The mechanism of genistein on hepatocellular carcinoma based on network pharmacology and bioinformatics
Objective To elucidate the mechanism of genistein on hepatocellular carcinoma by network pharmacology and bioinformatics.Methods Network pharmacology,bioinformatics and experimental valida-tion were used.The potential targets of genistein were obtained from the Pharm Mapper database.Gene Cards database was used to obtain the pathogenic genes of hepatocellular carcinoma,and the intersection genes of po-tential targets of genistein and hepatocellular carcinoma-related targets were analyzed and determined.The clinical information of TCGA hepatocellular carcinoma tissue samples and normal tissue samples were used to screen out differentially expressed common target genes,and gene ontology(GO)functional annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis were performed.The dif-ferential genes(DEGs)affecting the overall survival of patients were screened by univariate Cox analysis.The STRING platform was used to construct the target interaction network of DEGs,and the core genes were screened for verification.Molecular docking experiments were performed to detect the effect of genistein on the proliferation of hepatocellular carcinoma.Results A total of 235 potential targets of genistein and 9 415 therapeutic targets of hepatocellular carcinoma were screened out,of which 40 differentially expressed com-mon target genes affected the patient's back.Among them,ESR1,AR,HRAS,CCNA2,MMP9 and CYP3A4 were the core targets.GO functional annotation enrichment analysis obtained 333 enrichment items,and KEGG pathway enrichment analysis obtained 23 enrichment.The results of molecular docking showed that genistein had a strong binding ability with the core target protein.In vitro experiments confirmed that genistein significantly inhibited the proliferation of hepatocellular carcinoma.Conclusion Genistein inhibits the development of hepatocellular carcinoma through multiple metabolic and signaling pathways.The expres-sion levels of ESR1,AR,HRAS,CCNA2,MMP9 and CYP3A4 can be used to predict the prognosis of patients with hepatocellular carcinoma and provide valuable targets for treatment.
万方数据
维普
