Exploring the Role of Chemokine-Related Gene Deregulation and Immune Infiltration in Ischemic Stroke: Insights into CXCL16 and SEMA3E as Potential Biomarkers

Ischemic stroke is a leading cause of mortality and disability globally. Understanding the role of chemokine-related differently expressed genes (CDGs) in ischemic stroke pathophysiology is essential for advancing diagnostic and therapeutic strategies. We conducted comprehensive analyses using the GSE16561 dataset: chemokine pathway enrichment via GSVA, differential expression of 12 CDGs, Pearson correlation, and functional enrichment analyses (GO and KEGG). Machine learning algorithms were employed to develop diagnostic models, evaluated using ROC curve analysis. A nomogram was constructed and validated with independent datasets (GSE58294). Gene set enrichment analysis (GSEA) and immuno-infiltration analysis were also performed. Chemokine pathway scores were significantly elevated in ischemic stroke, indicating their potential involvement. Logistic regression emerged as the most effective diagnostic model, with CXCL16 and SEMA3E as significant biomarkers. The nomogram exhibited high discriminatory ability (AUC = 0.964), well-calibrated predictions, and clinical utility across datasets. GSEA highlighted key biological pathways associated with CXCL16 and SEMA3E. Immuno-infiltration analysis revealed significant differences in immune cell infiltration between control and ischemic stroke groups, with distinct correlations between CXCL16 and SEMA3E expression and immune cell populations. This study highlights the deregulation of CDGs in ischemic stroke and their implications in critical biological processes. CXCL16 and SEMA3E are identified as key biomarkers with potential diagnostic utility. Insights from gene set enrichment and immuno-infiltration analyses provide mechanistic understanding, suggesting novel therapeutic targets and enhancing clinical decision-making in ischemic stroke management.