Evidence map›Paper›PMID 40875208›Full record

ArticleJAMA oncology2025

Established Cancer Predisposition Genes in Single and Multiple Cancer Diagnoses.

Jeffrey W Shevach, Jianfeng Xu, Nathan Snyder, Jun Wei, Zhuqing Shi, Huy Tran, S Lilly Zheng, Jennifer L Beebe-Dimmer, Kathleen A Cooney

Abstract read
In one paragraph

Article in JAMA oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Identification ofOncology research · 2026
    Article
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

9 authors.

Jeffrey W ShevachDepartment of Medicine and the Duke Cancer Institute, Duke University School of Medicine, Durham, North Carolina.
Jianfeng XuProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois.
Nathan SnyderDepartment of Medicine and the Duke Cancer Institute, Duke University School of Medicine, Durham, North Carolina.
Jun WeiProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois.
Zhuqing ShiProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois.
Huy TranProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois.
S Lilly ZhengProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois.
Jennifer L Beebe-DimmerDepartment of Oncology, Wayne State University School of Medicine, Detroit, Michigan.
Kathleen A CooneyDepartment of Medicine and the Duke Cancer Institute, Duke University School of Medicine, Durham, North Carolina.

Funding

Project 2P01CA272239 · NCI · WAYNE STATE UNIVERSITY · PI Ann G. Schwartz · 2024 to 2026
$5.0M
NCI NIH HHS P01 CA272239
6 · The paper itself

Abstract

Importance: Much of the understanding of cancer risk associated with rare pathogenic variants (RPVs) is derived from family-based studies or clinically ascertained samples, which may be limited by ascertainment and selection bias. Objective: To quantify associations between RPVs in previously implicated cancer predisposition genes and single and multiple cancer diagnoses in a large population-based study. Design, Setting, and Participants: In this genetic association study, whole-exome sequencing data were used from the UK Biobank, a UK population-based cohort that enrolled participants aged 40 to 69 years between 2006 and 2010. Participants who were involved in the whole-exome sequencing release of 200 000 genomes in 2020 were included in this study. This analysis included White participants only, as findings in other racial and ethnic groups had small sample sizes. Participants were diagnosed before or after biobank enrollment until March 2024. Exposures: The sequencing data of a set of 96 previously implicated cancer predisposition genes were analyzed and compared using 2 methods. To determine the statistical significance of an association, a robust optimal sequence kernel association test was used, while odds ratios (ORs) and 95% CIs were obtained through Firth logistic regression. Main Outcomes and Measures: The primary study outcome was the diagnosis of 1 of 11 cancers (bladder, breast, central nervous system, colorectal, lung, melanoma, ovary, pancreatic, prostate, renal, thyroid) defined by relevant diagnosis codes in inpatient hospital diagnosis, cancer registry, and/or death registry data. Results: Data from 183 627 participants (101 414 [55.2%] female) were analyzed, including 25 824 participants with at least 1 cancer diagnosis, of whom 23 704 (91.8%) had a single cancer diagnosis and 2130 (8.2%) had 2 or more cancer diagnoses. A total of 157 793 controls had no cancer diagnosis. The median (IQR) age was 62 (56-65) years in participants with at least 1 cancer diagnosis, compared to 57 (50-63) years in those without a cancer diagnosis. Genetic variation in 16 genes was significantly associated with at least 1 cancer of interest (ATM, BARD1, BRCA1, BRCA2, BRIP1, CDKN2A, CHEK2, HOXB13, MITF, MLH1, MSH2, MSH6, NF1, PALB2, RAD51C, and RAD51D). The presence of an RPV in 1 of these 16 genes was associated with increased odds of at least 1 cancer (OR, 1.87; 95% CI, 1.76-1.98) and multiple primary cancers (OR, 2.56; 95% CI, 2.18-2.99). Carrier frequency was 6.28% and 8.36%, respectively. Conclusions and Relevance: This genetic association study demonstrates several established associations between cancer predisposition genes and cancer diagnoses in an unselected population-based study. These results also demonstrate that RPVs in cancer predisposition genes are associated with multiple primary cancer diagnoses, suggesting that multigene panel testing may be warranted in these individuals.

Indexed as

Genetic Predisposition to DiseaseNeoplasmsAdultAgedExome SequencingFemaleHumansMaleMiddle AgedUnited Kingdom

Identifiers

PMID40875208
PMCPMC12395360

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.