S1PR1-Associated Molecular Signature Predicts Survival in Patients with Sepsis. Issue 3 (March 2020)

• Record Type: Journal Article
• Authors: Feng, Anlin; Rice, Amanda D.; Zhang, Yao; Kelly, Gabriel T.; Zhou, Tong; Wang, Ting
• Is Part Of: Shock. Volume 53:Issue 3(2020)
• Publication Date: 2020-03
• Subjects: Microarray -- S1PR1 -- sepsis -- SMS -- Abbreviations -- AUC -- area under the curve -- DEGs -- differentially expressed genes -- GEO -- gene expression omnibus -- OS -- overall survival -- PPI -- protein-protein interaction -- ROC -- receiver operating characteristic -- S1PR1 -- sphingosine-1-phosphate and its receptor S1P receptor 1 -- SMS -- S1PR1-related molecular signatures; Shock -- Periodicals; Shock -- Periodicals; Choc (Pathologie) -- Périodiques; Shock; Periodicals; 616.0475
• DOI: 10.1097/SHK.0000000000001376
• Languages: English
• ISSNs: 1073-2322

Abstract

ABSTRACT: Background: Sepsis is a potentially life-threatening complication of an underlying infection that quickly triggers tissue damage in multiple organ systems. To date, there are no established useful prognostic biomarkers for sepsis survival prediction. Sphingosine-1-phosphate (S1P) and its receptor S1P receptor 1 (S1PR1) are potential therapeutic targets and biomarkers for sepsis, as both are active regulators of sepsis-relevant signaling events. However, the identification of an S1PR1 -related gene signature for prediction of survival in sepsis patients has yet to be identified. This study aims to find S1PR1 -associated biomarkers which could predict the survival of patients with sepsis using gene expression profiles of peripheral blood to be used as potential prognostic and diagnostic tools. Methods: Gene expression analysis from sepsis patients enrolled in published datasets from Gene Expression Omnibus was utilized to identify both S1PR1 -related genes (co-expression genes or functional-related genes) and sepsis survival-related genes. Results: We identified 62-gene and 16-gene S1PR1 -related molecular signatures (SMS) associated with survival of patients with sepsis in discovery cohort. Both SMS genes are significantly enriched in multiple key immunity-related pathways that are known to play critical roles in sepsis development. Meanwhile, the SMS performs well in a validation cohort containing sepsis patients. We further confirmed our SMSs, as newly developed gene signatures, perform significantly better than random gene signatures with the same gene size, in sepsis survival prognosis. Conclusions: Our results have confirmed the significant involvement of S1PR1 -dependent genes in the development of sepsis and provided new gene signatures for predicting survival of sepsis patients. Abstract : Supplemental Digital Content is available in the text