Network-based pharmacology to predict the mechanism of Ginger and Forsythia combined treatment of viral pneumonia

Background: Viral pneumonia (VP) is a common inflammatory disease caused by a virus in the upper respiratory tract. However, current treatment options for pneumonia are limited because of the strong infectivity and lack of research. Method: Based on various databases, the mechanisms of Ginger and Forsythia were predicted by network pharmacology. The possible active ingredients of Ginger and Forsythia were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and screened by pharmacokinetic parameters. Their possible targets were predicted by the TCMSP database. The VP-related targets were collected from the GeneCards and OMIM databases. The compound-target-disease network was visualized by Cytoscape 3.7.1. In addition, the protein functional annotation and identification of signalling pathways of possible targets were performed with Gene Ontology (GO) and KEGG enrichment analysis. Molecular docking was finally employed for in silico simulation matching between representative Ginger and Forsythia compounds and their core genes. Results: Twenty-eight active ingredients of Ginger and Forsythia were found and 30 common targets for the combined treatment of VP were obtained. The enrichment analysis of GO functions and KEGG pathways included 186 GO function entries and 56 KEGG pathways. Molecular docking showed that the main ingredients can closely bind three targets (CASP3, JUN, and ESR1). Thus, Ginger and Forsythia play significant roles in the prevention and treatment of VP, and this study showed their mechanism was “multicomponent, multitarget, and multipathway” for the prevention and treatment of VP. Conclusion: We successfully predicted the active components and targets of Ginger and Forsythia for prevention and treatment of VP. This may systematically clarify its mechanism of action and provide a direction for future research.     

Identification of the key pathways and genes involved in HER2-positive breast cancer with brain metastasis

BackgroundThe risk of brain metastasis (BM) in HER2-positive (+) breast cancer (BC) patients is significantly higher than that in HER2-negative (-) BC patients. The high incidence and mortality rate makes it urgent to elucidate the key pathways and genes involved and identify patients who are more at risk of developing BM.Materials and methodsTo identify the target genes in HER2+BC patients with BM, we analyzed the microarray datasets (GSE43837) derived from the Gene Expression Omnibus (GEO) database. The GEO2R tool was used to extract the differentially expressed genes (DEGs) involved in HER2+ primary BC and BC with BM. Bioinformatics methods including Gene Ontology (GO) functional annotation analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed with the screened DEGs. The protein-protein interactions of the DEGs were analyzed using the Search Tool for the Retrieval of Interacting Genes (STRING) database and visualized using Cytoscape software. Finally, GSEA analysis was performed to identify the hub genes and the important pathways.ResultsA total of 751 upregulated and 285 downregulated DEGs were identified. The GO function and KEGG pathway enrichment analyses indicated that the DEGs were all enriched in the protein binding molecular function. The top five hub nodes were screened out, included PHLPP1, UBC, ACACB, TGFB1, and ACTB. The GSEA results demonstrated that the five hub genes are mainly enriched in the ribosomal pathway.ConclusionOur study suggests that the five hub genes (PHLPP1, UBC, ACACB, TGFB1, and ACTB) are associated with HER2+BC with BM. The GSEA analysis revealed that the ribosomal pathway seems to play a very important role in the pathogenesis of HER2+BC with BM.     

Using network pharmacology approaches to identify treatment mechanisms for codonopsis in esophageal cancer

Objective: We explored codonopsis mechanisms for the treatment of esophageal cancer using a network pharmacology approach. Materials and methods: Using the Laboratory of Systems Pharmacology website, codonopsis compounds and targets were gathered. After identifying esophageal cancer target intersections from the GeneCards website, possible codonopsis targets for esophageal cancer were screened. A protein-protein interaction (PPI) network diagram of protein targets was then constructed using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analyses were performed in R 3.6.0 software. A network diagram of “disease-drug-component-target-pathways” was also constructed using Cytoscape 3.7.1. Results: We screened 21 codonopsis compounds as possible esophageal cancer treatments and 31 drug-disease intersecting targets. GO enrichment analysis identified 778 biological process (BP) components, 15 cellular component (CC) components, and 50 molecular function (MF) components, and KEGG analyses identified 90 signaling pathways. Our analyses showed that p53 and PI3K-Akt signaling pathways (among others) were significant pathways in these processes. Conclusions: Codonopsis may be used to treat esophageal cancer by multiple components, targets, and pathways.     

Identification of core genes and potential molecular mechanisms in breast cancer using bioinformatics analysis

BackgroundBreast cancer is the most frequently diagnosed cancer in women worldwide. This study aimed to elucidate the potential key candidate genes and pathways in breast cancer.MethodsThe gene expression profile dataset GSE65212 was downloaded from GEO database. Differentially expressed genes (DEGs) were obtained by the R Bioconductor packages. The Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed using DAVID database. The protein–protein interaction (PPI) network was then established by STRING and visualized by Cytoscape software. Module analysis of the PPI network was performed by the plug-in Molecular Complex Detection (MCODE). Then, the identified genes were verified by Kaplan–Meier plotter online database and quantitative real-time PCR (qPCR) in breast cancer tissue samples.ResultsA total of 857 differential expressed genes were identified, of which, the upregulated genes were mainly enriched in the cell cycle, while the downregulated genes were mainly enriched in PPAR signaling pathway. Moreover, six hub genes with high degree were identified, including TOP2A, PCNA, CCNB1, CDC20, BIRC5 and CCNA2. Lastly, the Kaplan–Meier plotter online database confirmed that higher expression levels of these hub genes were related to lower overall survival. Experimental validation showed that all six hub genes had the same expression trend as predicted.ConclusionThese results identified key genes, which could be used as a new biomarker for breast cancer diagnosis and treatment.     

Sulfatase 1 and sulfatase 2 in hepatocellular carcinoma: associated signaling pathways, tumor phenotypes, and survival

The heparin-degrading endosulfatases sulfatase 1 (SULF1) and sulfatase 2 (SULF2) have opposing effects in hepatocarcinogenesis despite structural similarity. Using mRNA expression arrays, we analyzed the correlations of SULF expression with signaling networks in human hepatocellular carcinomas (HCCs) and the associations of SULF expression with tumor phenotype and patient survival. Data from two mRNA microarray analyses of 139 and 36 HCCs and adjacent tissues were used as training and validation sets. Partek and Metacore software were used to identify SULF correlated genes and their associated signaling pathways. Associations between SULF expression, the hepatoblast subtype of HCC, and survival were examined. Both SULF1 and 2 had strong positive correlations with periostin, IQGAP1, TGFB1, and vimentin and inverse correlations with HNF4A and IQGAP2. Genes correlated with both SULFs were highly associated with the cell adhesion, cytoskeletal remodeling, blood coagulation, TGFB, and Wnt/β-catenin and epithelial mesenchymal transition signaling pathways. Genes uniquely correlated with SULF2 were more associated with neoplastic processes than genes uniquely correlated with SULF1. High SULF expression was associated with the hepatoblast subtype of HCC. There was a bimodal effect of SULF1 expression on prognosis, with patients in the lowest or highest tertile having a worse prognosis than those in the middle tertile. SULFs have complex effects on HCC signaling and patient survival. There are functionally similar associations with cell adhesion, ECM remodeling, TGFB, and WNT pathways, but also unique associations of SULF1 and SULF2. The roles and targeting of the SULFs in cancer require further investigation.     

The clinical significance and potential molecular mechanism of integrin subunit beta 4 in laryngeal squamous cell carcinoma

The relationship between integrin beta 4 (ITGB4) expression and laryngeal squamous cell carcinoma (LSCC) remains unclarified. The object of the present study was to explore the clinical significance and potential molecular mechanism of ITGB4 in LSCC. The protein level of ITGB4 was significantly higher in 46 LSCC patients than in 26 non-LSCC tissues detected by in-house immunohistochemistry. Consistently, ITGB4 mRNA level was also greatly upregulated based on microarray and RNA-seq data (standard mean difference, SMD = 1.62, 95 % CI: 1.23–2.00). And the area under curves (AUC) of summary receiver operator characteristic (SROC) was 0.87 (95 % CI: 0.84–0.90) based on 172 cases of LSCC and 59 cases of non-cancerous controls. Ninety genes were intersected by the ITGB4 related genes and LSCC differential expressed genes (DEGs) from all available microarray and RNA-seq datasets. Based on Gene Ontology (GO) analysis, the top terms of biological process (BP), cellular component (CC) and molecular function (MF) for the 90 ITGB4 related DEGs were extracellular matrix organization, basement membrane and extracellular matrix structural constituent, respectively. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that ITGB4 related DEGs mainly participated in the pathways of ECM-receptor interaction, Focal adhesion and Small cell lung cancer. Moreover, the Protein-Protein Interaction (PPI) network indicated that ITGA3, ITGA5, ITGB4, MET, LAMA3, and COL4A1 might be the core genes of LSCC development related to ITGB4. In conclusion, high ITGB4 expression may lead to the occurrence and development of LSCC via various signaling pathways.     

NLRP3 inflammasome blockade reduces adipose tissue inflammation and extracellular matrix remodeling

The NLRP3-IL-1β pathway plays an important role in adipose tissue (AT)-induced inflammation and the development of obesity-associated comorbidities. We aimed to determine the impact of NLRP3 on obesity and its associated metabolic alterations as well as its role in adipocyte inflammation and extracellular matrix (ECM) remodeling. Samples obtained from 98 subjects were used in a case−control study. The expression of different components of the inflammasome as well as their main effectors and inflammation- and ECM remodeling-related genes were analyzed. The impact of blocking NLRP3 using siRNA in lipopolysaccharide (LPS)-mediated inflammation and ECM remodeling signaling pathways was evaluated. We demonstrated that obesity (P < 0.01), obesity-associated T2D (P < 0.01) and NAFLD (P < 0.05) increased the expression of different components of the inflammasome as well as the expression and release of IL-1β and IL-18 in AT. We also found that obese patients with T2D exhibited increased (P < 0.05) hepatic gene expression levels of NLRP3, IL1B and IL18. We showed that NLRP3, but not NLRP1, is regulated by inflammation and hypoxia in visceral adipocytes. We revealed that the inhibition of NLRP3 in human visceral adipocytes significantly blocked (P < 0.01) LPS-induced inflammation by downregulating the mRNA levels of CCL2, IL1B, IL6, IL8, S100A8, S100A9, TLR4 and TNF as well as inhibiting (P < 0.01) the secretion of IL1-β into the culture medium. Furthermore, blocking NLRP3 attenuated (P < 0.01) the LPS-induced expression of important molecules involved in AT fibrosis (COL1A1, COL4A3, COL6A3 and MMP2). These novel findings provide evidence that blocking the expression of NLRP3 reduces AT inflammation with significant fibrosis attenuation.     

去分化脂肪肉瘤潜在核心基因的生物信息学预测及分析

目的 探讨去分化脂肪肉瘤的潜在核心基因在其恶性生物学行为中的作用.方法 获取基因表达数据库(gene expres-sion omnibus,GEO)数据库中GSE21122和GSE52390的芯片数据,通过GEO2R筛选差异表达基因,对差异表达基因进行GO功能、KEGG通路富集分析和蛋白互作分析,并用Cytoscap...     

Identification of gene ontology and pathways implicated in suicide behavior: Systematic review and enrichment analysis of GWAS studies

Multiple large‐scale studies such as genome‐wide association studies (GWAS) have been performed to identify genetic contributors to suicidal behaviors (SB). We aimed to summarize and analyze the information obtained in SB GWAS, to explore the biological process gene ontology (GO) of genes associated with SB from GWAS, and to determine the possible implications of the genes associated with SB in Kyoto encyclopedias of genes and genomes (KEGG) biological pathways. The articles included in the analysis were obtained from PubMed and Scopus databases. Enrichment analyses were performed in Enrichr to evaluate the KEGG pathways and GO of the genes associated with SB of GWAS. The findings of biological process GO analysis showed 924 GO involved in genes related with SB; of those, the regulation of glucose import in response to insulin stimulus, regulation of protein localization to plasma membrane, positive regulation of endopeptidase activity, heterotypic cell–cell adhesion, regulation of cardiac muscle cell contraction, positive regulation of protein localization to plasma membrane, and positive regulation of protein localization to cell periphery biological process GO showed significant statistical association. Furthermore, we obtained 130 KEGG pathways involved in genes related with SB, which Aldosterone synthesis and secretion, Rap1 signaling pathway and arrhythmogenic right ventricular cardiomyopathy pathways showed a significant statistical association. These findings give a better perspective of the biological participation of genes associated with SB, which will be important to perform adequate strategies to prevent and treat SB.     

Next generation sequencing targeted detection of somatic mutations in patients with mucinous adenocarcinoma of the appendix

The aim of this study was to investigate the mutations in mucinous adenocarcinoma of the appendix (MAA). SNV was detected in 15 patients with MAA, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and reactome pathway analyses were performed. Tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH), microsatellite instability (MSI) was analysis. Finally, the human leukocyte antigen (HLA) typing of the samples was detected. The results showed that TP53 (27 %) and KRAS (20 %) were the highest mutation frequency in the sample, mainly occur in p53 pathway and RTK-RAS pathway. GO analysis reveals mutated genes are closely related to the regulation of GTPase activity, regulation of small GTPase mediated signal transduction and other BP, related to the CC and MF. Analysis of KEGG pathways indicated that the top canonical pathways associated with SNV was Wnt signaling pathway. Reactome pathway analysis further revealed that the mutant genes were closely related to muscle contraction. Only one patient had moderate TMB level and one patient with high MSI. In conclusion, the most common mutated genes and the signaling pathways closely related to MAA development were detected in this study, which will contribute to the development of immunotherapy for patients with MAA.     

In vitro differentiation of bone marrow mesenchymal stem cells into endometrial epithelial cells in mouse: a proteomic analysis

Objective: Mouse bone marrow mesenchymal stem cells (BMSCs) have been demonstrated to differentiate into female endometrial epithelial cells (EECs) in vivo. Our previous studies demonstrated that BMSCs can differentiate in the direction of EECs when co-cultured with endometrial stromal cells in vitro. Here, we obtain and analyse differential proteins and their relevant pathways in the process of BMSCs differentiating into EECs by isobaric tags for relative and absolute quantitation (iTRAQ) proteomic analysis. Methods: A 0.4-μm pore size indirect co-culture system was established with female mice endometrial stromal cells (EStCs) restricted in the upper Transwell chamber and BMSCs in the lower well plate. After indirect co-culture for several days, the BMSCs were revealed to progressively differentiate towards EECs in vitro. Then, four groups were divided according to different co-culture days with single culture groups of BMSCs as controls. Proteins were detected using iTRAQ based on 2DLC-ESI-MS/MS and data were analysed by bioinformatics. Results: A total number of 311 proteins were detected, of which 210 proteins were identified with relative quantitation. Among them, 107 proteins were differentially expressed with a 1.2-fold change as the benchmark, with 61 up-regulated and 46 down-regulated proteins. Differential proteins CK19 and CK8 were epithelial markers and upregulated. Stromal marker vimentin were downregulated. Top canonical pathways was “remodeling of epithelial adhesions junctions” and “actin cytoskeleton signaling”. Top networks was “cell-to-cell signaling and interaction, tissue development and cellular movement” regulated by ERK/MAPK and α-catenin. Conclusion: To the best of our knowledge, this is the first preliminary study of differential protein expression in the differentiation process of BMSCs into EECs in vitro. We further elucidated BMSCs differentiated in the direction of EECs. In addition, ERK/MAPK and α-catenin played important roles by regulating core differential proteins in the “cell-to-cell signaling and interaction, tissue development and cellular movement” network.     

Investigation of microRNA expression signatures in HCC via microRNA Gene Chip and bioinformatics analysis

BackgroundDysregulation of miRNAs is closely involved with hepatocellular carcinoma (HCC) progression, oncogenesis and signalling pathways. The aim of this study was to investigate differences in expression of miRNAs in HCC tissue in comparison to healthy liver tissue, as well as to explore the key miRNA-targeted genes.MethodsGene Chip microarray analysis was used to analyse differentially expressed miRNAs (DEMs) in tissues, and qRT-PCR was performed to validate the top 9 downregulated miRNAs. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed for target genes using the DAVID database. A protein-protein interaction (PPI) network of the target genes was created by STRING and visualised using Cytoscape. Three online miRNA databases were utilised to aid in the prediction of genes targeted by the top 10 significantly altered DEMs.ResultsIn total, 153 upregulated and 206 downregulated miRNAs were identified in HCC tissue. The genes targeted by the top 10 increased and decreased miRNAs were 6 and 1060, respectively. Moreover, FOXO1 was projected to be regulated by all twenty miRNAs. A PPI network was constructed that consisted of 956 nodes and 1298 edges. Four significant modules, consisting of 66 hub genes, were detected from the PPI system via MCODE. Functional enrichment demonstrated that miRNAs have a vital function in cancer development and advancement.ConclusionIn summary, our study identified DEMs in HCC tissue, major target genes and possible molecular mechanisms that underlie HCC, providing novel insights for treatment approaches.     

Pathway-based genome-wide association analysis of coronary heart disease identifies biologically important gene sets

Genome-wide association (GWA) studies of complex diseases including coronary heart disease (CHD) challenge investigators attempting to identify relevant genetic variants among hundreds of thousands of markers being tested. A selection strategy based purely on statistical significance will result in many false negative findings after adjustment for multiple testing. Thus, an integrated analysis using information from the learned genetic pathways, molecular functions, and biological processes is desirable. In this study, we applied a customized method, variable set enrichment analysis (VSEA), to the Framingham Heart Study data (404 467 variants, n=6421) to evaluate enrichment of genetic association in 1395 gene sets for their contribution to CHD. We identified 25 gene sets with nominal P<0.01; at least four sets are previously known for their roles in CHD: vascular genesis (GO:0001570), fatty-acid biosynthetic process (GO:0006633), fatty-acid metabolic process (GO:0006631), and glycerolipid metabolic process (GO:0046486). Although the four gene sets include 170 genes, only three of the genes contain a variant ranked among the top 100 in single-variant association tests of the 404 467 variants tested. Significant enrichment for novel gene sets less known for their importance to CHD were also identified: Rac 1 cell-motility signaling pathway (h_rac1 Pathway, P<0.001) and sulfur amino-acid metabolic process (GO:0000096, P<0.001). In summary, we showed that the pathway-based VSEA can help prioritize association signals in GWA studies by identifying biologically plausible targets for downstream searches of genetic variants associated with CHD.     

Brief Exercises Affect Gene Expression in Circulating Monocytes

We aimed to give a systematic hypothesis on the functions of exercise on circulating monocytes by identifying a discrete set of genes in circulating monocytes that were altered by exercise. The microarray expression profile of GSE51835 was downloaded from gene expression omnibus (GEO) database for the identification of differentially expressed genes (DEGs) using limma and affy packages in R language. Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed for DEGs, followed by the construction of co‐expression network and protein–protein interaction (PPI) network. The top 10 nodes in PPI network were screened, and subnetwork was constructed for the key genes identification. Totally, 35 DEGs, including 2 upregulated genes and 33 downregulated genes, were identified. The enriched GO terms were mainly linked to immune response and defence response, and the enriched KEGG pathways were mainly associated with natural killer cell‐mediated cytotoxicity and graft‐versus‐host disease. Dual‐specificity phosphatase 2 (DUSP2) was identified as a key node in the co‐expression network. In the PPI network, CD247 module (CD247), chemokine (C‐X‐C motif) receptor 4 (CXCR4), granzyme B (GZMB) and perforin 1 (PRF1) were identified as key nodes. An important interaction, GZMB/PRF1, was detected. Five key genes, including DUSP2, CD247, CXCR4, GZMB and PRF1, and an interaction of GZMB/PRF1, were significant factors in the immune processes of circulating monocytes, which might be regulated by brief exercises, leading to the enhancement of immune function.     

Identification of key genes and pathways in castrate-resistant prostate cancer by integrated bioinformatics analysis

ObjectiveTo identify hub genes and pathways involved in castrate-resistant prostate cancer (CRPC).MethodsThe gene expression profiles of GSE70768 were downloaded from Gene Expression Omnibus (GEO) datasets. A total of 13 CRPC samples and 110 tumor samples were identified. The differentially expressed genes (DEGs) were identified, and the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis was performed. Protein-protein interaction (PPI) network module analysis was constructed and performed in Cytoscape software. Weighted correlation network analysis (WGCNA) was conducted to determine hub genes involved in the development and progression of CRPC. The gene expression profiles of GSE80609 were used for validation.ResultsA total of 1738 DEGs were identified, consisting of 962 significantly down-regulated DEGs and 776 significantly upregulated DEGs for the subsequent analysis. GO term enrichment analysis suggested that DEGs were mainly enriched in the extracellular matrix organization, extracellular exosome, extracellular matrix, and extracellular space. KEGG pathway analysis found DEGs significantly enriched in the focal adhesion pathway. PPI network demonstrated that the top 10 hub genes were ALB, ACACB, KLK3, CDH1, IL10, ALDH1A3, KLK2, ALDH3B2, HBA1, COL1A1. Also, WGCNA identified the top 5 hub genes in the turquoise module, including MBD4, BLZF1, PIP5K2B, ZNF486, LRRC37B2. Plus, the Venn diagram demonstrated that HBA1 was the key gene in both GSE70768 and GSE80609 datasets.ConclusionsThese newly identified genes and pathways could help urologists understand the differences in the mechanism between CRPC and PCa. Besides, it might be promising targets for the treatment of CRPC.     

利什曼原虫感染树突状细胞早期基因表达差异分析及关键基因筛选

目的:分析利什曼原虫感染树突状细胞(DCs)早期的基因表达与信号通路变化,探究DCs感染后应答,寻找利什曼原虫感染后基于DCs的免疫治疗方法。方法:GEO数据库下载利什曼原虫感染前后DCs基因芯片数据,RStudio软件筛选差异表达基因(DEGs),STRING构建DEGs蛋白质相互作用网络(PPI),Cytoscape筛选差异表达蛋白质的核心模块,RStudio软件对DEGs进行GO和KEGG富集分析。结果:共筛选出DEGs 129个,其中IL12B与CXCL10差异最为显著,GO分析共富集23个过程,主要涉及病毒感染过程相关细胞反应及Ⅰ-IFN相关免疫反应;KEGG分析共富集3条信号通路,分别为甲型流感、麻疹及DNA复制信号通路。结论:利什曼原虫感染DCs前后Ⅰ-IFN信号通路和TLR4/NF-κB信号通路激活,影响IL12表达,提示Ⅰ-IFN/IL12信号通路与TLR4/NF-κB/IL12信号通路可作为利什曼原虫感染治疗的靶点,CXCL10也有望成为潜在的治疗靶点;利什曼原虫感染后,出现类似病毒感染现象,推测抗病毒免疫疗法可能在对抗利什曼原虫感染中具有一定疗效。     

Gene expression profiling analysis of lung adenocarcinoma

The present study screened potential genes related to lung adenocarcinoma, with the aim of further understanding disease pathogenesis. The {"type":"entrez-geo","attrs":{"text":"GSE2514","term_id":"2514"}}GSE2514 dataset including 20 lung adenocarcinoma and 19 adjacent normal tissue samples from 10 patients with lung adenocarcinoma aged 45-73 years was downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) between the two groups were screened using the t-test. Potential gene functions were predicted using functional and pathway enrichment analysis, and protein-protein interaction (PPI) networks obtained from the STRING database were constructed with Cytoscape. Module analysis of PPI networks was performed through MCODE in Cytoscape. In total, 535 upregulated and 465 downregulated DEGs were identified. These included ATP5D, UQCRC2, UQCR11 and genes encoding nicotinamide adenine dinucleotide (NADH), which are mainly associated with mitochondrial ATP synthesis coupled electron transport, and which were enriched in the oxidative phosphorylation pathway. Other DEGs were associated with DNA replication (PRIM1, MCM3, and RNASEH2A), cell surface receptor-linked signal transduction and the enzyme-linked receptor protein signaling pathway (MAPK1, STAT3, RAF1, and JAK1), and regulation of the cytoskeleton and phosphatidylinositol signaling system (PIP5K1B, PIP5K1C, and PIP4K2B). Our findings suggest that DEGs encoding subunits of NADH, PRIM1, MCM3, MAPK1, STAT3, RAF1, and JAK1 might be associated with the development of lung adenocarcinoma.     

基于网络药理学和分子对接探讨蠲痹汤治疗骨关节炎的机制

目的采用网络药理学和分子对接探讨蠲痹汤治疗骨关节炎的机制。方法应用TCMSP数据库获取蠲痹汤的活性成分和对应靶点,检索GeneCards数据库、OMIM数据库、PharmGkb数据库和TTD数据库获得骨关节炎的治疗靶点。运用R语言软件(版本4.0.2)获得蠲痹汤治疗骨关节炎的交集靶点,使用Cytoscape软件(版本3.8.0)构建“活性成分—治疗靶点”网络并将关键成分进行排序,同时通过蛋白质相互作用(PPI)网络筛选出其核心靶点。运用R语言软件对蠲痹汤治疗骨关节炎的作用靶点进行基因本体(GO)富集分析和京都基因与基因组百科全书(KEGG)富集分析。运用AutoDockVina(版本1.1.2)等软件对上述核心靶点及关键成分进行分子对接验证。结果应用TCMSP数据库共得到蠲痹汤活性成分165个及对应靶点2529个,药物药效靶点与骨关节炎治疗靶点取交集得到115个靶点,关键成分有槲皮素、山柰酚、柚皮素等,核心靶点有STAT3、TNF、MAPK14等。GO富集分析得到2306个生物过程条目,144个分子功能条目,69个细胞组成条目;KEGG富集分析得到TNF信号通路、IL-17信号通路、PI3K-AKT信号通路等相关通路。分子对接结果显示,蠲痹汤治疗骨关节炎的关键成分槲皮素、山柰酚、柚皮素、甘草酮A、刺芒柄花素与其对应的核心靶点有较好的结合性。结论蠲痹汤可能通过多成分、多靶点、多通路的相互作用发挥对骨关节炎的治疗作用。