Mechanism of emodin in treating hepatitis B virus-associated hepatocellular carcinoma: network pharmacology and cell experiments.

Hepatocellular carcinoma (HCC) is a pressing global issue, with Hepatitis B virus (HBV) infection remaining the primary. Emodin, an anthraquinone compound extracted from the natural plant's. This study investigates the molecular targets and possible mechanisms of emodin in treating HBV-related HCC based on network pharmacology and molecular docking and validates the screened molecular targets through in vitro experiments. Potential targets related to emodin were obtained through PubChem, CTD, PharmMapper, SuperPred, and TargetNet databases. Potential disease targets for HBV and HCC were identified using the DisGeNET, GeneCards, OMIM, and TTD databases. A Venn diagram was used to determine overlapping genes between the drug and the diseases. Enrichment analysis of these genes was performed using GO and KEGG via bioinformatics websites. The overlapping genes were imported into STRING to construct a protein-protein interaction network. Cytoscape 3.9.1 software was used for visualizing and analyzing the core targets. Molecular docking analysis of the drug and core targets was performed using Schrodinger. The regulatory effects of emodin on these core targets were validate through in vitro experiments. A total of 43 overlapping genes were identified. GO analysis recognized 926 entries, and KEGG analysis identified 135 entries. The main pathways involved in the KEGG analysis included cancer, human cytomegalovirus infection and prostate cancer. The binding energies of emodin with HSP90AA1, PTGS2, GSTP1, SOD2, MAPK3, and PCNA were all less than -5 kcal/mol. Compared to normal liver tissue, the mRNA levels of XRCC1, MAPK3, and PCNA were significantly elevated in liver cancer tissue. The expression levels of XRCC1, HIF1A, MAPK3, and PCNA genes were closely related to HCC progression. High expressions of HSP90AA1, TGFB1, HIF1A, MAPK3, and PCNA were all closely associated with poor prognosis in HCC. In vitro experiments demonstrated that emodin significantly downregulated the expression of HSP90AA1, MAPK3, XRCC1, PCNA, and SOD2, while significantly upregulating the expression of PTGS2 and GSTP1. This study, based on network pharmacology and molecular docking validation, suggests that emodin may exert therapeutic effects on HBV-related HCC by downregulating the expression of XRCC1, MAPK3, PCNA, HSP90AA1, and SOD2, and upregulating the expression of PTGS2 and GSTP1.

Wang Y ，Li S ，Ren T ，Zhang Y ，Li B ，Geng X ... -  《Frontiers in Cellular and Infection Microbiology》

Exploring the mechanism of aloe-emodin in the treatment of liver cancer through network pharmacology and cell experiments.

Zhu M ，He Q ，Wang Y ，Duan L ，Rong K ，Wu Y ，Ding Y ，Mi Y ，Ge X ，Yang X ，Yu Y ... -  《Frontiers in Pharmacology》

Integrating network pharmacology, bioinformatics, and experimental validation to unveil the molecular targets and mechanisms of galangin for treating hepatocellular carcinoma.

Galangin, a flavonoid compound, is derived from Alpinia officinarum Hance. Previous studies have shown that galangin can inhibit the proliferation of hepatocellular carcinoma (HCC), but its mechanism is still unclear. This study aims to investigate the potential targets and molecular mechanisms of galangin on HCC through network pharmacology, bioinformatics, molecular docking, and experimental in vitro validation. In this study, network pharmacology was used to investigate the targets and mechanisms of galangin in the treatment of HCC. AutoDockTools software was used to simulate and calculate the binding of galangin to its core targets. GO and KEGG enrichment analyses were conducted in the DAVID database to explore the main biological functions and signaling pathways impacted by galangin intervention. In addition, bioinformatics was applied to examine the correlation between the differential expressions of the anti-HCC core targets of galangin and the survival of patients with HCC. Finally, the findings obtained from network pharmacology and bioinformatics were verified in cell experiments. A total of 67 overlapping target genes of galangin and HCC were identified. Through the analysis of the protein-protein interaction (PPI) network, 10 hub genes with the highest degree of freedom were identified, including SRC, ESR1, MMP9, CDK4, CCNB1, MMP2, CDK2, CDK1, CHK1, and PLK1. These genes were found to be closely related to the degradation of the extracellular matrix, signal transduction, and the cell cycle. GO and KEGG enrichment analyses revealed that galangin exerts an anti-HCC role by affecting various signaling pathways, including the cell cycle, pathways in cancer, and the PI3K-Akt signaling pathway. The results of molecular docking indicated a significant interaction between galangin and CCNB1, CDK4, CDK1, and PLK1. Bioinformatics analysis revealed that CCNB1, CDK4, CDK1, and PLK1 were upregulated in the liver of patients with HCC at both the mRNA and protein levels. Flow cytometry analysis showed that galangin induced G0/G1 phase arrest and cell apoptosis in HepG2 and Huh7 cells. Additionally, galangin suppressed the expression of key proteins and mRNAs involved in the cell cycle pathway. These results suggest that galangin inhibits the growth of HCC cells by arresting the cell cycle at the G0/G1 phase.

Li X ，Zhou M ，Chen W ，Sun J ，Zhao Y ，Wang G ，Wang B ，Pan Y ，Zhang J ，Xu J ... -  《BMC Complementary Medicine and Therapies》

Research on the Regulatory Mechanism of Ginseng on the Tumor Microenvironment of Colorectal Cancer based on Network Pharmacology and Bioinformatics Validation.

A network pharmacology study on the biological action of ginseng in the treatment of colorectal cancer (CRC) by regulating the tumor microenvironment (TME). To investigate the potential mechanism of action of ginseng in the treatment of CRC by regulating TME. This research employed network pharmacology, molecular docking techniques, and bioinformatics validation. Firstly, the active ingredients and the corresponding targets of ginseng were retrieved using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), the Traditional Chinese Medicine Integrated Database (TCMID), and the Traditional Chinese Medicine Database@Taiwan (TCM Database@Taiwan). Secondly, the targets related to CRC were retrieved using Genecards, Therapeutic Target Database (TTD), and Online Mendelian Inheritance in Man (OMIM). Tertiary, the targets related to TME were derived from screening the GeneCards and National Center for Biotechnology Information (NCBI)-Gene. Then the common targets of ginseng, CRC, and TME were obtained by Venn diagram. Afterward, the Protein-protein interaction (PPI) network was constructed in the STRING 11.5 database, intersecting targets identified by PPI analysis were introduced into Cytoscape 3.8.2 software cytoHubba plugin, and the final determination of core targets was based on degree value. The OmicShare Tools platform was used to analyze the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the core targets. Autodock and PyMOL were used for molecular docking verification and visual data analysis of docking results. Finally, we verified the core targets by Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) databases in bioinformatics. A total of 22 active ingredients and 202 targets were identified to be closely related to the TME of CRC. PPI network mapping identified SRC, STAT3, PIK3R1, HSP90AA1, and AKT1 as possible core targets. Go enrichment analysis showed that it was mainly involved in T cell co-stimulation, lymphocyte co-stimulation, growth hormone response, protein input, and other biological processes; KEGG pathway analysis found 123 related signal pathways, including EGFR tyrosine kinase inhibitor resistance, chemokine signaling pathway, VEGF signaling pathway, ErbB signaling pathway, PD-L1 expression and PD-1 checkpoint pathway in cancer, etc. The molecular docking results showed that the main chemical components of ginseng have a stable binding activity to the core targets. The results of the GEPIA database showed that the mRNA levels of PIK3R1 were significantly lowly expressed and HSP90AA1 was significantly highly expressed in CRC tissues. Analysis of the relationship between core target mRNA levels and the pathological stage of CRC showed that the levels of SRC changed significantly with the pathological stage. The HPA database results showed that the expression levels of SRC were increased in CRC tissues, while the expression of STAT3, PIK3R1, HSP90AA1, and AKT1 were decreased in CRC tissues. Ginseng may act on SRC, STAT3, PIK3R1, HSP90AA1, and AKT1 to regulate T cell costimulation, lymphocyte costimulation, growth hormone response, protein input as a molecular mechanism regulating TME for CRC. It reflects the multi-target and multi-pathway role of ginseng in modulating TME for CRC, which provides new ideas to further reveal its pharmacological basis, mechanism of action and new drug design and development.

Wang T ，Zhang W ，Fang C ，Wang N ，Zhuang Y ，Gao S ... -  《-》

Study on the mechanism of quercetin in Sini Decoction Plus Ginseng Soup to inhibit liver cancer and HBV virus replication through CDK1.

To explore the anti-tumor and anti-virus key active ingredients of Sini Decoction Plus Ginseng Soup (SNRS) and their mechanisms. The main ingredients of SNRS were analyzed by network pharmacology, and quercetin was identified as the key active ingredient. Then, we obtained the targets of quercetin by using Drugbank, PharmMapper, and SwissTargetPrediction databases. Then, the targets of HBV-related hepatocellular carcinoma (HBV-related HCC) were obtained by using Genecards database. In addition, using the gene expression profiles of HBV-related HCC patients in GEO database and the genes with the greatest survival difference in GEPIA 2 database identified the potential targets of quercetin. In addition, the mechanism of potential genes was studied through GO, KEGG analysis, and PPI network. Using AUC and survival analysis to evaluate the diagnostic and prognostic value of cyclin-dependent kinase 1 (CDK1) and CCNB1. Finally, the effects of quercetin on proliferation of Hep3B and HepG2215 cells and the level of CDK1 and CCNB1 were verified in vitro. ELISA was used to measure the expression levels of hepatitis B surface antigen (HBsAg) and hepatitis B e antigen (HBeAg) after the intervention by quercetin for 24 h and 48 h in HepG2215 cell. The first 10 key ingredients of SNRS were identified, and quercetin was the most key ingredient. The 101 potential quercetin targets were identified for the treatment of HBV-related HCC. GO and KEGG showed that 101 potential target enrichment in cancer and cell cycle regulation. By Venn analysis, CDK1 and CCNB1 were intersection targets, which could be used as potential targets for the action of quercetin on HBV-related HCC. Moreover, the expression of CDK1 and CCNB1 was highly expressed in the high-risk group, while the OS rate was low. The 1-year, 3-year and 5-year area under the curve (AUC) curves of CDK1 and CCNB1 were 0.724, 0.676, 0.622 and 0.745, 0.678, 0.634, respectively. Moreover, experimental results also showed that quercetin inhibited cell proliferation and reduced CDK1 expression in Hep3B and HepG2215 cells. The expressions of HBsAg and HBeAg in HepG2215 cell supernatant and cell gradually decreased with the increase of intervention time of quercetin and CDK1 inhibitor. Quercetin is a key ingredient of anti-HBV-related HCC activity and inhibits HBV replication in SNRS by inhibiting CDK1.

Hao L ，Li S ，Chen G ，Nie A ，Zeng L ，Xiao Z ，Hu X ... -  《-》