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UNLABELLED: 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.

Original publication

DOI

10.1158/2159-8290.CD-15-1227

Type

Journal article

Journal

Cancer discov

Publication Date

09/2016

Volume

6

Pages

1052 - 1067

Keywords

Breast Neoplasms, Case-Control Studies, Chromosome Mapping, Datasets as Topic, Enhancer Elements, Genetic, Female, Gene Regulatory Networks, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Meta-Analysis as Topic, Organ Specificity, Ovarian Neoplasms, Polymorphism, Single Nucleotide, Prostatic Neoplasms, Quantitative Trait Loci, Signal Transduction