Alternative RNA Splicing as a Potential Major Source of Untapped Molecular Targets in Precision Oncology and Cancer Disparities

• Published in: Clinical cancer research 2019-05, Vol.25 (10), p.2963-2968
• Main Authors: Robinson, Timothy J, Freedman, Jennifer A, Al Abo, Muthana, Deveaux, April E, LaCroix, Bonnie, Patierno, Brendon M, George, Daniel J, Patierno, Steven R
• Format: Article
• Language: English
• Subjects: Alternative Splicing; Biomarkers, Tumor - genetics; Health Status Disparities; Humans; Molecular Targeted Therapy; Neoplasms - genetics; Neoplasms - pathology; Neoplasms - therapy; Precision Medicine - methods; RNA Splicing
• ISSN: 1078-0432; 1557-3265
• DOI: 10.1158/1078-0432.CCR-18-2445

Studies of alternative RNA splicing (ARS) have the potential to provide an abundance of novel targets for development of new biomarkers and therapeutics in oncology, which will be necessary to improve outcomes for patients with cancer and mitigate cancer disparities. ARS, a key step in gene expression enabling individual genes to encode multiple proteins, is emerging as a major driver of abnormal phenotypic heterogeneity. Recent studies have begun to identify RNA splicing-related genetic and genomic variation in tumors, oncogenes dysregulated by ARS, RNA splice variants driving race-related cancer aggressiveness and drug response, spliceosome-dependent transformation, and RNA splicing-related immunogenic epitopes in cancer. In addition, recent studies have begun to identify and test, preclinically and clinically, approaches to modulate and exploit ARS for therapeutic application, including splice-switching oligonucleotides, small molecules targeting RNA splicing or RNA splice variants, and combination regimens with immunotherapies. Although ARS data hold such promise for precision oncology, inclusion of studies of ARS in translational and clinical cancer research remains limited. Technologic developments in sequencing and bioinformatics are being routinely incorporated into clinical oncology that permit investigation of clinically relevant ARS events, yet ARS remains largely overlooked either because of a lack of awareness within the clinical oncology community or perceived barriers to the technical complexity of analyzing ARS. This perspective aims to increase such awareness, propose immediate opportunities to improve identification and analysis of ARS, and call for bioinformaticians and cancer researchers to work together to address the urgent need to incorporate ARS into cancer biology and precision oncology.