BackgroundSeptic shock occurs when sepsis is associated with critically low blood pressure, and has a high mortality rate. This study aimed to undertake a bioinformatics analysis of gene expression profiles for risk prediction in septic shock.Material/MethodsTwo good quality datasets associated with septic shock were downloaded from the Gene Expression Omnibus (GEO) database, GSE64457 and GSE57065. Patients with septic shock had both sepsis and hypotension, and a normal control group was included. The differentially expressed genes (DEGs) were identified using OmicShare tools based on R. Functional enrichment of DEGs was analyzed using DAVID. The protein-protein interaction (PPI) network was established using STRING. Survival curves of key genes were constructed using GraphPad Prism version 7.0. Each putative central gene was analyzed by receiver operating characteristic (ROC) curves using MedCalc statistical software.ResultsGSE64457 and GSE57065 included 130 RNA samples derived from whole blood from 97 patients with septic shock and 33 healthy volunteers to obtain 975 DEGs, 455 of which were significantly down-regulated and 520 were significantly upregulated (P<0.05). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis identified significantly enriched DEGs in four signaling pathways, MAPK, TNF, HIF-1, and insulin. Six genes, WDR82, ASH1L, NCOA1, TPR, SF1, and CREBBP in the center of the PPI network were associated with septic shock, according to survival curve and ROC analysis.ConclusionsBioinformatics analysis of gene expression profiles identified four signaling pathways and six genes, potentially representing molecular mechanisms for the occurrence, progression, and risk prediction in septic shock.

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Purpose To screen biomarkers in the serum of patients with sepsis by proteomics combined with RNA sequencing technology, and to find new diagnostic and therapeutic targets for sepsis. Patients and Methods Blood samples of 22 sepsis patients (sepsis group) and 10 healthy volunteers (normal group) were collected from January 2019 to December 2020. Data-independent acquisition (DIA) method was employed for protein profiling, RNA sequencing was employed for gene sequencing. Subsequently, quality control and differential analysis (FC≥2; FDR<0.05) of DIA data and RNA sequencing data were performed. Then we identified expression trend-consistent divergence factors by nine-quadrant analysis; subsequent protein-protein interaction (PPI) and gene ontology (GO) functional enrichment analysis of intersection factors was performed, and meta-analysis of targets at transcriptome level was implemented using public datasets. Finally, five Peripheral blood mononuclear cell (PBMC) samples (NC=2; SIRS=1; SEPSIS =2) were collected, and cell localization analysis of core genes was performed by 10× single-cell RNA sequencing (scRNA-seq). Results Compared with the normal group, there were 4681 differentially expressed genes and 202 differentially expressed proteins in the sepsis group. Among them, 25 factors were expressed in both proteome and transcriptome, and the analysis of PPI and GO found that they were mainly involved in biological processes such as white blood cell and neutrophil response, inflammatory and immune response. Four core genes GSTO1, C1QA, RETN, and GRN were screened by meta-analysis, all of which were highly expressed in the sepsis group compared with the normal group (P<0.05); scRNA-seq showed the core genes were mainly localized in macrophage cell lines. Conclusion The core genes GSTO1, C1QA, RETN and GRN are mainly expressed in macrophages, widely involved in inflammation and immune responses, and are highly expressed in plasma in the sepsis, suggesting that they may become potential research targets for sepsis.

Abstract Glioma is the most common malignant tumor in the human central nervous system. Although heterogeneous nuclear ribonucleoprotein A2/B1 (hnRNPA2/B1) was previously presumed to be a tumor-promoting gene, the relationship between hnRNPA2/B1 and glioma is unclear. Targeting hnRNPA2/B1 interference in glioma cells can significantly inhibit proliferation and increase apoptosis of human glioma cells in vitro. In a tumor xenograft model, knockdown of hnRNPA2/B1 suppressed tumor growth in glioma cells in vivo. In terms of a mechanism, the knockdown of hnRNPA2/B1 led to inactivation of the AKT and STAT3 signaling pathways, which ultimately reduced the expression of B-cell lymphoma-2 (Bcl-2), CyclinD1 and proliferating cell nuclear antigen (PCNA). Collectively, these data suggest that the inhibition of hnRNPA2/B1 can reduce the growth of gliomas through STAT3 and AKT signaling pathways, and this inhibition is expected to be a therapeutic target for gliomas.

The purpose of our study was to explore potential characteristic biomarkers in patients with sepsis. Peripheral blood specimens from sepsis patients and normal human volunteers were processed by liquid chromatography-mass spectrometry-based analysis. Outlier data were excluded by principal component analysis and orthogonal partial least squares-discriminant analysis using the metabolomics R software package metaX and MetaboAnalyst 5.0 (https://www.metaboanalyst.ca/home.xhtml) online analysis software, and differential metabolite counts were identified by using volcano and heatmaps. The obtained differential metabolites were combined with KEGG (Kyoto Gene and Kyoto Encyclopedia) analysis to screen out potential core differential metabolites, and ROC curves were drawn to analyze the changes in serum metabolites in sepsis patients and to explore the potential value of the metabolites in the diagnosis of sepsis patients. By metabolomic analysis, nine differential metabolites were screened for their significance in guiding the diagnosis and differential diagnosis of sepsis namely: 3-phenyl lactic acid, N-phenylacetylglutamine, phenylethylamine, traumatin, xanthine, methyl jasmonate, indole, l-tryptophan and 1107116. In this study, nine metabolites were finally screened based on metabolomic analysis and used as potential characteristic biomarkers for the diagnosis of sepsis.