Mining of Gene Modules and Identification of Key Genes for Early Diagnosis of Gastric Cancer

Gastric cancer (GC) is one of the most common malignant tumors with high incidence and mortality rates. Most patients with GC are not diagnosed until the advanced stage of cancer or during tumor screening, resulting in missing the best treatment time. This study identified key modules and hub genes associated with GC by weighted gene co-expression network analysis (WGCNA). The "limma" package in R was used to identify differentially expressed genes (DEGs) in GC samples from TCGA, and a total of 4892 DEGs were identified. GO enrichment and KEGG pathway enrichment analyses were conducted to detect the related pathways and functions of DEGs. These DEGs were primarily associated with extracellular matrix organization, DNA replication, cell cycle, and p53 signaling pathway. Gene modules associated with clinical characteristics were identified with WGCNA in tumor and normal samples. Six gene modules were obtained in the WGCNA network, of which two modules were significantly correlated with GC. Hub genes of key modules were identified using survival analysis and expression analysis. Finally, one-way ANOVA was used to explore the relationship between hub gene expression in normal tissues and different pathological stages of GC. Through survival and expression analysis, a total of 19 genes with good prognosis and significantly differential expressed were identified. The hub genes were significantly differential expressed in normal tissues and different pathological stages of GC, indicating that these genes have important diagnostic value for early GC and can be used as auxiliary indicators in the diagnosis of early GC.

COMMON HUB GENES AND DRUG CANDIDATES FOR DIABETIC KIDNEY DISEASE AND NON-ALCOHOLIC FATTY LIVER DISEASE: A COMPREHENSIVE BIOINFORMATIC STUDY

Diabetes mellitus (DM) is one of the most prevalent diseases responsible for worldwide morbidity and mortality. The kidney and liver are the most commonly affected organs resulting in diabetic kidney disease (DKD) and non-alcoholic fatty liver disease (NAFLD). However, pathophysiological mechanisms that may be common to both DKD and NAFLD have not been elaborated despite having a common underlying cause. This study aimed to identify the hub genes that are common to both DKD and NAFLD and explore the potential drugs for their treatment. Gene expression datasets for DKD and NAFLD from the gene expression omnibus database were analyzed to identify differentially expressed genes (DEGs). A functional enrichment analysis of the DEGs was done to reveal pathways important in the etiology of DKD and NAFLD. Protein-protein interaction (PPI) network was constructed and hub genes were identified. The hub genes were further analyzed to identify potentially viable drug candidates after screening. A total of 89 DEGs were found to be common between DKD and NAFLD. Functional enrichment of said DEGs found Ppar, FoxO signaling and hepatocellular carcinoma pathways to be most prevalent in DKD and NAFLD. From the PPI network, 32 common hub genes were identified. The hub genes were analyzed for interacting drugs. Finally, 9 drugs were identified as potential candidates for the treatment of both diseases. The hub genes identified can provide new insights into the common etiology of DKD and NAFLD. The potentially viable drugs may be repurposed for the treatment of both DKD and NAFLD.

Identification of overlay differentially expressed genes in both rats and goats with blast lung injury through comparative transcriptomics / 中华创伤杂志(英文版)

PURPOSE@#To identify the potential target genes of blast lung injury (BLI) for the diagnosis and treatment.@*METHODS@#This is an experimental study. The BLI models in rats and goats were established by conducting a fuel-air explosive power test in an unobstructed environment, which was subsequently validated through hematoxylin-eosin staining. Transcriptome sequencing was performed on lung tissues from both goats and rats. Differentially expressed genes were identified using the criteria of q ≤ 0.05 and |log2 fold change| ≥ 1. Following that, enrichment analyses were conducted for gene ontology and the Kyoto Encyclopedia of Genes and Genomes pathways. The potential target genes were further confirmed through quantitative real-time polymerase chain reaction and enzyme linked immunosorbent assay.@*RESULTS@#Observations through microscopy unveiled the presence of reddish edema fluid, erythrocytes, and instances of focal or patchy bleeding within the alveolar cavity. Transcriptome sequencing analysis identified a total of 83 differentially expressed genes in both rats and goats. Notably, 49 genes exhibited a consistent expression pattern, with 38 genes displaying up-regulation and 11 genes demonstrating down-regulation. Enrichment analysis highlighted the potential involvement of the interleukin-17 signaling pathway and vascular smooth muscle contraction pathway in the underlying mechanism of BLI. Furthermore, the experimental findings in both goats and rats demonstrated a strong association between BLI and several key genes, including anterior gradient 2, ankyrin repeat domain 65, bactericidal/permeability-increasing fold containing family A member 1, bactericidal/permeability-increasing fold containing family B member 1, and keratin 4, which exhibited up-regulation.@*CONCLUSIONS@#Anterior gradient 2, ankyrin repeat domain 65, bactericidal/permeability-increasing fold containing family A member 1, bactericidal/permeability-increasing fold containing family B member 1, and keratin 4 hold potential as target genes for the prognosis, diagnosis, and treatment of BLI.

Screening of IL-3 and IL-3+SCF Induce Differentially Expressed Genes and Signaling Pathways in Bone Marrow-derived Mast Cells Based on Bioinformatics / 现代检验医学杂志

Objective To identify the differentially expressed genes and pathways of bone marrow-derived mast cells(BMMCs)of mice induced by IL-3 and IL-3+stem cell factor(SCF)using bioinformatics analysis,which may provide a foundation for in vitro culture and functional study of mast cells(MC).Methods The matrix data of GSE35332 dataset in IL-3 and IL-3+SCF induced BMMCs was downloaded from the GEO database,and the R software was applied to screen differentially expressed genes(DEGs).The gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)pathway enrichment analysis of EDGs were performed based on the online tool DAVID database.The protein interaction network was constructed by STRING database and hub genes were screened through MCODE plugin of the Cytoscape software.Results The GSE35332 data set was analyzed by R software,and 1 339 DEGs were screened,including 723 up-regulated genes and 616 down-regulated genes.A total of 6 hub genes were screened through the MCODE plugin of Cytoscape software,namely Psmd8,Psmd6,Psmd14,Psmc4,Psma6 and Psma3.GO and KEGG analysis showed that the hub genes were concentrated in proteolysis,antigen processing and presentation of exogenous peptide antigen via MHC class I,proteasome-mediated ubiquitin-dependent protein catabolism process,and Epstein-Barr virus infection.Conclusion This study found that there were significant differences in BMMCs gene expression profiles in mice induced by two modes and 6 hub genes participated in ubiquitin-dependent protein decomposition process through bioinformatics based on the GEO database,providing help for further research on MC vitro culture and function.

Transcriptomic analysis of A549 cells infected with ON1 genotype of human respiratory syncytial virus subtype A isolated in Beijing / 中华微生物学和免疫学杂志

Objective:To analyze the differentially expressed genes of human respiratory syncytial virus (RSV) subtype A genotype ON1, a predominant genotype in Beijing, after infecting A549 cells using transcriptomic sequencing, and provide potential targets for RSV prevention and treatment.Methods:A local strain (61397-ON1) identified by whole-genome sequencing as ON1 genotype of RSV subtype A was selected to infect A549 cells. Total mRNA was extracted, and the differentially expressed genes in infected and uninfected A549 cells were screened by transcriptomic sequencing. GO analysis and KEGG pathway analysis were performed. Besides, six genes with differential expression ratio greater than two times were randomly selected for qRT-PCR verification.Results:There were 1 632 differentially expressed genes between infected and uninfected A549 cells, of which 807 genes were up-regulated and 825 genes were down-regulated. The differentially expressed genes were mainly involved in immune response-related biological processes such as cytokine response and positive regulation of MAPK cascades, and were enriched in MAPK signaling pathway, NOD-like receptor signaling pathway, p53 signaling pathway, TNF signaling pathway, IL-17 signaling pathway and NF-κB signaling pathway. The results of qRT-PCR for six differentially expressed genes were consistent with the trend of transcriptome data.Conclusions:The differentially expressed genes of RSV A subtype ON1 genotype after infecting A549 cells are mainly involved in cytokine response and immune-related signaling pathways. This study provides basic data for further study of the molecular mechanism of RSV infection and the development of prevention and treatment strategies.

Screening and experimental validation of hub genes for myocardial isch-emia-reperfusion injury based on bioinformatics / 中国病理生理杂志

AIM:Using bioinformatics analysis methods to identify the hub genes involved in myocardial isch-emia-reperfusion injury(MIRI).METHODS:Firstly,the rat MIRI related dataset GSE122020,E-MEXP-2098,and E-GEOD-4105 were downloaded from the database.Secondly,differentially expressed genes(DEGs)were screened from each dataset using the linear models for microarray data(limma)package,and robust DEGs were filtered using the robust rank aggregation(RRA)method.In addition,the surrogate variable analysis(SVA)package was used to merge all datas-ets into one,and merged DEGs were screened using the limma package.The common DEGs were obtained by taking the intersection of the two channels of DEGs.Next,the protein-protein interaction(PPI)network of common DEGs was con-structed,and the hub genes were identified using the density-maximizing neighborhood component(DMNC)algorithm.The receiver operating characteristic curve(ROC)was plotted to evaluate the diagnostic performance of the hub gene.Then,the mRNA and protein expression levels of hub genes were detected in the rat MIRI model,and the literature re-view analysis was carried out on the involvement of hub genes in MIRI.Finally,the gene set enrichment analysis(GSEA)was performed on hub gene to further reveal the possible mechanism in mediating MIRI.RESULTS:A total of 143 robust DEGs and 48 merged DEGs were identified.After taking the intersection of the two,48 common DEGs were obtained.In the PPI network of common DEGs,5 hub genes were screened out,namely MYC proto-oncogene bHLH transcription fac-tor(MYC),prostaglandin-endoperoxide synthase 2(PTGS2),heme oxygenase 1(HMOX1),caspase-3(CASP3),and plasminogen activator urokinase receptor(PLAUR).The ROC results showed that the area under the curve values for all hub genes were greater than 0.8.MYC,PTGS2,CASP3,and PLAUR showed high mRNA and protein expression in rat MIRI,while there was no difference in mRNA and protein expression for HMOX1.The literature review revealed that among the 5 hub genes,only PLAUR has not been reported to be involved in MIRI.The GSEA results for PLAUR indicat-ed that its functional enrichment mainly focused on pathways such as NOD-like receptor signaling pathway,P53 signaling pathway,Toll-like receptor signaling pathway,apoptosis,and fatty acid metabolism.CONCLUSION:MYC,PTGS2,CASP3,HMOX1,and PLAUR are involved in the pathological process of MIRI.PLAUR is a potential hub gene that can mediate MIRI by regulating pathways such as NOD like receptor signaling,P53 signaling,Toll like receptor signaling,cell apoptosis,and fatty acid metabolism.The results can provide reference for further investigation into the molecular mechanisms and therapeutic targets of MIRI.

Key genes and related pathways of hepatic fibrosis based on bioinformatics analysis / 局解手术学杂志

Objective By screening key genes and related pathways for hepatic fibrosis treatment through bioinformatics analysis,the differentially expressed genes of hepatic fibrosis patients were mined to predict potential therapeutic targets for liver fibrosis.Methods Gene expression profiles GSE197112 were obtained from GEO database.Differentially expressed genes were screened by Limma.DAVID online database was used to conduct GO enrichment analysis and KEGG signaling pathway enrichment analysis of differentially expressed genes.The protein-protein interaction(PPI)network diagram of differentially expressed genes were obtained from STRING database and visualize by Cytoscape software.At the same time,the plug-in CytoHubba in Cytoscape software was used to screen the target genes of hepatic fibrosis.Results A total of 399 differentially expressed genes were screened(P<0.01,∣log2FC∣>1.5),including 300 down-regulated genes and 99 up-regulated genes.These genes were mainly involved in GO biological processes such as mitosis checkpoint,DNA replication,chromosome segregation,cell division,apoptosis,adaptive immune response and so on,and mainly regulated the intestinal immune network for IgA production,progesterone-mediated oocyte maturation,human T-cell leukemia virus 1 infection,cell cycle,antigen processing and presentation,p53 signaling pathway,cancer transcription disorder,cell adhesion molecules and so on.Five target genes were screened by Cytoscape software:TTK,KIF2C,ASPM,DLGAP5,PBK.Conclusion In this study,399 differentially expressed genes and 5 target genes in hepatic fibrosis were screened by bioinformatics methods,which play key roles in the biological processes related to hepatic fibrosis,and provide a new direction for the pharmacological treatment of liver fibrosis.

Study on the role of NR1H4 in chronic atrophic gastritis and drug prediction based on bioinformatics / 中国现代医生

Objective To explore the differential gene expression profile and small molecule drugs for chronic atrophic gastritis(CAG)by bioinformatics technology.Methods Two gene expression samples of CAG chips(GSE27411,GSE116312)were obtained through the Gene Expression Synthesis(GEO)database,screen the differentially expressed genes(DEGs)of CAG by R language,and CAG immune-related genes were obtained for gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)analysis.Protein-protein interaction(PPI)network was constructed using STRING database to screen out core genes,further study on immune invasion of core genes based on GSE27411 dataset,small molecular compounds interacting with core genes were predicted,molecular docking was carried out by MOE2022,and survival analysis was carried out by GEPIA2 website.Results A total of 517 DEGs were screened out based on GEO database.GO function enrichment analysis found that it mainly involved in granulocyte chemotaxis、leukocyte chemotaxis and neutrophil chemotaxis biological processes.KEGG pathway enrichment analysis showed that it mainly involved in cytokine-cytokine receptor interaction、nuclear factor kappa B signaling pathway、interleukin-17 signaling pathway.Six key genes of NR1H4、CCK、CCL20、CXCL1、LCN2、SAA1 were obtained by PPI network,through relevant verification,NR1H4 was regarded as the core gene.Immune cell infiltration analysis showed that central memory CD8 T cell、effector memeory CD4 T cell、gamma delta T cell、natural killer T cell、neutrophil and other immune cells may be involved in the development of CAG,and the neutrophil was positively correlated with NR1H4.It was predicted that six small molecular drugs,corilagin,stigmasterol,geniposide,tangeretin,chenodeoxycholic acid and epigallocatechin 3-gallate,have good binding force with NR1H4.Conclusion The potential mechanism of CAG is preliminarily explored in this study,the key gene of NR1H4 and neutrophil may play an important role in the"inflammatory cancer transformation"process of CAG,which can provide a certain reference for the study of the"inflammatory cancer transformation"mechanism of CAG.

Identification of differentially expressed genes, pathways, and immune infiltration in diabetes

ABSTRACT This study aimed to perform exhaustive bioinformatic analysis by using GSE29221 micro-array maps obtained from healthy controls and Type 2 Diabetes (T2DM) patients. Raw data are downloaded from the Gene Expression Omnibus database and processed by the limma package in R software to identify Differentially Expressed Genes (DEGs). Gene ontology functional analysis and Kyoto Gene Encyclopedia and Genome Pathway analysis are performed to determine the biological functions and pathways of DEGs. A protein interaction network is constructed using the STRING database and Cytoscape software to identify key genes. Finally, immune infiltration analysis is performed using the Cibersort method. This study has implications for understanding the underlying molecular mechanism of T2DM and provides potential targets for further research.

Integrated aqueous humor ceRNA and miRNA–TF–mRNA network analysis reveals potential molecular mechanisms governing primary open-angle glaucoma pathogenesis

To conduct an integrated bioinformatics analysis of extant aqueous humor (AH) gene expression datasets in order to identify key genes and the regulatory mechanism governing primary open?angle glaucoma (POAG) progression. Methods: Two datasets (GSE101727 and GSE105269) were downloaded from the Gene Expression Omnibus, and the messenger RNAs (mRNAs), microRNAs (miRNAs), and long noncoding RNAs (lncRNAs) were identified between controls and POAG patients. Differentially expressed (DE) mRNAs and DElncRNAs were then subjected to pathway enrichment analyses, after which a protein–protein interaction (PPI) network was generated. This network was then expanded to establish lncRNA–miRNA–mRNA and miRNA–transcription factor (TF)–mRNA networks. Results: The GSE101727 dataset was used to identify 2746 DElncRNAs and 2208 DEmRNAs, while the GSE105269 dataset was used to identify 45 DEmiRNAs. We ultimately constructed a competing endogenous RNA (ceRNA) network incorporating 47 lncRNAs, six miRNAs, and 17 mRNAs. The proteins encoded by these 17 hub mRNAs were found to be significantly enriched for activities that may be linked to POAG pathogenesis. In addition, we generated a miRNA–TF–mRNA regulatory network containing two miRNAs (miR?135a?5p and miR?139?5p), five TFs (TGIF2, TCF3, FOS, and so on), and five mRNAs (SHISA7, ST6GAL2, TXNIP, and so on). Conclusion: The SHISA7, ST6GAL2, TXNIP, FOS, and DCBLD2 genes may be viable therapeutic targets for the prevention or treatment of POAG and are regulated by the TFs (TGIF2, HNF1A, TCF3, and FOS)

Identification of potential hub genes involved in alcohol use disorder via bioinformatics analysis / 四川精神卫生

BackgroundAlcohol use disorder （AUD） is a type of chronic relapsing brain disorder. Genetic factors play an important role in the pathogenesis of AUD. And screening for molecular markers of AUD is of great significance for further elucidating the pathogenesis of the disease， discovering novel therapeutic targets and preventing relapse. ObjectiveTo explore relevant hub genes and potential signal pathways associated with the development of AUD through bioinformatics analysis， and to provide a new direction for the prevention and treatment of AUD. MethodsThe GSE161986 dataset was acquired from the Gene Expression Omnibus （GEO） database. The limma package in R was utilized to identify differentially expressed genes （DEGs）. Gene set enrichment analysis （GSEA） was carried out using the Database for Annotation， Visualization and Integrated Discovery （DAVID）. A protein–protein interaction （PPI） network of DEGs was assessed using the STRING database and visualized by Cytoscape software. Finally， hub genes were validated in GSE44456 dataset. ResultsA total of 114 DEGs were identified. GSEA revealed that these genes were mainly involved in the regulation of signal transduction， protein binding， membrane trafficking and MAPK signaling pathway. PPI network and validation study indicated that GAD1， TIMP1 and CD44 were potential hub genes involved in AUD. ConclusionAberrant expression of GAD1 and TIMP1 as well as MAPK signaling pathway may play a key role in the pathogenesis of AUD， and may serve as potential molecular targets for the diagnosis and treatment of AUD. ［Funded by "Flying Project" of Shanghai Mental Health Center （number， 2022-FX-01）］

Effect of Flavanomarein from Coreopsis tinctoria Ethanol Extract in Small Intestinal Organoids in Insulin-resistant Mice Based on Transcriptome Sequencing / 中国实验方剂学杂志

ObjectiveTo investigate the effects of flavanomarein on the transcriptome of small intestinal organoids in insulin-resistant mice. MethodFirstly， small intestinal organoids of C57BL/6J and db/db mice were established. Ki-67 and E-cadherin expression was determined by immunofluorescence. Small intestinal organoids were divided into the following three groups： C57BL/6J mouse small intestinal organoids as the normal control group， db/db mouse small intestinal organoids as the model group （IR group）， and db/db mouse small intestinal organoids treated with flavanomarein as the administration group （FM group）. Western blot was used to detect the expression of glucagon-like peptide-1（GLP-1） protein on the small intestinal organoids of the three groups. Finally， transcriptome sequencing was performed on samples from the three groups. ResultOn the 6th day of small intestine organoids culture， a cyclic structure was formed around the lumen， and a small intestine organoids culture model was preliminarily established. Immunofluorescence detection showed that ki-67 and E-cadherin were expressed in small intestinal organoids. Western blot results showed that the expression of GLP-1 protein was increased by flavanomarein. In the results of differential expressed gene （DEG） screening， there were 1 862 DEGs in the IR group as compared with the normal control group， and 2 282 DEGs in the FM group as compared with the IR group. Through protein-protein interaction（PPI） network analysis of the DEGs of the two groups， 10 Hub genes， including Nr1i3， Cyp2c44， Ugt2b1， Gsta1， Gstm2， Ptgs1， Gstm4， Cyp2c38， Cyp4a32， and Gpx3， were obtained. These genes were highly expressed in the normal control group， and their expression was reduced in the IR group. After the intervention of flavanomarein， the expression of the above genes was reversed. ConclusionFlavanomarein may play its role in improving insulin resistance by reversing the expression levels of 10 Hub genes， including Nr1i3， Cyp2c44， Ugt2b1， Gsta1， Gstm2， Ptgs1， Gstm4， Cyp2c38， Cyp4a32， and Gpx3.

Mechanism of Huangjing Qianshi Decoction in treatment of prediabetic mice based on transcriptome sequencing / 中国中药杂志

Based on transcriptome sequencing technology, the mouse model of prediabetes treated with Huangjing Qianshi Decoction was sequenced to explore the possible mechanism of treating prediabetes. First of all, transcriptome sequencing was performed on the normal BKS-DB mouse group, the prediabetic model group, and the Huangjing Qianshi Decoction treatment group(treatment group) to obtain differentially expressed genes in the skeletal muscle samples of mice. The serum biochemical indexes were detected in each group to screen out the core genes of Huangjing Qianshi Decoction in prediabetes. Gene Ontology(GO) database and Kyoto Encyclopedia of Genes and Genomes(KEGG) database were used to conduct signaling pathway enrichment analysis of differentially expressed genes, and real-time quantitative polymerase chain reaction(RT-qPCR) was used to verify them. The results showed that the levels of fasting blood glucose(FBG), fasting insulin(FINS), insulin resistance index(HOMA-IR), total cholesterol(TC), triglycerides(TG), and low-density lipoprotein cholesterol(LDL-C) in the mouse model were significantly decreased after treatment with Huangjing Qianshi Decoction. In the results of differential gene screening, there were 1 666 differentially expressed genes in the model group as compared with the normal group, and there were 971 differentially expressed genes in the treatment group as compared with the model group. Among them, interleukin-6(IL-6) and NR3C2 genes, which were closely related to the regulation of insulin resis-tance function, were significantly up-regulated between the model group and the normal group, and vascular endothelial growth factor A(VEGFA) genes were significantly down-regulated between the model group and the normal group. However, the expression results of IL-6, NR3C2, and VEGFA genes were adverse between the treatment group and the model group. GO functional enrichment analysis found that the biological process annotation mainly focused on cell synthesis, cycle, and metabolism; cell component annotation mainly focused on organelles and internal components; and molecular function annotation mainly focused on binding molecular functions. KEGG pathway enrichment analysis found that it involved the protein tyrosine kinase 6(PTK6) pathway, CD28-dependent phosphoinositide 3-kinase/protein kinase B(PI3K/AKT) pathway, p53 pathway, etc. Therefore, Huangjing Qianshi Decoction can improve the state of prediabetes, and the mechanism may be related to cell cycle and apoptosis, PI3K/AKT pathway, p53 pathway, and other biological pathways regulated by IL-6, NR3C2, and VEGFA.

Comparative analysis of differentially expressed genes for biosynthesis of active ingredients in fruits of different cultivars of Lycium barbarum L. based on transcriptome sequencing / 生物工程学报

To explore the differentially expressed genes (DEGs) related to biosynthesis of active ingredients in wolfberry fruits of different varieties of Lycium barbarum L. and reveal the molecular mechanism of the differences of active ingredients, we utilized Illumina NovaSeq 6000 high-throughput sequencing technology to conduct transcriptome sequencing on the fruits of 'Ningqi No.1' and 'Ningqi No.7' during the green fruit stage, color turning stage and maturity stage. Subsequently, we compared the profiles of related gene expression in the fruits of the two varieties at different development stages. The results showed that a total of 811 818 178 clean reads were obtained, resulting in 121.76 Gb of valid data. There were 2 827, 2 552 and 2 311 DEGs obtained during the green fruit stage, color turning stage and maturity stage of 'Ningqi No. 1' and 'Ningqi No. 7', respectively, among which 2 153, 2 050 and 1 825 genes were annotated in six databases, including gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) and clusters of orthologous groups of proteins (KOG). In GO database, 1 307, 865 and 624 DEGs of green fruit stage, color turning stage and maturity stage were found to be enriched in biological processes, cell components and molecular functions, respectively. In the KEGG database, the DEGs at three developmental stages were mainly concentrated in metabolic pathways, biosynthesis of secondary metabolites and plant-pathogen interaction. In KOG database, 1 775, 1 751 and 1 541 DEGs were annotated at three developmental stages, respectively. Searching the annotated genes against the PubMed database revealed 18, 26 and 24 DEGs related to the synthesis of active ingredients were mined at the green fruit stage, color turning stage and maturity stage, respectively. These genes are involved in carotenoid, flavonoid, terpenoid, alkaloid, vitamin metabolic pathways, etc. Seven DEGs were verified by RT-qPCR, which showed consistent results with transcriptome sequencing. This study provides preliminary evidences for the differences in the content of active ingredients in different Lycium barbarum L. varieties from the transcriptional level. These evidences may facilitate further exploring the key genes for active ingredients biosynthesis in Lycium barbarum L. and analyzing their expression regulation mechanism.

Mechanism of Huashi Baidu Prescription in Treating Influenza Viral Pneumonia Based on Transcriptome / 中国实验方剂学杂志

ObjectiveTo clarify the therapeutic effect of Huashi Baidu prescription on pneumonia in mice caused by influenza A （H1N1） virus and explore its mechanism based on the transcriptome. MethodA mouse influenza viral pneumonia model was built by intranasal infection with influenza A virus， and mice were continuously administered the drug for five days， so as to investigate the general condition， lung index， viral load， pathological morphology of lung tissue， survival time， and prolongation rate of survival time of mice and clarify the therapeutic effect of Huashi Baidu prescription on influenza viral pneumonia. Transcriptome technology was used to detect the differentially expressed genes in the lung tissue of mice in the model group and the normal group， as well as the Huashi Baidu prescription group and the model group， and the potential core target of the Huashi Baidu prescription for the treatment of influenza viral pneumonia was screened. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to verify the effect of Huashi Baidu prescription on the mRNA expression level of core target genes. ResultCompared with the normal group， the lung index and viral load in the lung tissue of the model group were significantly increased （P<0.05， P<0.01）. Compared with the model group， the high-dose group of Huashi Baidu prescription significantly prolonged the survival time of mice infected with influenza A virus （P<0.05） and significantly reduced the lung index value of mice （P<0.05） and the viral load of lung tissue. The high-dose， medium-dose， and low-dose groups of Huashi Baidu prescription could significantly reduce lung tissue inflammation， blood stasis， swelling， and other pathological changes in mice （P<0.05， P<0.01）. Transcriptome analysis of lung tissue showed that core genes were mainly enriched in the nuclear transcription factor-κB （NF-κB） signaling pathway， interleukin-17 （IL-17） signaling pathway， cytokine-cytokine receptor interaction， and other pathways after the intervention of Huashi Baidu prescription. TRAF6， NFKBIA， CCL2， CCL7， and CXCL2 were the top five node genes with combined score values. Real-time PCR validation showed that Huashi Baidu prescription significantly downregulated the mRNA expression of key genes TRAF6 and NFKBIA in the NF-κB signaling pathway， as well as chemokines CCL2， CCL7， and CXCL2 （P<0.05， P<0.01）. ConclusionHuashi Baidu prescription has a therapeutic effect on influenza viral pneumonia， possibly by inhibiting the expression of key nodes TRAF6 and NFKBIA in the NF-κB signaling pathway and that of chemokines CCL2， CCL7， and CXCL2， reducing the recruitment of inflammatory cells and viral load， and exerting anti-influenza viral pneumonia effects.

Bioinformatics screening and analysis of prognostic genes in breast cancer / 实用肿瘤学杂志

Objective Bioinformatics techniques were used to analyze the key genes that affect the survival of patients with breast cancer,so as to provide theoretical basis for the prognosis evaluation and targeted therapy of breast cancer.Methods The dif-ferentially expressed genes between breast cancer samples and normal breast samples were screened by TCGA database,enriched and analyzed by gene ontology(GO)and Kyoto Encyclopedia of Gene and Genome(KEGG).The protein-protein interaction network was constructed and the key genes were screened.The Kaplan-Meier method was used to find and verify the genes that might be used as potential prognostic biomarkers for breast cancer,and to explore the correlation between prognostic target genes and molecular typing and staging.The Timer database was used to analyze the correlation between prognosis-related target genes and immune cell infiltra-tion.Results A total of 1,285 differentially expressed genes were screened,including 318 up-regulated genes and 967 down-regu-lated genes(|log2FC| ≥ 1,P＜0.05).Differentially expressed genes were mainly enriched in cytokine-cytokine receptor interac-tions,PI3K-AKT signaling pathway,cAMP signaling pathway,and so on.A total of 10 key genes(AURKB,CDC20,CCNA2,NCAPG,BUB1,TOP2A,BUB1B,CCNB1,CDK1,and KIF11)were screened from the protein interaction network.Among them,the ex-pression of CCNA2,NCAPG and BUB1 in breast cancer tissues were higher than those in normal tissues.Their high expression was as-sociated with the poor prognosis of patient's overall survival(P＜0.05),and was significantly associated with the molecular typing and staging of breast cancer.The results of immune infiltration showed a significant correlation between the expression of CCNA2,NCAPG,BUB1 and the infiltration of immune cells such as B lymphocytes,CD8+T lymphocytes,neutrophils,dendritic cells and other immune cells.Conclusion CCNA2,NCAPG and BUB1 may be key genes in the occurrence and development of breast cancer,and their high expression is related to poor prognosis of breast cancer patients,which can be used as potential biomarkers for the prognosis of breast cancer.

Protein-based Bioinformatics Analysis of Cervical Cancer Related Genes / 医学信息学杂志

Purpose/Significance To explore the characteristics and clinical significance of differentially expressed genes closely re-lated to HPV E6/E7 by using bioinformatics.Method/Process The cervical tissue and clinical information of cervical cancer in TCGA and GTEx of UCSC are used as the training set.The expression profile chip GSE63514 related to cervical cancer in GEO is used as the validation set.Firstly,the limma package of R software is used to screen DEGs of tumor and normal samples,and Venn map of genes re-lated to E6/E7 protein in MigDB is made.Survival analysis is performed by survival kit and verified by ROC and protein expression lev-els.Secondly,key genes are obtained by copy number variation and methylation correlation.Finally,the specific co-expression network is constructed and enrichment analysis and immune infiltration analysis are performed.Result/Conclusion There are 101 differentially expressed genes related to HPV E6/E7 protein,and three genes are found to have significance after screening,namely E2F1,MCM4 and PCNA.At the same time,it is found that the genes in the specific coexpression network are significantly enriched in the DNA replication and chromosome organization pathways.Immune correlation analysis shows that key genes are significantly associated with CD4 T cells,B cells and neutrophils.DNA replication,chromosome organization,etc.,are the molecular mechanisms and key genes significantly related to the development of cervical squamous cell carcinoma and HPV E6/E7 encoded proteins.

Bioinformatics Analysis of Cardiac Aging based on GEO Database / 医学研究杂志

Objective To explore the key genes of cardiac aging by bioinformatic analysis,and conduce to prevent and treat cardio-vascular diseases in the elderly.Methods The gene expression of GSE8146 was downloaded from the Gene Expression Omnibus(GEO)database."R"software was used to screen out differentially expressed genes in the hearts of young and old mice,and DAVID online anal-ysis tool was used for Gene Ontology(GO)function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)signa-ling pathway enrichment analysis of differentially expressed genes.Hub genes were obtained by protein-protein interaction(PPI)analy-sis based on the STRING online database.Results A total of 55 differentially expressed genes were screened,including 22 up-regula-ted genes and 33down-regulated genes.The differentially expressed genes were significantly enriched in lipid metabolism,fatty acid me-tabolism and other processes,mainly involvded in peroxisome proliferators-activated receptor(PPAR)signaling pathway and Adenosine 5′-monophosphate(AMP)-activated protein kinase(AMPK)signaling pathway.The hub genes such as Fasn,Pck1,Adipoq,Cpt1a,Pdk4,Pnpla2,Slc27a1,Hmgcs2,Cidec,Ucp3 were screened out.Conclusion Cardiac aging may be related to the disorder of cellular energy metabolism,and hub genes such as Fasn,Pck1,Adipoq,Cpt1a,Pdk4,Pnpla2,Slc27a1,Hmgcs2,Ucp3,PPAR signaling path-way and AMPK signaling pathway may play an important role in the development of cardiac aging.

Key Genes and Regulatory Networks of Acute-on-chronic Liver Failure Based on Multiple Bioinformatics Analysis / 医学研究杂志

Objective To screen key genes and pathways of acute on-chronic liver failure(ACLF)by multiple bioinformatics,and to provide theoretical basis for molecular biology studies and biomarker screening of ACLF.Methods ACLF transcriptome mRNA mi-croarray data set was downloaded from Gene Expression Omnibus(GEO),and limma package in R software was used to analyze the difference expression genes.The gene ontology(GO)function enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)anal-ysis were analyzed differential genes through David database.Protein-protein interaction(PPI)network was analyzed using STRING da-tabase,the key differential genes were screened by Cytoscape software.Results A total of 329differentially expressed genes were screened,including 185 up-regulated genes and 144 down-regulated genes.GO functional enrichment analysis obtained 385 items,in-cluding immune receptor activity,cytokine receptor activity,T cell receptor binding and other biological functions(P＜0.05).KEGG pathway enrichment analysis screened 36signaling pathways,among which the immune and inflammatory pathways including Th1 and Th2 cell differentiation,Th17 cell differentiation pathway,T cell receptor signaling pathway,primary immune deficiency,NF-κB signaling pathway and TNF signaling pathway.Among these key genes,CD3G,CD3D,IL7R,LCK,IL1R2,IL18R1,IL1R1 and MAPK14 related to ACLF were further obtained,which may become potential biomarkers and therapeutic targets of ACLF.Conclusion This study demon-strates that CD3G,CD3D,IL7R,LCK,IL1R2,IL18R1,IL1R1 and MAPK14may become the core genes related to the occurrence and development of ACLF and new therapeutic targets in the future.

Expression analysis of hypoxic-related differentially expressed genes in ischemic stroke based on gene expression omnibus database / 中国脑血管病杂志

Objective Based on the gene expression omnibus(GEO)database,bioinformatics methods were employed to analyze the expression characteristics of hypoxia-related differentially expressed genes(HRDEGs)in ischemic stroke,and key genes were screened,to provide important support for a deeper understanding of ischemic stroke.Methods The GSE16561 and GSE58294 datasets were downloaded from the GEO database,and Python software was used for data integration.The Combat method was employed to eliminate batch effects while retaining disease grouping characteristics.Principal component analysis was conducted to reduce dimensionality of the data before and after batch effect removal,and intraclass correlation coefficient(ICC)testing was performed on the ischemic stroke and normal control groups.Gene set enrichment analysis(GSEA)and single-sample GSEA were conducted on the merged and batch effects eliminated dataset,with a nominal P-value(NOM P-val)＜0.05 and false discovery rate P-value(FDR P-val)＜0.25 used as criteria to select significantly different gene sets.Differential expression genes between the ischemic stroke samples and normal control samples after merging and eliminating batch effects of the GSE16561 and GSE58294 datasets were identified using R software,with an absolute value of log2 gene expression fold change(FC)≥0.58 and adjusted P-value(Padj)＜0.05 as selection criteria.Intersection with hypoxia-related genes obtained from the National Center for Biotechnology Information(NCBI)in the United States yielded the HRDEGs.Gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)enrichment analyses were performed on the HRDEGs,and the STRING database was used to construct a protein-protein interaction network of differentially expressed genes.The top 10 key genes were filtered using Cytoscape 3.8 software.Results The ICC analysis results showed excellent consistency in the ischemic stroke and normal control samples after batch effect removal,with ICC values of 0.94 and 0.98 for the GSE16561 and GSE58294datasets,respectively.GSEA results demonstrated significant enrichment of 34 gene sets in the stroke samples in the newly merged and batch effects removed dataset from GSE16561 and GSE58294,leading to the identification of 404 differentially expressed genes(all with Padj＜0.05),including 354 upregulated genes and 50 downregulated genes.Intersection with hypoxia-related genes yielded 64 HRDEGs.GO enrichment analysis indicated significant enrichment of HRDEGs in vesicle lumen,cytoplasmic vesicle lumen,secretory granule lumen,with molecular functions such as amide binding,peptide binding,phospholipid binding,and enzyme inhibitor activity.These genes are primarily involved in the positive regulation of cytokine production,regulation of immune response,response to bacterium-derived molecules,and response to lipopolysaccharide,among other biological processes.KEGG enrichment analysis revealed enrichment of HRDEGs in pathways related to lipid and atherosclerosis,Salmonella infection,neutrophil extracellular trap formation,nucleotide-binding oligomerization domain-like receptor signaling pathway,protein glycosylation in cancer,tuberculosis,and necroptosis.Based on the protein-protein interaction network,10 key genes were identified,including arginase1(ARG1),caspase1(CASP1),interleukin1 receptor type 1(IL-1R1),integrin subunit alpha M(ITGAM),matrix metalloproteinase9(MMP9),prostaglandin-endoperoxide synthase 2(PTGS2),signal transducer and activator of transcription 3(STAT3),Toll-like receptor2(TLR2),TLR4,and TLR8.Conclusion This study has identified 10 key genes associated with ischemic stroke and hypoxia through bioinformatics mining,which maybe provid potential targets for subsequent research and diagnostic and therapeutic interventions.