PURPOSE

Traditional Chinese medicine (TCM) sometimes plays a crucial role in advanced cancer treatment. Despite the significant therapeutic efficacy in hepatocellular carcinoma (HCC) that Planch root extract (acRoots) has proven, its complex composition and underlying mechanism have not been fully elucidated. Therefore, this study analyzed the multiple chemical compounds in acRoots and their targets via network pharmacology and bioinformatics analysis, with the overarching goal of revealing the potential mechanisms of the anti-HCC effect.

METHODS

The main ingredients contained in acRoots were initially screened from the traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the candidate bioactive ingredient targets were identified using DrugBank and the UniProt public databases. Second, the biological processes of the targets of active molecules filtered from the ingredients of acRoots were evaluated using gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Third, weighted gene coexpression network analysis (WGCNA) was performed to identify gene coexpression modules associated with HCC. The hub genes of acRoots in HCC were defined via contrasting the above module eigengenes with candidate target genes of acRoots. Furthermore, the target-pathway network was analyzed to explore the mechanism for anti-HCC effect of hub genes. Kaplan-Meier plotter database analysis was performed to validate the hub genes of acRoots correlation with prognostic values in HCC. In order to verify the results of the network pharmacological analysis, we performed a molecular docking approach on the active ingredients and key targets using the Discovery Studio software. The viability of SMMC-7721 and HL-7702 cells was determined by Cell counting kit-8 (CCK-8) after being treated with different concentrations of (+)-catechin (0, 50, 100, 150, 200, and 250 g/ml) for 24, 48, and 72 hours, respectively. Finally, qRT-PCR and Western blot involving human hepatocarcinoma cells were utilized to verify the impact of (+)-catechin on the hub genes associated with prognosis.

RESULTS

6 out of 26 active ingredients extracted from TCMSP were deemed as the core ingredients of acRoots. 175 bioactive-ingredient targets of acRoots were obtained and a bioactive-ingredient targets network was established correspondingly. The biological processes (BP) of target genes mainly involved processes, such as toxic substance and wounding. The results of KEGG pathways indicated that the target genes were mainly enriched in pathways in cancer, AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, and other pathways. Also, the two hub genes (i.e., ESR1 and CAT) were closely associated with the prognosis of HCC patients. As a consequence, we predicated a series of signaling pathways, including estrogen signaling pathway and longevity regulation pathway, through which acRoots could facilitate the treatment for HCC. The molecular docking experiment ascertained that ESR1 and CAT had an effective binding force with (+)-catechin, one of the core ingredients of acRoots. Furthermore, (+)-catechin inhibited SMMC-7721 cell growth in a dose-dependent manner and a time-dependent manner. Finally, we suggest that the expression level of ESR1 and CAT is positively related to the (+)-catechin concentrations in in-vitro experiments.

CONCLUSION

The bioactive ingredients of acRoots, including quercetin, (+)-catechin, beta-sitosterol, and aloe-emodin, have synergistic interactions in reinforcing the anticancer effect in HCC. Evidently, acRoots took effect by regulating multitargets and multipathways through its active ingredients. Further, (+)-catechin, the possible paramount anti-HCC active ingredient in acRoots, helped improve the prognosis of HCC patients by increasing the expression of ESR1 and CAT. Additionally, the findings yielded provide a conceptual guidance for the clinical treatment of HCC and the methods adopted are potentially applicable in the future comprehensive analysis of the underlying mechanisms of TCMs.