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Prediction of breast cancer risk based on profiling with common genetic variants.


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Authors

Pharoah, Paul DP 
Michailidou, Kyriaki 
Brook, Mark N 

Abstract

BACKGROUND: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. METHODS: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. RESULTS: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. CONCLUSIONS: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.

Description

Keywords

Adult, Aged, Biomarkers, Tumor, Breast Neoplasms, Europe, Female, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Genetic Predisposition to Disease, Genotype, Humans, Middle Aged, Odds Ratio, Polymorphism, Single Nucleotide, Predictive Value of Tests, Receptors, Estrogen, Risk Assessment, Risk Factors

Journal Title

J Natl Cancer Inst

Conference Name

Journal ISSN

0027-8874
1460-2105

Volume Title

107

Publisher

Oxford University Press (OUP)
Sponsorship
National Cancer Institute (U19CA148537)
National Cancer Institute (R01CA128978)
National Cancer Institute (U19CA148065)
Cancer Research Uk (None)
Cancer Research Uk (None)
European Commission (223175)
Cancer Research UK (10710)
Cancer Research UK (12014)
Cancer Research UK (10118)
Cancer Research Uk (None)
Cancer Research UK (16563)
Cancer Research UK (16565)
This work was supported by Cancer Research-UK (grant numbers C1287/A10118, C1287/A12014) and the European Community’s Seventh Framework Programme (223175 [HEALTH-F2-2009–223175]) (COGS). Genotyping of the iCOGS array was funded by the European Union (HEALTH-F2-2009–223175), Cancer Research UK (C1287/A10710), the Canadian Institutes of Health Research (CIHR) for the “CIHR Team in Familial Risks of Breast Cancer” program, and the Ministry of Economic Development, Innovation and Export Trade of Quebec (PSR-SIIRI-701). This work was also supported by Breakthrough Breast Cancer funding (to MGC). Analysis was supported in part by the National Institutes of Health Post-Genome Wide Association initiative (1U19CA148065 (DRIVE) and 1U19CA148537 (ELLIPSE)). Laboratory infrastructure was funded by Cancer Research UK (C8197/A10123). This work was also supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research and the Ministère de l’enseignement supérieur, de la recherche, de la science et de la technologie du Québec through Génome Québec for the PERSPECTIVE project. Breast Cancer Association Consortium meetings were funded by the European Union European Cooperation in Science and Technology (COST) programme (BM0606).