROR score were assessed and verified. Training with bootstrapping (n = 59) was followed by validation (n = 48) using adjusted, research use only (RUO) NanoString-based algorithms. In the validation set, there was excellent concordance between the RUO scores and their commercial counterparts (r<sub>c</sub>(RS) = 0.96, 95% CI 0.93-0.97 with level of agreement (LoA) of -7.69 to 8.12; r<sub>c</sub>(EP) = 0.97, 95% CI 0.96-0.98 with LoA of -0.64 to 1.26 and r<sub>c</sub>(ROR) = 0.97 (95% CI 0.94-0.98) with LoA of -8.65 to 10.54). There was also a strong agreement in risk stratification: (RS: κ = 0.86, p < 0.0001; EP: κ = 0.87, p < 0.0001; ROR: κ = 0.92, p < 0.001). In conclusion, the calibrated algorithms recapitulate the commercial RS and EP scores on individual biopsies and ROR scores on samples based on subgroup-centreing method using NanoString expression data.
The rapidly evolving landscape of immuno-oncology (IO) is redefining the treatment of a number of cancer types. IO treatments are becoming increasingly complex, with different types of drugs emerging beyond checkpoint inhibitors. However, many of the new drugs either do not progress from phase I-II clinical trials or even fail in late-phase trials. We have identified at least five areas in the development of promising IO treatments that should be redefined for more efficient designs and accelerated approvals. Here we review those critical aspects of IO drug development that could be optimized for more successful outcome rates in all cancer types. It is important to focus our efforts on the mechanisms of action, types of response and adverse events of these novel agents. The use of appropriate clinical trial designs with robust biomarkers of response and surrogate endpoints will undoubtedly facilitate the development and subsequent approval of these drugs. Further research is also needed to establish biomarker-driven strategies to select which patients may benefit from immunotherapy and identify potential mechanisms of resistance.
The concept of precision medicine has been around for many years and recent advances in high-throughput sequencing techniques are enabling this to become reality. Within the field of breast cancer, a number of signatures have been developed to molecularly sub-classify tumours. Notable examples recently approved by National Institute for Health and Care Excellence in the UK to guide treatment decisions for oestrogen receptors (ER)+ human epidermal growth factor receptor 2 (HER2)- patients include Prosigna test, EndoPredict, and Oncotype DX. However, a population of still unmet need are those with triple negative breast cancer (TNBC). Accounting for 15-20% of patients, this population has comparatively poor prognosis and as yet no targeted treatment options. Studies have shown that some patients with TNBC respond favourably to DNA damaging drugs (carboplatin) or agents which inhibit DNA damage response (poly ADP ribose polymerase (PARP) inhibitors). Known to be a heterogeneous population, there is a need to identify further TNBC patients who may benefit from these treatments. A number of signatures have been identified based on association with treatment response or specific genetic features/pathways however many of these were not restricted to TNBC patients and as of yet are not common practice in the clinic.
Breast cancer is a highly heterogeneous disease. Although differences between intrinsic breast cancer subtypes have been well studied, heterogeneity within each subtype, especially luminal-A cancers, requires further interrogation to personalize disease management. Here, we applied well-characterized and cancer-associated heterocellular signatures representing stem, mesenchymal, stromal, immune, and epithelial cell types to breast cancer. This analysis stratified the luminal-A breast cancer samples into five subtypes with a majority of them enriched for a subtype (stem-like) that has increased stem and stromal cell gene signatures, representing potential luminal progenitor origin. The enrichment of immune checkpoint genes and other immune cell types in two (including stem-like) of the five heterocellular subtypes of luminal-A tumors suggest their potential response to immunotherapy. These immune-enriched subtypes of luminal-A tumors (containing only estrogen receptor positive samples) showed good or intermediate prognosis along with the two other differentiated subtypes as assessed using recurrence-free and distant metastasis-free patient survival outcomes. On the other hand, a partially differentiated subtype of luminal-A breast cancer with transit-amplifying colon-crypt characteristics showed poor prognosis. Furthermore, published luminal-A subtypes associated with specific somatic copy number alterations and mutations shared similar cellular and mutational characteristics to colorectal cancer subtypes where the heterocellular signatures were derived. These heterocellular subtypes reveal transcriptome and cell-type based heterogeneity of luminal-A and other breast cancer subtypes that may be useful for additional understanding of the cancer type and potential patient stratification and personalized medicine.
<h4>Purpose</h4>CDK4/6 inhibitors are used to treat estrogen receptor (ER)-positive metastatic breast cancer (BC) in combination with endocrine therapy. PALLET is a phase II randomized trial that evaluated the effects of combination palbociclib plus letrozole as neoadjuvant therapy.<h4>Patients and methods</h4>Postmenopausal women with ER-positive primary BC and tumors greater than or equal to 2.0 cm were randomly assigned 3:2:2:2 to letrozole (2.5 mg/d) for 14 weeks (A); letrozole for 2 weeks, then palbociclib plus letrozole to 14 weeks (B); palbociclib for 2 weeks, then palbociclib plus letrozole to 14 weeks (C); or palbociclib plus letrozole for 14 weeks. Palbociclib 125 mg/d was administered orally on a 21-days-on, 7-days-off schedule. Core-cut biopsies were taken at baseline and 2 and 14 weeks. Coprimary end points for letrozole versus palbociclib plus letrozole groups (A v B + C + D) were change in Ki-67 (protein encoded by the MKI67 gene; immunohistochemistry) between baseline and 14 weeks and clinical response (ordinal and ultrasound) after 14 weeks. Complete cell-cycle arrest was defined as Ki-67 less than or equal to 2.7%. Apoptosis was characterized by cleaved poly (ADP-ribose) polymerase.<h4>Results</h4>Three hundred seven patients were recruited. Clinical response was not significantly different between palbociclib plus letrozole and letrozole groups ( P = .20; complete response + partial response, 54.3% v 49.5%), and progressive disease was 3.2% versus 5.4%, respectively. Median log-fold change in Ki-67 was greater with palbociclib plus letrozole compared with letrozole (-4.1 v -2.2; P < .001) in the 190 evaluable patients (61.9%), corresponding to a geometric mean change of -97.4% versus -88.5%. More patients on palbociclib plus letrozole achieved complete cell-cycle arrest (90% v 59%; P < .001). Median log-fold change (suppression) of cleaved poly (ADP-ribose) polymerase was greater with palbociclib plus letrozole versus letrozole (-0.80 v -0.42; P < .001). More patients had grade 3 or greater toxicity on palbociclib plus letrozole (49.8% v 17.0%; P < .001) mainly because of asymptomatic neutropenia.<h4>Conclusion</h4>Adding palbociclib to letrozole significantly enhanced the suppression of malignant cell proliferation (Ki-67) in primary ER-positive BC, but did not increase the clinical response rate over 14 weeks, which was possibly related to a concurrent reduction in apoptosis.
<h4>Purpose</h4>To identify potential immune targets in post-neoadjuvant chemotherapy (NAC)-resistant triple-negative breast cancer (TNBC) and ER+HER2- breast cancer disease.<h4>Experimental design</h4>Following pathology review, 153 patients were identified as having residual cancer burden (RCB) II/III disease (TNBC n = 80; ER+HER2-n = 73). Baseline pre-NAC samples were available for evaluation for 32 of 80 TNBC and 36 of 73 ER+HER2- cases. Bright-field hematoxylin and eosin assessment allowed for tumor-infiltrating lymphocyte (TIL) evaluation in all cases. Multiplexed immunofluorescence was used to identify the abundance and distribution of immune cell subsets. Levels of checkpoints including PD-1/PD-L1 expression were also quantified. Findings were then validated using expression profiling of cancer and immune-related genes. Cytometry by time-of-flight characterized the dynamic changes in circulating immune cells with NAC.<h4>Results</h4>RCB II/III TNBC and ER+HER2- breast cancer were immunologically "cold" at baseline and end of NAC. Although the distribution of immune cell subsets across subtypes was similar, the mRNA expression profiles were both subtype- and chemotherapy-specific. TNBC RCB II/III disease was enriched with genes related to neutrophil degranulation, and displayed strong interplay across immune and cancer pathways. We observed similarities in the dynamic changes in B-cell biology following NAC irrespective of subtype. However, NAC induced changes in the local and circulating tumor immune microenvironment (TIME) that varied by subtype and response. Specifically, in TNBC residual disease, we observed downregulation of stimulatory (CD40/OX40L) and inhibitory (PD-L1/PD-1) receptor expression and an increase in NK cell populations (especially non-cytolytic, exhausted CD56dimCD16-) within both the local TIME and peripheral white cell populations.<h4>Conclusions</h4>This study identifies several potential immunologic pathways in residual disease, which may be targeted to benefit high-risk patients.
Soft tissue sarcomas (STS) are rare and diverse mesenchymal cancers with limited treatment options. Here we undertake comprehensive proteomic profiling of tumour specimens from 321 STS patients representing 11 histological subtypes. Within leiomyosarcomas, we identify three proteomic subtypes with distinct myogenesis and immune features, anatomical site distribution and survival outcomes. Characterisation of undifferentiated pleomorphic sarcomas and dedifferentiated liposarcomas with low infiltrating CD3 + T-lymphocyte levels nominates the complement cascade as a candidate immunotherapeutic target. Comparative analysis of proteomic and transcriptomic profiles highlights the proteomic-specific features for optimal risk stratification in angiosarcomas. Finally, we define functional signatures termed Sarcoma Proteomic Modules which transcend histological subtype classification and show that a vesicle transport protein signature is an independent prognostic factor for distant metastasis. Our study highlights the utility of proteomics for identifying molecular subgroups with implications for risk stratification and therapy selection and provides a rich resource for future sarcoma research.
Aromatase inhibitors (AIs) reduce recurrences and mortality in postmenopausal patients with oestrogen receptor positive (ER+) breast cancer (BC), but >20% of patients will eventually relapse. Given the limited understanding of intrinsic resistance in these tumours, here we conduct a large-scale molecular analysis to identify features that impact on the response of ER + HER2- BC to AI. We compare the 15% of poorest responders (PRs, n = 177) as measured by proportional Ki67 changes after 2 weeks of neoadjuvant AI to good responders (GRs, n = 190) selected from the top 50% responders in the POETIC trial and matched for baseline Ki67 categories. In this work, low ESR1 levels are associated with poor response, high proliferation, high expression of growth factor pathways and non-luminal subtypes. PRs having high ESR1 expression have similar proportions of luminal subtypes to GRs but lower plasma estradiol levels, lower expression of estrogen response genes, higher levels of tumor infiltrating lymphocytes and immune markers, and more TP53 mutations.
BACKGROUND: Several prognostic signatures for early oestrogen receptor-positive (ER+) breast cancer have been established with a 10-year follow-up. We tested the hypothesis that signatures optimised for 0-5-year and 5-10-year follow-up separately are more prognostic than a single signature optimised for 10 years. METHODS: Genes previously identified as prognostic or associated with endocrine resistance were tested in publicly available microarray data set using Cox regression of 747 ER+/HER2- samples from post-menopausal patients treated with 5 years of endocrine therapy. RNA expression of the selected genes was assayed in primary ER+/HER2- tumours from 948 post-menopausal patients treated with 5 years of anastrozole or tamoxifen in the TransATAC cohort. Prognostic signatures for 0-10, 0-5 and 5-10 years were derived using a penalised Cox regression (elastic net). Signature comparison was performed with likelihood ratio statistics. Validation was done by a case-control (POLAR) study in 422 samples derived from a cohort of 1449. RESULTS: Ninety-three genes were selected by the modelling of microarray data; 63 of these were significantly prognostic in TransATAC, most similarly across each time period. Contrary to our hypothesis, the derived early and late signatures were not significantly more prognostic than the 18-gene 10-year signature. The 18-gene 10-year signature was internally validated in the TransATAC validation set, showing prognostic information similar to that of Oncotype DX Recurrence Score, PAM50 risk of recurrence score, Breast Cancer Index and IHC4 (score based on four IHC markers), as well as in the external POLAR case-control set. CONCLUSIONS: The derived 10-year signature predicts risk of metastasis in patients with ER+/HER2- breast cancer similar to commercial signatures. The hypothesis that early and late prognostic signatures are significantly more informative than a single signature was rejected.
BACKGROUND: Preoperative and perioperative aromatase inhibitor (POAI) therapy has the potential to improve outcomes in women with operable oestrogen receptor-positive primary breast cancer. It has also been suggested that tumour Ki67 values after 2 weeks (Ki672W) of POAI predicts individual patient outcome better than baseline Ki67 (Ki67B). The POETIC trial aimed to test these two hypotheses. METHODS: POETIC was an open-label, multicentre, parallel-group, randomised, phase 3 trial (done in 130 UK hospitals) in which postmenopausal women aged at least 50 years with WHO performance status 0-1 and hormone receptor-positive, operable breast cancer were randomly assigned (2:1) to POAI (letrozole 2·5 mg per day orally or anastrozole 1 mg per day orally) for 14 days before and following surgery or no POAI (control). Adjuvant treatment was given as per UK standard local practice. Randomisation was done centrally by computer-generated permuted block method (variable block size of six or nine) and was stratified by hospital. Treatment allocation was not masked. The primary endpoint was time to recurrence. A key second objective explored association between Ki67 (dichotomised at 10%) and disease outcomes. The primary analysis for clinical endpoints was by modified intention to treat (excluding patients who withdrew consent). For Ki67 biomarker association and endpoint analysis, the evaluable population included all randomly assigned patients who had paired Ki67 values available. This study is registered with ClinicalTrials.gov, NCT02338310; the European Clinical Trials database, EudraCT2007-003877-21; and the ISRCTN registry, ISRCTN63882543. Recruitment is complete and long-term follow-up is ongoing. FINDINGS: Between Oct 13, 2008, and April 16, 2014, 4480 women were recruited and randomly assigned to POAI (n=2976) or control (n=1504). On Feb 6, 2018, median follow-up was 62·9 months (IQR 58·1-74·1). 434 (10%) of 4480 women had a breast cancer recurrence (280 [9%] POAI; 154 [10%] control), hazard ratio 0·92 (95% CI 0·75-1·12); p=0·40 with the proportion free from breast cancer recurrence at 5 years of 91·0% (95% CI 89·9-92·0) for patients in the POAI group and 90·4% (88·7-91·9) in the control group. Within the POAI-treated HER2-negative subpopulation, 5-year recurrence risk in women with low Ki67B and Ki672W (low-low) was 4·3% (95% CI 2·9-6·3), 8·4% (6·8-10·5) with high Ki67B and low Ki672W (high-low) and 21·5% (17·1-27·0) with high Ki67B and Ki672W (high-high). Within the POAI-treated HER2-positive subpopulation, 5-year recurrence risk in the low-low group was 10·1% (95% CI 3·2-31·3), 7·7% (3·4-17·5) in the high-low group, and 15·7% (10·1-24·4) in the high-high group. The most commonly reported grade 3 adverse events were hot flushes (20 [1%] of 2801 patients in the POAI group vs six [<1%] of 1400 in the control group) and musculoskeletal pain (29 [1%] vs 13 [1%]). No treatment-related deaths were reported. INTERPRETATION: POAI has not been shown to improve treatment outcome, but can be used without detriment to help select appropriate adjuvant therapy based on tumour Ki67. Most patients with low Ki67B or low POAI-induced Ki672W do well with adjuvant standard endocrine therapy (giving consideration to clinical-pathological factors), whereas those whose POAI-induced Ki672W remains high might benefit from further adjuvant treatment or trials of new therapies. FUNDING: Cancer Research UK.
<h4>Purpose</h4>The TNT trial (NCT00532727) showed no evidence of carboplatin superiority over docetaxel in metastatic triple-negative breast cancer (mTNBC), but carboplatin benefit was observed in the germline BRCA1/2 mutation subgroup. Broader response-predictive biomarkers are needed. We explored the predictive ability of DNA damage response (DDR) and immune markers.<h4>Experimental design</h4>Tumor-infiltrating lymphocytes were evaluated for 222 of 376 patients. Primary tumors (PT) from 186 TNT participants (13 matched recurrences) were profiled using total RNA sequencing. Four transcriptional DDR-related and 25 immune-related signatures were evaluated. We assessed their association with objective response rate (ORR) and progression-free survival (PFS). Conditional inference forest clustering was applied to integrate multimodal data. The biology of subgroups was characterized by 693 gene expression modules and other markers.<h4>Results</h4>Transcriptional DDR-related biomarkers were not predictive of ORR to either treatment overall. Changes from PT to recurrence were demonstrated; in chemotherapy-naïve patients, transcriptional DDR markers separated carboplatin responders from nonresponders (P values = 0.017; 0.046). High immune infiltration was associated with docetaxel ORR (interaction P values < 0.05). Six subgroups were identified; the immune-enriched cluster had preferential docetaxel response [62.5% (D) vs. 29.4% (C); P = 0.016]. The immune-depleted cluster had preferential carboplatin response [8.0% (D) vs. 40.0% (C); P = 0.011]. DDR-related subgroups were too small to assess ORR.<h4>Conclusions</h4>High immune features predict docetaxel response, and high DDR signature scores predict carboplatin response in treatment-naïve mTNBC. Integrating multimodal DDR and immune-related markers identifies subgroups with differential treatment sensitivity. Treatment options for patients with immune-low and DDR-proficient tumors remains an outstanding need. Caution is needed using PT-derived transcriptional signatures to direct treatment in mTNBC, particularly DDR-related markers following prior chemotherapy.
Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.
The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
<h4>Background</h4>Resistance to therapies that target homologous recombination deficiency (HRD) in breast cancer limits their overall effectiveness. Multiple, preclinically validated, mechanisms of resistance have been proposed, but their existence and relative frequency in clinical disease are unclear, as is how to target resistance.<h4>Patients and methods</h4>Longitudinal mutation and methylation profiling of circulating tumour (ct)DNA was carried out in 47 patients with metastatic BRCA1-, BRCA2- or PALB2-mutant breast cancer treated with HRD-targeted therapy who developed progressive disease-18 patients had primary resistance and 29 exhibited response followed by resistance. ctDNA isolated at multiple time points in the patient treatment course (before, on-treatment and at progression) was sequenced using a novel >750-gene intron/exon targeted sequencing panel. Where available, matched tumour biopsies were whole exome and RNA sequenced and also used to assess nuclear RAD51.<h4>Results</h4>BRCA1/2 reversion mutations were present in 60% of patients and were the most prevalent form of resistance. In 10 cases, reversions were detected in ctDNA before clinical progression. Two new reversion-based mechanisms were identified: (i) intragenic BRCA1/2 deletions with intronic breakpoints; and (ii) intragenic BRCA1/2 secondary mutations that formed novel splice acceptor sites, the latter being confirmed by in vitro minigene reporter assays. When seen before commencing subsequent treatment, reversions were associated with significantly shorter time to progression. Tumours with reversions retained HRD mutational signatures but had functional homologous recombination based on RAD51 status. Although less frequent than reversions, nonreversion mechanisms [loss-of-function (LoF) mutations in TP53BP1, RIF1 or PAXIP1] were evident in patients with acquired resistance and occasionally coexisted with reversions, challenging the notion that singular resistance mechanisms emerge in each patient.<h4>Conclusions</h4>These observations map the prevalence of candidate drivers of resistance across time in a clinical setting, information with implications for clinical management and trial design in HRD breast cancers.
Intrinsic breast cancer molecular subtyping (IBCMS) provides significant prognostic information for patients with breast cancer and helps determine treatment. This study compared IBCMS methods on various gene-expression platforms in PALOMA-2 and PALLET trials. PALOMA-2 tumor samples were profiled using EdgeSeq and nanostring and subtyped with AIMS, PAM50, and research-use-only (ruo)Prosigna. PALLET tumor biopsies were profiled using mRNA sequencing and subtyped with AIMS and PAM50. In PALOMA-2 (n = 222), a 54% agreement was observed between results from AIMS and gold-standard ruoProsigna, with AIMS assigning 67% basal-like to HER2-enriched. In PALLET (n = 224), a 69% agreement was observed between results from PAM50 and AIMS. Different IBCMS methods may lead to different results and could misguide treatment selection; hence, a standardized clinical PAM50 assay and computational approach should be used.Trial number: NCT01740427.
Interactions between cells in the tumor microenvironment (TME) shape cancer progression and patient prognosis. To gain insights into how the TME influences cancer outcomes, we derive gene expression signatures indicative of signaling between stromal fibroblasts and cancer cells, and demonstrate their prognostic significance in multiple and independent squamous cell carcinoma cohorts. By leveraging information within the signatures, we discover that the HB-EGF/EGFR/MAPK axis represents a hub of tumor-stroma crosstalk, promoting the expression of CSF2 and LIF and favoring the recruitment of macrophages. Together, these analyses demonstrate the utility of our approach for interrogating the extent and consequences of TME crosstalk.