Evidence map›Paper›PMID 39154125›Full record

ArticleProstate cancer and prostatic diseases2025

Using gene and gene-set association tests to identify lethal prostate cancer genes.

Bing-Jian Feng, Julie L Boyle, Jun Wei, Courtney Carroll, Nathan A Snyder, Zhuqing Shi, S Lilly Zheng, Jianfeng Xu, William B Isaacs, Kathleen A Cooney

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In one paragraph

Article in Prostate cancer and prostatic diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Bing-Jian FengDepartment of Dermatology, University of Utah, Salt Lake City, UT, USA.ORCID http://orcid.org/0000-0002-6669-6640
Julie L BoyleDepartment of Family and Preventative Medicine, University of Utah, Salt Lake City, UT, USA.
Jun WeiProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois, USA.ORCID http://orcid.org/0000-0002-8234-4741
Courtney CarrollDepartment of Family and Preventative Medicine, University of Utah, Salt Lake City, UT, USA.ORCID http://orcid.org/0000-0003-4906-549X
Nathan A SnyderDepartment of Medicine and the Duke Cancer Institute, Duke University School of Medicine, Durham, NC, USA.ORCID http://orcid.org/0000-0001-9204-8420
Zhuqing ShiProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois, USA.
S Lilly ZhengProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois, USA.
Jianfeng XuProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois, USA.ORCID http://orcid.org/0000-0002-1343-8752
William B IsaacsDepartment of Urology and the James Buchanan Brady Urologic Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Kathleen A CooneyDepartment of Medicine and the Duke Cancer Institute, Duke University School of Medicine, Durham, NC, USA. kathleen.cooney@duke.edu.ORCID http://orcid.org/0000-0003-3831-6943

Funding

From genomics to natural language processing: A protected environment for research computing in the health scienceS10OD021644 · OD · UNIVERSITY OF UTAH · PI CHEATHAM, THOMAS E. · 2017 to 2017
$494k
U.S. Department of Defense (United States Department of Defense) PC150797U.S. Department of Health and Human Services (U.S. Department of Health & Human Services) 1S10OD021644-01A1
6 · The paper itself

Abstract

backgroundRecent advances in the detection and treatment of prostate cancer (PCa) have reduced morbidity and mortality from this common cancer. Despite these improvements, PCa remains the second leading cause of cancer death in men in the United States. Further understanding of the genetic underpinnings of lethal PCa is required to drive risk detection and prevention and ultimately reduce mortality. We therefore set out to identify germline variants associated with cases of lethal prostate cancer (LPCa).

methodsUsing a two-stage study design, we compared whole-exome sequencing data of 550 LPCa patients to 488 healthy male controls. Men were classified as having LPCa based on medical record review. Candidate genes were identified using gene- and gene-set-based rare truncating variant association tests. Case-control burden testing through Firth's penalized logistic regression and case-gnomAD allelic burden testing through a one-sided mid-p Fisher's exact test were conducted. Each gene's p-values from these tests were combined into an omnibus p-value for candidate gene selection. In the subsequent validation stage, genes were assessed using the UK Biobank and Firth's penalized logistic regression for each ancestry, combined through meta-analysis.

resultsGene-based rare variant association tests identified 12 genes nominally associated with LPCa. Rare-variant association tests identified a gene set with a significantly higher burden of truncating germline mutations in LPCa patients than controls. Combining gene- and gene-set test results, four nominally significant genes (PPP1R3A, TG, PPFIBP2, and BTN3A3) were selected as candidates. Subsequent validation using the UK Biobank found that PPP1R3A was significantly associated with LPCa risk (odds ratio 2.34, CI 1.20-4.59). Specifically, pGln662ArgfsTer7 was identified as the predominant variant in PPP1R3A among LPCa patients in our dataset.

conclusionsBoth individual gene and gene-set analyses identified candidates associated with LPCa. The novel association of PPP1R3A and LPCa risk merits further investigation.

Indexed as

Biomarkers, TumorGenetic Predisposition to DiseaseProstatic NeoplasmsAgedCase-Control StudiesExome SequencingGerm-Line MutationHumansMaleMiddle AgedBiomarkers, Tumor

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.