In silico RNA isoform screening to identify potential cancer driver exons with therapeutic applications

Area of Science:

• Molecular Biology
• Genomics
• Cancer Research

Background:

• Alternative splicing plays a critical role in cancer development and presents a potential therapeutic target.
• Identifying specific driver exons that influence cancer progression genome-wide is a significant challenge in the field.

Purpose of the Study:

• To develop a computational method for identifying cancer driver exons by integrating gene expression and splicing data with cancer dependency screens.
• To enable in silico RNA screening for prioritizing therapeutic targets in splicing-based cancer therapies.

Main Methods:

• Statistical association of gene-level cancer dependencies from knockdown viability screens with splicing profiles and gene expression data.
• Development of predictive models to simulate the impact of splicing perturbations on cell proliferation using transcriptomic data.
• Experimental validation of identified driver exons in cancer cell lines.

Main Results:

• Identification of 1,073 exons that significantly impact cell proliferation, including many from genes not previously associated with cancer.
• Experimental validation confirmed the influence of these exons on proliferation, particularly in rapidly dividing cancer cell lines.
• Integration with pharmacological screens revealed potential driver exons affecting drug sensitivity and enabled prediction of treatment outcomes from tumor transcriptomes.

Conclusions:

• The study presents a novel approach for identifying cancer driver exons and their therapeutic potential, highlighting alternative splicing as a key area for cancer treatment.
• The developed models offer a powerful tool for in silico RNA screening and hold promise for applications in precision oncology.
• This work underscores the importance of alternative splicing as a target for developing novel cancer therapies.