Data from A Cross-Cancer Genetic Association Analysis of the DNA Repair and DNA Damage Signaling Pathways for Lung, Ovary, Prostate, Breast, and Colorectal Cancer

Abstract

<div>Abstract<p><b>Background:</b> DNA damage is an established mediator of carcinogenesis, although genome-wide association studies (GWAS) have identified few significant loci. This cross-cancer site, pooled analysis was performed to increase the power to detect common variants of DNA repair genes associated with cancer susceptibility.</p><p><b>Methods:</b> We conducted a cross-cancer analysis of 60,297 single nucleotide polymorphisms, at 229 DNA repair gene regions, using data from the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) Network. Our analysis included data from 32 GWAS and 48,734 controls and 51,537 cases across five cancer sites (breast, colon, lung, ovary, and prostate). Because of the unavailability of individual data, data were analyzed at the aggregate level. Meta-analysis was performed using the Association analysis for SubSETs (ASSET) software. To test for genetic associations that might escape individual variant testing due to small effect sizes, pathway analysis of eight DNA repair pathways was performed using hierarchical modeling.</p><p><b>Results:</b> We identified three susceptibility DNA repair genes, <i>RAD51B</i> (<i>P</i> < 5.09 × 10<sup>−6</sup>), <i>MSH5</i> (<i>P</i> < 5.09 × 10<sup>−6</sup>), and <i>BRCA2</i> (<i>P</i> = 5.70 × 10<sup>−6</sup>). Hierarchical modeling identified several pleiotropic associations with cancer risk in the base excision repair, nucleotide excision repair, mismatch repair, and homologous recombination pathways.</p><p><b>Conclusions:</b> Only three susceptibility loci were identified, which had all been previously reported. In contrast, hierarchical modeling identified several pleiotropic cancer risk associations in key DNA repair pathways.</p><p><b>Impact:</b> Results suggest that many common variants in DNA repair genes are likely associated with cancer susceptibility through small effect sizes that do not meet stringent significance testing criteria. <i>Cancer Epidemiol Biomarkers Prev; 25(1); 193–200. ©2015 AACR</i>.</p></div>