Exploring mechanism of Xihuang pills in treatment of gastric cancer based on network pharmacology and machine learning
Objective To explore the potential mechanism of Xihuang pills in the treatment of gastric cancer(GC)based on network pharmacology and machine learning.Methods All the data collection and analysis were conducted between November 2023 and August 2024.The study involved various stages,including data collection,gene target prediction,network model construction,and statistical analysis.The chemical composition data of Xihuang pills were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP).The active ingredient targets were predicted using the Swiss Target Prediction and HERB databases.The disease-related targets were collected from GeneCard,and differential targets were filtered.The disease target genes were further filtered using the support vector machine(SVM)machine learning algorithm.The potential targets of Xihuang pills for gastric cancer were identified as the intersection of disease targets and active ingredient targets.Gene ontology(GO)enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis of the potential targets were performed using the clusterProfiler package.The active ingredients and potential targets were imported into the Cytoscape 3.10.0 software to construct a"drug-active ingredient-target"network.The topological analysis was performed to identify the core components of Xihuang pills in the treatment of gastric cancer.The LASSO regression was used to screen the core targets of Xihuang pills for gastric cancer.The Cibersort algorithm was employed for immune infiltration analysis of the core targets.The data were processed using the R 4.2.1 software,and statistical tests were conducted using t test and one-way analysis of variance.Results A total of 41 active ingredients and 182 related targets were identified,with 2 410 gastric cancer-related genes and 119 intersecting genes.The GO enrichment analysis identified 2 049 GO terms(P＜0.05);the KEGG pathway enrichment analysis revealed 177 KEGG signaling pathways(P＜0.05).The network analysis of the"drug-active ingredient-target"revealed that quercetin might be a potential core component of Xihuang pills for gastric cancer.The LASSO regression identified CD36,GJA1,and SERPINE1 as potential core targets for Xihuang pills in the treatment of gastric cancer.The data analysis revealed that compared to normal samples,GJA1 and SERPINE1 genes were highly expressed in patients with gastric cancer(both P＜0.01),while CD36 showed a trend of low expression(P＜0.001);all the three had good diagnostic efficacy.The prognostic analysis indicated that higher expression levels of core targets were negatively correlated with patients'prognosis,meaning that the higher the expression levels of the core targets,the worse the prognosis.The immune infiltration analysis suggested that the development of gastric cancer is associated with the dysregulation of multiple immune cells.The core targets,CD36,GJA1,and SERPINE1,may alleviate the progression of gastric cancer regulating the infiltration of various immune cells.Conclusion Xihuang Pills may exert therapeutic effects on gastric cancer through anti-inflammatory mechanisms and by regulating immune cell functions.
万方数据
维普
