Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types

Abstract

Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis.

Significance: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.

Figure 1

Manhattan plot of results from the combined breast, ovarian, and prostate cancer meta-analysis. The black and gray dots represent the 2,231 variants nominally associated (P < 0.05) with every cancer type individually that had the same direction of effect across all three cancers. The red line corresponds to a threshold of P = 10⁻⁸. Eighteen independent loci were identified at this threshold. The green dots highlight index SNPs at 11 loci out of these 18 where model selection using ASSET confirmed contribution from all three cancer types to the association signal and that remained at P < 10⁻⁸ after adjusting for the controls shared between the breast and ovarian cancer studies. Gene names identify the three loci out of the 11 that were > 1 Mb away from previously identified index SNPs for any of the three cancers.

Figure 2

Forest plots of odds ratio estimates for the new cross-cancer index SNPs (> 1 Mb from known index SNPs) for susceptibility to (A) breast, ovarian, and prostate cancer and (B) breast and ovarian cancer, and breast and prostate cancer. Error bars indicate 95% confidence intervals and het_P is the P-value calculated from Cochran’s Q-test for heterogeneity.

Figure 3

Regional association plot of results from the three-cancer meta-analysis for the rs1469713/19p13 breast, ovarian, and prostate cancer susceptibility locus. The black dots represent all variants nominally associated (P < 0.05) with every cancer type individually that had the same direction of effect across all three cancers. The purple dashed line corresponds to a threshold of P = 10⁻⁸. Tracks immediately below the regional association plot show the locations of enhancers in breast (pink), ovarian (green), and prostate (blue) cell types. Interactions derived from ChIA-PET experiments, which have only been assayed in breast cells, are labeled as experimental interactions. Where the same gene is predicted to be a target of enhancers that intersect with the same P < 10⁻⁸ SNP in all three cell types (or two for the 2q13 region), it is shown in red. All other genes in the region are in gray. The corresponding P < 10⁻⁸ SNP locations are marked by grey vertical stripes. The lower tracks show arcs between enhancers and target genes for both computationally predicted and experimentally derived interactions. Arc colors reflect the cell type in which the enhancer-promoter pair was identified.

Figure 4

Regional association plot of results from the three-cancer meta-analysis for the rs17041869/2q13 breast, ovarian, and prostate cancer susceptibility locus. The black dots represent all variants nominally associated (P < 0.05) with every cancer type individually that had the same direction of effect across all three cancers. The purple dashed line corresponds to a threshold of P = 10⁻⁸. Tracks immediately below the regional association plot show the locations of enhancers in breast (pink), ovarian (green), and prostate (blue) cell types. Interactions derived from ChIA-PET experiments, which have only been assayed in breast cells, are labeled as experimental interactions. Where the same gene is predicted to be a target of enhancers that intersect with the same P < 10⁻⁸ SNP in all three cell types (or two for the 2q13 region), it is shown in red. All other genes in the region are in gray. The corresponding P < 10⁻⁸ SNP locations are marked by grey vertical stripes. The lower tracks show arcs between enhancers and target genes for both computationally predicted and experimentally derived interactions. Arc colors reflect the cell type in which the enhancer-promoter pair was identified.