Literature DB >> 33866309

Comprehensive Analysis of Multiple Cohort Datasets Deciphers the Utility of Germline Single-Nucleotide Polymorphisms in Prostate Cancer Diagnosis.

Wensheng Zhang1, Yan Dong2, Oliver Sartor3, Kun Zhang4,5.   

Abstract

Prostate cancer susceptibility is a polygenic trait. We aimed to examine the controversial diagnostic utility of single-nucleotide polymorphisms (SNP) for prostate cancer. We analyzed two datasets collected from Europeans and one from Africans. These datasets were generated by the genome-wide association studies, that is, CGEMS, BPC3, and MEC-Africans, respectively. About 540,000 SNPs, including 61 risk markers that constitute a panel termed MK-61, were commonly genotyped. For each dataset, we augmented the MK-61 panel to generate an MK-61+ one by adding several thousands of SNPs that were moderately associated with prostate cancer occurrence in external dataset(s). We assessed the diagnostic utility of both panels by measuring their predictive strength for prostate cancer occurrence with AUC statistics. We calculated the theoretical AUCs using quantitative genetics model-based formulae and obtained the empirical estimates via 10-fold cross-validation using statistical and machine learning techniques. For the MK-61 panel, the 95% confidence intervals of the theoretical AUCs (AUC-CI.95) were 0.578-0.655, 0.596-0.656, and 0.539-0.596 in the CGEMS, BPC3, and MEC-Africans cohorts, respectively. For the MK-61+ panels, the corresponding AUC-CI.95 were 0.617-0.663, 0.527-0.736, and 0.547-0.565. The empirical AUCs largely fell within the theoretical interval. A promising result (AUC = 0.703, FNR = 0.354, FPR = 0.353) was obtained in the BPC3 cohort when the MK-61+ panel was used. In the CGEMS cohort, the MK-61+ panel complemented PSA in predicting the disease status of PSA ≥ 2.0 ng/mL samples. This study demonstrates that augmented risk SNP panels can enhance prostate cancer prediction for males of European ancestry, especially those with [Formula: see text]ng/mL. PREVENTION RELEVANCE: This study demonstrates that augmented risk SNP panels can enhance prostate cancer prediction for males of European ancestry, especially those with PSA ≥ 2 ng/mL. ©2021 American Association for Cancer Research.

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Year:  2021        PMID: 33866309      PMCID: PMC8295202          DOI: 10.1158/1940-6207.CAPR-20-0534

Source DB:  PubMed          Journal:  Cancer Prev Res (Phila)        ISSN: 1940-6215


  40 in total

1.  PLINK: a tool set for whole-genome association and population-based linkage analyses.

Authors:  Shaun Purcell; Benjamin Neale; Kathe Todd-Brown; Lori Thomas; Manuel A R Ferreira; David Bender; Julian Maller; Pamela Sklar; Paul I W de Bakker; Mark J Daly; Pak C Sham
Journal:  Am J Hum Genet       Date:  2007-07-25       Impact factor: 11.025

Review 2.  Systematic enrichment analysis of potentially functional regions for 103 prostate cancer risk-associated loci.

Authors:  Haitao Chen; Hongjie Yu; Jianqing Wang; Zheng Zhang; Zhengrong Gao; Zhuo Chen; Yulan Lu; Wennuan Liu; Deke Jiang; S Lilly Zheng; Gong-Hong Wei; William B Issacs; Junjie Feng; Jianfeng Xu
Journal:  Prostate       Date:  2015-05-25       Impact factor: 4.104

3.  Genome-wide association study of prostate cancer identifies a second risk locus at 8q24.

Authors:  Meredith Yeager; Nick Orr; Richard B Hayes; Kevin B Jacobs; Peter Kraft; Sholom Wacholder; Mark J Minichiello; Paul Fearnhead; Kai Yu; Nilanjan Chatterjee; Zhaoming Wang; Robert Welch; Brian J Staats; Eugenia E Calle; Heather Spencer Feigelson; Michael J Thun; Carmen Rodriguez; Demetrius Albanes; Jarmo Virtamo; Stephanie Weinstein; Fredrick R Schumacher; Edward Giovannucci; Walter C Willett; Geraldine Cancel-Tassin; Olivier Cussenot; Antoine Valeri; Gerald L Andriole; Edward P Gelmann; Margaret Tucker; Daniela S Gerhard; Joseph F Fraumeni; Robert Hoover; David J Hunter; Stephen J Chanock; Gilles Thomas
Journal:  Nat Genet       Date:  2007-04-01       Impact factor: 38.330

4.  Personalized prostate cancer screening: improving PSA tests with genomic information.

Authors:  John S Witte
Journal:  Sci Transl Med       Date:  2010-12-15       Impact factor: 17.956

Review 5.  A Review of Prostate Cancer Genome-Wide Association Studies (GWAS).

Authors:  Sarah Benafif; Zsofia Kote-Jarai; Rosalind A Eeles
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2018-01-18       Impact factor: 4.254

Review 6.  Do African-American men need separate prostate cancer screening guidelines?

Authors:  Divya Shenoy; Satyaseelan Packianathan; Allen M Chen; Srinivasan Vijayakumar
Journal:  BMC Urol       Date:  2016-05-10       Impact factor: 2.264

Review 7.  Emerging biomarkers in the diagnosis of prostate cancer.

Authors:  Xavier Filella; Esther Fernández-Galan; Rosa Fernández Bonifacio; Laura Foj
Journal:  Pharmgenomics Pers Med       Date:  2018-05-16

8.  Identification of a new prostate cancer susceptibility locus on chromosome 8q24.

Authors:  Meredith Yeager; Nilanjan Chatterjee; Julia Ciampa; Kevin B Jacobs; Jesus Gonzalez-Bosquet; Richard B Hayes; Peter Kraft; Sholom Wacholder; Nick Orr; Sonja Berndt; Kai Yu; Amy Hutchinson; Zhaoming Wang; Laufey Amundadottir; Heather Spencer Feigelson; Michael J Thun; W Ryan Diver; Demetrius Albanes; Jarmo Virtamo; Stephanie Weinstein; Fredrick R Schumacher; Geraldine Cancel-Tassin; Olivier Cussenot; Antoine Valeri; Gerald L Andriole; E David Crawford; Christopher A Haiman; Brian Henderson; Laurence Kolonel; Loic Le Marchand; Afshan Siddiq; Elio Riboli; Timothy J Key; Rudolf Kaaks; William Isaacs; Sarah Isaacs; Kathleen E Wiley; Henrik Gronberg; Fredrik Wiklund; Pär Stattin; Jianfeng Xu; S Lilly Zheng; Jielin Sun; Lars J Vatten; Kristian Hveem; Merethe Kumle; Margaret Tucker; Daniela S Gerhard; Robert N Hoover; Joseph F Fraumeni; David J Hunter; Gilles Thomas; Stephen J Chanock
Journal:  Nat Genet       Date:  2009-09-20       Impact factor: 38.330

9.  Prostate-specific antigen testing accuracy in community practice.

Authors:  Richard M Hoffman; Frank D Gilliland; Meg Adams-Cameron; William C Hunt; Charles R Key
Journal:  BMC Fam Pract       Date:  2002-10-24       Impact factor: 2.497

10.  Power and predictive accuracy of polygenic risk scores.

Authors:  Frank Dudbridge
Journal:  PLoS Genet       Date:  2013-03-21       Impact factor: 5.917

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  1 in total

1.  Deciphering the Polygenic Basis of Racial Disparities in Prostate Cancer By an Integrative Analysis of Genomic and Transcriptomic Data.

Authors:  Wensheng Zhang; Thea Nicholson; Kun Zhang
Journal:  Cancer Prev Res (Phila)       Date:  2022-03-01
  1 in total

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