The dysregulation of alternative splicing (AS) is increasingly recognized as a pivotal player in the pathogenesis, progression, and treatment resistance of B-cell acute lymphoblastic leukemia (B-ALL). Despite its significance, the clinical implications of AS events in B-ALL remain largely unexplored. This study developed a prognostic model based on 18 AS events (18-AS), derived from a meticulous integration of bioinformatics methodologies and advanced machine learning algorithms. The 18-AS signature observed in B-ALL distinctly categorized patients into different groups with significant differences in immune infiltration, V(D)J rearrangement, drug sensitivity, and immunotherapy outcomes. Patients classified within the high 18-AS group exhibited lower immune infiltration scores, poorer chemo- and immune-therapy responses, and worse overall survival, underscoring the model's potential in refining therapeutic strategies. To validate the clinical applicability of the 18-AS, we established an SF-AS regulatory network and identified candidate drugs. More importantly, we conducted in vitro cell proliferation assays to confirm our analysis, demonstrating that the High-18AS cell line (SUP-B15) exhibited significantly enhanced sensitivity to Dasatinib, Dovitinib, and Midostaurin compared to the Low-18AS cell line (REH). These findings reveal AS events as novel prognostic biomarkers and therapeutic targets, advancing personalized treatment strategies in B-ALL management.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11380455 | PMC |
http://dx.doi.org/10.7150/ijbs.98899 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!