Evidence map›Paper›PMID 39585897›Full record

ArticlePLoS genetics2024

GWAS and 3D chromatin mapping identifies multicancer risk genes associated with hormone-dependent cancers.

Isela Sarahi Rivera, Juliet D French, Mainá Bitar, Haran Sivakumaran, Sneha Nair, Susanne Kaufmann, Kristine M Hillman, Mahdi Moradi Marjaneh, Jonathan Beesley, Stacey L Edwards

Abstract read
In one paragraph

Article in PLoS genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Isela Sarahi RiveraCancer Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Juliet D FrenchCancer Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.ORCID https://orcid.org/0000-0002-9770-0198
Mainá BitarCancer Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Haran SivakumaranCancer Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.ORCID https://orcid.org/0000-0002-4691-4989
Sneha NairCancer Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Susanne KaufmannCancer Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Kristine M HillmanCancer Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.ORCID https://orcid.org/0000-0003-3039-4437
Mahdi Moradi MarjanehCancer Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.ORCID https://orcid.org/0000-0002-9412-9029
Jonathan BeesleyCancer Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Stacey L EdwardsCancer Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.ORCID https://orcid.org/0000-0001-7428-4139

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hormone-dependent cancers (HDCs) share several risk factors, suggesting a common aetiology. Using data from genome-wide association studies, we showed spatial clustering of risk variants across four HDCs (breast, endometrial, ovarian and prostate cancers), contrasting with genetically uncorrelated traits. We identified 44 multi-HDC risk regions across the genome, defined as overlapping risk regions for at least two HDCs: two regions contained risk variants for all four HDCs, 13 for three HDCs and 28 for two HDCs. Integrating GWAS data, epigenomic profiling and promoter capture HiC maps from diverse cell line models, we annotated 53 candidate risk genes at 22 multi-HDC risk regions. These targets were enriched for established genes from the COSMIC Cancer Gene Census, but many had no previously reported pleiotropic roles. Additionally, we pinpointed lncRNAs as potential HDC targets and identified risk alleles in several regions that altered transcription factors motifs, suggesting regulatory mechanisms. Known drug targets were over-represented among the candidate multi-HDC risk genes, implying that some may serve as targets for therapeutic development or facilitate the repurposing of existing treatments for HDC. Our approach provides a framework for identifying common target genes driving complex traits and enhances understanding of HDC susceptibility.

Indexed as

Breast NeoplasmsChromatinGenetic Predisposition to DiseaseGenome-Wide Association StudyProstatic NeoplasmsCell Line, TumorChromosome MappingEndometrial NeoplasmsFemaleHumansMaleNeoplasmsOvarian NeoplasmsPolymorphism, Single NucleotideRisk FactorsRNA, Long NoncodingChromatinRNA, Long Noncoding

Identifiers

PMID39585897
PMCPMC11627375

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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.