Faculty, Staff and Student Publications
Language
English
Publication Date
10-1-2025
Journal
British Journal of Cancer
DOI
10.1038/s41416-025-03141-y
PMID
40775447
PMCID
PMC12449480
PubMedCentral® Posted Date
8-7-2025
PubMedCentral® Full Text Version
Post-print
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) significantly improves discovery of genetic associations compared to gene-level approaches, identifying 164% more significant associations (6163 vs. 2336) with isoTWAS-prioritized genes enriched 4-fold for evolutionarily-constrained genes. isoTWAS tags transcriptomic associations at 52% more independent GWAS loci across the six cancers. Isoform expression mediates an estimated 63% greater proportion of cancer risk SNP heritability compared to gene expression. We highlight several isoTWAS associations that demonstrate GWAS colocalization at the isoform level but not at the gene level, including CLPTM1L (lung cancer), LAMC1 (colorectal), and BABAM1 (breast).
Conclusion: These results underscore the importance of modeling isoforms to maximize discovery of genetic risk mechanisms for cancers.
Keywords
Humans, Genome-Wide Association Study, Genetic Predisposition to Disease, Female, Male, Polymorphism, Single Nucleotide, Neoplasms, Protein Isoforms, Lung Neoplasms, Transcriptome, Breast Neoplasms, Prostatic Neoplasms, Gene Expression Profiling, Alternative Splicing, Ovarian Neoplasms, Colorectal Neoplasms, Endometrial Neoplasms, Cancer genomics, Cancer genetics, Gene regulation
Published Open-Access
yes
Recommended Citation
Chang, Yung-Han; Bresnahan, Sean T; Taylor Head, S; et al., "Isoform-Level Analyses of 6 Cancers Uncover Extensive Genetic Risk Mechanisms Undetected at the Gene-Level" (2025). Faculty, Staff and Student Publications. 5356.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/5356
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Genetic Phenomena Commons, Medical Genetics Commons, Oncology Commons