Six-gene Signature Based on Metabolism Is Closely Related to the Prognosis and Immune Infiltration of Patients With Sepsis

Abstract Background Sepsis is a leading cause of mortality and morbidity in the intensive care unit. Current studies indicated that metabolism associated genes (MAGs) have critical roles in sepsis T his study aim s to construct a gene signature for sepsis and explore its possible mechanism ss. Methods: Differentially expressed metabolism associated genes (DEMAGs) were identified in sepsis patients based on the Gene Expression Omnibus (GEO) database. Univariate and multivariate Cox regression analyses were performed to identify and construct the prognostic gene signature. Quantitative real time PCR was applied to examine the mRNA level of sig nature genes in the sepsis mice model established by cecalligation and puncture (CLP). Next, Gene S et Enrichment Analysis (GSEA) was performed to further understand the underlying molecular mechanisms of gene signature We then assessed the abundance of infiltrating immune cell s in each sample to explore the immune microenvironment of sepsis patient s Finally, the Tumor Immune Dysfunction and Exclusion (TIDE ) and SubMap algorithms were used to explore the immunotherapy response of sepsis patients .Results: A novel six gene signature (including ELANE , NQO2 , TLR2 , PTGDS , SMAD3 , CD3E ) was established for sepsis prognosis prediction , which could accurately predict the overall survival ( of sepsis patients. In the sepsis mice model, except PTGDS, the mRNA expression of the other five genes was consistent with that of sepsis patients. T he result s of GSEA analysis indicate that the prognostic signature w as closely related to immunity function Besides , we found that the risk score was strikingly negatively correlated with the tumor microenvironment (TME) immunecells infiltration and expression of critical immune checkpoints The patients in the low risk group were more likely to benefit from immune therapy through the TIDE and SubMap analysis Conclusion : In conclusion, our signature can predict the OS of sepsis patients and provide potential guidance for exploring patients who may benefit from immunotherapy.