Integrative Cancer Epidemiology Group

The Integrative Cancer Epidemiology Group uses epidemiological methods to better understand carcinogenic processes and improve risk assessment for precision prevention. 


Professor Montse Garcia-Closas

Group Leader:

Integrative Cancer Epidemiology Headshot of Montse Garcia-Closas

Professor Montserrat García-Closas is physician epidemiologist expert in genetic susceptibility, etiologic heterogeneity, and risk prediction for breast cancer. She co-leads the Cancer Epidemiology and Prevention Unit at ICR and Imperial College, and is a member and leader of several large international consortia in cancer epidemiology.

Researchers in this group

headshot of daniel adams .

Phone: +44 20 3437 6233

Email: [email protected]

Location: Sutton

Dr Daniel Adams joined The Generations Study research team in 2023 with Professor Garcia-Closas. A medical doctor by training, Daniel practiced as a General Practitioner in the South of England after obtaining his medical degree from Semmelweis University in Budapest, Hungary. His interest in data science led to a degree in Health Data Analytics and Machine Learning from Imperial College London. At the ICR, Daniel combines his clinical experience and data science training to analyse digital images of breast tissue using AI. He also conducts statistical analyses for breast cancer survival and risk factors.

Headshot of Tal Cohen .

Email: [email protected]

Location: Sutton

Tal joined the Generations Study research team in 2025 with Professor Garcia-Closas. After professional experience in large-scale automated data pipeline creation and management, he received his MSc in Epidemiology from The London School of Hygiene and Tropical Medicine after completing his thesis on the long-term drivers of interepidemic periods of dengue virus. His work at the ICR centres around creating and managing efficient data pipelines and responsible delivery of data to analysts in alignment with FAIR principles.

Penny Coulson headshot .

Phone: +44 20 8722 4196

Email: [email protected]

Location: Sutton

Penny joined The Generations Study research team in 2010 having transferred from being a Study Co-ordinator on the ICR Cancer Screening Evaluation Team. Responsible for managing pathology and mammographic density data among others, Penny understands the entire sample collection management system. She provides operational support for the day-to-day data collection as well as longitudinal cohort data for the research analysts.

Headshot of Ana Ferreira .

Phone: +44 20 3437 6319

Email: [email protected]

Location: Sutton

Ana joined The Generations Study research team in 2024 with Professor Garcia-Closas. A biomedical scientist by training, Ana holds a MSc in Experimental Pathology and has worked at the ICR for nearly ten years. She transferred from the Cancer Biomarkers Team where she investigated biomarkers of metastatic prostate cancer for the development of novel cancer therapies. Ana is responsible for the management of biological specimens and digital pathology processes within the study by establishing workflows and quality control metrics for scanning, storing and analysing the tissue slides. These will be used to understand how risk factors are related to different types of breast cancer, and to identify tissue biomarkers of transformation from benign breast disease to breast cancer.

Headshot of Reuben Frost .

Phone: +44 20 3437 6232

Email: [email protected]

Location: Sutton

Reuben joined The Generations Study research team in 2023 with Professor Garcia-Closas. Previously, he graduated from University of Oxford with a Masters in Mathematics and Statistics, completing his dissertation utilizing Markov Chain Monte Carlo methods to phase imputed genetic samples. Reuben's research focusses on evaluating the performance of models assessing breast cancer risk, and collaborating with other groups to improve these models. He also works on descriptive epidemiology studies, working to find patterns in cancer rates and risk factors in the UK population with the view of projecting these trends into the future.

Headshot of Sanjay Hegde .

Phone: +44 20 3437 6351

Email: [email protected]

Location: Sutton

Sanjay joined The Generations Study research team in 2024 working with Professor Garcia-Closas. He holds an MSc in Data Science from the University of Birmingham and has expertise in Python, Spark, SQL, and MS Azure, along with knowledge in Machine Learning and Large Language Models. Currently, Sanjay is engaged in Data Management and Transformation of Generations Study data systems to improve the use of data following FAIR principles.

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Phone: +44 20 8722 4362

Email: [email protected]

Location: Sutton

Headshot of Jane Lebihan .

Phone: +44 20 8722 4394

Email: [email protected]

Location: Sutton

Jane joined The Generations Study research team in 2010 working as a PA/Research Administrator and is currently working as a Senior Research Administrator. Jane is responsible for the pathology collection of samples and pathology reports. These are requested from hospitals all around the country. Samples and pathology reports have been collected for breast and ovarian cancers. These samples are then processed in our laboratory in order to investigate risk and prognostic factors for these cancers and the data from the pathology reports are used by the study scientists.

Headshot of June Palmer .

Phone: +44 20 8722 4470

Email: [email protected]

Location: Sutton

June joined The Generations Study research team in 2016. Her role includes sending and receiving files from organisations such as the NHS and uploading them securely into SQL Server. She helps to implement online questionnaires for the Generations participants. The results are then fed into existing processes for use by the analysts in the team. She regularly extracts the data and pseudo anonymises it for use by outside collaborators.

Headshot of Zoey Richards .

Phone: +44 20 3437 6411

Email: [email protected]

Location: Sutton

Zoey joined The Generations Study research team in 2024 with Professor Garcia-Closas. She moved into the role after graduating from London School of Hygiene and Tropical Medicine with a MSc in Epidemiology where she wrote her dissertation on how physical proximity to health facilities impacted implant contraceptive use in Senegal. Zoey is working on increasing study access and awareness of the Generations Study. On the research side, she uses geospatial analyses to identify social and environmental risk factors for breast cancer to identify and help address health inequities through public health policy and interventions.

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Email: [email protected]

Location: Sutton

Irina joined The Generations Study research team in 2024 as a PhD student to investigate tissue-based biomarkers on benign breast biopsies and the associations with future breast cancer. Previously she worked as an R&D Graduate Scientist in Data Science and AI at AstraZeneca, specialising in leveraging computer vision and artificial intelligence to analyse histopathology images to assist patient stratification and inform clinical research. Irina's research is aimed to integrate computational pathology and statistical modelling to assess breast cancer risk for women with benign breast diseases and explore tissue models to enhance our understanding of breast carcinogenesis.

Professor Montse Garcia-Closas's group have written 50 publications

Most recent new publication 10/2010

See all their publications

Recent discoveries from this group

22/01/25

Doctors could soon be able to better predict an individual patient’s chances of getting cancer and offer them personalised detection and prevention strategies, thanks to a new research project co-led by scientists at The Institute of Cancer Research, London. 

Today, Cancer Research UK, the National Institute for Health and Care Research (NIHR) and the Engineering and Physical Sciences Research Council (EPSRC) announced the launch of the Cancer Data-Driven Detection programme.   

The £10million programme, which will be led by the University of Cambridge, aims to access and link vast quantities of data from different sources - including health records, genomics, family history, demographics, and behavioural data. The research teams will then develop advanced statistical models that will help scientists more accurately predict who is most likely to get cancer.  

Alongside this, the programme will develop powerful new tools which use AI to analyse the data and calculate an individual’s risk of cancer throughout their lifetime.   

Building the infrastructure

Over the next five years, the funding will be used to build the infrastructure required to access and link these datasets, train new data scientists, create the algorithms behind the risk models and evaluate the algorithms and AI tools to ensure that they are giving accurate and clinically useful information about cancer risk.  

The data generated from this research could be used to offer more frequent cancer screening sessions or screening at a younger age to those at higher risk. Those at lower risk could be spared unnecessary tests. People identified as higher risk could also fast-tracked for cancer testing when they go to their GP with possible cancer signs or symptoms.  

The Institute of Cancer Research (ICR)’s role in the project will be to harmonise and analyse the combined data from diverse sources across the UK, including a cohort from the long-running Breast Cancer Now Generations study, to capture a wide range of ethnic, geographical, and socioeconomic characteristics for cancer research.  

Analysing trends in cancer incidence

The ICR team, led by Professor Montserrat Garcia-Closas, will work within the Cancer Epidemiology and Prevention Research Unit (CEPRU) she co-directs, a collaboration between ICR and Imperial College London, and other key institutions across the UK. 

Professor Montserrat Garcia-Closas, Group Leader for the Integrative Epidemiology Group at The Institute of Cancer Research, London, said:  

“We are delighted to be part of this UK-wide initiative involving many institutions working together to ensure a truly national and inclusive approach to cancer data science. We will be examining trends in cancer incidence across population groups and regions and addressing health inequities by analysing how risk factors affect different demographic and geographic subgroups.  

“The risk models we develop will be used to guide public health policies for prevention and early detection of cancer, with applications extending beyond risk predictions for individuals to optimise resource allocation and maximise population-level impact.” 

Finding those most at risk of cancer

Director of the Cancer Data Driven Detection programme and Professor of Cancer Risk Prediction at the University of Cambridge, Professor Antonis Antoniou, said:  

“Finding people at the highest risk of developing cancer, including those with vague symptoms, is a major challenge. The UK’s strengths in population-scale data resources, combined with advanced analytical tools like AI, offer tremendous opportunities to link disparate datasets and uncover clues that could lead to earlier detection, diagnosis, and prevention of more cancers.”    

“The Cancer Data Driven Detection programme will build the partnerships and infrastructure needed to make data-driven cancer early detection, diagnosis and prevention a routine part of frontline healthcare. Ultimately, it could inform public health policy and empower individuals and their healthcare providers to make shared decisions. By understanding individual cancer risks, people can take proactive steps to stop cancer before it gets worse or even begins in the first place.”  

Head of Prevention and Early Detection Research at Cancer Research UK, Dr David Crosby, said:  

“The single most important thing we can do to beat cancer is to find it earlier, when treatment is more likely to be successful. With half a million cancer cases per year expected in the UK by 2040, we need a major shift towards more accurate diagnosis and detection of early cancer.   

“The Cancer Data Driven Detection programme will link health data sources together and build the powerful new tools doctors need to identify those at highest risk of cancer and prioritise resources towards them.  

“Moving towards a preventative approach to healthcare will not be easy and will take time. Cancer Research UK’s investment in the programme is an investment in the future of cancer care.”    

Lord Vallance, Minister of State for Science, Research and Innovation, said:

 “There are huge opportunities in AI to improve UK healthcare, from scans detecting illnesses earlier to bringing NHS waiting lists down by planning appointments more efficiently, and these will continue to develop.  

 “This investment in harnessing the potential of data to spot those at risk of cancer represents the sort of innovation the Government’s new AI Opportunities Action Plan sets out to realise, so this technology improves lives, while transforming public services and boosting growth.”