Objective To identify potential hub genes and key pathways in the early period of septic shock via bioinformatics analysis. MethodsThe gene expression profile GSE110487 dataset was downloaded from the Gene Expression Omnibus database. Differentially expressed genes were identified by using DESeq2 package of R project. Then Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were constructed to investigated pathways and biological processes using clusterProfiler package. Subsequently, protein-protein interaction (PPI) network was mapped using ggnetwork package and the molecular complex detection (MCODE) analysis was implemented to further investigate the interactions of differentially expressed genes using Cytoscape software. Results A total of 468 differentially expressed genes were identified in septic shock patients with different responses who accepted early supportive hemodynamic therapy, including 255 upregulated genes and 213 downregulated genes. The results of GO and the KEGG pathway enrichment analysis indicated that these up-regulated genes were highly associated with the immune-related biological processes, and the down-regulated genes are involved in biological processes related to organonitrogen compound, multicellular organismal process, ion transport. Finally, a total of 23 hub genes were identified based on PPI and the subcluster analysis through MCODE software plugin in Cytoscape, which included 19 upregulated hub genes, such as CD28, CD3D, CD8B, CD8A, CD160, CXCR6, CCR3, CCR8, CCR9, TLR3, EOMES, GZMB, PTGDR2, CXCL8, GZMA, FASLG, GPR18, PRF1, IDO1, and additional 4 downregulated hub genes, such as CNR1, GPER1, TMIGD3, GRM2. KEGG pathway enrichment analysis and GO functional annotation showed that differentially expressed genes were primarily associated with the items related to cytokine-cytokine receptor interaction, natural killer cell mediated cytotoxicity, hematopoietic cell lineage, T cell receptor signaling pathway, phospholipase D signaling pathway, cell adhesion molecules, viral protein interaction with cytokine and cytokine receptor, primary immunodeficiency, graft-versus-host disease, type 1 diabetes mellitus. Conclusions Some lymphocytes such as T cells and natural killer cells, cytokines and chemokines participate in the immune process, which plays an important role in the early treatment of septic shock, and CD160, CNR1, GPER1, and GRM2 may be considered as new biomarkers.
ObjectiveTo explore the mechanism of paucigranulocytic asthma and to find therapeutic target for paucigranulocytic asthma.MethodsGSE143303 data and platform information were downloaded from GEO. Gene Set Enrichment Analysis were performed to construct positive and negative gene-gene interaction network correlation with paucigranulocytic asthma. Differential expression analysis, pathway commonality analysis were performed with R language.ResultsGSE143303 data set contained 47 endobronchial biopsies from adult (16 cases of paucigranulocytic asthma, 13 cases of healthy control). Compared with control group, the paucigranulocytic asthma group had 115 differential genes set (37 positive and 78 negative). The results of pathway commonality analysis showed that the crosslink existed within the negative gene-gene interaction network correlation with paucigranulocytic asthma. Among these, most of the genes belonged to the protein HLA gene family. Differential expression analysis show that HLA-DQB1, HLA-DRB5 were differential genes and TNFRSF13B was significantly downregulated genes in the intersect genes.ConclusionTNFRSF13B, HLA-DQB1, HLA-DRB5 and regulatory networks associated with them are the crucial factors contributing to paucigranulocytic asthma.
Objective To detect the expression and clinical significance of POLD1 gene in non-small cell lung cancer (NSCLC) via bioinformatics method. Methods The expression difference of POLD1 in NSCLC tissue and normal lung tissue was investigated by TIMER database. UALCAN database was used to further verify different expression of POLD1 as well as the relationship between POLD1 expression and clinicopathological characteristics of NSCLC. The correlation between POLD1 gene and prognosis of NSCLC patients was detected by GEPIA and TIMER database. cBioPortal database was used to analyze frequencies of POLD1 gene mutation. POLD1-related protein-protein interaction network was constructed by STRING database. The relationship between POLD1 and immune infiltration was based on TISIDB database. Results The expression of POLD1 gene in lung adenocarcinoma and lung squamous cell carcinoma was significantly higher than that in normal lung tissue. In lung adenocarcinoma, patients with lower POLD1 level showed better prognosis. 1.2% of lung adenocarcinoma patients and 1.8% of lung squamous cell carcinoma patients carried mutated POLD1 gene, mainly missense mutations. POLD1 may interact with POLD2, POLD3, POLD4, POLE, RPA1, PCNA, MSH6, MSH2 and FEN1. The biological processes include DNA replication, mismatch repair, etc. Besides, the expression of POLD1 in NSCLC was correlated with the number of different immune cells. Conclusions The POLD1 gene is highly expressed in NSCLC patients, and negatively related with survival prognosis in patients of lung adenocarcinoma. POLD1 gene may be a potential diagnostic target and prognostic marker in NSCLC.
ObjectiveAlthough evidence links idiopathic pulmonary fibrosis (IPF) and diabetes mellitus (DM), the exact underlying common mechanism of its occurrence is unclear. This study aims to explore further the molecular mechanism between these two diseases. MethodsThe microarray data of idiopathic pulmonary fibrosis and diabetes mellitus in the Gene Expression Omnibus (GEO) database were downloaded. Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify co-expression genes related to idiopathic pulmonary fibrosis and diabetes mellitus. Subsequently, differentially expressed genes (DEGs) analysis and three public databases were employed to analyze and screen the gene targets related to idiopathic pulmonary fibrosis and diabetes mellitus. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by Metascape. In addition, common microRNAs (miRNAs), common in idiopathic pulmonary fibrosis and diabetes mellitus, were obtained from the Human microRNA Disease Database (HMDD), and their target genes were predicted by miRTarbase. Finally, we constructed a common miRNAs-mRNAs network by using the overlapping genes of the target gene and the shared gene. ResultsThe results of common gene analysis suggested that remodeling of the extracellular matrix might be a key factor in the interconnection of DM and IPF. Finally, hub genes (MMP1, IL1R1, SPP1) were further screened. miRNA-gene network suggested that has-let-19a-3p may play a key role in the common molecular mechanism between IPF and DM. ConclusionsThis study provides new insights into the potential pathogenic mechanisms between idiopathic pulmonary fibrosis and diabetes mellitus. These common pathways and hub genes may provide new ideas for further experimental studies.
ObjectiveTo explore the clinical significance and possible potential mechanism of hepatocellular carcinoma through the screening of key genes in hepatocellular carcinoma.MethodsHepatocellular carcinoma gene chip was obtained from GEO database, differentially expressed genes (DEGs) were screened by GEO2R online tools and Venn map, GO analysis and KEGG pathway analysis were performed in DAVID database, core genes were screened by STRING and Cytscape software, core genes were analyzed in Kaplan-Meier Plotter for survival analysis, and expression was analyzed by GEPIA database. The core genes related to prognosis and highly expressed in hepatocellular carcinoma were analyzed by Metascape online tool for function and pathway enrichment analysis. Finally, the key genes were verified in hepatocellular carcinoma and paracancerous tissues.ResultsA total of 94 DEGs were screened from three gene chips GSE14520, GSE60502, and GSE102079, obtained from GEO. After the selected DEGs was analyzed by GO function analysis, KEGG pathway enrichment analysis, STRING and Cytscape software by DAVID, 19 core DEGs were screened. After 19 core DEGs were analyzed by Kaplan-Meier Plotter website, 9 genes [ribonucleotide reductase M2 (RRM2), polycomb repressive complex 1 (PRC1), topoisomerase Ⅱ alpha (TOP2A), aurora kinase A (AURKA), nucleolar spindle-associated protein 1 (NUSAP1), Rac-GTPase activating protein 1 (RACGAP1), abnormal spindle-like microcephaly-associated (ASPM), cyclin dependent kinase 1 (CDK1) and GINS complex subunit 1 (GINS1)] were found to be associated with the prognosis of hepatocellular carcinoma. The expressions of these 9 genes were analyzed by GEPIA, and the results showed that all 9 genes were highly expressed in hepatocellular carcinoma tissues. The functions and pathways of 9 highly expressed genes were analyzed by metascape website. Finally, RRM2 was selected for verification in hepatocellular carcinoma tissues and adjacent tissues, and it was found that the staining score of RRM2 in hepatocellular carcinoma tissues was (10.9±1.5) points, which was significantly higher than its staining score in adjacent tissues [(4.5±1.2) points], P<0.001.ConclusionThe nine genes identified by bioinformatics analysis may be the key genes in the occurrence and development of hepatocellular carcinoma, which can provide reference for further study on the pathogenesis, diagnosis and treatment of hepatocellular carcinoma.
ObjectiveTo observe the expressions of miR-143-3p in gastric cancer cells and gastric carcinoma tissues with its clinical significance, and to analyze the target genes with enriched pathway by using bioinformatics methods.MethodsThe expressions of miR-143-3p in different differentiation gastric cancer cells and normal gastric mucosa cell line, and the expressions in gastric cancer tissues and adjacent tissues were detected by real-time fluorescent quantitative PCR. In addition, OncomiR and YM500 databases were used to analyze the expression of miR-143-3p in gastric cancer tissues compared with adjacent tissues. Furthermore, the targets of miR-143-3p were predicted by using the software of miRecords website database, and at least three software-supported target genes were chosen to analyze the enriched the signal pathways in which the target gene was involved with DAVID 6.7 software.ResultsThe expressions of miR-143-3p in the different differentiation degree of gastric cancer cells compared with normal gastric mucosa cell line were downregulated (P<0.001), and the expression of miR-143-3p in gastric cancer tissues compared with adjacent tissues was also downregulated (downregulated in 36 cases, upregulated in 18 cases, and no alteration in 4 cases). The expression of miR-143-3p in gastric cancer tissues was associated with lymph node metastasis and invasion depth (P<0.05). Bioinformatics analysis results showed that the target genes of miR-143-3p were enriched in 38 signaling pathways associated with cancer.ConclusionMiR-143-3p is a down-regulated molecular marker in gastric cancer and a potentially clinically related tumor suppressor gene, which may be involved in the cancerous phenotype in carcinogenesis and development of gastric cancer.
Objective To explore depression-related biomarkers and potential therapeutic drugs in order to alleviate depression symptoms and improve patients’ quality of life. Methods From November 2022 to January 2024, gene expression profiles of depression patients and healthy volunteers were downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed to identify differentially expressed genes. Enrichment analysis of these genes was conducted, followed by the construction of a protein-protein interaction network. Finally, Cytoscape software with the Cytohubba plugin was used to identify potential key genes, and drug prediction was performed. Results Through differential expression analysis, a total of 110 differentially expressed genes (74 upregulated and 36 downregulated) were identified. Protein-protein interaction network identified 10 key genes, and differential expression analysis showed that 8 of these genes (CPA3, HDC, IL3RA, ENPP3, PTGDR2, VTN, SPP1, and SERPINE1) exhibited significant differences in expression levels between healthy volunteers and patients with depression (P<0.05). Enrichment analysis revealed that the upregulated genes were significantly enriched in pathways related to circadian rhythm, niacin and nicotinamide metabolism, and pyrimidine metabolism, while the downregulated genes were primarily enriched in extracellular matrix-receptor interaction and interleukin-17 signaling pathways. Six overlapping verification genes (SALL2, AKAP12, GCSAML, CPA3, FCRL3, and MS4A3) were obtained across two datasets using the Wayn diagram. Single-cell sequencing analysis indicated that these genes were significantly expressed in astrocytes and neurons. Mendelian randomization analysis suggested that the FCRL3 gene might play a critical role in the development of depression. Drug prediction analysis revealed several potential antidepressant agents, such as cefotiam, harmol, lincomycin, and ribavirin. Conclusions Circadian rhythm, nicotinate and nicotinamide metabolism, and pyrimidine metabolism pathways may represent potential pathogenic mechanisms in depression. Harmol may be a potential therapeutic drug for the treatment of depression.
Objective To explore key genes and mechanisms of depression aggravating Crohn disease. Methods In March 2023, the Public Health Genomics and Precision Health Knowledge Base and Gene Expression Omnibus database were used to identify the overlapping differentially expressed genes between Crohn disease and depression and the key genes were screened by Metascape, STRING, Cytoscape, and protein interaction network analysis. The Gene Expression Omnibus database was used to analyze the correlations between key genes and clinical pathologies such as Crohn Disease Endoscopic Index of Severity and intestinal microvilli length. Results There were 137 overlapping differentially expressed genes between Crohn disease and depression, and 25 key genes were further screened out. Among them, CREB1, FKBP5, MAPT, NTSR1, OXTR, PROK2, POMC, HTR2B, and PPARGC1A genes were significantly correlated with multiple clinical parameters. The functions of PROK2 and PROK2-related genes were mainly enriched in neutrophil and granulocyte migration, neutrophil and granulocyte chemotaxis, etc. Conclusions There are 25 key genes, especially CREB1, FKBP5, MAPT, NTSR1, OXTR, PROK2, POMC, HTR2B, and PPARGC1A, that possibly contribute to the establishment and deterioration of Crohn disease caused by depressive disorder. Among these genes, PROK2 showes the possibility of regulating immune cell (neutrophils and CD8+ T cells) infiltration.
ObjectiveTo investigate the relation between disulfidptosis-related genes (DRGs) and prognosis or immunotherapy response of patients with pancreatic cancer (PC). MethodsThe transcriptome data, somatic mutation data, and corresponding clinical information of the patients with PC in The Cancer Genome Atlas (TCGA) were downloaded. The DRGs mutated in the PC were screened out from the 15 known DRGs. The DRGs subtypes were identified by consensus clustering algorithm, and then the relation between the identified DRGs subtypes and the prognosis of patients with PC, immune cell infiltration or functional enrichment pathway was analyzed. Further, a risk score was calculated according to the DRGs gene expression level, and the patients were categorized into high-risk and low-risk groups based on the mean value of the risk score. The risk score and overall survival of the patients with high-risk and low-risk were compared. Finally, the relation between the risk score and (or) tumor mutation burden (TMB) and the prognosis of patients with PC was assessed. ResultsThe transcriptome data and corresponding clinical information of the 177 patients with PC were downloaded from TCGA, including 161 patients with somatic mutation data. A total of 10 mutated DRGs were screened out. Two DRGs subtypes were identified, namely subtype A and subtype B. The overall survival of PC patients with subtype A was better than that of patients with subtype B (χ2=8.316, P=0.003). The abundance of immune cell infiltration in the PC patients with subtype A was higher and mainly enriched in the metabolic and conduction related pathways as compaired with the patients with subtype B. The mean risk score of 177 patients with PC was 1.921, including 157 cases in the high-risk group and 20 cases in the low-risk group. The risk score of patients with subtype B was higher than that of patients with subtype A (t=14.031, P<0.001). The overall survival of the low-risk group was better than that of the high-risk group (χ2=17.058, P<0.001), and the TMB value of the PC patients with high-risk was higher than that of the PC patients with low-risk (t=5.642, P=0.014). The mean TMB of 161 patients with somatic mutation data was 2.767, including 128 cases in the high-TMB group and 33 cases in the low-TMB group. The overall survival of patients in the high-TMB group was worse than that of patients in the low-TMB group (χ2=7.425, P=0.006). ConclusionDRGs are closely related to the prognosis and immunotherapy response of patients with PC, and targeted treatment of DRGs might potentially provide a new idea for the diagnosis and treatment of PC.
Objective To explore the role and clinical significance of cell-cycle dependent kinase 1 (CDK1) and its upstream and downstream molecules in the development of malignant peripheral nerve sheath tumor (MPNST) through the analysis of clinical tissue samples. Methods A total of 56 tumor samples from MPNST patients (“Tianjin” dataset) who underwent surgical resection, confirmed by histology and pathology between September 2011 and March 2020, along with 17 normal tissue samples, were selected as the research subjects. MPNST-related hub genes were identified through transcriptome sequencing, bioinformatics analysis, immunohistochemistry staining, and survival analysis, and their expression levels and prognostic associations were analyzed. Results Transcriptome sequencing and bioinformatics analysis revealed that upregulated genes in MPNST were predominantly enriched in cell cycle-related pathways, with CDK1 occupying a central position among all differentially expressed genes. Further differential analysis demonstrated that CDK1 mRNA expression in sarcoma tissues was significantly higher than in normal tissues [based on searching the cancer genome atlas (TCGA) dataset, P<0.05]. In MPNST tissues, CDK1 mRNA expression was not only significantly higher than in normal tissues (based on Tianjin, GSE141438 datasets, P<0.05), but also significantly higher than in neurofibromatosis (NF) and plexiform neurofibromas (PNF) (based on GSE66743 and GSE145064 datasets, P<0.05). Immunohistochemical staining results indicated that the expression rate of CDK1 protein in MPNST tissues was 40.31%. Survival analysis results demonstrated that CDK1 expression was associated with poor prognosis. The survival time of MPNST patients with high CDK1 mRNA expression was significantly lower than that of the low expression group (P<0.05), and the overall survival trend of patients with positive CDK1 protein expression was worse than that of patients with negative CDK1 expression. Additionally, differential analysis of CDK family genes (CDK1-8) revealed that only CDK1 was significantly upregulated in MPNST, NF, and PNF. Conclusion Increased expression of CDK1 is associated with poor prognosis in MPNST patients. Compared to other CDK family members, CDK1 exhibits a unique expression pattern, suggesting its potential as a therapeutic target for MPNST.