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Drug-Target Interaction Network Analysis of Gene-Phenotype Connectivity Maintained by Genistein.

ABSTRACT: Genistein is a type of isoflavone, which has been widely described as an antitumor agent in many cancers. The present study aimed to provide information on the mechanisms of genistein's activity and thus enable a wider range of targeted therapies in hepatitis B virus (HBV)-related liver cancer. We searched the DrugBank database for direct targets of genistein, which were then analyzed through the STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) database to predict their secondary protein targets. Thirteen primary protein targets of genistein and 209 secondary protein targets-associated genes were identified. The data were integrated into the network of protein targets-associated genes and visualized with the Cytoscape software. We further carried out GO (Gene Ontology) analysis and KEGG (Kyoto Encyclopedia of Gene and Genome) pathway analysis using DAVID (database for annotation, visualization, and integrated discovery) tool. The top 14 KEGG pathways were further assessed, and 19 overlapping genes derived from pathways of hepatitis B and cancer were discovered. The overlapping targets were further mapped in the online tool UALCAN to evaluate the survival rate of hepatocellular carcinoma (HCC) patients. We found that the overexpression of Grb2 (growth factor receptor-binding protein 2) (p < 0.0001) was linked to poor overall survival for liver HCC patients, followed by AKT1 (p?=?0.0015) and PIK3CA (p?=?0.0088). The present study analyzes the drug-target-disease network and may prove to be a useful tool in gene-phenotype connectivity for genistein in HBV-related liver cancer. Our data also pave the way for further research on Grb2 during the development of chronic HBV infection in liver cancer.

SUBMITTER: Li B

PROVIDER: S-EPMC7757588 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Drug-Target Interaction Network Analysis of Gene-Phenotype Connectivity Maintained by Genistein.

Li Baoshan B Jiang Yi Y Chu Jingxin J Zhou Qian Q

Journal of computational biology : a journal of computational molecular cell biology 20200416 12

Genistein is a type of isoflavone, which has been widely described as an antitumor agent in many cancers. The present study aimed to provide information on the mechanisms of genistein's activity and thus enable a wider range of targeted therapies in hepatitis B virus (HBV)-related liver cancer. We searched the DrugBank database for direct targets of genistein, which were then analyzed through the STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) database to predict their secon ...[more]

PMID: 32298608

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Project description:PurposeGenistein belongs to the group of isoflavones, which include powerful anticancer agents. Its antitumor properties have been intensively described in many cancers, but related studies assessing ovarian cancer are scarce. The aim of this study was to develop a new method of the underlying mechanisms of genistein's effects and broaden the perspective of targeted therapies in ovarian carcinoma.Materials and methodsGenistein targets were searched in the DrugBank database. Prediction of drug interactions with targets (including secondary targets) was performed with STRING database. Interaction pairs with overall score above 0.9 were recorded for protein-protein interaction (PPI) network generation based on the Cytoscape software. Genes with intense interconnections were grouped into a module. Then, PPI network modules with significance were assessed using Molecular Complex Detection (MCODE) analysis tool. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed for the critical genes. Furthermore, disease targets were searched in Comparative Toxicogenomics Database (CTD). The overlapping targets were studied using a Kaplan-Meier analysis to evaluate ovarian carcinoma survival.ResultsA total of 13 direct targets and 372 secondary targets were identified for genistein and further analyzed with the MCODE analysis tool to identify critical genes. The top 72 genes were further assessed with KEGG. Then, the term "ovarian cancer" was searched in CTD, and 123 genes associated only with the marker "T" or "M" were recorded. Next, seven overlapping genes (CDKN1B, PTEN, EGFR, MAPK1, MAPK3, PIK3C, and AKT1) resulting from the intersection of three pathways and 123 genes were obtained from CTD. Elevated CDKN1B amounts showed correlation with overall survival (log-rank P=0.021) according to Kaplan-Meier analysis.ConclusionThe current findings indicated that drug-target-disease network analysis represents a useful tool in gene-phenotype connectivity for genistein in ovarian cancer. Our result also showed that CDKN1B is worthy of further research.

Project description:BackgroundThe anti-tumor properties of curcumin have been demonstrated for many types of cancer. However, a systematic functional and biological analysis of its target proteins has yet to be fully documented. The aim of this study was to explore the underlying mechanisms of curcumin and broaden the perspective of targeted therapies.MethodsDirect protein targets (DPTs) of curcumin were searched in the DrugBank database. Using the STRING database, the interactions between curcumin and DPTs and indirect protein targets (IPTs) weres documented. The protein-protein interaction (PPI) network of curcumin-mediated proteins was visualized using Cytoscape. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed for all curcumin-mediated proteins. Furthermore, the cancer targets were searched in the Comparative Toxicogenomics Database (CTD). The overlapping targets were studied using Kaplan-Meier analysis to evaluate cancer survival. Further genomic analysis of overlapping genes was conducted using the cBioPortal database. Lastly, MTT, quantitative polymerase chain reaction (qPCR), and western blot (WB) analysis were used to validate the predicted results on hepatocellular carcinoma (HCC) cells.ResultsA total of five DPTs and 199 IPTs were found. These protein targets were found in 121 molecular pathways analyzed via KEGG enrichment. Based on the anti-tumor properties of curcumin, two pathways were selected, including pathways in cancer (36 genes) and HCC (22 genes). Overlapping with 505 HCC-related gene sets identified in CTD, five genes (TP53, RB1, TGFB1, GSTP1, and GSTM1) were finally identified. High mRNA levels of TP53, RB1, and GSTM1 indicated a prolonged overall survival (OS) in HCC, whereas elevated mRNA levels of TGFB1 were correlated with poor prognosis. The viability of both HepG2 cells and Hep3B cells was significantly reduced by curcumin at concentrations of 20 or 30 μM after 48 or 72 h of culture. At a concentration of 20 μM curcumin cultured for 48 h, the expression of TGFB1 and GSTP1 in Hep3B cells was reduced significantly in qPCR analysis, and reduced TGFB1 protein expression was also found in Hep3B cells.

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Drug-Target Interaction Network Analysis of Gene-Phenotype Connectivity Maintained by Genistein.

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Drug-Target Interaction Network Analysis of Gene-Phenotype Connectivity Maintained by Genistein.

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