Exploring the Molecular Mechanisms of Huaier on Modulating Metabolic Reprogramming of Hepatocellular Carcinoma: A Study based on Network Pharmacology, Molecular Docking and Bioinformatics.

Wan Y ，Jiang H ，Liu Z ，Bai C ，Lian Y ，Zhang C ，Zhang Q ，Huang J ... -  《-》

A Strategy based on Bioinformatics and Machine Learning Algorithms Reveals Potential Mechanisms of Shelian Capsule against Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a prevalent and life-threatening form of cancer, with Shelian Capsule (SLC), a traditional Chinese medicine (TCM) formulation, being recommended for clinical treatment. However, the mechanisms underlying its efficacy remain elusive. This study sought to uncover the potential mechanisms of SLC in HCC treatment using bioinformatics methods. Bioactive components of SLC were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and HCC-related microarray chip data were sourced from the Gene Expression Omnibus (GEO) database. The selection criteria for components included OB ≧ 30% and DL ≧ 0.18. By integrating the results of differential expression analysis and weighted gene co-expression network analysis (WGCNA), disease-related genes were identified. Therapeutic targets were determined as shared items between candidate targets and disease genes. Protein-protein interaction (PPI) network analysis was conducted for concatenated genes, with core protein clusters identified using the MCODE plugin. Machine learning algorithms were applied to identify signature genes within therapeutic targets. Subsequently, immune cell infiltration analysis, single-cell RNA sequencing (sc-RNA seq) analysis, molecular docking, and ADME analysis were performed for the screened genes. A total of 153 SLC ingredients and 170 candidate targets were identified, along with 494 HCCrelated disease genes. Overlapping items between disease genes and drug candidates represented therapeutic genes, and PPI network analysis was conducted using concatenated genes. MCODE1 and MCODE2 cluster genes underwent Disease Ontology (DO), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Four signature genes (TOP2A, CYP1A2, CYP2B6, and IGFBP3) were identified from 28 therapeutic genes using 3 machine learning algorithms, with ROC curves plotted. Molecular docking validated the interaction modes and binding abilities between signature genes and corresponding compounds, with free binding energy all <-7 kcal/mol. Finally, ADME analysis revealed similarities between certain SLC components and the clinical drugs Sorafenib and Lenvatinib. In summary, our study revealed that the mechanism underlying the anti-HCC effects of SLC involves interactions at three levels: components (quercetin, beta-sitosterol, kaempferol, baicalein, stigmasterol, and luteolin), pathways (PI3K-Akt signaling pathway, TNF signaling pathway, and IL-17 signaling pathway), and targets (TOP2A, CYP1A2, CYP2B6, and IGFBP3). This study provides preliminary insights into the potential pharmacological mechanisms of SLC in HCC treatment, aiming to support its clinical application and serve as a reference for future laboratory investigations.

Zhou X ，Tan F ，Zhang S ，Wang A ，Zhang T ... -  《-》

Identification of the molecular targets and mechanisms of compound mylabris capsules for hepatocellular carcinoma treatment through network pharmacology and bioinformatics analysis.

Traditional Chinese herbal formulas have been proven to exert an inhibitory effect on tumor. Compound mylabris capsules (CMC) has been used for treating cancer, especially hepatocellular carcinoma (HCC), for years in China. However, its therapeutic mechanisms on HCC remain unclear. This research aimed to elucidate the molecular targets and mechanisms of CMC for treating HCC. First, the bioactive ingredients and potential targets of CMC, as well as HCC-related targets were retrieved from publicly available databases. Next, the overlapped genes between potential targets of CMC and HCC-related targets were determined using bioinformatics analysis. Then, networks of ingredient-target and gene-pathway were constructed. Finally, cell experiments were carried out to examine the effects of CMC-medicated serum on HCC and validate the core molecular targets. In total, 151 bioactive ingredients and 255 potential targets of CMC were selected, 982 differentially expressed genes of HCC were identified. Among them, 34 overlapped genes were finally selected. In addition, 20 pathways and 429 GO terms were significantly enriched. Protein-protein interaction and gene-pathway networks indicated that Cyclin B1(CCNB1) and Cyclin Dependent Kinase 1(CDK1) were the core gene targets for the treatment of CMC on HCC. Moreover, in vitro studies showed that CMC-medicated serum significantly inhibited the viability of HepG2 cells. Furthermore, CMC downregulated CCNB1 and CDK1 expressions and induced G2/M phase cell cycle arrest. CMC plays a therapeutic role in HCC via multi-component, -target and -pathway mechanisms, in which CCNB1 and CDK1 may be the core molecular targets. This study indicates that the integration of network pharmacology and bioinformatics analysis, followed by experimental validation, can serves as an effective tool for studying the therapeutic mechanisms of traditional Chinese medicine.

Wei J ，Ma L ，Liu W ，Wang Y ，Shen C ，Zhao X ，Zhao C ... -  《-》

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》

Study on the anti-tumor mechanism related to immune microenvironment of Bombyx Batryticatus on viral and non-viral infections of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a malignant primary liver cancer with poor prognosis. Most previous studies on anti-HCC effects of traditional Chinese medicines (TCM) have focused on the mechanism of direct action and few researchers considered that TCM can inhibit tumor progression and improve prognosis of HCC patients through regulating tumor microenvironment (TME). In this study, network pharmacology combined bioinformatics methods were employed to analysis mechanism of Bombyx batryticatus (B. batryticatus, one of the most frequently used traditional Chinese animal medicines, has been used in some Asian countries for centuries as an anticancer agent, anti-inflammatory agent, and antioxidant.) in regulating TME of HCC. The results showed that 24 core targets and 2 compounds were identified from overlapping between differential expression genes related to HCC in the cancer genome atlas (TCGA) database and targets of B. batryticatus in TCMSP database. For further analyzing the role of TME heterogeneity of HCC on anti-HCC mechanism of B. batryticatus, the correlation of core targets related with overall survival of HCC with TME cells in hepatitis C or hepatitis B virus-associated hepatocellular carcinoma (VIR) and non-hepatitis C or hepatitis B virus-associated hepatocellular carcinoma (NVIR) were calculated, respectively. The results showed that AKR1C3, SPP1 were significantly related with macrophages in VIR and other targets including NR1I2, CYP1A2 and CYP3A4 were significantly associated with macrophages in NVIR; the target protein AKR1C3 was significantly negative correlated with macrophages M1 in VIR (cor=-0.35, P-value<0.001) and the correlation between AKR1C3 and macrophages M1 was poor in NVIR group (cor = 0.064, P-value = 0.36). Additionally, survival curve of AKR1C3 showed that poor prognosis in VIR group can be related to high level of AKR1C3 (HR = 2.32, 95 % CI: 1.18-4.56, P-value = 0.012), and no signified gene can be found in NVIR group (P-value>0.05). In conclusion, the molecular mechanism of anti-HCC of B. batryticatus can be related to the tumor microenvironment to some extent. B. batryticatus may exert its anti-cancer effects and improve prognosis of patients by regulating macrophages M1 in VIR and NVIR through acting on different targets.

Yuan L ，Bing Z ，Han J ，An X ，Liu X ，Li R ，Wang C ，Sun X ，Yang L ，Yang K ... -  《-》