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. 2022 Jan 19:15:711-728.
doi: 10.2147/IJGM.S338486. eCollection 2022.

CD63 and C3AR1: The Potential Molecular Targets in the Progression of Septic Shock

Affiliations

CD63 and C3AR1: The Potential Molecular Targets in the Progression of Septic Shock

Ning Yu et al. Int J Gen Med. .

Abstract

Background: The molecular mechanism of septic shock is unknown. We studied the pathogenesis of septic shock and provide a novel strategy for treating and improving the prognosis of septic shock.

Methods: Gluten-Sensitive Enteropathy (GSE) 131761, GSE119217, GSE26378 datasets were downloaded from the Gene Expression Omnibus (GEO) database. The three datasets included 204 septic shock samples and 48 normal samples. The R packages "affy" and "limma" were employed to identify the differently expressed genes (DEGs) between septic shock and normal samples. Weighted gene co-expression network analysis (WGCNA) was performed to search for modules that play an important role in septic shock. Functional annotation of DEGs and construction and analysis of hub genes were used to explore the pathomechanism of septic shock. The receiver operating characteristic (ROC) curves were obtained using MedCalc software. The drug molecules that could regulate hub genes associated with septic shock were searched for in the CMap database. An animal model of septic shock was constructed to analyze the role of these hub genes.

Results: The merged series contained 321 up-regulated and 255 down-regulated genes. WGCNA showed the brown module had the highest correlation with the status of septic shock. GO and KEGG enrichment analysis results of the brown module genes showed they were mainly enriched in "leukocyte differentiation", "Ras-proximate-1 (Rap1) signaling pathway", and "cytokine-cytokine receptor interaction". Through construction and analysis of a protein-protein interaction (PPI) network, cluster of differentiation 63 (CD63) and complement component 3a receptor 1 (C3AR1) were identified as hub genes of septic shock. The area under curve (AUC) of C3AR1 for the septic shock is 0.772 (P<0.001), and the AUC of CD63 for the septic shock is 0.871 (P<0.001). Small molecule drugs were filtered by the number of instances (n>3) and P-values <0.05, including "monensin", "verteporfin", "ikarugamycin", "tetrahydroalstonine", "cefamandole", "etoposide". In the animal model, the relative expression levels of interleukin-6 (IL-6), Tumor Necrosis Factor-α (TNF-α), and lactic acid were significantly higher in the septic shock group compared with the control group. Results of Real Time Quantitative PCR (RT-qPCR) and enzyme-linked immunosorbent assay (ELISA) analysis for CD63 and C3AR1 showed that their relative expression levels were significantly lower in the septic shock group compared with the control group (P<0.05).

Conclusion: CD63 and C3AR1 are significant hub genes of septic shock and may represent potential molecular targets for future studies of septic shock.

Keywords: C3AR1; CD63; animal model; hub genes; septic shock.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1
Differential expression analysis and weighted gene co-expression network analysis (WGCNA) of the genes in the merged series. (A) Volcano plots of the genes showing differentially expressed Genes (DEGs) between the septic shock and normal groups. (B) Heatmaps of the 576 DEGs. (C) The lowest power for which scale Independence was observed. (D) Repeated hierarchical clustering tree of all genes. (E) The dendrogram and heatmap of all genes. (F) Interactions between these modules. (G) The associations between clinical traits and the modules.
Figure 2
Figure 2
Gene functional enrichment analysis of the brown model genes by Gene Set Enrichment Analysis (GSEA) and Metascape. (A) Gene ontology (GO) analyses by GSEA. (B) Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses by GSEA. (C) Enrichment_GO_ColorByCluster analyses by Metascape. (D) Enrichment_KEGG_ColorByCluster analyses by Metascape. (E) Enrichment_heatmap_HeatmapSelected GO analyses by Metascape. (F) Enrichment_heatmap_HeatmapSelected KEGG analyses by Metascape.
Figure 3
Figure 3
Relationship between differentially expressed Genes (DEGs). (A) The DEGs in the brown model genes. (B) Protein–protein interaction (PPI) network, the higher the number of connections, the larger the protein. (C) Common hub genes identified using different algorithms. (D) The common hub genes of the PPI network.
Figure 4
Figure 4
Relationship between the septic shock and normal groups related to hub genes based on the comparative toxicogenomics database (CTD) database.
Figure 5
Figure 5
Functional and pathway enrichment analysis related with hub genes. (A) Biological processes (BP) analyses. (B) Cell components (CC) analyses. (C) Molecular functions (MF) analyses. (D) Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses.
Figure 6
Figure 6
ROC curves of the hub genes. The orange curve represents the main line, the upper purple curve represents the upper boundary of the feasible interval, the lower purple curve represents the lower boundary of the feasible interval, and the purple line is the diagonal line.
Figure 7
Figure 7
The construction of the animal model of septic shock. (A-C) Expression levels of interleukin-6 (IL-6), TNF-α, and lactic acid. *P≤0.05.
Figure 8
Figure 8
Results of RT-qPCR and ELISA analysis for CD63. (A) CD63 expression in control group (B) CD63 expression in septic shock group. *P≤0.05.
Figure 9
Figure 9
Results of RT-qPCR reverse transcription polymerase chain reaction and ELISA analysis for C3AR1. (A) C3AR1 expression in septic shock group (B) C3AR1 expression in control group. *P≤0.05.
Figure 10
Figure 10
Comparison of CD63 and C3AR1 expression in patients with sepsis from those with septic shock. *P≤0.05.
Figure 11
Figure 11
Comparison of C5a and C5AR1 expression between control mice and septic shock mice. *P≤0.05.

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