It has been estimated that >1,000 genetic loci have yet to be identified for breast cancer risk. Here we report the first study utilizing targeted next-generation sequencing to identify single-nucleotide polymorphisms (SNP) associated with breast cancer risk. Targeted sequencing of 283 genes was performed in 240 women with early-onset breast cancer (≤40 years) or a family history of breast and/or ovarian cancer. Common coding variants with minor allele frequencies (MAF) >1% that were identified were presumed initially to be SNPs, but further database inspections revealed variants had MAF of ≤1% in the general population. Through prioritization and stringent selection criteria, we selected 24 SNPs for further genotyping in 1,516 breast cancer cases and 1,189 noncancer controls. Overall, we identified the JAK2 SNP rs56118985 to be significantly associated with overall breast cancer risk. Subtype analysis performed for patient subgroups defined by ER, PR, and HER2 status suggested additional associations of the NOTCH3 SNP rs200504060 and the HIF1A SNP rs142179458 with breast cancer risk. In silico analysis indicated that coding amino acids encoded at these three SNP sites were conserved evolutionarily and associated with decreased protein stability, suggesting a likely impact on protein function. Our results offer proof of concept for identifying novel cancer risk loci from next-generation sequencing data, with iterative data analysis from targeted, whole-exome, or whole-genome sequencing a wellspring to identify new SNPs associated with cancer risk. Cancer Res; 77(19); 5428-37. ©2017 AACR.
©2017 American Association for Cancer Research.