iSoMAs: Finding isoform expression and somatic mutation associations in human cancers

Area of Science:

• Genomics
• Cancer Biology
• Bioinformatics

Background:

• Aberrant alternative splicing is a hallmark of cancer, affecting proliferation, angiogenesis, and invasion.
• Somatic point mutations often disrupt splicing, promoting cancer cell survival by altering functional pathways.

Purpose of the Study:

• To develop an efficient computational pipeline, iSoMAs (isoform expression and somatic Mutation Association), to analyze the impact of somatic mutations on transcriptome-wide gene expression at the isoform level.
• To identify genes where somatic mutations are significantly associated with altered isoform expression across multiple cancer types.

Main Methods:

• Development of iSoMAs, a computational pipeline utilizing principal component analysis for dimension reduction.
• Application of iSoMAs to 9,738 tumor samples from 33 cancer types in The Cancer Genome Atlas.
• Wet-lab validation of TP53 mutations' association with differential isoform expression in cell cycle genes.

Main Results:

• Identified 908 somatically mutated genes significantly associated with altered isoform expression in at least three cancer types.
• Discovered that mutations influence isoform expression through cis- and trans-acting mechanisms, involving oncogenes, tumor suppressors, RNA-binding proteins, and splicing factors.
• Validated direct associations between TP53 mutations and differential isoform expression in cell cycle genes, with further literature validation for other identified genes.

Conclusions:

• iSoMAs provides an efficient and computationally scalable method for investigating mutation-driven isoform expression changes in cancer.
• The study reveals critical associations between regulatory factors, including splicing factors and RNA-binding proteins, and the transcriptional landscape in cancer.
• Findings highlight the importance of alternative splicing dysregulation in cancer and identify novel candidate genes for therapeutic targeting.