ObjectiveTo analyze the expression and clinical significance of cyclin-dependent kinase 1 (CDK1) in lung adenocarcinoma by bioinformatics.MethodsBased on the gene expression data of lung adenocarcinoma patients in The Cancer Genome Atlas (TCGA), the differential expression of CDK1 in lung adenocarcinoma tissues and normal lung tissues was analyzed. The expression of CDK1 gene in lung adenocarcinoma was analyzed by UALCAN at different angles. Survival analysis of different levels of CDK1 gene expression in lung adenocarcinoma was performed using Kaplan-Meier Plotter. Correlation Cox analysis of CDK1 expression and overall survival was based on clinical data of lung adenocarcinoma in TCGA. Gene set enrichment analysis was performed on gene sequences related to CDK1 expression in clinical cases. The protein interaction network of CDK1 from Homo sapiens was obtained by STRING. CDK1-related gene proteins were obtained and analyzed by the web server Gene Expression Profiling Interactive Analysis (GEPIA).ResultsBased on the analysis of TCGA gene expression data, CDK1 expression in lung adenocarcinoma was higher than that in normal lung tissues. UALCAN analysis showed that high CDK1 expression may be associated with smoking. Survival analysis indicated that when CDK1 gene was highly expressed, patients with lung adenocarcinoma had a poor prognosis. Univariate and multivariate Cox regression analysis of CDK1 expression and overall survival showed that high CDK1 expression was an independent risk factor for survival of patients with lung adenocarcinoma. Gene set enrichment analysis revealed that high CDK1 expression was closely related to DNA replication, cell cycle, cancer pathway and p53 signaling pathway.ConclusionCDK1 may be a potential molecular marker for prognosis of lung adenocarcinoma. In addition, CDK1 regulation may play an important role in DNA replication, cell cycle, cancer pathway and p53 signaling pathway in lung adenocarcinoma.
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.
Objective To analyze the relationship between the expression of carbonic anhydrase 3 (CA3) in breast cancer tissues, its prognostic potential and the number of immune cells by a variety of online databases. Methods GEPIA2.0 and TIMER databases were used to analyze the difference of CA3 mRNA expression in breast cancer tissues. Bc-GenExMinerv4.7 database was used to analyze the difference of CA3 mRNA expression in breast cancer subcategories. Kaplan-Meier plotter, Bc-GenExMinerv4.7 and PrognoScan databases were used to analyze the effect of CA3 mRNA expression levels on prognosis of patient. LinkedOmics database was used to analyze of the biological behavior involved in CA3 co-expressed genes. TIMER database was used to analyze the relationship between CA3 mRNA expression and immune cells infiltration in breast cancer tissues. Results The expression of CA3 mRNA in breast cancer tissues was lower than that in normal breast tissues (P<0.05), and the expression levels of CA3 mRNA were higher in ER negative (P<0.05), PR negative (P<0.05), HER2 negative (P<0.05) and no lymphatic metastasis (P<0.05). In addition, the expression level of CA3 in breast cancer patients with high Ki67 expression was lower (P<0.05) and closely related to SBR and NPI grade (P<0.05). Breast cancer patients with low expression of CA3 mRNA had lower overall survivall, recurrence free survival, and disease free survival ( P<0.05). Ten of the top 50 positively correlated co-expressed genes screened out had low risk ratio (P<0.05), and 11 of the top 50 negatively correlated co-expressed genes screened out had high risk ratio (P<0.05). The expression of CA3 mRNA was positively correlated with CD4+ T cells and CD8+ T cells in breast cancer tissues (rs=0.175, P<0.001; rs=0.137, P<0.001), and negatively correlated with T cell failure markers LAG3, TIM-3 and PVRL2 (rs=–0.100, P<0.01; rs=–0.143, P<0.001; rs=–0.082, P<0.05). Conclusions The low expression of CA3 mRNA in breast cancer tissues is correlated with the occurrence, development and prognosis of breast cancer. CA3 can be used as a potential independent prognostic marker for breast cancer and may be related to immune infiltration.
Objective To explore the correlation and mechanism of ferroptosis with pulmonary fibrosis. Methods Pulmonary fibrosis tissue sequencing data were obtained from Gene Expression Omnibus and FerrDb databases from January 2019 to December 2023. Differentially expressed genes (DEGs) between the normal control group and the pulmonary fibrosis group were analyzed by bioinformatic method, and DEGs related to pulmonary iron addiction were extracted. The hub genes were screened by enrichment analysis, protein-protein interaction (PPI) analysis and random forest algorithm. The mouse model of pulmonary fibrosis was made for exercise intervention, and the expression of hub genes was verified by real-time quantitative reverse transcription polymerase chain reaction. Results A comparison of 103 patients with idiopathic pulmonary fibrosis and 103 normal lung tissues showed that 13 up-regulated genes and 7 down-regulated genes were identified as ferroptosis-related DEGs. PPI results showed that there was an interaction between these ferroptosis-related genes. The Kyoto Encyclopedia of Genes and Genomes pathway enrichment and Genome Ontology enrichment analysis showed that ferroptosis-related genes were involved in organic anion transport, hypoxia response, oxygen level reduction response, hypoxia-inducible factor-1 signaling pathway, renal cell carcinoma, and arachidonic acid metabolic signaling pathway. Genes identified by PPI analysis and random forest algorithm included CAV1, NOS2, GDF15, HNF4A, and CDKN2A. Real-time fluorescence quantitative polymerase chain reaction results of mouse fibrotic lung tissue showed that compared with the exercise group, the mRNA levels of NOS2, PTGS2 and GDF15 were up-regulated and the mRNA levels of CAV1 and CDKN2A were down-regulated in the bleomycin group (P<0.05); compared with the bleomycin group, the expression of CAV1 and CDKN2A increased and the expression of NOS2, PTGS2 and GDF15 decreased in the bleomycin + exercise group (P<0.05). Conclusions Bioinformatic analysis identifies 20 potential genes associating with ferroptosis in pulmonary fibrosis. CAV1, NOS2, GDF15, and CDKN2A influence the development of pulmonary fibrosis by modulating ferroptosis. Treadmill training can reduce ferroptosis in fibrotic tissues, thereby reducing lung inflammation.
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.
ObjectiveTo explore the functional heterogeneity of T lymphocytes in various organs after SARS-CoV-2 infection. Methods Using the public database GEO data (GSE171668, GSE159812, GSE159556, GSE167747) and the analysis method of single-cell technology, the functional differences of T lymphocytes in various organs of patients after infection with SARS-CoV-2 were analyzed. Results Through single-cell data extraction of 16 livers, 19 hearts,2 spleens, 6 brains, 58 lungs, 21 kidneys and 5 pancreases from SARS-CoV-2 infected patients, invasion genes were relatively highly expressed in T lymphocytes of the lung and pancreas. The lung had a special ability to express the interferon signaling pathway, while the expression of other organs was relatively low; at the same time, the T lymphocytes of the lung also highly expressed fatty acid binding sites. Conclusion After SARS-CoV-2 infection, compared with other organs, the lung has a special interferon-activated signaling pathway and fatty acid binding site.
Objective To screen the key genes in childhood therapy-resistant asthma by bioinformatic method, and to verify its expression and diagnostic value in peripheral blood of children with therapy-resistant asthma. Methods The transcriptome dataset GSE27011 of peripheral blood mononuclear cells from healthy children (healthy control group), mild asthma (MA) children (MA group) and severe asthma (SA) children (SA group) was downloaded from the Gene Expression Omnibus of the National Center for Biotechnology Information of the United States. Key genes were obtained by using R software for gene differential expression analysis, weighted gene co-expression network analysis (WGCNA) and clinical phenotypic correlation analysis. The differential expression levels of key genes were verified in children with asthma and immune cell transcriptome datasets. Seventy-eight children with asthma and 30 healthy children who were diagnosed in the Department of Pediatrics of Tangshan People’s Hospital between September 2020 and September 2021 were selected and divided into control group, MA group and SA group. Peripheral blood samples from children with asthma and healthy children who underwent physical examination were collected to detect the expression levels of key genes and inflammatory factors interleukin (IL)-4 and IL-17 in peripheral blood of children. Receiver operating characteristic curve was used to evaluate the sensitivity, specificity and accuracy of key genes in predicting childhood therapy-resistant asthma. Results The key gene GNA15 was obtained by bioinformatic analysis. Analysis of asthma validation dataset showed that GNA15 was up-regulated in asthma groups, and was specifically expressed in eosinophils. Clinical results showed that the expression levels of IL-4, IL-17 and GNA15 among the three groups were significantly different (P<0.05). The expression levels of IL-4 and IL-17 in the MA group and the SA group were higher than those in the control group (P<0.05). Compared with the control group and the MA group, the expression level of GNA15 in the SA group was up-regulated (P<0.05). Neither the difference in the expression level of IL-4 or IL-17 between the MA group and the SA group, nor the difference in the expression level of GNA15 between the control group and the MA group was statistically significant (P>0.05). The specificity, sensitivity and accuracy of GNA15 in predicting SA were 92.90%, 80.00% and 86.10%, respectively. Conclusion GNA15 has a significant clinical value in predicting the childhood therapy-resistant asthma, and may become a potential diagnostic marker for predicting the severity of asthma in children.
ObjectiveTo investigate differentially expressed genes (DEGs) and potential molecular mechanisms between hepatitis C-related hepatocellular carcinoma (HCV-HCC) and hepatitis B-related HCC (HBV-HCC). MethodsThe data of HCV-HCC and HBV-HCC gene expressions were downloaded and integrated from the public gene expression database, and the limma package was used to investigate the DEGs between the HCV-HCC and HBV-HCC samples. The gene set enrichment analysis (GSEA) was used to explore the differences in suppressed or activated gene sets between the HCV-HCC and HBV-HCC samples, and the MCODE was used to explore the key molecular modules, and then the potential biological processes and molecular pathways of the key molecular modules were analyzed. The effect of key genes on survival of the HCC patients was analyzed by the Kaplan-Meier-Plotter database.ResultsIn this study, 119 HBV-HCC samples and 163 HCV-HCC samples were obtained, and the 199 DEGs were screened out. Compared with HBV-HCC, the activated gene sets of HCV-HCC were mainly enriched in the gene sets of inflammation, complement, up-regulation of genes in response to interferon, up-regulation of genes in response to KRAS, genes regulated by the nuclear factor- κB-tumor necrosis factor pathway, and apoptosis. However, the cell cycle-related gene sets were obviously suppressed. Eight key molecular modules enriched by DEGs were found, which included 18 key genes (IFI27, DDX60, MX1, IRF9, OAS3, OAS1, RSAD2, GBP4, HERC6, ISG15, IFIT1, CMPK2, EPSTI1, IFI44, IFI44L, HERC5, IFITM1, CXCL10). GO analysis showed that the biological process was mainly concentrated in the body response related to virus infection, the molecular component was mainly in the host cells, and the molecular function was mainly enriched in the biological combination. KEGG analysis showed that the key genes were mainly involved in the molecular signaling pathway related to virus infection. The survival analysis showed that the 9 key genes (CXCL10, HERC6, DDX60, IFITM1, IFI27, GBP4, IFI44L, IFI44, MX1) were closely related to better prognosis of patients with HCC (HR<1, P<0.05). ConclusionsThere is an essential difference between HBV-HCC and HCV-HCC. Occurrence of HCV-HCC is mainly related to virus infection and immune response induced by the virus. Therefore, for HCV infection, active antiviral treatment is necessary for avoiding hepatitis turning into chronic viral infection and preventing or blocking HCV infection converting to HCC.
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.
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.