Study on the mechanism of action of Garcinia cambogia decoction in the treatment of colorectal cancer based on network pharmacology and bioinformatics
LUO Zicheng
YANG Tao
CHEN Jiang
CAO Yibo
HU Wenting
ZENG Lian
XIAO Tianbao
Abstract：Objective To explore the potential mechanism of action and prognostic effects of Garcinia cambogia decoction in the treatment of colorectal cancer(CRC)using bioinformatics technology and network pharmacology.Methods TCMSP and SymMap databases were used to search the active ingredients and targets of Garcinia cambogia decoction.CRC disease targets were screened by GeneCards,TTD,OMIM,and DisGeNET databases,and differential genes between CRC patients and healthy individuals were screened based on The Cancer Genome Atlas database set.Venny 2.1 platform was used to obtain the common targets of Garcinia Cambogia decoction and disease,and protein-protein interaction(PPI)network was constructed through STRING database and Cytoscape 3.9.1 to obtain the core targets of this network and construct the network diagram of"drug-active ingredient-target-pathway of action".GO and KEGG functional enrichment analyses of the common targets were performed with the help of Metascape database.Results A total of 30 active ingredients,622 drug targets,27 057 disease targets and 417"prescription-disease"key targets were obtained from Garcinia cambogia decoction.The core active ingredients of Garcinia cambogia decoction for CRC include quercetin,isorhamnetin,oridonin,etc.The first 15 core targets screened in PPI network were AKT1,STAT3,TP53,ESR1,MYC,etc.Conclusion This study preliminarily revealed the potential mechanism of action and prognostic effects of Garcinia cambogia decoction in the treatment of CRC,indicating that this prescription has the pharmacodynamic characteristics of multi-component,multi-target and multi-pathway in the treatment of CRC,and may be beneficial to the survival of patients,which will provide new ideas and basis for future related studies.
Keywords：Garcinia cambogia decoctioncolorectal cancernetwork pharmacologybioinformaticsprognostic analysis
Publication Date：2024-03-28
Online Publishing Date：2026-08-26(First online date of this platform, not the publication date of the document)
Pages：8( 311-318 )