ArticleCancer medicine2025
A Transcriptome-Wide Association Study Identifies Candidate Susceptibility Loci and Genes for Lung Cancer Risk.
Article in Cancer medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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Who cites it
1 citing paper in PubMed.
- A Transcriptome-Wide Association Study Identifies Candidate Susceptibility Loci and Genes for Lung Cancer Risk.Cancer medicine · 2025Article
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Authors and funding
14 authors.
Funding
Abstract
backgroundGenome-wide association studies (GWAS) have identified over 80 susceptibility loci for lung cancer risk. However, the genes underlying these associations remain largely unknown.
methodsWe conducted a large transcriptome-wide association study (TWAS) to identify lung cancer susceptibility genes. We leveraged gene expression data from lungs and 48 other tissue types and whole-genome sequencing data from up to 706 samples of European ancestry in the GTEx (version 8) to build lung-tissue and joint-tissue gene expression prediction models. These models were applied to GWAS data, including 29,266 lung cancer cases and 56,450 controls, to assess the associations of genetically predicted gene expression levels with lung cancer risk.
resultsA total of 8624 genes were successfully built for single-tissue models, and 11,341 genes for joint-tissue models (12,133 unique genes altogether). Among 40 genes whose expression levels were associated with the risk of lung cancer at a Bonferroni-corrected significance level, ZKSCAN4 was located more than 2 Mb away from the GWAS-identified variants linked to lung cancer. Among the remaining 39 genes within 2 Mb of GWAS-identified variants, seven genes were independent of these. Among 53 genes associated with the risk of lung cancer subtypes, 13 genes were beyond 2 Mb of GWAS-identified variants, and four genes were independent of the GWAS-identified variants within 2 Mb regions.
conclusionOur TWAS identified over 50 candidate susceptibility genes for lung cancer, providing new insights into lung cancer genetics.
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