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. 2016 Jan;25(1):193-200.
doi: 10.1158/1055-9965.EPI-15-0649. Epub 2015 Dec 4.

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

Peter M Scarbrough  1 , Rachel Palmieri Weber  2 , Edwin S Iversen  3 , Yonathan Brhane  4 , Christopher I Amos  5 , Peter Kraft  6 , Rayjean J Hung  4 , Thomas A Sellers  7 , John S Witte  8 , Paul Pharoah  9 , Brian E Henderson  10 , Stephen B Gruber  10 , David J Hunter  6 , Judy E Garber  11 , Amit D Joshi  6 , Kevin McDonnell  10 , Doug F Easton  12 , Ros Eeles  13 , Zsofia Kote-Jarai  13 , Kenneth Muir  14 , Jennifer A Doherty  5 , Joellen M Schildkraut  15
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A Cross-Cancer Genetic Association Analysis of the DNA Repair and DNA Damage Signaling Pathways for Lung, Ovary, Prostate, Breast, and Colorectal Cancer

Peter M Scarbrough et al. Cancer Epidemiol Biomarkers Prev. 2016 Jan.

Abstract

Background: 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.

Methods: 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.

Results: We identified three susceptibility DNA repair genes, RAD51B (P < 5.09 × 10(-6)), MSH5 (P < 5.09 × 10(-6)), and BRCA2 (P = 5.70 × 10(-6)). Hierarchical modeling identified several pleiotropic associations with cancer risk in the base excision repair, nucleotide excision repair, mismatch repair, and homologous recombination pathways.

Conclusions: 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.

Impact: 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.

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Conflict of interest statement

Conflict of Interest Statement

Dr. Ros Eeles has research support from Janssen and also received an honorarium from Speakers Bureau. Dr. Judy Garber is a consultant for Pfizer and Sequenom and has a commercial research grant from Myriad Genetic Labs. Dr. Garber also has immediate family members who have a commercial research grant from Novartis and who are consultants for Pfizer and SV Life Sciences. All other authors have no conflicts of interest to report.

Figures

Figure 1
Figure 1
Manhattan plot, illustrating p-values from 60,297 SNP associations generated from 1-sided ASSET meta-analysis. Statistical significance threshold is denoted by the red line (p = 5.09 × 10−6).
Figure 2
Figure 2
Observed versus expected p-values of DNA repair gene SNPs, by cancer site and overall meta-analysis. SNPs plotted were filtered using the SNAP online tool (see Methods and Materials) and were eliminated from the analysis if R2 > 0.70. Black dots = p-values from indicated dataset, green lines = 95% pointwise expected interval under the null hypothesis, red line = expected observations under the null hypothesis.
See this image and copyright information in PMC

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