Elucidating the role of SF3B3 in coronary atherosclerosis: integrating bioinformatics and machine learning for advanced insights

Atherosclerosis (AS) is a chronic inflammatory disease that compromises vascular health and underlies major cardiovascular events. SF3B3, a core spliceosome component, mediates exon–intron processing, yet its role in AS remains unclear. We performed integrative analyses of differentially expressed genes across GEO datasets (GSE43292 and GSE9820) and immune-related gene sets from ImmPort. Feature selection was refined using LASSO regression and SVM-RFE. Functional enrichment was assessed via GSEA and GSVA, while immune associations were evaluated with CIBERSORT and ESTIMATE. Key findings were validated in an independent dataset (GSE9820). Thirteen hub genes associated with SF3B3 were identified. SF3B3 expression correlated with enhanced antiviral defense, cytokine production, and immune signaling pathways. Higher SF3B3 levels were positively associated with adaptive immune populations—including memory and naïve B cells, CD4⁺ and CD8⁺ T cells, follicular helper T cells, and regulatory T cells—while inversely correlated with activated memory CD4⁺ T cells, monocytes, macrophages, eosinophils, and activated dendritic cells. SF3B3 is closely linked to immune infiltration patterns in AS, highlighting its potential as a biomarker and a candidate target for therapeutic intervention. These findings provide a framework for future mechanistic studies and clinical applications.