Integrative analysis of transcriptome and single-cell sequencing combined with experimental validation identifies biomarkers associated with T cell and senescence in sepsis

Background Sepsis is an infection-induced systemic inflammatory response syndrome. T cell remodeling and senescence are linked to sepsis, so identifying T cell-related genes (TCRGs) and senescence-related genes (SRGs) as biomarkers is crucial for elucidating mechanisms, diagnosis, and targeted therapy. Methods TCRGs were derived from single-cell sequencing data. Biomarkers were screened via differential expression analysis, machine learning, and expression analysis of public transcriptome data. Molecular mechanisms were explored through artificial neural network (ANN), GSEA, immune infiltration analysis, and drug prediction, with RT-qPCR validation in clinical samples. Results PATZ1, SIN3B, BLK, and MTHFD2 were identified. MTHFD2 was upregulated in sepsis, while the other three were downregulated (P < 0.001); MTHFD2 showed no significant difference in validation (P>0.05). The ANN had high prediction accuracy. These genes were enriched in phosphatidylinositol signaling, hematopoietic cell lineage, and DNA replication. Immune infiltration analysis revealed correlations between the biomarkers and immune cells (e.g., PATZ1 with CD8 T cells/neutrophils). Emetine, latamoxef, and dihydroergotamine bound stably to the biomarkers. Conclusion PATZ1, SIN3B, BLK, and MTHFD2, as T cell and senescence-related biomarkers in sepsis, offered valuable insights into sepsis pathogenesis and targeted therapy.