Evidence map›Paper›PMID 40002276›Full record

ReviewCancers2025

Ancestry-Specific DNA Damage Repair Gene Mutations and Prostate Cancer.

Talaibek Borbiev, Kevin Babcock, Kayleigh Sinopole, Gregory T Chesnut, Gyorgy Petrovics

Abstract readReview
In one paragraph

Review in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Talaibek BorbievCenter for Prostate Disease Research, Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.
Kevin BabcockInternal Medicine, Alexander T. Augusta Military Medicine Center, Fort Belvoir, VA 22060, USA.
Kayleigh SinopoleSchool of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.
Gregory T ChesnutCenter for Prostate Disease Research, Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.
Gyorgy PetrovicsCenter for Prostate Disease Research, Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review is intended to reflect the currently available literature on both clinically significant germline mutations in DNA damage repair (DDR) genes as well as the importance of ancestral diversity in the pathogenesis of prostate cancer (PCa). The second most prevalent cancer worldwide in men is PCa, causing significant morbidity and mortality in its advanced stage. Emerging data highlight the substantial role of germline mutations of DDR genes in PCa pathogenesis, especially in progression to aggressive forms of the disease. Germline genetic testing is recognized as a necessary tool for efficient, individualized patient care. NCCR guidelines recommend inquiring about the family history of PCa and known germline variants and, if indicated, proceeding with germline multigene testing followed by post-test genetic counseling. Depending on the germline mutations in HR repair genes or in MMR genes, specific treatment options may provide clinical benefit. We will discuss specific germline mutations that are involved in PCa progression and prognosis in racially diverse populations.

Indexed as

DNA damage repair genesgermline mutationsprostate cancersomatic mutations

Identifiers

PMID40002276
PMCPMC11853348

What OpenQuestion holds

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Registered trials

None linked

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.