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Up to 30% of all breast cancer cases may be inherited and up to 85% of those may be due to segregation of susceptibility genes with low and moderate risk [odds ratios (OR) ≤ 3] for (mostly peri- and post-menopausal) breast cancer. The majority of low/moderate-risk genes, particularly those with minor allele frequencies (MAF) of < 30%, have not been identified and/or validated due to limitations of conventional association testing approaches, which include the agnostic nature of Genome Wide Association Studies (GWAS). To overcome these limitations, we used a hypothesis-driven integrative genomics approach to test the association of breast cancer with candidate genes by analyzing multi-omics data. Our candidate-gene association analyses of GWAS datasets suggested an increased risk of breast cancer with  ERCC6  (main effect: 1.29 ≤ OR ≤ 2.91, 0.005 ≤ p ≤ 0.04, 11.8 ≤ MAF ≤ 40.9%), and implicated its interaction with  ERCC8  (joint effect: 3.03 ≤ OR ≤ 5.31, 0.01 ≤ p interaction  ≤ 0.03). We found significant upregulation of  ERCC6  (p = 7.95 × 10 –6 ) and  ERCC8  (p = 4.67 × 10 –6 ) in breast cancer and similar frequencies of  ERCC6  (1.8%) and  ERCC8  (0.3%) mutations in breast tumors to known breast cancer susceptibility genes such as  BLM  (1.9%) and  LSP1  (0.3%). Our integrative genomics approach suggests that  ERCC6  may be a previously unreported low- to moderate-risk breast cancer susceptibility gene, which may also interact with  ERCC8 .

Integrative genomic analysis implicates ERCC6 and its interaction with ERCC8 in susceptibility to breast cancer