Prognosis of patients with septic shock predicted by bioinformatics analysis based on gene expression profiling

Abstract Objective: The aim of this study was to perform bioinformatic analysis of gene expression profiles in septic shock in order to explore potential characteristic genes in patients with septic shock and thus to predict prognosis of septic shock. Methods: Peripheral blood specimens from patients with septic shock (n=11) and normal human volunteers (n=10) were sequenced for RNA, and the R-language based integrated differential expression and pathway analysis (iDEP) (http://bioinformatics.sdstate.edu/idep/) web tool was used to perform gene high and low expression groups Screening analysis ultimately yielded differentially expressed genes (DEGs, log2FC ≥ 4, q-value ≤ 0.01). DEGs were analysed by gene ontology enrichment and screened for potential core genes using protein-protein interactions (PPI). In addition, survival data in GSE95233 were used to observe the correlation between core genes and prognosis. Results: The analysis resulted in the screening of four differential genes that are indicative of the diagnosis, differential diagnosis and prognosis of septic shock disease, namely: CD6, CD247, LCK and CD3E. Conclusion: This study identified five signalling pathways and four core genes through bioinformatic analysis of gene expression profiles that may represent molecular mechanisms for the onset, progression and risk prediction of septic shock.