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

ABSTRACT:

Background

Integrating genome-wide association study (GWAS) and transcriptomic datasets can 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.

Methods

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).

Results

Directly modeling isoforms using transcriptome-wide association studies (isoTWAS)

SUBMITTER: Chang YH 

PROVIDER: S-EPMC12449480 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature