Polygenic Scores for Cancer Prevention – Self-paced module – IARC-ESMO Cancer Prevention Learning and Capacity-Building Initiative

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Date of the recording: 2 March 2022

Webinar organized with the support of and in collaboration with the European Society for Medical Oncology (ESMO).

INTRODUCTION BY

Dr James McKay

Deputy Head, Genomic Epidemiology Branch

International Agency for Research on Cancer, Lyon, France

About Dr James McKay

SPEAKERS

POLYGENIC SCORES FOR STRATIFIED CANCER PREVENTION

Dr Nilanjan Chatterjee

Bloomberg Distinguished Professor of Biostatistics and Genetic Epidemiology

Johns Hopkins University, Baltimore, USA

Genome-wide association studies of increasing sample size and diverse ancestry are now leading to polygenic scores with significant potential for risk stratification across cancers. This presentation will provide a brief overview of emerging opportunities and discuss some limitations of the use of polygenic scores for developing risk-stratified approaches to cancer prevention. Dr Chatterjee will describe results from a recent study on the validation of a breast cancer risk prediction model that integrates polygenic scores with other established risk factors and will provide an assessment of the potential clinical utility of the model for breast cancer prevention.

Short biography: Dr Nilanjan Chatterjee

Nilanjan Chatterjee, PhD, is a Bloomberg Distinguished Professor of Biostatistics and Genetic Epidemiology at Johns Hopkins University. Before joining Johns Hopkins, he was the Chief of the Biostatistics Branch of the Division of Cancer Epidemiology and Genetics at the United States National Cancer Institute. He leads a broad research programme in developing and applying novel methods for the investigation of genetic and environmental causes of cancers, development of models for risk prediction, and evaluation of their utility for cancer prevention. He is currently a member of the Scientific Advisory Committee of the Radiation Effects Research Foundation, Hiroshima, Japan, and the Prevention and Population Committee of Cancer Research UK. He is a Fellow of the American Statistical Association and the American Epidemiological Society, and he has received numerous prestigious awards for his fundamental contributions to biostatistical methods.

GENETIC DETERMINANTS FOR PROSTATE-SPECIFIC ANTIGEN LEVELS IMPROVE CANCER SCREENING UTILITY

Dr Linda Kachuri

Assistant Professor in the Department of Epidemiology and Population Health

Stanford University, USA

Prostate-specific antigen (PSA) screening for prostate cancer is widely used, but it remains controversial because of issues with sensitivity and specificity. PSA level is highly heritable, and therefore one avenue for improving its diagnostic accuracy is to account for variation in PSA level that is due to genetics and does not reflect prostate cancer. Dr Kachuri will present findings from the largest genome-wide association study of PSA levels and will demonstrate how using a polygenic score to correct PSA values can improve the clinical utility by reducing overdiagnosis and unnecessary testing and increasing detection of aggressive disease.

Short biography: Dr Linda Kachuri

Dr Linda Kachuri is a Postdoctoral Scholar at the University of California San Francisco and an incoming Assistant Professor in the Department of Epidemiology and Population Health at Stanford University. Her research in cancer epidemiology focuses on using genetics to decipher etiological mechanisms, improve risk prediction, and reduce cancer disparities. Dr Kachuri uses a range of methods, such as Mendelian randomization, polygenic risk scores, and integrative analyses of transcriptomic and proteomic data. She is a member of the American Society of Human Genetics (ASHG) and the International Genetic Epidemiology Society, and she received the ASHG Charles J. Epstein Trainee Award for Excellence in Human Genetics Research for her work on the application of polygenic risk scores in cancer.

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Questions and Answers – Webinar 6

Test your knowledge on polygenic risk scores for cancer prevention!

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REFERENCES

And other not-to-be-missed resources on polygenic scores

VIDEO: Polygenic risk scores improve cancer risk prediction and stratification (4 minutes)

Hurson A N et al. for the B-CAST Risk Modelling Group (2021). Prospective evaluation of a breast-cancer risk model integrating classical risk factors and polygenic risk in 15 cohorts from six countries. Int J of Epidemiol. 50(6): 1897-1911.

Kachuri et al. (2023). Genetically adjusted PSA levels for prostate cancer screening. Nat Med. https://doi.org/10.1101/2022.04.18.22273850

Kachuri L (2021). Polygenic risk scores improve cancer risk prediction and stratification, Behind the Paper, Nature Portfolio Cancer Community.

Kachuri L et al. (2020). Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction. Nature Communications. 11(1): 6084.

Wang T et al. (2021). Commentary: Polygenic risk for breast cancer: in search for potential clinical utility. Int J of Epidemiol. 50(6): 1911-1913.

Resource Content

Dr James McKay (6 min.)

Dr Nilanjan Chatterjee (18 min.)

Dr Linda Kachuri (22 min.)

Questions and Answers – Webinar 6 Sample Sequence

Test your knowledge on polygenic risk scores for cancer prevention!