Work

The Mechanism of Lycium Barbarum for Liver Cancer Treatment Was Analyzed Based on Network Pharmacology

Year: 2024

Type: article

Abstract: Aim: The mechanism of lycium barbarum treatment liver cancer was explored based on network pharmacology. Methods: The active ingredients, action targets of Lycium barbarum and disease targets of liver cancer were searched in public database platforms TCMSP, GeneCards, DisGeNET, OMIM and TTD, and the potential target of lycium barbarum in the treatment of liver cancer was obtained by intersection of drug component target and disease target. The protein interaction network (PPI) of lycium barbarum in treating liver cancer was obtained through STRING database, and the core target was identified by Cytoscape3.9.1 software analysis. The signaling pathway of lycium barbarum on hepatocarcinoma were screened by gene ontology (GO) enrichment analysis and Genomic Encyclopedia (KEGG) pathway enrichment analysis. Results: 45 active ingredients and 430 targets of Lycium barbarum, and 6489 targets related to liver cancer were selected. There were 272 common targets of drug-disease intersection. The analysis results showed that the active components of Lycium berry mainly included δ-carotene, lano-8-enol, lano-8-ene-3beta-alcohol, 14b-pregnane, β-sitosterol, and carotenin. The core targets of lycium barbarum in the treatment of liver cancer include AKT1, TNF, EGFR, ESR1, SRC, PPARG and HSP90AA1. GO enrichment is mainly involved in biological processes such as protein phosphorylation, response to exogenous stimuli, and negative regulation of apoptosis. KEGG is mainly involved in metabolic pathway, cancer pathway, PI3K-Akt signaling pathway. Conclusions: The results of this study show that Lycium barbarum may play an important role for treatment liver cancer in protein phosphorylation, exogenous stimulus response and negative regulation of apoptosis through key targets such as AKT1, TNF, EGFR, ESR1, SRC, PPARG and HSP90AA1 in "metabolic pathway", "tumor pathway" and "PI3K-Akt signaling pathway".

Source: Clinical Medicine Frontiers

DOI: 10.57237/j.cmf.2024.03.001

Authors: Mengxiao Liu, Yuanyi Zhang, Kui Yu, Shuying Li, Ji Li

Institutions: North China University of Science and Technology, North China University of Science and Technology Jitang College

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

Funder: Natural Science Foundation of Hebei Province