Mechanism of Phellodendron and Anemarrhena Drug Pair on the Treatment of Liver Cancer Based on Network Pharmacology and Bioinformatics

Abstract

BackgroundThis study aims to explore the key targets and signaling pathways of the traditional Chinese medicine Phellodendron and Anemarrhena drug pair (PADP) for the treatment of liver cancer.MethodsFirstly, bioinformatics technology was used to analyze GSE62232 gene chip to obtain the differential genes of liver cancer. A network pharmacology technology was used to find the active components of PADP and their targets. Secondly, the differential genes were imported into STRING database to draw a PPI network, and network topology structure map combined with Cytoscape software. And the R language was used to identify differential gene targets and pathways through GO and KEGG pathway enrichment analysis. In addition, AutoDock Vina was used for molecular docking of core targets and core compounds. Moreover, GEPIA online analysis tool was used to perform survival analysis of the core target genes. Finally, RT-PCR was used to verify the changes of key target genes. CCK−8 assay was performed to detect cell proliferation. Flow cytometry was performed to detect the cell cycle and apoptotic. Transwell invasion assay was performed to detect cell invasion.ResultsFirstly, a total of 21,654 genes were obtained. After screening, 1019 differential genes were obtained, including 614 down-regulated genes and 405 up-regulated genes. Furthermore, after screening by ADME standards, 52 active ingredients were obtained, of which 37 were Phellodendron and 15 were Anemarrhena. And a total of 36 differential genes have been identified, including 13 up-regulated genes and 23 down-regulated genes. Moreover, through enrichment analysis, we found that PADP may treat liver cancer through multiple channels and multiple pathways including the p53 signaling pathway, IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway and so on. Secondly, the molecular docking results showed that there was certain affinity between the core compounds and core target genes. In addition, GEPIA online analysis showed that ESR1, AR, CCNB1, CDK1, AKR1C3 and CCNA2 might become potential target genes for the survival and prognosis of PADP for the treatment of liver cancer. Finally, it was found that PADP could up regulate genes ESR1 and AR, down regulate genes CCNB1, CDK1, AKR1C3, and CCNA2. PADP could promote the apoptosis of liver cancer cells, shorten the cell cycle, and inhibit the proliferation and invasion of liver cancer cells.ConclusionPADP may treat liver cancer through multiple targets, multiple channels, and multiple pathways, thereby suppressing cancer cells and improving the living quality of patients.

The pathogenesis of liver cancer and the therapeutic potential of bioactive substances

“…In the future, it is necessary to further explore the specific targets of active ingredients. Through network pharmacology, genomics, metabolomics and other methods to sort out relevant targets, find the possibility of a variety of active ingredients working together to fight cancer in an all-round way, and provide a more powerful reference for the development of more scientific and effective anti-cancer drugs ( Ruan et al, 2022 ). 5) More toxicity and dose studies are needed for biologically active substances.…”

Diosbulbin C, a novel active ingredient in Dioscorea bulbifera L. extract, inhibits lung cancer cell proliferation by inducing G0/G1 phase cell cycle arrest

“…To assess the binding affinity of diosbulbin C to potential targets, Discovery Studio (DS) 2019 was used for flexible docking diosbulbin C and candidate targets [ 19 ]. Drug ligands and protein receptors were downloaded from PubChem and PDB database, respectively [ 20 ].…”

Elucidation of the mechanism of action of ailanthone in the treatment of colorectal cancer: integration of network pharmacology, bioinformatics analysis and experimental validation

“…Network pharmacology is employed to identify candidate targets and elucidate bioactive compound functions in disease treatment and bioinformatics analysis is instrumental in investigating complicated gene–disease relationships and regulatory mechanisms ( Wang et al, 2022 ). These approaches have deepened our understanding regarding the action mechanisms of drugs ( Zou et al, 2022 ), successfully revealing the multitargeted pharmacological roles of several compounds including Fumaria indica and the Phellodendron–Anemarrhena drug pair in hepatocellular carcinoma treatment ( Batool et al, 2022 ; Ruan et al, 2022 ). Similarly, Xia et al used bioinformatics and network pharmacology to determine the inhibition mechanism of luteolin on the proliferation and migration of glioblastoma cells through the key targets BIRC5 and CCNB1, which impacted the prognosis of patients with glioblastoma ( Xia Z. et al, 2022b ).…”