Integrating network pharmacology and bioinformatics analysis to explore the mechanism of Yupingfengsan in treating lung adenocarcinoma

Introduction: Yupingfengsan () is a classical traditional Chinese formulae with proven therapeutic effect on the disease of respiratory system. However, its action mechanism remains obscure for lung adenocarcinoma (LAD). This study aimed to investigate the potential target genes and the mechanism of Yupingfengsan in the treatment of LAD. Methods: Yupingfengsan chemical ingredients and related targets were predicted by public databases. Differential expression genes of LAD were obtained from The Cancer Genome Atlas (TCGA) database. Gene set enrichment analysis (GSEA) was used to execute gene ontology function and pathway enrichment analysis. The protein interaction network was constructed by Cytoscape. Finally, potential target genes and mechanism of Yupingfengsan on LAD were predicted. The differential expression and prognostic analysis of target genes were verified by TCGA database and the Kaplan-Meier plotter, respectively. Results: A total of 253 targets from 30 active ingredients of Yupingfengsan were predicted. 4426 DEGs were identified from TCGA LAD data sets. 32 upregulated and 52 downregulated genes were obtained between Yupingfengsan putative targets and DEGs of LAD. MAPK, VEGF, and ErbB signaling pathways seemed to be the most likely mechanism. 6 potential target genes, PLA2G4A, PRKCB, PIK3R1, KDR, PLA2G1B and PTGS2 were extracted. These 6 candidates were verified significantly different expression between LAD and paired adjacent normal tissues, and PRKCB, PIK3R1, KDR, PLA2G1B suggested a significant correlation with LAD prognosis. Conclusion: Differentially expressed in tumors, PLA2G4A, PRKCB, PIK3R1, KDR, PLA2G1B and PTGS2 are potential therapeutic targets of Yupingfengsan in the treatment of LAD, and MAPK, VEGF and ErbB signaling pathways are involved.