The exact mechanisms associated with secondary brain damage following traumatic brain injury(TBI)remain unclear;therefore,identifying the critical molecular mechanisms involved in TBI is essential.The m RNA expression...The exact mechanisms associated with secondary brain damage following traumatic brain injury(TBI)remain unclear;therefore,identifying the critical molecular mechanisms involved in TBI is essential.The m RNA expression microarray GSE2871 was downloaded from the Gene Expression Omnibus(GEO)repository.GSE2871 comprises a total of 31 cerebral cortex samples,including two post-TBI time points.The microarray features eight control and seven TBI samples,from 4 hours post-TBI,and eight control and eight TBI samples from 24 hours post-TBI.In this bioinformatics-based study,109 and 66 differentially expressed genes(DEGs)were identified in a Sprague-Dawley(SD)rat TBI model,4 and 24 hours post-TBI,respectively.Functional enrichment analysis showed that the identified DEGs were significantly enriched in several terms,such as positive regulation of nuclear factor-κB transcription factor activity,mitogen-activated protein kinase signaling pathway,negative regulation of apoptotic process,and tumor necrosis factor signaling pathway.Moreover,the hub genes with high connectivity degrees were primarily related to inflammatory mediators.To validate the top five hub genes,a rat model of TBI was established using the weight-drop method,and real-time quantitative polymerase chain reaction analysis of the cerebral cortex was performed.The results showed that compared with control rats,Tnf-α,c-Myc,Spp1,Cxcl10,Ptprc,Egf,Mmp9,and Lcn2 were upregulated,and Fn1 was downregulated in TBI rats.Among these hub genes,Fn1,c-Myc,and Ptprc may represent novel biomarkers or therapeutic targets for TBI.These identified pathways and key genes may provide insights into the molecular mechanisms of TBI and provide potential treatment targets for patients with TBI.This study was approved by the Experimental Animal Ethics Committee of the First Affiliated Hospital of Nanchang University,China(approval No.003)in January 2016.展开更多
AIM:To explore hub genes for glaucoma based on bioinformatics analysis and an experimental model verification.METHODS:In the Gene Expression Omnibus(GEO)database,the GSE25812 and GSE26299 datasets were selected to ana...AIM:To explore hub genes for glaucoma based on bioinformatics analysis and an experimental model verification.METHODS:In the Gene Expression Omnibus(GEO)database,the GSE25812 and GSE26299 datasets were selected to analyze differentially expressed genes(DEGs)by the GEO2R tool.Through bioinformatics analysis,9 hub genes were identified.Receiver operating characteristic(ROC)curves and principal component analysis(PCA)were performed to verify whether the hub gene can distinguish glaucoma from normal eyes.The mouse model of glaucoma was constructed,and the real-time reverse transcriptasepolymerase chain reaction(RT-q PCR)assay was performed to detect the expression levels of hub genes in glaucoma.RESULTS:There were 128 overlapping DEGs in the GSE25812 and GSE26299 datasets,mainly involved in intracellular signalling,cell adhesion molecules and the Ras signalling pathway.A total of 9 hub genes were screened out,including GNAL,BGN,ETS2,FCGP4,MAPK10,MMP15,STAT1,TSPAN8,and VCAM1.The area under the curve(AUC)values of 9 hub genes were greater than 0.8.The PC1 axle could provide a 70.5%interpretation rate to distinguish glaucoma from normal eyes.In the ocular tissues of glaucoma in the mice model,the expression of BGN,ETS2,FCGR4,STAT1,TSPAN8,and VCAM1 was increased,while the expression of GNAL,MAPK10,and MMP15 was decreased.CONCLUSION:Nine hub genes in glaucoma are identified,which may provide new biomarkers and therapeutic targets for glaucoma.展开更多
Peripheral T-cell lymphoma(PTCL)is a very aggressive and heterogeneous hematological malignancy and has no effective targeted therapy.The molecular pathogenesis of PTCL remains unknown.In this study,we chose the gene ...Peripheral T-cell lymphoma(PTCL)is a very aggressive and heterogeneous hematological malignancy and has no effective targeted therapy.The molecular pathogenesis of PTCL remains unknown.In this study,we chose the gene expression profile of GSE6338 from the Gene Expression Omnibus(GEO)database to identify hub genes and key pathways and explore possible molecular pathogenesis of PTCL by bioinformatic analysis.Diferentially expressed gencs(DEGs)between PTCL and normal T cells were selected using GEO2R tool.Gene ontology(GO)analysis and Kyoto Encyclopedia of Gene and Genome(KEGG)pathway analysis were performed using Database for Annotation,Visualization and Integrated Discovery(DAVID).Moreover,the Search Tool for the Retrieval of Interacting Genes(STRING)and Molecular Complex Detection(MCODE)were utilized to construct protein-protein interaction(PPI)network and perform module analysis of these DEGs.A total of 518 DEGs were identifed,including 413 down-regulated and 105 up-regulated gencs.The down-regulated genes were enriched in osteoclast differentiation,Chagas disease and mitogen-activated protein kinase(MAPK)signaling pathway.The up-regulated genes were mainly associated with extracellular matrix(ECM)-receptor interaction,focal adhesion and pertussis.F our important modules were detected from the PPI network by using MCODE software.Fifteen hub genes with a high degree of connectivity were selected.Our study identifed DEGs,hub genes and pathways associated with PTCL by bioinformatic analysis.Results provide a basis for further study on the pathogenesis of PTCL.展开更多
BACKGROUND Helicobacter pylori(H.pylori)infection is related to various extragastric diseases including type 2 diabetes mellitus(T2DM).However,the possible mechanisms connecting H.pylori infection and T2DM remain unkn...BACKGROUND Helicobacter pylori(H.pylori)infection is related to various extragastric diseases including type 2 diabetes mellitus(T2DM).However,the possible mechanisms connecting H.pylori infection and T2DM remain unknown.AIM To explore potential molecular connections between H.pylori infection and T2DM.METHODS We extracted gene expression arrays from three online datasets(GSE60427,GSE27411 and GSE115601).Differentially expressed genes(DEGs)commonly present in patients with H.pylori infection and T2DM were identified.Hub genes were validated using human gastric biopsy samples.Correlations between hub genes and immune cell infiltration,miRNAs,and transcription factors(TFs)were further analyzed.RESULTS A total of 67 DEGs were commonly presented in patients with H.pylori infection and T2DM.Five significantly upregulated hub genes,including TLR4,ITGAM,C5AR1,FCER1G,and FCGR2A,were finally identified,all of which are closely related to immune cell infiltration.The gene-miRNA analysis detected 13 miRNAs with at least two gene cross-links.TF-gene interaction networks showed that TLR4 was coregulated by 26 TFs,the largest number of TFs among the 5 hub genes.CONCLUSION We identified five hub genes that may have molecular connections between H.pylori infection and T2DM.This study provides new insights into the pathogenesis of H.pylori-induced onset of T2DM.展开更多
Introduction:The difficulty in treating lung adenocarcinoma(LUAD)is caused by a shortage of knowledge about the biological mechanisms and a lack of treatment choices.Objectives:The aim of this study was to identify a ...Introduction:The difficulty in treating lung adenocarcinoma(LUAD)is caused by a shortage of knowledge about the biological mechanisms and a lack of treatment choices.Objectives:The aim of this study was to identify a valuable molecular target for the treatment of LUAD.Methods:Using multiple databases,we screened for hub genes in LUAD using Cytoscape and explored the expression and prognosis of DLG associated protein 5(DLGAP5)in LUAD.We investigated the genetic variation,functional enrichment,and epigenetic activity of DLGAP5.Furthermore,we evaluated the relationship between the tumor microenvironment(TME)and DLGAP5.Results:Our study identified 10 hub genes in LUAD:CDC45,KIAA0101,DLGAP5,CDT1,NCAPG,CCNB1,CDCA5,CDC20,KIF11,and AURKA.We discovered that DLGAP5 was overexpressed and associated with poor prognosis in LUAD.DLGAP5 exhibited an overall genetic variation frequency of 2%,and its DNA promoter was hypomethylated in LUAD(p<0.05).The expression of DLGAP5 in LUAD showed a positive correlation with the majority of N6-methyladenosine(m6A)-methylation genes.Additionally,DLGAP5 was primarily associated with the cell cycle in LUAD.Notably,there was a significant favorable association between DLGAP5 and CD274,CTLA4,HAVCR2,and LAG3 in LUAD.Conclusion:DLGAP5 may be a therapeutic target for LUAD,as it affects cancer cells proliferation and development through the regulation of cell-cycle checkpoints and modulation of immune cell infiltration and immune checkpoints in the TME.展开更多
BACKGROUND The identification of specific gene expression patterns is crucial for understanding the mechanisms underlying primary biliary cholangitis(PBC)and finding relevant biomarkers for diagnosis and therapeutic e...BACKGROUND The identification of specific gene expression patterns is crucial for understanding the mechanisms underlying primary biliary cholangitis(PBC)and finding relevant biomarkers for diagnosis and therapeutic evaluation.AIM To determine PBC-associated hub genes and assess their clinical utility for disease prediction.METHODS PBC expression data were obtained from the Gene Expression Omnibus database.Overlapping genes from differential expression analysis and weighted gene coexpression network analysis(WGCNA)were identified as key genes for PBC.Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were performed to explore the potential roles of key genes.Hub genes were identified in protein-protein interaction(PPI)networks using the Degree algorithm in Cytoscape software.The relationship between hub genes and immune cells was investigated.Finally,a Mendelian randomization study was conducted to determine the causal effects of hub genes on PBC.RESULTS We identified 71 overlapping key genes using differential expression analysis and WGCNA.These genes were primarily enriched in pathways related to cytokinecytokine receptor interaction,and Th1,Th2,and Th17 cell differentiation.We utilized Cytoscape software and identified five hub genes(CD247,IL10,CCL5,CCL3,and STAT3)in PPI networks.These hub genes showed a strong correlation with immune cell infiltration in PBC.However,inverse variance weighting analysis did not indicate the causal effects of hub genes on PBC risk.CONCLUSION Hub genes can potentially serve as valuable biomarkers for PBC prediction and treatment,thereby offering significant clinical utility.展开更多
<strong>Objective:</strong><span style="font-family:""><span style="font-family:Verdana;"> This study aimed to identify hub genes that are associated with hepatocellula...<strong>Objective:</strong><span style="font-family:""><span style="font-family:Verdana;"> This study aimed to identify hub genes that are associated with hepatocellular carcinoma (HCC) prognosis by bioinformatics analysis. </span><b><span style="font-family:Verdana;">Methods:</span></b><span style="font-family:Verdana;"> Data were collected from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) liver HCC datasets. </span><a name="_Hlk11768117"></a><span style="font-family:Verdana;">The robust rank ag</span><span style="font-family:Verdana;">gregation algorithm was used in integrating the data on differentially ex</span><span style="font-family:Verdana;">pressed genes (DEGs). Online databases DAVID 6.8 and REACTOME were used for </span><span style="font-family:Verdana;">gene ontology and pathway enrichment analysis. R software version 3.5.1, </span><span style="font-family:Verdana;">Cytoscape, and Kaplan-Meier plotter were used to identify hub genes. </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> Six GEO datasets and the TCGA liver HCC dataset were included in this analysis. A total of 151 upregulated and 245 downregulated DEGs were iden</span><span style="font-family:Verdana;">tified. The upregulated DEGs most significantly enriched in the functional</span><span style="font-family:Verdana;"> categories of cell division, chromosomes, centromeric regions, and </span><span style="font-family:Verdana;">protein binding, whereas the downregulated DEGs most significantly</span><span style="font-family:Verdana;"> enriched in the </span><a name="_Hlk11059934"></a><span style="font-family:Verdana;">epoxygenase P450 pathway, extracellular region, and heme binding, with respect to biological process, cellular component, and molecular function analysis, respectively. Upregulated DEGS most significantly enriched the cell cycle pathway, whereas downregulated DEGs most significantly enriched </span><span style="font-family:Verdana;">the metabolism pathway. Finally, 88 upregulated and 40 downregulated genes were </span><span><span style="font-family:Verdana;">identified as hub genes. The top 10 upregulated hub DEGs were </span><i><span style="font-family:Verdana;">CDK</span></i><span style="font-family:Verdana;">1,</span></span><i><span style="font-family:Verdana;"> CCNB</span></i><span><span style="font-family:Verdana;">1,</span><i><span style="font-family:Verdana;"> CCNB</span></i><span style="font-family:Verdana;">2,</span><i><span style="font-family:Verdana;"> CDC</span></i><span style="font-family:Verdana;">20,</span><i><span style="font-family:Verdana;"> CCNA</span></i><span style="font-family:Verdana;">2,</span><i><span style="font-family:Verdana;"> AURKA</span></i><span style="font-family:Verdana;">,</span><i><span style="font-family:Verdana;"> MAD</span></i><span style="font-family:Verdana;">2</span><i><span style="font-family:Verdana;">L</span></i><span style="font-family:Verdana;">1,</span><i><span style="font-family:Verdana;"> TOP</span></i><span style="font-family:Verdana;">2</span><i><span style="font-family:Verdana;">A</span></i><span style="font-family:Verdana;">,</span><i><span style="font-family:Verdana;"> BUB</span></i><span style="font-family:Verdana;">1</span><i><span style="font-family:Verdana;">B </span></i><span style="font-family:Verdana;">and</span></span><i> <span style="font-family:Verdana;">BUB</span></i><span><span style="font-family:Verdana;">1. The top 10 downregulated hub DEGs were </span><i><span style="font-family:Verdana;">ESR</span></i><span style="font-family:Verdana;">1,</span><i><span style="font-family:Verdana;"> IGF</span></i><span style="font-family:Verdana;">1,</span><i><span style="font-family:Verdana;"> FTCD</span></i><span style="font-family:Verdana;">,</span></span><i><span style="font-family:Verdana;"> CYP</span></i><span style="font-family:Verdana;">3</span><i><span style="font-family:Verdana;">A</span></i><span style="font-family:Verdana;">4,</span><i><span style="font-family:Verdana;"> SPP</span></i><span style="font-family:Verdana;">2,</span><i> <span style="font-family:Verdana;">C</span></i><span><span style="font-family:Verdana;">8</span><i><span style="font-family:Verdana;">A</span></i><span style="font-family:Verdana;">,</span><i><span style="font-family:Verdana;"> CYP</span></i><span style="font-family:Verdana;">2</span><i><span style="font-family:Verdana;">E</span></i><span style="font-family:Verdana;">1,</span><i><span style="font-family:Verdana;"> TAT</span></i><span style="font-family:Verdana;">,</span><i><span style="font-family:Verdana;"> F</span></i><span style="font-family:Verdana;">9 and </span><i><span style="font-family:Verdana;">CYP</span></i><span style="font-family:Verdana;">2</span><i><span style="font-family:Verdana;">C</span></i><span style="font-family:Verdana;">9. </span><b><span style="font-family:Verdana;">Conclusions:</span></b><span style="font-family:Verdana;"> This study identified</span></span><span style="font-family:Verdana;"> several upregulated and downregulated hub genes that are associated with the prognosis of HCC patients. Verification of these results using </span><i><span style="font-family:Verdana;">in vitro</span></i><span style="font-family:Verdana;"> and </span><i><span style="font-family:Verdana;">in vivo</span></i><span style="font-family:Verdana;"> studies is warranted.</span></span>展开更多
Objective:to screen the genes differentially expressed in autism using bioinformatics methods,and to explore their functional enrichment,related signaling pathways and the tissue-specific expression of hub genes.Metho...Objective:to screen the genes differentially expressed in autism using bioinformatics methods,and to explore their functional enrichment,related signaling pathways and the tissue-specific expression of hub genes.Methods:the autism expression profile chip numbered GSE77103 in the Gene Expression Omnibus(GEO)database was selected for examination.R language and related R packages were used for the screening and visualization of the diflerentially expressed genes.Gene Ontology(GO)function enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway analysis of the differential genes were carried out using the relevant R package of R language.The database STRING was used to construct the interaction network of the proteins encoded by the differentially expressed genes,and the software Cytoscape was used to screen the hub genes in the network.The selected hub genes were imported into the BioGPS database to analyze the tissue-specific expression of the hub genes.Results:six hundred and sixty diflerentially expressed genes were screened out.Three hundred and seventy-three up-regulated genes and 287 down-regulated genes in the peripheral blood mononuclear cells of autistic children were compared with the peripheral blood mononuclear cells of healthy children.GO functional enrichment results showed that biological processes(BP)were mainly involved in viral response,negative regulation of viral genome replication,negative regulation of multiple biological processes,negative reg ulation reg ulation of viral life cycle,and defense responses to viruses.Cell components(CC)were involved in vesicles,lysosomal membranes,lysosomal lumen,etc.;molecular functions(MF)were involved in regulating glutathione transferase activity peroxidase activity,oxidoreductase activity,Glutathione peroxidase and transferase activity,etc.The results of KEGG signaling pathway analysis showed that the differentially expressed genes were related to the lysosomal pathway,the glutathione metabolism pathway and the arachidonic acid metabolism pathway.The hub genes screened by cytoHubba were:interferon regulatory factor 7(IRF7),interferon stimulated exonuclease gene 15(ISG15),XIAP associated factor 1(XAF1),MX dynamin like GTPase 1(MX1),interferon induced protein with tetratricopeptide repeats 1(IFIT1),interferon induced protein with tetratricopeptide repeats 5(IFIT5),29-55-oligoadenylate synthetase 3(OAS3),interferon induced protein 44(IFI44),HECT and the RLD domain containing E3 ubiquitin protein ligase 5(HERC5),interferon stimulated exonuclease gene 20(ISG20).Conclusion:there are genes that are diflerentially expressed in the peripheral blood mononuclear cells of autistic toddlers and healthy toddlers.IRF7,ISG15,XAF1,MX],IFIT1,IFIT5,OAS3,IFI44,HERC5,ISG20 are the hub regulatory genes of autism.展开更多
Objective:To identify the thyroid cancer-related hub genes and pathways by bioinformatics initially in order to lay the foundation for further study.Methods:The expression profile chips and data of thyroid cancer were...Objective:To identify the thyroid cancer-related hub genes and pathways by bioinformatics initially in order to lay the foundation for further study.Methods:The expression profile chips and data of thyroid cancer were screened and downloaded from the gene expression omnibus(GEO).The GEO2R was applied to identify the differential expressed genes between thyroid cancer tissues and normal thyroid tissues.And the Metascape online website was used for pathway and function enrichment.With the usage of STRING and Cytoscape,the protein-protein interaction network was constructed,and the plug-in app cytoHubba in Cytoscape was applied to screen hub genes.Kaplan-Meier Plotter was implemented to conduct survival analysis of hub genes for further screening and discussion.Results:A total of 304 differential expressed genes were screened,and were mainly enriched in the biological processes of extracellular matrix,cell-substrate adhesion,response to wounding,muscle structure development and hormone metabolic process etc.by Metascape.Protein-protein interaction network visualized 284 nodes;the top ten scores of Maximal Clique Centrality algorithm were taken as the criteria to screen out the hub genes with high connectivity in the gene expression network.The KM plotter analysis confirmed that 5 of 9 hub genes were correlated with the prognosis of thyroid cancer patients.Conclusion:FN1,SPP1,TIMP1,VCAN,COL1A1,COL1A2,MMP1,DCN,COMP and FMOD may play a significant role in the development of thyroid cancer.Genes which have prognostic significance in survival analyses were found to be relevant to the composition and regulation of extracellular matrix.展开更多
Background:Cold exposure is linked to numerous diseases,yet the changes in key genes and pathways in mice under cold exposure remain unexplored.Understanding these alterations could offer insights into the mechanisms ...Background:Cold exposure is linked to numerous diseases,yet the changes in key genes and pathways in mice under cold exposure remain unexplored.Understanding these alterations could offer insights into the mechanisms of cold resistance and contribute valuable ideas for treating cold-related diseases.Methods:The dataset GSE148361 was obtained from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were identified using the"limma"package in R software.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analyses were performed on DEGs.The STRING(Search Tool for the Retrieval of Interacting Genes)database was used to construct a protein-protein interaction(PPI)network.Additionally,gene set enrichment analysis(GSEA)was conducted to identify pathways associated with key genes.miRNAs and upstream transcription factors(TFs)were predicted using the miRNet database.Results:A total of 208 DEGs were identified,with 137 upregulated and 71 downregulated.In biological processes,DEGs were enriched in nucleotide and purine-containing compound metabolism.For cellular components,DEGs were involved in condensed chromosomes and mitochondrial protein complexes.In molecular functions,proton transmembrane transporter activity was enriched.KEGG pathway analysis showed significant enrichment in biosynthesis of unsaturated fatty acids,fatty acids,and pyruvate metabolism.From the PPI network,12 hub genes were identified using MCODE.Four hub genes(Col3a1,Ifi203,Rtp4,Vcan)demonstrated similar trends in a validation set(GSE110420)and were significantly differentially expressed.GSEA analysis indicated that these four genes were enriched in pathways such as ECM-receptor interaction and cytokine-cytokine receptor interaction.The hub gene network included 93 miRNAs and one TF.Conclusion:This study identified four hub genes as potential diagnostic biomarkers for cold exposure,providing insights for further research on the effects of cold on gene expression and disease.展开更多
BACKGROUND Breast cancer(BC)is the most common malignant tumor in women.AIM To investigate BC-associated hub genes to obtain a better understanding of BC tumorigenesis.METHODS In total,1203 BC samples were downloaded ...BACKGROUND Breast cancer(BC)is the most common malignant tumor in women.AIM To investigate BC-associated hub genes to obtain a better understanding of BC tumorigenesis.METHODS In total,1203 BC samples were downloaded from The Cancer Genome Atlas database,which included 113 normal samples and 1090 tumor samples.The limma package of R software was used to analyze the differentially expressed genes(DEGs)in tumor tissues compared with normal tissues.The cluster Profiler package was used to perform Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis of upregulated and downregulated genes.Univariate Cox regression was conducted to explore the DEGs with statistical significance.Protein-protein interaction(PPI)network analysis was employed to investigate the hub genes using the CytoHubba plug-in of Cytoscape software.Survival analyses of the hub genes were carried out using the Kaplan-Meier method.The expression level of these hub genes was validated in the Gene Expression Profiling Interactive Analysis database and Human Protein Atlas database.RESULTS A total of 1317 DEGs(fold change>2;P<0.01)were confirmed through bioinformatics analysis,which included 744 upregulated and 573 downregulated genes in BC samples.KEGG enrichment analysis indicated that the upregulated genes were mainly enriched in the cytokine-cytokine receptor interaction,cell cycle,and the p53 signaling pathway(P<0.01);and the downregulated genes were mainly enriched in the cytokine-cytokine receptor interaction,peroxisome proliferator-activated receptor signaling pathway,and AMP-activated protein kinase signaling pathway(P<0.01).CONCLUSION In view of the results of PPI analysis,which were verified by survival and expression analyses,we conclude that MAD2L1,PLK1,SAA1,CCNB1,SHCBP1,KIF4A,ANLN,and ERCC6L may act as biomarkers for the diagnosis and prognosis in BC patients.展开更多
Traumatic brain injury(TBI)is a common injury caused by external forces that lead to damaged brain function or pathological changes in the brain tissue.To explore the molecular mechanism and the hub genes of TBI,we do...Traumatic brain injury(TBI)is a common injury caused by external forces that lead to damaged brain function or pathological changes in the brain tissue.To explore the molecular mechanism and the hub genes of TBI,we downloaded gene expression profiles of the TBI model of rat and the sham control for the subsequent gene set enrichment analysis,pathway analysis and protein-protein interactions analysis.The results of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis indicated that multiple biological pathways,including immune response,inflammatory response and cellular response to interleukin-1,as well as signaling pathways,such as tumor necrosis factor signaling pathway,chcmokine signaling pathway,cytokine-cytokine receptor interaction,Toll-like receptor signaling pathway and nuclear factor kappa B signaling pathway were implicated in the TBI.In conclusion,this study provides insights into the molecular mechanism of TBI by screening the differentially expressed genes and hub genes that can be used as biomarkers and therapeutic targets.展开更多
This study was conducted to elucidate the potential key candidate genes and pathways in role of astrocyte involved in glaucoma with ocular hypertension.Methods Expression profiles GSE2378 and GSE758 including 27 react...This study was conducted to elucidate the potential key candidate genes and pathways in role of astrocyte involved in glaucoma with ocular hypertension.Methods Expression profiles GSE2378 and GSE758 including 27 reactive optic nerve head astrocytes(ONHAs)by hypertensions and 26 normal controls,were integrated and deeply analyzed.Differentially expressed genes(DEGs)were sorted and candidate genes and pathways enrichment were analyzed.DEGs-associated protein-protein interaction network(PPI)was performed.Results A total of 119 consistently expressed genes were identified from 281 commonly changed DEGs,including 68 up-regulated genes and 51 down-regulated genes.PPI network complex filtered 75 DEGs(43 up-regulated and 32 down-regulated genes)of the 119 consistently altered DEGs and developed 117 edges,and 10 hub genes were identified.The most significant 3 modules were filtered from PPI,pathway enrichment analysis showed that module 1 was associated with extracellular exosome.Module 2 was mainly associated with antibody-dependent cellular cytotoxicity(ADCC)and module 3 was mainly associated with Hippo signaling pathway.Conclusion Taken above,using integrated bioinformatical analysis,we have identified DEGs candidate genes and pathways in role of astrocyte involved in glaucoma with ocular hypertension,which could improve our understanding of the cause and underlying molecular events,and these candidate genes and pathways could be therapeutic targets for glaucoma.展开更多
Alzheimer’s disease(AD)remains clinically incurable,raising a significant public health issue,particularly with its continuously increased incidence.1 Inflammatory bowel disease,including ulcerative colitis and Crohn...Alzheimer’s disease(AD)remains clinically incurable,raising a significant public health issue,particularly with its continuously increased incidence.1 Inflammatory bowel disease,including ulcerative colitis and Crohn’s disease(CD),is characterized by long-standing inflammation and immunological imbalance of the gastrointestinal system.2 Recent epidemiological studies suggest a link between increased AD risk and inflammatory bowel disease.展开更多
IMP （inosine 5＇-monophosphate） is a compound that enhances the flavor of poultry meat. IMP has become a new breeding trait to improve poultry meat quality. We tried to identify several potential regulatory genes, a...IMP （inosine 5＇-monophosphate） is a compound that enhances the flavor of poultry meat. IMP has become a new breeding trait to improve poultry meat quality. We tried to identify several potential regulatory genes, and construct their predicted regulatory relationships. Time series gene expression profiles of thigh muscle tissues of Rugao chicken, a famous indigenous breed in China, were performed for analysis of genes that are co-expressed or correlated with the concentration of IMP. We found 15 crucial co-expression genes, which are Hspa2, Pten, Gabpa, Bpi, Mkll, Srf,, Cd34, Hspa4, EtvS, Bmpr2, Gdel, IgfbpS, Cd28, Pecam1 and Gja1, that may directly or indirectly regulate IMP metabolism. Eventually, we computed the correlation coefficient between 19 IMP Genes and 15 CGs （15 co-expression genes）, and we identified and constructed a predicted regulation network. In conclusion, variation of IMP concentration was primarily connected with the muscle development process. During this process, 15 CGs were identified that may have significant influence on IMP metabolism. In particular, Bmpr2, Pten and co-expression genes correlated with Entpd8 might play important roles in regulating IMP de novo synthesis, decomposition and salvage synthesis.展开更多
Peripheral nerve injury repair requires a certain degree of cooperation between axon regeneration and Wallerian degeneration.Therefore,investigating how axon regeneration and degeneration work together to repair perip...Peripheral nerve injury repair requires a certain degree of cooperation between axon regeneration and Wallerian degeneration.Therefore,investigating how axon regeneration and degeneration work together to repair peripheral nerve injury may uncover the molecular mechanisms and signal cascades underlying peripheral nerve repair and provide potential strategies for improving the low axon regeneration capacity of the central nervous system.In this study,we applied weighted gene co-expression network analysis to identify differentially expressed genes in proximal and distal sciatic nerve segments from rats with sciatic nerve injury.We identified 31 and 15 co-expression modules from the proximal and distal sciatic nerve segments,respectively.Functional enrichment analysis revealed that the differentially expressed genes in proximal modules promoted regeneration,while the differentially expressed genes in distal modules promoted neurodegeneration.Next,we constructed hub gene networks for selected modules and identified a key hub gene,Kif22,which was up-regulated in both nerve segments.In vitro experiments confirmed that Kif22 knockdown inhibited proliferation and migration of Schwann cells by modulating the activity of the extracellular signal-regulated kinase signaling pathway.Collectively,our findings provide a comparative framework of gene modules that are co-expressed in injured proximal and distal sciatic nerve segments,and identify Kif22 as a potential therapeutic target for promoting peripheral nerve injury repair via Schwann cell proliferation and migration.All animal experiments were approved by the Institutional Animal Ethics Committee of Nantong University,China(approval No.S20210322-008)on March 22,2021.展开更多
Proanthocyanidin(PA)is an important bioactive compound with multiple physiological benefits in jujube(Ziziphus jujube Mill.).However,the molecular mechanisms underlying PA biosynthesis in jujube fruit have not been in...Proanthocyanidin(PA)is an important bioactive compound with multiple physiological benefits in jujube(Ziziphus jujube Mill.).However,the molecular mechanisms underlying PA biosynthesis in jujube fruit have not been investigated.Here,the profiling of PA,(+)-catechin and(–)-epicatechin and transcriptome sequencing of three jujube cultivars from Xinjiang Uyghur Autonomous Region of China at five developmental stages were analyzed.The levels of total PAs and catechin exhibited a decreased trend over jujube ripening,and epicatechin content of two jujube cultivars increased first and then declined.Transcriptome analysis revealed that the differentially expressed genes(DEGs)were mainly enriched in ribosome,glycolysis/gluconeogenesis,fructose and mannose metabolism.17 DEGs encoding PAL,CHS,CHI,CHS,F3'H,LAR,ANR,C4Hs,4CLs,FLSs,DFRs and UFGTs involved in PA biosynthesis were relatively abundant.The highly transcribed LAR gene may greatly contribute to epicatechin accumulation.A weighted gene co-expression network analysis(WGCNA)was performed,and a network module including 1620 genes highly correlated with content of Pas and catechin was established.We identified 58 genes including 9 structural genes and 49 regulatory genes related to PA biosynthesis and regulation in the WGCNA module.Sixteen genes encoding 9 families of transcriptional factors(i.e.,MYB,bHLH,ERF,bZIP,NAC,SBP,MIKC,HB,WRKY)were considered as hub genes.The results of qRT-PCR analysis validating 10 genes were well consistent with the transcriptome data.These findings provide valuable knowledge to facilitate its genetic studies and molecular breeding.展开更多
AIM:To prevent neovascularization in diabetic retinopathy(DR)patients and partially control disease progression.METHODS:Hypoxia-related differentially expressed genes(DEGs)were identified from the GSE60436 and GSE1024...AIM:To prevent neovascularization in diabetic retinopathy(DR)patients and partially control disease progression.METHODS:Hypoxia-related differentially expressed genes(DEGs)were identified from the GSE60436 and GSE102485 datasets,followed by gene ontology(GO)functional annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis.Potential candidate drugs were screened using the CMap database.Subsequently,a protein-protein interaction(PPI)network was constructed to identify hypoxia-related hub genes.A nomogram was generated using the rms R package,and the correlation of hub genes was analyzed using the Hmisc R package.The clinical significance of hub genes was validated by comparing their expression levels between disease and normal groups and constructing receiver operating characteristic curve(ROC)curves.Finally,a hypoxia-related miRNA-transcription factor(TF)-Hub gene network was constructed using the NetworkAnalyst online tool.RESULTS:Totally 48 hypoxia-related DEGs and screened 10 potential candidate drugs with interaction relationships to upregulated hypoxia-related genes were identified,such as ruxolitinib,meprylcaine,and deferiprone.In addition,8 hub genes were also identified:glycogen phosphorylase muscle associated(PYGM),glyceraldehyde-3-phosphate dehydrogenase spermatogenic(GAPDHS),enolase 3(ENO3),aldolase fructose-bisphosphate C(ALDOC),phosphoglucomutase 2(PGM2),enolase 2(ENO2),phosphoglycerate mutase 2(PGAM2),and 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3(PFKFB3).Based on hub gene predictions,the miRNA-TF-Hub gene network revealed complex interactions between 163 miRNAs,77 TFs,and hub genes.The results of ROC showed that the except for GAPDHS,the area under curve(AUC)values of the other 7 hub genes were greater than 0.758,indicating their favorable diagnostic performance.CONCLUSION:PYGM,GAPDHS,ENO3,ALDOC,PGM2,ENO2,PGAM2,and PFKFB3 are hub genes in DR,and hypoxia-related hub genes exhibited favorable diagnostic performance.展开更多
Bladder,kidney,prostate and testicular carcinoma are the top four genitourinary cancers in China.Here we analyzed mRNA and miRNA expression profiles of carcinomas of the bladder(TCC),kidney(ccRCC)and testis(TGCT)to un...Bladder,kidney,prostate and testicular carcinoma are the top four genitourinary cancers in China.Here we analyzed mRNA and miRNA expression profiles of carcinomas of the bladder(TCC),kidney(ccRCC)and testis(TGCT)to uncover their specific regulatory mechanisms.The gene expression profiles of GSE31617 were downloaded from GEO database,which contained 27 samples,including 10 TCC,7 TGCT and 10 ccRCC.Specific up-and downregulated differentially expressed genes(DEGs)and differentially expressed microRNAs(DEmiRNAs)of each cancer were selected and target genes of DEmiRNAs were predicted.Gene interaction network of the shared genes and target genes of DEmiRNAs of each cancer was predicted by STRING and constructed by Cytoscape.In each cancer,we build regulatory networks of hub genes selected and conducted GO analysis of enriched genes.Furthermore,we chose four hub genes(SALL4,RHEB,CDC42 and TNN)for survival analysis in OncoLnc database,and they all had effects on the survival rate of another genitourinary cancer-kidney renal clear cell carcinoma(KIRC).In conclusion,the present study indicated that the identified hub genes promote our understanding of molecular mechanisms underlying the development of three genitourinary cancers,and might be used as molecular targets and diagnostic biomarkers for the treatment of them.展开更多
基金supported by the National Natural Science Foundation of China,Nos.81860409(to ZF),81660382(to ZF)Graduate Students Innovation Fund Project in Jiangxi Province of China,No.YC2019-B036(to YLT)。
文摘The exact mechanisms associated with secondary brain damage following traumatic brain injury(TBI)remain unclear;therefore,identifying the critical molecular mechanisms involved in TBI is essential.The m RNA expression microarray GSE2871 was downloaded from the Gene Expression Omnibus(GEO)repository.GSE2871 comprises a total of 31 cerebral cortex samples,including two post-TBI time points.The microarray features eight control and seven TBI samples,from 4 hours post-TBI,and eight control and eight TBI samples from 24 hours post-TBI.In this bioinformatics-based study,109 and 66 differentially expressed genes(DEGs)were identified in a Sprague-Dawley(SD)rat TBI model,4 and 24 hours post-TBI,respectively.Functional enrichment analysis showed that the identified DEGs were significantly enriched in several terms,such as positive regulation of nuclear factor-κB transcription factor activity,mitogen-activated protein kinase signaling pathway,negative regulation of apoptotic process,and tumor necrosis factor signaling pathway.Moreover,the hub genes with high connectivity degrees were primarily related to inflammatory mediators.To validate the top five hub genes,a rat model of TBI was established using the weight-drop method,and real-time quantitative polymerase chain reaction analysis of the cerebral cortex was performed.The results showed that compared with control rats,Tnf-α,c-Myc,Spp1,Cxcl10,Ptprc,Egf,Mmp9,and Lcn2 were upregulated,and Fn1 was downregulated in TBI rats.Among these hub genes,Fn1,c-Myc,and Ptprc may represent novel biomarkers or therapeutic targets for TBI.These identified pathways and key genes may provide insights into the molecular mechanisms of TBI and provide potential treatment targets for patients with TBI.This study was approved by the Experimental Animal Ethics Committee of the First Affiliated Hospital of Nanchang University,China(approval No.003)in January 2016.
基金Supported by Research Fund of Anhui Institute of Translational Medicine(No.2022zhyx-C73)。
文摘AIM:To explore hub genes for glaucoma based on bioinformatics analysis and an experimental model verification.METHODS:In the Gene Expression Omnibus(GEO)database,the GSE25812 and GSE26299 datasets were selected to analyze differentially expressed genes(DEGs)by the GEO2R tool.Through bioinformatics analysis,9 hub genes were identified.Receiver operating characteristic(ROC)curves and principal component analysis(PCA)were performed to verify whether the hub gene can distinguish glaucoma from normal eyes.The mouse model of glaucoma was constructed,and the real-time reverse transcriptasepolymerase chain reaction(RT-q PCR)assay was performed to detect the expression levels of hub genes in glaucoma.RESULTS:There were 128 overlapping DEGs in the GSE25812 and GSE26299 datasets,mainly involved in intracellular signalling,cell adhesion molecules and the Ras signalling pathway.A total of 9 hub genes were screened out,including GNAL,BGN,ETS2,FCGP4,MAPK10,MMP15,STAT1,TSPAN8,and VCAM1.The area under the curve(AUC)values of 9 hub genes were greater than 0.8.The PC1 axle could provide a 70.5%interpretation rate to distinguish glaucoma from normal eyes.In the ocular tissues of glaucoma in the mice model,the expression of BGN,ETS2,FCGR4,STAT1,TSPAN8,and VCAM1 was increased,while the expression of GNAL,MAPK10,and MMP15 was decreased.CONCLUSION:Nine hub genes in glaucoma are identified,which may provide new biomarkers and therapeutic targets for glaucoma.
基金The study was supported by grants from the National Natural Science Foundation of China(No.81660036)the Project of the Bingtuan Science and Technology(No.2019DB012).
文摘Peripheral T-cell lymphoma(PTCL)is a very aggressive and heterogeneous hematological malignancy and has no effective targeted therapy.The molecular pathogenesis of PTCL remains unknown.In this study,we chose the gene expression profile of GSE6338 from the Gene Expression Omnibus(GEO)database to identify hub genes and key pathways and explore possible molecular pathogenesis of PTCL by bioinformatic analysis.Diferentially expressed gencs(DEGs)between PTCL and normal T cells were selected using GEO2R tool.Gene ontology(GO)analysis and Kyoto Encyclopedia of Gene and Genome(KEGG)pathway analysis were performed using Database for Annotation,Visualization and Integrated Discovery(DAVID).Moreover,the Search Tool for the Retrieval of Interacting Genes(STRING)and Molecular Complex Detection(MCODE)were utilized to construct protein-protein interaction(PPI)network and perform module analysis of these DEGs.A total of 518 DEGs were identifed,including 413 down-regulated and 105 up-regulated gencs.The down-regulated genes were enriched in osteoclast differentiation,Chagas disease and mitogen-activated protein kinase(MAPK)signaling pathway.The up-regulated genes were mainly associated with extracellular matrix(ECM)-receptor interaction,focal adhesion and pertussis.F our important modules were detected from the PPI network by using MCODE software.Fifteen hub genes with a high degree of connectivity were selected.Our study identifed DEGs,hub genes and pathways associated with PTCL by bioinformatic analysis.Results provide a basis for further study on the pathogenesis of PTCL.
基金Supported by National Natural Science Foundation of China,No.82100594.
文摘BACKGROUND Helicobacter pylori(H.pylori)infection is related to various extragastric diseases including type 2 diabetes mellitus(T2DM).However,the possible mechanisms connecting H.pylori infection and T2DM remain unknown.AIM To explore potential molecular connections between H.pylori infection and T2DM.METHODS We extracted gene expression arrays from three online datasets(GSE60427,GSE27411 and GSE115601).Differentially expressed genes(DEGs)commonly present in patients with H.pylori infection and T2DM were identified.Hub genes were validated using human gastric biopsy samples.Correlations between hub genes and immune cell infiltration,miRNAs,and transcription factors(TFs)were further analyzed.RESULTS A total of 67 DEGs were commonly presented in patients with H.pylori infection and T2DM.Five significantly upregulated hub genes,including TLR4,ITGAM,C5AR1,FCER1G,and FCGR2A,were finally identified,all of which are closely related to immune cell infiltration.The gene-miRNA analysis detected 13 miRNAs with at least two gene cross-links.TF-gene interaction networks showed that TLR4 was coregulated by 26 TFs,the largest number of TFs among the 5 hub genes.CONCLUSION We identified five hub genes that may have molecular connections between H.pylori infection and T2DM.This study provides new insights into the pathogenesis of H.pylori-induced onset of T2DM.
基金funded by the supporting funds for scientific research of the Sixth Affiliated Hospital,Sun Yat-sen University(P20200217202404781).
文摘Introduction:The difficulty in treating lung adenocarcinoma(LUAD)is caused by a shortage of knowledge about the biological mechanisms and a lack of treatment choices.Objectives:The aim of this study was to identify a valuable molecular target for the treatment of LUAD.Methods:Using multiple databases,we screened for hub genes in LUAD using Cytoscape and explored the expression and prognosis of DLG associated protein 5(DLGAP5)in LUAD.We investigated the genetic variation,functional enrichment,and epigenetic activity of DLGAP5.Furthermore,we evaluated the relationship between the tumor microenvironment(TME)and DLGAP5.Results:Our study identified 10 hub genes in LUAD:CDC45,KIAA0101,DLGAP5,CDT1,NCAPG,CCNB1,CDCA5,CDC20,KIF11,and AURKA.We discovered that DLGAP5 was overexpressed and associated with poor prognosis in LUAD.DLGAP5 exhibited an overall genetic variation frequency of 2%,and its DNA promoter was hypomethylated in LUAD(p<0.05).The expression of DLGAP5 in LUAD showed a positive correlation with the majority of N6-methyladenosine(m6A)-methylation genes.Additionally,DLGAP5 was primarily associated with the cell cycle in LUAD.Notably,there was a significant favorable association between DLGAP5 and CD274,CTLA4,HAVCR2,and LAG3 in LUAD.Conclusion:DLGAP5 may be a therapeutic target for LUAD,as it affects cancer cells proliferation and development through the regulation of cell-cycle checkpoints and modulation of immune cell infiltration and immune checkpoints in the TME.
基金Supported by School-Level Key Projects at Bengbu Medical College,No.2021byzd109。
文摘BACKGROUND The identification of specific gene expression patterns is crucial for understanding the mechanisms underlying primary biliary cholangitis(PBC)and finding relevant biomarkers for diagnosis and therapeutic evaluation.AIM To determine PBC-associated hub genes and assess their clinical utility for disease prediction.METHODS PBC expression data were obtained from the Gene Expression Omnibus database.Overlapping genes from differential expression analysis and weighted gene coexpression network analysis(WGCNA)were identified as key genes for PBC.Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were performed to explore the potential roles of key genes.Hub genes were identified in protein-protein interaction(PPI)networks using the Degree algorithm in Cytoscape software.The relationship between hub genes and immune cells was investigated.Finally,a Mendelian randomization study was conducted to determine the causal effects of hub genes on PBC.RESULTS We identified 71 overlapping key genes using differential expression analysis and WGCNA.These genes were primarily enriched in pathways related to cytokinecytokine receptor interaction,and Th1,Th2,and Th17 cell differentiation.We utilized Cytoscape software and identified five hub genes(CD247,IL10,CCL5,CCL3,and STAT3)in PPI networks.These hub genes showed a strong correlation with immune cell infiltration in PBC.However,inverse variance weighting analysis did not indicate the causal effects of hub genes on PBC risk.CONCLUSION Hub genes can potentially serve as valuable biomarkers for PBC prediction and treatment,thereby offering significant clinical utility.
文摘<strong>Objective:</strong><span style="font-family:""><span style="font-family:Verdana;"> This study aimed to identify hub genes that are associated with hepatocellular carcinoma (HCC) prognosis by bioinformatics analysis. </span><b><span style="font-family:Verdana;">Methods:</span></b><span style="font-family:Verdana;"> Data were collected from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) liver HCC datasets. </span><a name="_Hlk11768117"></a><span style="font-family:Verdana;">The robust rank ag</span><span style="font-family:Verdana;">gregation algorithm was used in integrating the data on differentially ex</span><span style="font-family:Verdana;">pressed genes (DEGs). Online databases DAVID 6.8 and REACTOME were used for </span><span style="font-family:Verdana;">gene ontology and pathway enrichment analysis. R software version 3.5.1, </span><span style="font-family:Verdana;">Cytoscape, and Kaplan-Meier plotter were used to identify hub genes. </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> Six GEO datasets and the TCGA liver HCC dataset were included in this analysis. A total of 151 upregulated and 245 downregulated DEGs were iden</span><span style="font-family:Verdana;">tified. The upregulated DEGs most significantly enriched in the functional</span><span style="font-family:Verdana;"> categories of cell division, chromosomes, centromeric regions, and </span><span style="font-family:Verdana;">protein binding, whereas the downregulated DEGs most significantly</span><span style="font-family:Verdana;"> enriched in the </span><a name="_Hlk11059934"></a><span style="font-family:Verdana;">epoxygenase P450 pathway, extracellular region, and heme binding, with respect to biological process, cellular component, and molecular function analysis, respectively. Upregulated DEGS most significantly enriched the cell cycle pathway, whereas downregulated DEGs most significantly enriched </span><span style="font-family:Verdana;">the metabolism pathway. Finally, 88 upregulated and 40 downregulated genes were </span><span><span style="font-family:Verdana;">identified as hub genes. The top 10 upregulated hub DEGs were </span><i><span style="font-family:Verdana;">CDK</span></i><span style="font-family:Verdana;">1,</span></span><i><span style="font-family:Verdana;"> CCNB</span></i><span><span style="font-family:Verdana;">1,</span><i><span style="font-family:Verdana;"> CCNB</span></i><span style="font-family:Verdana;">2,</span><i><span style="font-family:Verdana;"> CDC</span></i><span style="font-family:Verdana;">20,</span><i><span style="font-family:Verdana;"> CCNA</span></i><span style="font-family:Verdana;">2,</span><i><span style="font-family:Verdana;"> AURKA</span></i><span style="font-family:Verdana;">,</span><i><span style="font-family:Verdana;"> MAD</span></i><span style="font-family:Verdana;">2</span><i><span style="font-family:Verdana;">L</span></i><span style="font-family:Verdana;">1,</span><i><span style="font-family:Verdana;"> TOP</span></i><span style="font-family:Verdana;">2</span><i><span style="font-family:Verdana;">A</span></i><span style="font-family:Verdana;">,</span><i><span style="font-family:Verdana;"> BUB</span></i><span style="font-family:Verdana;">1</span><i><span style="font-family:Verdana;">B </span></i><span style="font-family:Verdana;">and</span></span><i> <span style="font-family:Verdana;">BUB</span></i><span><span style="font-family:Verdana;">1. The top 10 downregulated hub DEGs were </span><i><span style="font-family:Verdana;">ESR</span></i><span style="font-family:Verdana;">1,</span><i><span style="font-family:Verdana;"> IGF</span></i><span style="font-family:Verdana;">1,</span><i><span style="font-family:Verdana;"> FTCD</span></i><span style="font-family:Verdana;">,</span></span><i><span style="font-family:Verdana;"> CYP</span></i><span style="font-family:Verdana;">3</span><i><span style="font-family:Verdana;">A</span></i><span style="font-family:Verdana;">4,</span><i><span style="font-family:Verdana;"> SPP</span></i><span style="font-family:Verdana;">2,</span><i> <span style="font-family:Verdana;">C</span></i><span><span style="font-family:Verdana;">8</span><i><span style="font-family:Verdana;">A</span></i><span style="font-family:Verdana;">,</span><i><span style="font-family:Verdana;"> CYP</span></i><span style="font-family:Verdana;">2</span><i><span style="font-family:Verdana;">E</span></i><span style="font-family:Verdana;">1,</span><i><span style="font-family:Verdana;"> TAT</span></i><span style="font-family:Verdana;">,</span><i><span style="font-family:Verdana;"> F</span></i><span style="font-family:Verdana;">9 and </span><i><span style="font-family:Verdana;">CYP</span></i><span style="font-family:Verdana;">2</span><i><span style="font-family:Verdana;">C</span></i><span style="font-family:Verdana;">9. </span><b><span style="font-family:Verdana;">Conclusions:</span></b><span style="font-family:Verdana;"> This study identified</span></span><span style="font-family:Verdana;"> several upregulated and downregulated hub genes that are associated with the prognosis of HCC patients. Verification of these results using </span><i><span style="font-family:Verdana;">in vitro</span></i><span style="font-family:Verdana;"> and </span><i><span style="font-family:Verdana;">in vivo</span></i><span style="font-family:Verdana;"> studies is warranted.</span></span>
文摘Objective:to screen the genes differentially expressed in autism using bioinformatics methods,and to explore their functional enrichment,related signaling pathways and the tissue-specific expression of hub genes.Methods:the autism expression profile chip numbered GSE77103 in the Gene Expression Omnibus(GEO)database was selected for examination.R language and related R packages were used for the screening and visualization of the diflerentially expressed genes.Gene Ontology(GO)function enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway analysis of the differential genes were carried out using the relevant R package of R language.The database STRING was used to construct the interaction network of the proteins encoded by the differentially expressed genes,and the software Cytoscape was used to screen the hub genes in the network.The selected hub genes were imported into the BioGPS database to analyze the tissue-specific expression of the hub genes.Results:six hundred and sixty diflerentially expressed genes were screened out.Three hundred and seventy-three up-regulated genes and 287 down-regulated genes in the peripheral blood mononuclear cells of autistic children were compared with the peripheral blood mononuclear cells of healthy children.GO functional enrichment results showed that biological processes(BP)were mainly involved in viral response,negative regulation of viral genome replication,negative regulation of multiple biological processes,negative reg ulation reg ulation of viral life cycle,and defense responses to viruses.Cell components(CC)were involved in vesicles,lysosomal membranes,lysosomal lumen,etc.;molecular functions(MF)were involved in regulating glutathione transferase activity peroxidase activity,oxidoreductase activity,Glutathione peroxidase and transferase activity,etc.The results of KEGG signaling pathway analysis showed that the differentially expressed genes were related to the lysosomal pathway,the glutathione metabolism pathway and the arachidonic acid metabolism pathway.The hub genes screened by cytoHubba were:interferon regulatory factor 7(IRF7),interferon stimulated exonuclease gene 15(ISG15),XIAP associated factor 1(XAF1),MX dynamin like GTPase 1(MX1),interferon induced protein with tetratricopeptide repeats 1(IFIT1),interferon induced protein with tetratricopeptide repeats 5(IFIT5),29-55-oligoadenylate synthetase 3(OAS3),interferon induced protein 44(IFI44),HECT and the RLD domain containing E3 ubiquitin protein ligase 5(HERC5),interferon stimulated exonuclease gene 20(ISG20).Conclusion:there are genes that are diflerentially expressed in the peripheral blood mononuclear cells of autistic toddlers and healthy toddlers.IRF7,ISG15,XAF1,MX],IFIT1,IFIT5,OAS3,IFI44,HERC5,ISG20 are the hub regulatory genes of autism.
文摘Objective:To identify the thyroid cancer-related hub genes and pathways by bioinformatics initially in order to lay the foundation for further study.Methods:The expression profile chips and data of thyroid cancer were screened and downloaded from the gene expression omnibus(GEO).The GEO2R was applied to identify the differential expressed genes between thyroid cancer tissues and normal thyroid tissues.And the Metascape online website was used for pathway and function enrichment.With the usage of STRING and Cytoscape,the protein-protein interaction network was constructed,and the plug-in app cytoHubba in Cytoscape was applied to screen hub genes.Kaplan-Meier Plotter was implemented to conduct survival analysis of hub genes for further screening and discussion.Results:A total of 304 differential expressed genes were screened,and were mainly enriched in the biological processes of extracellular matrix,cell-substrate adhesion,response to wounding,muscle structure development and hormone metabolic process etc.by Metascape.Protein-protein interaction network visualized 284 nodes;the top ten scores of Maximal Clique Centrality algorithm were taken as the criteria to screen out the hub genes with high connectivity in the gene expression network.The KM plotter analysis confirmed that 5 of 9 hub genes were correlated with the prognosis of thyroid cancer patients.Conclusion:FN1,SPP1,TIMP1,VCAN,COL1A1,COL1A2,MMP1,DCN,COMP and FMOD may play a significant role in the development of thyroid cancer.Genes which have prognostic significance in survival analyses were found to be relevant to the composition and regulation of extracellular matrix.
文摘Background:Cold exposure is linked to numerous diseases,yet the changes in key genes and pathways in mice under cold exposure remain unexplored.Understanding these alterations could offer insights into the mechanisms of cold resistance and contribute valuable ideas for treating cold-related diseases.Methods:The dataset GSE148361 was obtained from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were identified using the"limma"package in R software.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analyses were performed on DEGs.The STRING(Search Tool for the Retrieval of Interacting Genes)database was used to construct a protein-protein interaction(PPI)network.Additionally,gene set enrichment analysis(GSEA)was conducted to identify pathways associated with key genes.miRNAs and upstream transcription factors(TFs)were predicted using the miRNet database.Results:A total of 208 DEGs were identified,with 137 upregulated and 71 downregulated.In biological processes,DEGs were enriched in nucleotide and purine-containing compound metabolism.For cellular components,DEGs were involved in condensed chromosomes and mitochondrial protein complexes.In molecular functions,proton transmembrane transporter activity was enriched.KEGG pathway analysis showed significant enrichment in biosynthesis of unsaturated fatty acids,fatty acids,and pyruvate metabolism.From the PPI network,12 hub genes were identified using MCODE.Four hub genes(Col3a1,Ifi203,Rtp4,Vcan)demonstrated similar trends in a validation set(GSE110420)and were significantly differentially expressed.GSEA analysis indicated that these four genes were enriched in pathways such as ECM-receptor interaction and cytokine-cytokine receptor interaction.The hub gene network included 93 miRNAs and one TF.Conclusion:This study identified four hub genes as potential diagnostic biomarkers for cold exposure,providing insights for further research on the effects of cold on gene expression and disease.
文摘BACKGROUND Breast cancer(BC)is the most common malignant tumor in women.AIM To investigate BC-associated hub genes to obtain a better understanding of BC tumorigenesis.METHODS In total,1203 BC samples were downloaded from The Cancer Genome Atlas database,which included 113 normal samples and 1090 tumor samples.The limma package of R software was used to analyze the differentially expressed genes(DEGs)in tumor tissues compared with normal tissues.The cluster Profiler package was used to perform Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis of upregulated and downregulated genes.Univariate Cox regression was conducted to explore the DEGs with statistical significance.Protein-protein interaction(PPI)network analysis was employed to investigate the hub genes using the CytoHubba plug-in of Cytoscape software.Survival analyses of the hub genes were carried out using the Kaplan-Meier method.The expression level of these hub genes was validated in the Gene Expression Profiling Interactive Analysis database and Human Protein Atlas database.RESULTS A total of 1317 DEGs(fold change>2;P<0.01)were confirmed through bioinformatics analysis,which included 744 upregulated and 573 downregulated genes in BC samples.KEGG enrichment analysis indicated that the upregulated genes were mainly enriched in the cytokine-cytokine receptor interaction,cell cycle,and the p53 signaling pathway(P<0.01);and the downregulated genes were mainly enriched in the cytokine-cytokine receptor interaction,peroxisome proliferator-activated receptor signaling pathway,and AMP-activated protein kinase signaling pathway(P<0.01).CONCLUSION In view of the results of PPI analysis,which were verified by survival and expression analyses,we conclude that MAD2L1,PLK1,SAA1,CCNB1,SHCBP1,KIF4A,ANLN,and ERCC6L may act as biomarkers for the diagnosis and prognosis in BC patients.
基金the Military Logistics Scientific Research Project(No.CLB20J027).
文摘Traumatic brain injury(TBI)is a common injury caused by external forces that lead to damaged brain function or pathological changes in the brain tissue.To explore the molecular mechanism and the hub genes of TBI,we downloaded gene expression profiles of the TBI model of rat and the sham control for the subsequent gene set enrichment analysis,pathway analysis and protein-protein interactions analysis.The results of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis indicated that multiple biological pathways,including immune response,inflammatory response and cellular response to interleukin-1,as well as signaling pathways,such as tumor necrosis factor signaling pathway,chcmokine signaling pathway,cytokine-cytokine receptor interaction,Toll-like receptor signaling pathway and nuclear factor kappa B signaling pathway were implicated in the TBI.In conclusion,this study provides insights into the molecular mechanism of TBI by screening the differentially expressed genes and hub genes that can be used as biomarkers and therapeutic targets.
基金support from the China National Natural Science Foundation Funding Project(NO.81804150)Hunan University of Chinese Medicine,National Key Discipline of TCM Diagnostics Foundation Funding Project(No.2015ZYZD02)+5 种基金The Domestic First-class Discipline Construction Project of Chinese Medicine of Hunan University of Chinese MedicineHunan Provincial Department of Education Innovation Platform Open Fund Project(16K065)Chinese Medicine Key Laboratory of Prevention and Treatment of Disease in Hunan Province(2017TP1018)Changsha Science and Technology Plan Project(KC1704005)Hunan Engineering Technology Research Center for the Prevention and Treatment of Otorhinolaryngologic Diseases and Protection of Visual Function with Chinese MedicineHunan Provincial Research Innovation Project for Graduate students(CX2017B426)
文摘This study was conducted to elucidate the potential key candidate genes and pathways in role of astrocyte involved in glaucoma with ocular hypertension.Methods Expression profiles GSE2378 and GSE758 including 27 reactive optic nerve head astrocytes(ONHAs)by hypertensions and 26 normal controls,were integrated and deeply analyzed.Differentially expressed genes(DEGs)were sorted and candidate genes and pathways enrichment were analyzed.DEGs-associated protein-protein interaction network(PPI)was performed.Results A total of 119 consistently expressed genes were identified from 281 commonly changed DEGs,including 68 up-regulated genes and 51 down-regulated genes.PPI network complex filtered 75 DEGs(43 up-regulated and 32 down-regulated genes)of the 119 consistently altered DEGs and developed 117 edges,and 10 hub genes were identified.The most significant 3 modules were filtered from PPI,pathway enrichment analysis showed that module 1 was associated with extracellular exosome.Module 2 was mainly associated with antibody-dependent cellular cytotoxicity(ADCC)and module 3 was mainly associated with Hippo signaling pathway.Conclusion Taken above,using integrated bioinformatical analysis,we have identified DEGs candidate genes and pathways in role of astrocyte involved in glaucoma with ocular hypertension,which could improve our understanding of the cause and underlying molecular events,and these candidate genes and pathways could be therapeutic targets for glaucoma.
基金supported by the Key R&D Program of the Science and Technology Ministry of China(No.2021YFC2701100)the National Natural Science Foundation of China(No.82150008,81930036)。
文摘Alzheimer’s disease(AD)remains clinically incurable,raising a significant public health issue,particularly with its continuously increased incidence.1 Inflammatory bowel disease,including ulcerative colitis and Crohn’s disease(CD),is characterized by long-standing inflammation and immunological imbalance of the gastrointestinal system.2 Recent epidemiological studies suggest a link between increased AD risk and inflammatory bowel disease.
基金supported by the National Natural Science Foundation of China(No.82300114)the Natural Science Foundation of Hubei Province General Program(No.2023AFB684)the Natural Science Foundation of Hubei Province Youth Program(No.2022CFB671).
文摘Objective Sepsis-induced acute lung injury(ALI)poses a critical challenge in critical care,yet its immunoregulatory mechanisms remain poorly defined.This study aimed to delineate immune dysregulation networks and identify therapeutic targets through multiomics data integration.Methods Transcriptomic datasets(GSE40180 and GSE165226)were analyzed through a multiphase bioinformatics workflow,including gene set enrichment analysis(GSEA),immune cell deconvolution(CIBERSORT),differential gene expression profiling(|log2FC|>1.5,P.adj<0.05),and pathway annotation(GO/KEGG).Protein–protein interaction(PPI)networks were constructed to identify hub genes.Experimental validation was done using a murine cecal ligation and puncture(CLP)model with histopathological lung injury scoring and RT-qPCR-based hub gene verification.Results Integrated analysis revealed 26 consensus biological processes(24 upregulated,2 downregulated)dominated by innate immune activation.CIBERSORT revealed significant infiltration of M1 macrophages,neutrophils,activated dendritic cells(DCs),and activated natural killer(NK)cells in septic lungs,which was concurrent with Th17/naive CD8+T-cell dysregulation.Among the 58 differentially expressed genes(DEG),7 hub genes(Cxcl1,Cxcl2,Ccl3,Cd14,Saa3,Timp1,and Socs3)were significantly correlated with immune cell dynamics.CLP modeling confirmed severe alveolar damage(lung injury score:8.11±1.17 vs.1.97±0.29;P<0.0001)and upregulated hub gene expression(all P<0.01)in septic lungs,with hub gene expression levels strongly correlated with the lung injury score(Pearson’s r>0.85,P<0.001).Conclusion Innate adaptive immune crosstalk,particularly dysregulated immune cell infiltration,drives sepsis-induced ALI pathogenesis.The 7 hub genes mechanistically connect immune dyshomeostasis to tissue injury,suggesting novel targets for precision immunomodulation and biomarker development in critical care.
基金supported by National Natural Science Foundation of China (31172199,30972088)the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘IMP （inosine 5＇-monophosphate） is a compound that enhances the flavor of poultry meat. IMP has become a new breeding trait to improve poultry meat quality. We tried to identify several potential regulatory genes, and construct their predicted regulatory relationships. Time series gene expression profiles of thigh muscle tissues of Rugao chicken, a famous indigenous breed in China, were performed for analysis of genes that are co-expressed or correlated with the concentration of IMP. We found 15 crucial co-expression genes, which are Hspa2, Pten, Gabpa, Bpi, Mkll, Srf,, Cd34, Hspa4, EtvS, Bmpr2, Gdel, IgfbpS, Cd28, Pecam1 and Gja1, that may directly or indirectly regulate IMP metabolism. Eventually, we computed the correlation coefficient between 19 IMP Genes and 15 CGs （15 co-expression genes）, and we identified and constructed a predicted regulation network. In conclusion, variation of IMP concentration was primarily connected with the muscle development process. During this process, 15 CGs were identified that may have significant influence on IMP metabolism. In particular, Bmpr2, Pten and co-expression genes correlated with Entpd8 might play important roles in regulating IMP de novo synthesis, decomposition and salvage synthesis.
基金supported by the National Major Project of Research and Development of China,No.2017YFA0104701(to BY)the National Natural Science Foundation of China,No.32000725(to QQC)+1 种基金the Natural Science Foundation of Jiangsu Province of China,No.BK20200973(to QQC)the Jiangsu Provincial University Innovation Training Key Project of China,No.202010304021Z(to ML)。
文摘Peripheral nerve injury repair requires a certain degree of cooperation between axon regeneration and Wallerian degeneration.Therefore,investigating how axon regeneration and degeneration work together to repair peripheral nerve injury may uncover the molecular mechanisms and signal cascades underlying peripheral nerve repair and provide potential strategies for improving the low axon regeneration capacity of the central nervous system.In this study,we applied weighted gene co-expression network analysis to identify differentially expressed genes in proximal and distal sciatic nerve segments from rats with sciatic nerve injury.We identified 31 and 15 co-expression modules from the proximal and distal sciatic nerve segments,respectively.Functional enrichment analysis revealed that the differentially expressed genes in proximal modules promoted regeneration,while the differentially expressed genes in distal modules promoted neurodegeneration.Next,we constructed hub gene networks for selected modules and identified a key hub gene,Kif22,which was up-regulated in both nerve segments.In vitro experiments confirmed that Kif22 knockdown inhibited proliferation and migration of Schwann cells by modulating the activity of the extracellular signal-regulated kinase signaling pathway.Collectively,our findings provide a comparative framework of gene modules that are co-expressed in injured proximal and distal sciatic nerve segments,and identify Kif22 as a potential therapeutic target for promoting peripheral nerve injury repair via Schwann cell proliferation and migration.All animal experiments were approved by the Institutional Animal Ethics Committee of Nantong University,China(approval No.S20210322-008)on March 22,2021.
基金supported by Major scientific and technological projects of Xinjiang Production and Construction Corps(2017DB006 and 2020KWZ-012)。
文摘Proanthocyanidin(PA)is an important bioactive compound with multiple physiological benefits in jujube(Ziziphus jujube Mill.).However,the molecular mechanisms underlying PA biosynthesis in jujube fruit have not been investigated.Here,the profiling of PA,(+)-catechin and(–)-epicatechin and transcriptome sequencing of three jujube cultivars from Xinjiang Uyghur Autonomous Region of China at five developmental stages were analyzed.The levels of total PAs and catechin exhibited a decreased trend over jujube ripening,and epicatechin content of two jujube cultivars increased first and then declined.Transcriptome analysis revealed that the differentially expressed genes(DEGs)were mainly enriched in ribosome,glycolysis/gluconeogenesis,fructose and mannose metabolism.17 DEGs encoding PAL,CHS,CHI,CHS,F3'H,LAR,ANR,C4Hs,4CLs,FLSs,DFRs and UFGTs involved in PA biosynthesis were relatively abundant.The highly transcribed LAR gene may greatly contribute to epicatechin accumulation.A weighted gene co-expression network analysis(WGCNA)was performed,and a network module including 1620 genes highly correlated with content of Pas and catechin was established.We identified 58 genes including 9 structural genes and 49 regulatory genes related to PA biosynthesis and regulation in the WGCNA module.Sixteen genes encoding 9 families of transcriptional factors(i.e.,MYB,bHLH,ERF,bZIP,NAC,SBP,MIKC,HB,WRKY)were considered as hub genes.The results of qRT-PCR analysis validating 10 genes were well consistent with the transcriptome data.These findings provide valuable knowledge to facilitate its genetic studies and molecular breeding.
基金Supported by Scientific Research Project of Xianning Central Hospital in 2022 (No.2022XYB020)Science and Technology Plan Project of Xianning Municipal in 2022 (No.2022SFYF014).
文摘AIM:To prevent neovascularization in diabetic retinopathy(DR)patients and partially control disease progression.METHODS:Hypoxia-related differentially expressed genes(DEGs)were identified from the GSE60436 and GSE102485 datasets,followed by gene ontology(GO)functional annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis.Potential candidate drugs were screened using the CMap database.Subsequently,a protein-protein interaction(PPI)network was constructed to identify hypoxia-related hub genes.A nomogram was generated using the rms R package,and the correlation of hub genes was analyzed using the Hmisc R package.The clinical significance of hub genes was validated by comparing their expression levels between disease and normal groups and constructing receiver operating characteristic curve(ROC)curves.Finally,a hypoxia-related miRNA-transcription factor(TF)-Hub gene network was constructed using the NetworkAnalyst online tool.RESULTS:Totally 48 hypoxia-related DEGs and screened 10 potential candidate drugs with interaction relationships to upregulated hypoxia-related genes were identified,such as ruxolitinib,meprylcaine,and deferiprone.In addition,8 hub genes were also identified:glycogen phosphorylase muscle associated(PYGM),glyceraldehyde-3-phosphate dehydrogenase spermatogenic(GAPDHS),enolase 3(ENO3),aldolase fructose-bisphosphate C(ALDOC),phosphoglucomutase 2(PGM2),enolase 2(ENO2),phosphoglycerate mutase 2(PGAM2),and 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3(PFKFB3).Based on hub gene predictions,the miRNA-TF-Hub gene network revealed complex interactions between 163 miRNAs,77 TFs,and hub genes.The results of ROC showed that the except for GAPDHS,the area under curve(AUC)values of the other 7 hub genes were greater than 0.758,indicating their favorable diagnostic performance.CONCLUSION:PYGM,GAPDHS,ENO3,ALDOC,PGM2,ENO2,PGAM2,and PFKFB3 are hub genes in DR,and hypoxia-related hub genes exhibited favorable diagnostic performance.
文摘Bladder,kidney,prostate and testicular carcinoma are the top four genitourinary cancers in China.Here we analyzed mRNA and miRNA expression profiles of carcinomas of the bladder(TCC),kidney(ccRCC)and testis(TGCT)to uncover their specific regulatory mechanisms.The gene expression profiles of GSE31617 were downloaded from GEO database,which contained 27 samples,including 10 TCC,7 TGCT and 10 ccRCC.Specific up-and downregulated differentially expressed genes(DEGs)and differentially expressed microRNAs(DEmiRNAs)of each cancer were selected and target genes of DEmiRNAs were predicted.Gene interaction network of the shared genes and target genes of DEmiRNAs of each cancer was predicted by STRING and constructed by Cytoscape.In each cancer,we build regulatory networks of hub genes selected and conducted GO analysis of enriched genes.Furthermore,we chose four hub genes(SALL4,RHEB,CDC42 and TNN)for survival analysis in OncoLnc database,and they all had effects on the survival rate of another genitourinary cancer-kidney renal clear cell carcinoma(KIRC).In conclusion,the present study indicated that the identified hub genes promote our understanding of molecular mechanisms underlying the development of three genitourinary cancers,and might be used as molecular targets and diagnostic biomarkers for the treatment of them.
