Transcript Slide 1
The genetic epidemiology of common hormonal cancers Deborah Thompson Centre for Cancer Genetic Epidemiology The 15 Most Common Cancers, UK 2011 (Cancer Research UK) The 20 Most Common Cancers, UK 2011 (Cancer Research UK) Fam RR ~2 2-3 Account for 32% of UK cancers ~2 3-4 Example: The landscape for breast genetics in 1997 BRCA1 TP53 Relative Risk 10 BRCA2 PTEN ? ATM ? 1 0.000001 0.00001 0.0001 0.001 Allele frequency 0.01 0.1 1 Example: The landscape for breast genetics in 2014 CDH1 BRCA1 TP53 10 BRCA2 Relative Risk STK11 PALB2 PTEN CHEK2 ATM Risk SNPs 1 0.000001 0.00001 0.0001 0.001 Allele frequency 0.01 0.1 1 International Consortia in which CCGE plays a key role Cancer site Consortium No. studies CCGE involvement Breast BCAC 90 SEARCH study, SIBS study; Genetic + phenotypic data management, QC + statistical analyses, website Prostate PRACTICAL 78 SEARCH study; Genetic + phenotypic data management, QC + statistical analyses, website BRCA1/2 carriers CIMBA 65 EMBRACE study, UKFOCR study; Genetic + phenotypic data management, QC + statistical analyses, website Ovarian OCAC 50 SEARCH study, UKFOCR study, RMH study; Genetic data management, QC + statistical analyses, website Endometrial ECAC 16 SEARCH study; QC + statistical analyses + computing / bioinformatics + laboratory resources The Collaborative Oncological Geneenvironment Study (COGS) 211,115 SNPs SNP selection: BCAC OCAC PRACTICAL CIMBA “Common” • GWAS follow-up • fine-mapping • candidate variants Genotyped in >200,000 samples: • cancer cases/ctrls • BRCA1/2 carriers March 2013: 13 iCOGS papers, >70 new cancer loci Proportional of the Familial RR of Breast Cancer Explained Unexplained: 50% Other iCOGS estimated 14% Michailidou et al 2014 iCOGS SNPs 5% SNPs pre-iCOGS (GWAS) 9% TP53 PTEN LKB1 CHEK2 ATM PALB2 BRIP1 XRCC2 BRCA1 BRCA2 Proportional of the Familial RRs of: Unexplained: 54% Ovarian Cancer BRCA1 BRCA2 40% iCOGS 1% GWAS RAD51C RAD51D 3% BRIP1 2% Prostate Cancer Unexplained: 65% iCOGS 5% GWAS 25% BRCA1 BRCA2 HOXB13 MMR NBS1 CHEK2 5% Ten year breast cancer risk based on 77 SNP profile 10 yr breast cancer risk 0.10 Lowest risk quintile 0.09 Quintile 2 0.08 Quintile 3 0.07 Quintile 4 0.06 Highest risk quintile 0.05 Reference 0.04 0.03 0.02 0.01 0 20 25 30 35 40 45 50 55 Age (years) 60 65 70 Using our findings: the BOADICEA model 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). http://ccge.medschl.cam.ac.uk/boadicea/ GAME-ON OncoArray 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 GWAS Backbone OncoChip 250K 600K beadtypes Illumina Core Cancer Specific Variants ~320k Prostate Breast Ovarian Lung BRCA1/2 carriers Colon 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 Acknowledgements