Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could... Show morePolygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs. Show less
Ek, W.E.; Tobi, E.W.; Ahsan, M.; Lampa, E.; Ponzi, E.; Kyrtopoulos, S.A.; ... ; Epigenome-Wide Assoc Study Cons 2017
Extensive expression profiling studies have shown that sporadic breast cancer is composed of five clinically relevant molecular subtypes. However, although BRCA1-related tumours are known to be... Show moreExtensive expression profiling studies have shown that sporadic breast cancer is composed of five clinically relevant molecular subtypes. However, although BRCA1-related tumours are known to be predominantly basal-like, there are few published data on other classes of familial breast tumours. We analysed a cohort of 75 BRCA1, BRCA2 and non-BRCA1/2 breast tumours by gene expression profiling and found that 74% BRCA1 tumours were basal-like, 73% of BRCA2 tumours were luminal A or B, and 52% non-BRCA1/2 tumours were luminal A. Thirty-four tumours were also analysed by single nucleotide polymorphism-comparative genomic hybridization (SNP-CGH) arrays. Copy number data could predict whether a tumour was basal-like or luminal with high accuracy, but could not predict its mutation class. Basal-like BRCA1 and basal-like non-BRCA1 tumours were very similar, and contained the highest number of chromosome aberrations. We identified regions of frequent gain containing potential driver genes in the basal (8q and 12p) and luminal A tumours (1q and 17q). Regions of homozygous loss associated with decreased expression of potential tumour suppressor genes were also detected, including in basal tumours (5q and 9p), and basal and luminal tumours (10q). This study highlights the heterogeneity of familial tumours and the clinical consequences for treatment and prognosis. Show less
