Identifying cell-specific cancer susceptibility genes using transcriptome-wide association studies

Music City Center 

Background: Transcriptome-wide association studies (TWAS) integrate gene expression with GWAS data to identify disease susceptibility genes. Conventional TWAS methods rely on tissue-specific models, but accounting for cell type variation may enhance discovery.
Methods: We built cell type-specific gene expression models using scRNA-seq data from 982 individuals in the OneK1K cohort, comprising 1.27 million PBMCs across 14 cell types with matched genotypes. To enhance prediction accuracy, we developed a novel approach leveraging correlations across cell types. These models were applied to TWAS on GWAS data for six cancers (>280,000 cases total): breast, prostate, lung, melanoma, ovarian, and endometrial.
Results: TWAS identified 339 novel genes for breast cancer, 92 for prostate, 18 for lung, 51 for melanoma, and 9 for ovarian, most of which were cell type-specific. Notably, 139 significant genes were shared across cancer types, enriched in cell types like CD4-NC and CD8-ET. Gene-set analyses validated novel breast and prostate genes in UK Biobank replication datasets.
Conclusion: Cell type-specific models improve cancer gene discovery, revealing distinct genetic landscapes.

Transcriptome-wide association studies

Single-cell RNA sequencing

Cell type

Cancer

Genome-wide association studies 

Section on Statistics in Genomics and Genetics