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

BACKGROUND

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.

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.

RESULTS

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.

CONCLUSION

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.

Pharmacokinetic and Pharmacodynamic Factors Contribute to Synergism between Let-7c-5p and 5-Fluorouracil in Inhibiting Hepatocellular Carcinoma Cell Viability

Pharmacological interventions for hepatocellular carcinoma (HCC) are hindered by complex factors, and rational combination therapy may be developed to improve therapeutic outcomes. Very recently, we have identified a bioengineered microRNA let-7c-5p (or let-7c) agent as an effective inhibitor against HCC in vitro and in vivo. In this study, we sought to identify small-molecule drugs that may synergistically act with let-7c against HCC. Interestingly, we found that let-7c exhibited a strong synergism with 5-fluorouracil (5-FU) in the inhibition of HCC cell viability as manifested by average combination indices of 0.3 and 0.5 in Hep3B and Huh7 cells, respectively. By contrast, coadministration of let-7c with doxorubicin or sorafenib inhibited HCC cell viability with, rather surprisingly, no or minimal synergy. Further studies showed that protein levels of multidrug resistance–associated protein (MRP) ATP-binding cassette subfamily C member 5 (MRP5/ABCC5), a 5-FU efflux transporter, were reduced around 50% by let-7c in HCC cells. This led to a greater degree of intracellular accumulation of 5-FU in Huh7 cells as well as the second messenger cyclic adenosine monophosphate, an endogenous substrate of MRP5. Since 5-FU is an irreversible inhibitor of thymidylate synthetase (TS), we investigated the interactions of let-7c with 5-FU at pharmacodynamic level. Interestingly, our data revealed that let-7c significantly reduced TS protein levels in Huh7 cells, which was associated with the suppression of upstream transcriptional factors as well as other regulatory factors. Collectively, these results indicate that let-7c interacts with 5-FU at both pharmacokinetic and pharmacodynamic levels, and these findings shall offer insight into molecular mechanisms of synergistic drug combinations.

Prospects of multitarget drug designing strategies by linking molecular docking and molecular dynamics to explore the protein-ligand recognition process

The designing of drugs that can simultaneously affect different protein targets is one novel and promising way to treat complex diseases. Multitarget drugs act on multiple protein receptors each implicated in the same disease state, and may be considered to be more beneficial than conventional drug therapies. For example, these drugs can have improved therapeutic potency due to synergistic effects on multiple targets, as well as improved safety and resistance profiles due to the combined regulation of potential primary therapeutic targets and compensatory elements and lower dosage typically required. This review analyzes in-silico methods that facilitate multitarget drug design that facilitate the discovery and development of novel therapeutic agents. Here presented is a summary of the progress in structure-based drug discovery techniques that study the process of molecular recognition of targets and ligands, moving from static molecular docking to improved molecular dynamics approaches in multitarget drug design, and the advantages and limitations of each.

Blocking preferential glucose uptake sensitizes liver tumor-initiating cells to glucose restriction and sorafenib treatment

Cancer cells display altered metabolic phenotypes characterized by a high level of glycolysis, even under normoxic conditions. Because of a high rate of glycolytic flux and inadequate vascularization, tumor cells often suffer from nutrient deficiency and require metabolic adaptations to address such stresses. Although tumor-initiating cells (T-ICs) have been identified in various malignancies, the cells' metabolic phenotypes remain elusive. In this study, we observed that liver T-ICs preferentially survived under restricted glucose treatment. These cell populations compete successfully for glucose uptake by preferentially expressing glucose transporters (GLUT1 and GLUT3), whereas inhibition of GLUT1 or GLUT3 abolished the survival advantage and suppressed the tumorigenic potential of liver T-ICs. Among signaling pathways related to T-ICs, IL-6/STAT3 was identified to be responsible for the elevation of glucose uptake in liver T-ICs under glucose limitation. Further investigation revealed that IL-6 stimulation upregulated GLUT1 and GLUT3 expressions in CD133⁺ cells, particularly during glucose deprivation. More importantly, inhibition of glucose uptake sensitized liver T-ICs to sorafenib treatment and enhanced the therapeutic efficacy in vivo. Our findings suggest that blocking IL-6/STAT3-mediated preferential glucose uptake might be exploited for novel therapeutic targets during hepatocellular carcinoma (HCC) progression.

CI431, an Aqueous Compound from Ciona intestinalis L., Induces Apoptosis through a Mitochondria-Mediated Pathway in Human Hepatocellular Carcinoma Cells

In the present studies, a novel compound with potent anti-tumor activity from Ciona intestinalis L. was purified by acetone fractionation, ultrafiltration, gel chromatography and High Performance Liquid Chromatography. The molecular weight of the highly purified compound, designated CI431, was 431Da as determined by HPLC-MS analysis. CI431 exhibited significant cytotoxicity to several cancer cell types. However, only a slight inhibitory effect was found when treating the benign human liver cell line BEL-7702 with the compound. To explore its mechanism against hepatocellular carcinoma, BEL-7402 cells were treated with CI431 in vitro. We found that CI431 induced apoptotic death in BEL-7402 cells in a dose- and time-dependent manner. Cell cycle analysis demonstrated that CI431 caused cell cycle arrest at the G2/M phase, and a sub-G1 peak appeared after 24 h. The mitochondrial-mediated pathway was implicated in this CI431-induced apoptosis as evidenced by the disruption of mitochondrial membrane potential. The results suggest that the CI431 induces apoptosis in BEL-7402 human hepatoma cells by intrinsic mitochondrial pathway.

[New possibilities of targeted therapy in the treatment of hepatocellular carcinoma with the help of molecular biology]

Hepatocellular carcinoma (HCC) has a poor prognosis. Approximately 85% of patients are not candidates for curative treatments at the time of diagnosis; hence palliative modalities (transcatheter arterial chemoembolisation, radiofrequency ablation, systemic chemotherapy) are used. Systemic chemotherapies have disappointing results. The increasing knowledge in the molecular biology of HCC will increase the possibilities of targeted therapy. The multi-tyrosine kinase inhibitor sorafenib is the only drug which has approved. The VEGF-inhibitors (bevacizumab, sunitinib), EGFR-blocker agents (erlotinib), as well as the inhibition of mTOR (rapamycin) are promising. Combination of sorafenib or other anti-angiogenic agents with local ablative procedure (transcatheter arterial chemoembolisation, radiofrequency ablation), or with curative hepatectomy also can be favorable. Alteration of Wnt pathway, retinoid compounds, inhibition of the cell cycle as well as the proteosome, and epigenetic therapy can be other potential promising targets in HCC.

In-silico approaches to multi-target drug discovery : computer aided multi-target drug design, multi-target virtual screening

Multi-target drugs against selective multiple targets improve therapeutic efficacy, safety and resistance profiles by collective regulations of a primary therapeutic target together with compensatory elements and resistance activities. Efforts have been made to employ in-silico methods for facilitating the search and design of selective multi-target agents. These methods have shown promising potential in facilitating drug discovery directed at selective multiple targets.

Cucurbitacin B induces apoptosis and S phase cell cycle arrest in BEL-7402 human hepatocellular carcinoma cells and is effective via oral administration

Cucurbitacin B is an anti-cancer drug candidate and its efficacy has been demonstrated in hepatocellular carcinoma (HCC). To explore its mechanism against HCC, BEL-7402 cells were treated with cucurbitacin B in vitro. Treatment with cucurbitacin B induced S phase arrest and apoptosis. The growth inhibition effect was associated with cyclin D1 and cdc-2 down regulations. Western blotting analysis of cell signaling molecules indicated that cucurbitacin B inhibited c-Raf activation without affecting STAT3 phosphorylation. Moreover, in vivo study demonstrated that cucurbitacin B is effective against BEL-7402 xenograft when administrated orally.