Abstract
Objective: Septic shock is the severe complication of sepsis, with a high mortality. The inflammatory response regulates the immune status and mediates the progression of septic shock. In this study, we aim to identify the key immune-related genes (IRGs) of septic shock and explore their potential mechanism.Methods: Gene expression profiles of septic shock blood samples and normal whole blood samples were retrieved from the Gene Expression Omnibus (GEO) and Genotype-Tissue Expression Portal (GTEx). The differential expression genes (DEGs) and septic shock-specific immune-related genes (SSSIRGs) were evaluated and identified, along with the immune components by “cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT, version x)” algorithm. Additionally, in order to explore the key regulatory network, the relationship among SSSIRGs, upstream transcription factors (TFs), and downstream signaling pathways were also identified by Gene Set Variation Analysis (GSVA) and co-expression analysis. Moreover, the Connectivity Map (CMap) analysis was applied to find bioactive small molecules against the members of regulation network while Chromatin Immunoprecipitation sequencing (ChIP-seq) and Assay for Targeting Accessible-Chromatin with high-throughput sequencing (ATAC-seq) data were used to validate the regulation mechanism of the network.Results: A total of 14,843 DEGs were found between 63 septic shock blood samples and 337 normal whole blood samples. Then, we identified septic shock-specific 839 IRGs as the intersection of DEGs and IRGs. Moreover, we uncovered the regulatory networks based on co-expression analysis and found 28 co-expression interaction pairs. In the regulation network, protein phosphatase 3, catalytic subunit, alpha isozyme (PPP3CA) may regulate late estrogen response, glycolysis and TNFα signaling via NFκB and HLA; Kirsten rat sarcoma viral oncogene homolog (KRAS) may be related to late estrogen response and HLA; and Toll-like receptor 8 (TLR8) may be associated with TNFα signaling via NFκB. And the regulation mechanisms between TFs and IRGs (TLR8, PPP3CA, and KRAS) were validated by ChIP-seq and ATAC-seq.Conclusion: Our data identify three SSSIRGs (TLR8, PPP3CA, and KRAS) as candidate therapeutic targets for septic shock and provide constructed regulatory networks in septic shock to explore its potential mechanism.
Highlights
Septic shock is the most severe complication of a severe microbial infection, with a short treatment timewindow and a high death rate (Sharawy and Lehmann, 2015)
A total of 839 septic shock-specific immune-related genes (SSSIRGs) (666 down-regulated genes and 173 upregulated genes) were extracted from the intersection of 14,843 Differential expression genes (DEGs) and 2,498 immune-related genes (IRGs) in septic shock blood, and the expression level of these SSSIRGs were shown in the heat map (Figure 3A) and volcano plot (Figure 3B)
By the constructed regulatory network, we found the potential relationship between SSSIRGs (TLR8, PPP3CA, and Kirsten rat sarcoma viral oncogene homolog (KRAS)) and signaling pathways/immune gene sets (HLA)
Summary
Septic shock is the most severe complication of a severe microbial infection (sepsis), with a short treatment timewindow and a high death rate (Sharawy and Lehmann, 2015). The inflammatory response associated with “cytokine storm” leads to the damages to host tissues and organs, while the anti-inflammatory response reprograms the immune microenvironment and regulates the immune status (Russell and Walley, 2010). The regulation and dysregulation of immune microenvironment may play important roles in the development, progression, and prognosis of septic shock. Current therapeutic strategies often focus on controlling the infection source by antibiotic therapy and restoring hemodynamic homeostasis by norepinephrine (Kumar, 2014). Based on the crucial roles of immune microenvironment in septic shock, we suppose that targeting septic shock-specific immune-related genes (SSSIRGs) may be novel therapeutic options (Walley et al, 2014; Francois et al, 2018)
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