Data from Identification of Novel Breast Cancer Risk Loci

Abstract

<div>Abstract<p>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 <i>JAK2</i> 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 <i>NOTCH3</i> SNP rs200504060 and the <i>HIF1A</i> SNP rs142179458 with breast cancer risk. <i>In silico</i> 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. <i>Cancer Res; 77(19); 5428–37. ©2017 AACR</i>.</p></div>