BACKGROUND: Prostate cancer is the second leading cause of cancer-related deaths in men, accounting for more than 30,000 deaths annually. The purpose of this study was to test whether variation in selected candidate genes in biological pathways of interest for prostate cancer progression could help distinguish patients at higher risk for fatal prostate cancer. METHODS: In this hypothesis-driven study, we genotyped 937 single nucleotide polymorphisms (SNPs) in 156 candidate genes in a population-based cohort of 1,309 prostate cancer patients. We identified 22 top-ranking SNPs (P ≤ 0.01, FDR ≤ 0.70) associated with prostate cancer-specific mortality (PCSM). A subsequent validation study was completed in an independent population-based cohort of 2,875 prostate cancer patients. RESULTS: Five SNPs were validated (P ≤ 0.05) as being significantly associated with PCSM, one each in the LEPR, CRY1, RNASEL, IL4, and ARVCF genes. Compared with patients with 0 to 2 of the at-risk genotypes those with 4 to 5 at-risk genotypes had a 50% (95% CI, 1.2-1.9) higher risk of PCSM and risk increased with the number of at-risk genotypes carried (P(trend) = 0.001), adjusting for clinicopathologic factors known to influence prognosis. CONCLUSION: Five genetic markers were validated to be associated with lethal prostate cancer. IMPACT: This is the first population-based study to show that germline genetic variants provide prognostic information for prostate cancer-specific survival. The clinical utility of this five-SNP panel to stratify patients at higher risk for adverse outcomes should be evaluated.
BACKGROUND:Prostate cancer is the second leading cause of cancer-related deaths in men, accounting for more than 30,000 deaths annually. The purpose of this study was to test whether variation in selected candidate genes in biological pathways of interest for prostate cancer progression could help distinguish patients at higher risk for fatal prostate cancer. METHODS: In this hypothesis-driven study, we genotyped 937 single nucleotide polymorphisms (SNPs) in 156 candidate genes in a population-based cohort of 1,309 prostate cancerpatients. We identified 22 top-ranking SNPs (P ≤ 0.01, FDR ≤ 0.70) associated with prostate cancer-specific mortality (PCSM). A subsequent validation study was completed in an independent population-based cohort of 2,875 prostate cancerpatients. RESULTS: Five SNPs were validated (P ≤ 0.05) as being significantly associated with PCSM, one each in the LEPR, CRY1, RNASEL, IL4, and ARVCF genes. Compared with patients with 0 to 2 of the at-risk genotypes those with 4 to 5 at-risk genotypes had a 50% (95% CI, 1.2-1.9) higher risk of PCSM and risk increased with the number of at-risk genotypes carried (P(trend) = 0.001), adjusting for clinicopathologic factors known to influence prognosis. CONCLUSION: Five genetic markers were validated to be associated with lethal prostate cancer. IMPACT: This is the first population-based study to show that germline genetic variants provide prognostic information for prostate cancer-specific survival. The clinical utility of this five-SNP panel to stratify patients at higher risk for adverse outcomes should be evaluated.
Authors: M S Topp; M Koenigsmann; A Mire-Sluis; D Oberberg; F Eitelbach; Z von Marschall; M Notter; B Reufi; H Stein; E Thiel Journal: Blood Date: 1993-11-01 Impact factor: 22.113
Authors: Brian T Helfand; Kimberly A Roehl; Phillip R Cooper; Barry B McGuire; Liesel M Fitzgerald; Geraldine Cancel-Tassin; Jean-Nicolas Cornu; Scott Bauer; Erin L Van Blarigan; Xin Chen; David Duggan; Elaine A Ostrander; Mary Gwo-Shu; Zuo-Feng Zhang; Shen-Chih Chang; Somee Jeong; Elizabeth T H Fontham; Gary Smith; James L Mohler; Sonja I Berndt; Shannon K McDonnell; Rick Kittles; Benjamin A Rybicki; Matthew Freedman; Philip W Kantoff; Mark Pomerantz; Joan P Breyer; Jeffrey R Smith; Timothy R Rebbeck; Dan Mercola; William B Isaacs; Fredrick Wiklund; Olivier Cussenot; Stephen N Thibodeau; Daniel J Schaid; Lisa Cannon-Albright; Kathleen A Cooney; Stephen J Chanock; Janet L Stanford; June M Chan; John Witte; Jianfeng Xu; Jeannette T Bensen; Jack A Taylor; William J Catalona Journal: Hum Genet Date: 2015-02-26 Impact factor: 4.132
Authors: Danielle M Karyadi; Shanshan Zhao; Qianchuan He; Laura McIntosh; Jonathan L Wright; Elaine A Ostrander; Ziding Feng; Janet L Stanford Journal: Int J Cancer Date: 2014-10-13 Impact factor: 7.396
Authors: Sarah C Markt; Unnur A Valdimarsdottir; Irene M Shui; Lara G Sigurdardottir; Jennifer R Rider; Rulla M Tamimi; Julie L Batista; Sebastien Haneuse; Erin Flynn-Evans; Steven W Lockley; Charles A Czeisler; Meir J Stampfer; Lenore Launer; Tamara Harris; Albert Vernon Smith; Vilmundur Gudnason; Sara Lindstrom; Peter Kraft; Lorelei A Mucci Journal: Cancer Causes Control Date: 2014-11-12 Impact factor: 2.506