Exploring biomarkers associated with tetraspanins in sepsis: a comprehensive analysis of transcriptome consortium experimental validation.

Although Tetraspanin (TSPAN) plays a crucial physiological role in sepsis, the specific molecular mechanisms underlying its involvemenin sepsis pathophysiology remain incompletely elucidated. This study aimed to identify TSPAN-associated biomarkers in sepsis and clarify their potential molecular mechanisms. Sepsis transcriptome data and TSPAN-related genes were from public databases. TSPAN-defined molecular subtypes were identified via consensus clustering. Candidate genes were screened by intersecting TSPAN-related differentially expressed genes (DEGs) with sepsis DEGs; biomarkers were determined using machine learning, ROC curves, and expression validation. Finally, GSEA, immune cell abundance analysis, and compound prediction explored their functions, and RT-qPCR validated prognostic gene expression. Eleven candidate genes were identified; XK, CA1, AHSP and GYPA were confirmed as biomarkers, significantly upregulated in sepsis vs. controls and enriched in pathways like "martens tretinoin response up". Neutrophil, activated dendritic cell, and macrophage abundance differed between groups and correlated with biomarkers. 52 potential therapeutics (including zanamivir) were screened via biomarker interaction analysis. RT-qPCR confirmed higher expression of the four biomarkers in sepsis. In conclusion, XK, CA1, AHSP, and GYPA are TSPAN-associated biomarkers in sepsis and are significantly correlated with Type 17 T helper cells. The findings offered a promising theoretical foundation for the development of pharmaceuticals for sepsis.