1. The genetic epidemiology of common hormonal cancers Deborah Thompson Centre for Cancer Genetic Epidemiology

2. The 15 Most Common Cancers, UK 2011 (Cancer Research UK)

3. Fam RR ~2 2-3 ~2 3-4 The 20 Most Common Cancers, UK 2011 (Cancer Research UK) Account for 32% of UK cancers

4. Example: The landscape for breast genetics in 1997

5. Example: The landscape for breast genetics in 2014

6. International Consortia in which CCGE plays a key role Cancer siteConsortiumNo. studiesCCGE involvement BreastBCAC90SEARCH study, SIBS study; Genetic + phenotypic data management, QC + statistical analyses, website ProstatePRACTICAL78SEARCH study; Genetic + phenotypic data management, QC + statistical analyses, website BRCA1/2 carriersCIMBA65EMBRACE study, UKFOCR study; Genetic + phenotypic data management, QC + statistical analyses, website OvarianOCAC50SEARCH study, UKFOCR study, RMH study; Genetic data management, QC + statistical analyses, website EndometrialECAC16SEARCH study; QC + statistical analyses + computing / bioinformatics + laboratory resources

7. The Collaborative Oncological Gene- environment Study (COGS) GWAS follow-up fine-mapping candidate variants 211,115 SNPs SNP selection:BCAC OCAC PRACTICAL CIMBA “Common” Genotyped in >200,000 samples: cancer cases/ctrls BRCA1/2 carriers

8. March 2013: 13 iCOGS papers, >70 new cancer loci

9. Unexplained: 50% BRCA1 BRCA2 CHEK2 ATM PALB2 BRIP1 XRCC2 TP53 PTEN LKB1 SNPs pre-iCOGS (GWAS) Proportional of the Familial RR of Breast Cancer Explained iCOGS SNPs Other iCOGS estimated 9% 5% 14% Michailidou et al 2014

10. Proportional of the Familial RRs of: Unexplained: 54% BRCA1 BRCA2 40% GWAS 3% iCOGS 1% RAD51C RAD51D BRIP1 2% Ovarian Cancer Unexplained: 65% BRCA1 BRCA2 HOXB13 MMR NBS1 CHEK2 5% GWAS 25% iCOGS 5% Prostate Cancer

11. 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 20253035404550556065 10 yr breast cancer risk Age (years) Lowest risk quintile Quintile 2 Quintile 3 Quintile 4 Highest risk quintile Reference Ten year breast cancer risk based on 77 SNP profile 70

12. BOADICEA is a polygenic risk prediction model for familial breast and ovarian cancer. Based on cancer family-history it computes: age-specific risks of breast and ovarian cancer BRCA1 and BRCA2 mutation carrier probabilities The user-friendly BOADICEA web application allows researchers, clinicians and members of the public to estimate risks The web application has ~3,800 registered users worldwide Recommended as a risk assessment tool in NICE clinical guidelines and internationally (e.g. American Cancer Society, Ontario BSP). Using our findings: the BOADICEA model

14. http://ccge.medschl.cam.ac.uk/boadicea/

16. GAME-ON OncoArray OncoChip 600K beadtypes GWAS Backbone 250K Illumina Core Common Content – 40K Fine-mapping of common cancer susceptibility loci Ancestry Informative Markers Cross-Site meta analysis Pharmacogenetic components Quantitative traits Other cancers published GWAS variants Chromosome X and mitochondrial DNA variants Cancer Specific Variants ~320k Prostate Breast Ovarian Lung BRCA1/2 carriers Colon

17. What next? DISCOVERY: OncoArray Sequencing (targeted, whole-genome) FINE-MAPPING: looking at GWAS/iCOGS risk loci in more detailed multiple independent variables within loci? linking epidemiological and functional evidence APPLICATION: extension of BOADICEA developing risk-prediction models for other cancers

18. Acknowledgements