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

Abstract

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 Corydalis decumbens (Thunb.) Pers. in NSCLC based on network pharmacology and bioinformatics. The overlapping genes between Corydalis decumbens (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 AR and NCOA2, NCOA2, and RXRA and ESR1 and NCOA2. These overlapping genes were mainly enriched in the estrogen signaling pathway, calcium signaling pathway, cholinergic synapse, and PI3K-Akt signaling pathway. ESR2 mRNA levels were significantly downregulated in patients with lung adenocarcinoma (LUAD) getting worse, and KDR levels were lower in lung squamous cell carcinoma (LUSC) than those in normal tissue. PTGS2 expression was correlated with the median survival time of LUAD, and ESR1 expression was correlated with the median survival time of LUSC. The application of network pharmacology revealed the potential mechanism underlying the effects of Corydalis decumbens (Thunb.) Pers. in NSCLC treatment and provided a theoretical basis for further in-depth research in this field.

• Authors: Jun Liu, Zhibo He, Shan Li, Wenan Huang, Zhongjie Ren
• Journal: Evidence-based complementary and alternative medicine : eCAM (Evid Based Complement Alternat Med) Vol. 2021 Pg. 4341517 ( 2021) ISSN: 1741-427X [Print] United States
• PMID: 34497656 (Publication Type: Journal Article)
• Copyright: Copyright © 2021 Jun Liu et al.