基于网络药理学的灵芝调控肿瘤微环境治疗胰腺癌的机制OA

To investigate the potential molecular mechanisms by which Ganoderma lingzhi modulates the tumor microenvironment to treat pancreatic cancer(PC),an integrative approach combining bioinformatics and network pharmacology was employed to systematically analyze the targets and pathways of G.lingzhi active compounds.A total of 39 active constituents of G.lingzhi,including Ganoderic acid A,Ganoderic acid V1,and Lingzhi spore lactone B,were identified through the TCMSP database and literature review.Their potential targets were predicted using the SwissTarget Prediction database.The ESTIMATE algorithm was applied to assess immune and stromal scores in pancreatic cancer samples from the TCGA dataset,and weighted gene co-expression network analysis(WGCNA)was utilized to identify gene modules associated with the tumor microenvironment.By intersecting these modules with disease-related targets from DrugBank,GeneCards,and DisGeNET databases and the predicted targets of Ganoderma active compounds,53 potential core targets for pancreatic cancer treatment were identified,including VEGFA,KDR,and NTRK1.Protein-protein interaction network construction,along with Gene Ontology(GO)functional and KEGG pathway enrichment analyses,revealed that these targets are primarily involved in inflammatory responses,signal transduction,and pathways such as Ras and Rap1 signaling.Molecular docking validation demonstrated stable binding affinities between core targets and G.lingzhi active compounds.This study preliminarily elucidates that G.lingzhi may exert anti-pancreatic cancer effects through a multi-component,multi-target,and multi-pathway synergistic regulation of the tumor microenvironment,providing a theoretical foundation for further exploration of its therapeutic mechanisms.