Isoform-level analyses of 6 cancers uncover extensive genetic risk mechanisms undetected at the gene-level.

ABSTRACT: Integrating genome-wide association study (GWAS) and transcriptomic datasets can help identify mediators for genetic risk of cancer. Traditional methods often are insufficient as they rely on total gene expression measures and overlook alternative splicing, which generates different transcript-isoforms with potentially distinct effects. Here, we integrate multi-tissue isoform expression data from the Genotype Tissue-Expression Project with GWAS summary statistics (all N > 20,000 cases) to identify isoform- and gene-level associations with six cancers (breast, endometrial, colorectal, lung, ovarian, prostate) and six related cancer subtype classifications (N = 12 total). Directly modeling isoforms using transcriptome-wide association studies (isoTWAS) significantly improves discovery of gen

SUBMITTER: Chang YH 

PROVIDER: S-EPMC11581093 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature