ArticleJournal of the National Cancer Institute2024
Multi-tissue transcriptome-wide association studies identified 235 genes for intrinsic subtypes of breast cancer.
Article in Journal of the National Cancer Institute, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 6 citations in OpenAlex.
- Multi-ancestry transcriptome-wide association studies uncover insights into breast cancer genetics and biology.Nature communications · 2026Article
- Identification and functional validation of EPS15L1 as a key driver of triple-negative breast cancer.NPJ breast cancer · 2026Article
- Identification of susceptibility loci using a novel murine model for triple-negative breast cancer.G3 (Bethesda, Md.) · 2026Article
- Cell-type aware transcriptome-wide association study of mammographic density phenotypes.medRxiv : the preprint server for health sciences · 2025Article
- TransferTWAS: A transfer learning framework for cross-tissue transcriptome-wide association study.American journal of human genetics · 2025Article
- Understanding genetic architecture of breast cancer: how can proteome-wide association studies contribute?British journal of cancer · 2024Article
- A proteome-wide association study identifies putative causal proteins for breast cancer risk.British journal of cancer · 2024Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundAlthough genome-wide association studies (GWAS) of breast cancer (BC) identified common variants which differ between intrinsic subtypes, genes through which these variants act to impact BC risk have not been fully established. Transcriptome-wide association studies (TWAS) have identified genes associated with overall BC risk, but subtype-specific differences are largely unknown.
methodsWe performed two multi-tissue TWAS for each BC intrinsic subtype, including an expression-based approach that collated TWAS signals from expression quantitative trait loci (eQTLs) across multiple tissues and a novel splicing-based approach that collated signals from splicing QTLs (sQTLs) across intron clusters and subsequently across tissues. We used summary statistics for five intrinsic subtypes including Luminal A-like, Luminal B-like, Luminal B/HER2-negative-like, HER2-enriched-like, and triple-negative BC, generated from 106 278 BC cases and 91 477 controls in the Breast Cancer Association Consortium.
resultsOverall, we identified 235 genes in 88 loci that were associated with at least one of the five intrinsic subtypes. Most genes were subtype-specific, and many have not been reported in previous TWAS. We discovered common variants that modulate expression of CHEK2 confer increased risk to Luminal A-like BC, in contrast to the viewpoint that CHEK2 primarily harbors rare, penetrant mutations. Additionally, our splicing-based TWAS provided population-level support for MDM4 splice variants that increased the risk of triple-negative BC.
conclusionOur comprehensive, multi-tissue TWAS corroborated previous GWAS loci for overall BC risk and intrinsic subtypes, while underscoring how common variation that impacts expression and splicing of genes in multiple tissue types can be used to further elucidate the etiology of BC.
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