RNA-Based Strategies for Cancer Therapy: In Silico Design and Evaluation of ASOs for Targeted Exon Skipping

Area of Science:

• Oncology
• Molecular Biology
• Bioinformatics

Background:

• Precision medicine advances oncology with targeted therapies for specific genetic mutations.
• Many critical cancer driver genes are considered 'undruggable' with conventional drugs.
• RNA-based therapeutics, such as antisense oligonucleotides (ASOs), offer a novel strategy for targeting these challenging genes.

Purpose of the Study:

• To develop a comprehensive computational procedure for designing exon skipping (ES)-based cancer treatments.
• To create specific protein variants, including inactive oncogenes and partially restored tumor suppressors.
• To address the challenge of targeting 'undruggable' cancer driver genes.

Main Methods:

• A computational procedure was developed for target-exon selection and in silico prediction of ES products.
• Identification of optimal antisense oligonucleotide (ASO) candidate sequences for experimental validation.
• Application of the method to extensively mutated cancer genes, prioritizing those suitable for ES.

Main Results:

• The computational procedure was successfully applied to identify potential therapeutic targets.
• Specific target exons in genes like NRAS and VHL were identified as suitable for ES-based interventions.
• Optimal ASO sequences were devised to induce targeted exon skipping in these genes.

Conclusions:

• This work presents the first comprehensive computational procedure for designing ASO sequences for targeted exon skipping.
• The developed method offers a versatile and innovative approach to tackling undruggable cancer driver genes.
• This strategy holds promise for advancing RNA-based cancer therapeutics.