Research On The Mechanism Of Action Of Compound Kushen Injection In The Treatment Of Three Common Tumors Based On Integrated Bioinformatics

BackgroundOn a global scale,liver cancer,pancreatic cancer and lung cancer are the leading cause of both cancer morbidity and mortality,which are threatening people's lives and health,as well as placing a heavy burden on families and society.Traditional Chinese medicine injection(TCMI)has unique advantages in tumor treatment and is widely applied in clinic cases.However,due to the characteristics of multi-component,multi-pathway,multi-target,and multi-function of traditional Chinese medicine(TCM),the therapeutic material basis and mechanism are unclear.Moreover,it has increased the difficulty of research and affected the process of internationalization.Compound Kushen Injection(CKI)possesses the functions of clearing heat,expelling dampness,cooling blood,detoxification,and sanjie analgesic effect.It is extensively used for the treatment of malignant tumors,but the therapeutic mechanism of CKI have not been fully elucidated.Recently,with the rapid development of bioinformatics,new ideas have continuously emerged.Moreover,the combination of network pharmacology and bioinformatics has become an important way to improve the research level of TCM.Given that,this study applied integrated bioinformatics to explore the mechanism of CKI in the treatment of liver cancer,pancreatic cancer and lung cancer.ObjectiveTo discover the hub genes for liver cancer,pancreatic cancer and lung cancer.Adopting a network pharmacology method to gather compounds,predict and screen targets and pathways,and construct networks,and in order to systematically investigate the complex mechanism of CKI on liver cancer,pancreatic cancer and lung cancer.Methods1.Bioinformatics analysisIn the research of hub genes of liver cancer,the gene expression profile datasets were downloaded from the GEO database.For each of them,the differentially expressed genes(DEGs)between hepatocellular carcinoma and corresponding adjacent or normal tissues were filtered using the limma package in R software.Integration of DEGs identified from the datasets was performed by RobustRankAggreg package.A protein-protein interaction(PPI)network was constructed and analyzed using the STRING database and Cytoscape software.The MCODE plug-in was used to conduct module analysis and screen hub clustering modules in the network.The enrichment analyses of Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)were performed with DAVID.Gene Expression Profiling Interactive Analysis(GEPIA)and Kaplan-Meier plotter(KM plotter)were used to determine expression and prognostic values of hub genes.As for the research of hub genes of pancreatic cancer,the RNA sequencing data data and clinical information of patients with pancreatic adenocarcinoma were downloaded from the TCGA database.The WGCNA package was used to construct gene co-expression network,identify gene modules and correlate the gene modules with the clinical information.The module visualization was carried out through Cytoscape software,and the CytoHubba was used to identify the hub genes.The GO enrichment analysis was performed with the clusterProfiler package,and the KEGG pathway enrichment analysis was performed with DAVID.The univariate Cox regression analysis was conducted via the survival package.The genes which screened by P value were further used to perform the multivariate Cox regression analysis,and then built survival-related linear risk assessment model.The Kaplan-Meier curves were used to assess the difference of overall survival between high-and low-risk groups.The receiver operating characteristic(ROC)curves were drawn by survivalROC package,and was used to assess the predictive accuracy of this prognostic model.2.Network pharmacology analysisIn the study of the mechanism of CKI for the treatment of liver cancer,the compounds of CKI were selected form literature,and the targets of these compounds were predicted by STITCH,SuperPred,SwissTargetPrediction,and TCMSP.The hepatocellular carcinoma related genes were gathered from TTD,GEO,and TCGA.The compound-putative target network,compound-hepatocellular carcinoma target network and drug-compound-target-pathway network were established by Cytoscape software.The enrichment analyses of GO and KEGG were performed with DAVID.KM plotter and GEPIA were used to determine prognostic values and correlation of hub genes.The molecular docking simulation was performed with AutoDock.In the study of the mechanism of CKI for the treatment of pancreatic cancer,the compounds of CKI were selected form literature,and the targets of these compounds were predicted by STITCH,SuperPred,SwissTargetPrediction,and TCMSP.The pancreatic cancer related genes were obtained from TTD,TCGA,and the hub genes of WGCNA analysis.The PPI data were obtained from the STRING database.The compound-putative target network,compound-pancreatic cancer target PPI network and drug-compound-PPI target-pathway network were established by Cytoscape software.The MCODE plug-in was used to conduct module analysis screen hub clustering modules in the network.The enrichment analyses of GO and KEGG were performed with DAVID.The molecular docking simulation was performed with AutoDock.In the study of the mechanism of CKI for the treatment of lung cancer,the compounds of CKI were selected form literature,and the targets of these compounds were predicted by STITCH,SuperPred,and SwissTargetPrediction.The lung cancer related genes were obtained from TTD and OMIM.The PPI data were obtained from the STRING database.The compound-putative target network,PPI network of lung cancer targets,compound-lung cancer target network and herb-compound-target-pathway network were established by Cytoscape software.The enrichment analyses of GO and KEGG were performed with DAVID.And the molecular docking simulation was employed to assess the binding potential of selected target-compound pairs.Results1.The results of bioinformatics analysisThirteen microarray datasets of hepatocellular carcinoma were downloaded from GEO.After integrated analysis,380 DEGs(293 downregulated and 87 upregulated)were identified.The PPI network and module analyses showed two hub clustering modules and eleven hub genes(CDK1,CCNB2,CDC20,CCNB1,TOP2A,CCNA2,MELK,PBK,TPX2,KIF20A,and AURKA).Enrichment analyses indicated that the DEGs were significantly enriched in metabolism-associated pathways,and hub genes and module 1 were highly associated with cell cycle pathway.Survival analysis indicated that overexpression of the eleven hub genes was correlated with worse overall survival.Expression and correlation analysis indicated that eleven hub genes were definitely highly expressed in hepatocellular carcinoma tissues compared with normal tissues,and expression of CDK1 was strongly correlated with that of the other hub genes.The RNA sequencing data of pancreatic adenocarcinoma were downloaded from TCGA.And a total of 177 samples and 5000 genes were obtained for further WGCNA analysis.Eleven gene modules were obtained through analysis.The black module and blue module were strongly related to tumor grade and stage,respectively.And they were both associated with vital status.GO enrichment analysis showed that the black module was highly related to the occurrence and development of tumors;the blue module was closely related to differentiation,invasion and metastasis of tumors.KEGG enrichment analysis indicated that the black module was highly associated with cell cycle and p53 signaling pathway;the blue module was mainly related to mucin type O-Glycan biosynthesis,arachidonic acid metabolism,ECM-receptor interaction and tight junction.After network analysis,five hub genes(NCAPG,BUB1,CDK1,TPX2,DLGAP5;INAVA,MST1R,TMPRSS4,TMEM92,SFN)were screened from black and blue modules respectively,and these hub genes were overexpressed in pancreatic adenocarcinoma tissues.The survival analysis showed a five-gene prognostic signature,in which TSPOAP1 was protective prognostic gene,while ADGRG6,GPR87,FAM111B,and MMP28 were risky prognostic genes.2.The results of network pharmacology analysisIn the study for the mechanism of CKI in treating liver cancer,six hub targets(BCHE,SRD5A2,EPHX2,ADH1C,ADH1A,and CDK1)were screened.Among them,CDK1 was high-expressed in hepatocellular carcinoma tissues,and others were low-expressed in hepatocellular carcinoma tissues.GO enrichment analysis showed that the targets related to hepatocellular carcinoma regulated by CKI were mainly involved with cell cycle,regulation of apoptotic process,metabolic process and P450 pathway.KEGG enrichment analysis indicated that these targets were associated with drug metabolism-cytochrome P450 and arachidonic acid metabolism.Furthermore,correlation analysis indicated that SRD5A2,EPHX2,ADH1C,ADH1A had a strong negative correlation with CDK1.Survival analysis indicated that CDK1 was risky prognostic gene,and SRD5A2,EPHX2,ADH1C,ADH1A were protective prognostic genes.In the study for the mechanism of CKI in the treatment of pancreatic cancer,three hub clustering modules and six hub genes(AKT1,MAPK1,MAPK3,EGFR,CDK1,and JAK1)were obtained.GO enrichment analysis showed that the three modules were highly related to cell cycle,cell proliferation,JAK-STAT cascade,MAPK cascade,phosphorylation and regulation of apoptotic process.KEGG enrichment analysis indicated that the three modules were mainly involved with cell cycle,ErbB signaling pathway,PI3K-Akt signaling pathway,and mTOR signaling pathway.In the study for the mechanism of CKI for the treatment of lung cancer,eight hub targets(CHRNA3,DRD2,PRKCA,CDK1,CDK2,CHRNA5,MMP1,and MMP9)were screened.GO enrichment analysis showed that the targets related to lung cancer regulated by CKI were mainly involved with G1/S transition of mitotic cell cycle,protein phosphorylation,regulation of ERK1 and ERK2 cascade,and kinase activity.KEGG enrichment analysis indicated that CKI might exert a therapeutic role in lung cancer by regulating some important pathways,namely,pathways in cancer,proteoglycans in cancer,PI3K-Akt signaling pathway,non-small cell lung cancer,and small cell lung cancer.ConclusionThe current study integrated network pharmacology and bioinformatics to systematically disclose the compounds,targets and pathways of CKI against liver cancer,pancreatic cancer and lung cancer.Meanwhile,this study preliminary suggests that the mechanism of CKI in the treatment of liver cancer,pancreatic cancer and lung cancer might be mainly associated with its synergistic regulation on hub genes and important pathways.The study could provide ideas for study mechanism of TCMI in treating different types of malignant tumors,and provide reference for further basic experimental research of CKI in the treatment of liver cancer,pancreatic cancer and lung cancer,as well as promote the reasonable application of TCM in the clinical treatment of liver cancer,pancreatic cancer and lung cancer.