Association of Prostate Cancer Risk Variants with Gene Expression in Normal Prostate and Tumor Tissue. K. L. Penney1,2, J. A. Sinnott1,2,4, S. Tyekucheva2,6, T. Gerke2, I. Shui2, P. Kraft2,4, H. D. Sesso2,5, M. L. Freedman7,9, M. Loda7,8,9, L. A. Mucci1,2, M. J. Stampfer1,2,3 1) Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA; 2) Department of Epidemiology, Harvard School of Public Health, Boston, MA; 3) Department of Nutrition, Harvard School of Public Health, Boston, MA; 4) Department of Biostatistics, Harvard School of Public Health, Boston, MA; 5) Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA; 6) Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA; 7) Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA; 8) Department of Pathology, Brigham and Women's Hospital, Boston, MA; 9) The Broad Institute, Cambridge, MA.
Introduction: Numerous germline genetic variants are associated with prostate cancer risk, but their biological role is only beginning to be understood. One possibility is that these variants influence gene expression in prostate tissue. We therefore examined the association of prostate cancer risk variants with the expression of genes nearby and genome-wide. Methods: We generated mRNA expression data for 20,254 genes with the Affymetrix GeneChip Human Gene 1.0 ST microarray from both normal prostate and prostate tumor tissue from 264 participants of the Physicians Health Study and Health Professionals Follow-up Study Tumor Cohort. With linear models, we tested for the association of 39 risk variants with nearby genes (1 megabase window) and all genes. We also tested the association of each variant with canonical pathways using a global test. Results: In addition to confirming previously reported associations, we detected several new significant (p<0.05) associations of variants with the expression of nearby genes including C2orf43, ITGA6, MLPH, CHMP2B, BMPR1B, and MTL5. Genome-wide, four genes were statistically significantly associated after accounting for multiple comparisons (p<2.5x10-6), 367 genes in tumor and 16 genes in normal (including SRD5A1 and PSCA) had a false discovery rate <10%, and we observed significant associations with several pathways in tumor tissue. Conclusions: Several genes were associated with the risk variants, including promising prostate cancer candidates and lipid metabolism pathways that should be further explored in biological and epidemiological studies. Determining the biological role of these variants can lead to a mechanistic understanding of prostate cancer etiology and possibly identify new targets for chemoprevention.
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