Network Pharmacology-Based Analysis of the Effects of (Thunb.) Pers. in Non-Small Cell Lung Cancer.

Non-small cell lung cancer (NSCLC) is one of the most malignant tumors worldwide. The main treatment for NSCLC is based on Western medicine; however, the overall effect is unsatisfactory. This study aimed to investigate the potential therapeutic targets and pharmacological mechanisms of action of the traditional Chinese medicine (Thunb.) Pers. in NSCLC based on network pharmacology and bioinformatics. The overlapping genes between (Thunb.) Pers. and NSCLCs were screened using Venn analysis. Cytoscape 3.7.1 software was used to analyze the overlapping target protein-protein interaction (PPI) network. Gene ontology and pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomics database were performed to exploring biological functions of the overlapping genes. The gene expression profiling interactive analysis dataset was used to analyze the correlation between hub gene expression and disease. This study revealed 38 nodes with 191 edges, which may be therapeutic targets for NSCLC. PPI network analysis showed that the most likely association was between the genes and , , and and and . These overlapping genes were mainly enriched in the estrogen signaling pathway, calcium signaling pathway, cholinergic synapse, and PI3K-Akt signaling pathway. mRNA levels were significantly downregulated in patients with lung adenocarcinoma (LUAD) getting worse, and levels were lower in lung squamous cell carcinoma (LUSC) than those in normal tissue. expression was correlated with the median survival time of LUAD, and expression was correlated with the median survival time of LUSC. The application of network pharmacology revealed the potential mechanism underlying the effects of (Thunb.) Pers. in NSCLC treatment and provided a theoretical basis for further in-depth research in this field.