Background: Germline DNA copy number variation (CNV) is a ubiquitous source of genetic variation and remains largely unexplored in association with epithelial ovarian cancer (EOC) risk.Methods: CNV was quantified in the DNA of approximately 3,500 cases and controls genotyped with the Illumina 610k and HumanOmni2.5M arrays. We performed a genome-wide association study of common (>1%) CNV regions (CNVRs) with EOC and high-grade serous (HGSOC) risk and, using The Cancer Genome Atlas (TCGA), performed in silico analyses of tumor-gene expression.Results: Three CNVRs were associated (P < 0.01) with EOC risk: two large ($100 kb) regions within the 610k set and one small (<5 kb) region with the higher resolution 2.5M data. Large CNVRs included a duplication at LILRA6 (OR ¼ 2.57; P ¼ 0.001) and a deletion at CYP2A7 (OR ¼ 1.90; P ¼ 0.007) that were strongly associated with HGSOC risk (OR ¼ 3.02; P ¼ 8.98 Â 10 À5 ). Somatic CYP2A7 alterations correlated with EGLN2 expression in tumors (P ¼ 2.94 Â 10 À47 ). An intronic ERBB4/HER4 deletion was associated with reduced EOC risk (OR ¼ 0.33; P ¼ 9.5 Â 10 À2 ), and somatic deletions correlated with ERBB4 downregulation (P ¼ 7.05 Â 10 À5 ). Five CNVRs were associated with HGSOC, including two reduced-risk deletions: one at 1p36.33 (OR ¼ 0.28; P ¼ 0.001) that correlated with lower CDKIIA expression in TCGA tumors (P ¼ 2.7 Â 10 À7 ), and another at 8p21.2 (OR ¼ 0.52; P ¼ 0.002) that was present somatically where it correlated with lower GNRH1 expression (P ¼ 5.9 Â 10 À5 ).Conclusions: Though CNV appears to not contribute largely to EOC susceptibility, a number of low-to-common frequency variants may influence the risk of EOC and tumor-gene expression.Impact: Further research on CNV and EOC susceptibility is warranted, particularly with CNVs estimated from highdensity arrays.CNVR was defined by overlapping CNV segments across subjects. P values are from logistic regression adjusted for the first principal component. b CNV segments centered on the reported genes, which fell within the SNP-level significance region.
Authors' ContributionsConception and design: B.M. Reid, J.B. Permuth, E.L. Goode, T.A. Sellers Development of methodology: B.M. Reid Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): J.M. Cunningham, S. Narod, H. Risch, J.M. Schildkraut, T.A. Sellers Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis):