Abstract: Objective To screen the active chemical components with potential therapeutic effects against lung cancer in tea and to provide new insights into the treatment and prevention of lung cancer. Methods Based on network pharmacology, the main active components from 13 types of tea samples were analyzed using liquid chromatography-mass spectrometry(LC-MS). The targets of these small molecules were obtained from the BATMAN-TCM database to construct a “component-target-disease” network. Lung cancer-related disease targets were retrieved from the GeneCard and Malacard databases followed by Gene Ontology (GO) functional and KEGG pathway enrichment analyses of potential pharmacological targets. A protein-protein interaction (PPI) network was constructed using the STRING database. The molecular docking was employed to screen small molecules with potential anti-cancer activity, and their potential inhibition to proliferation of human non-small cell lung cancer cell line A549 and human large cell lung cancer cell line H460. Results A total of 37 active components and 429 targets were identified in tea, with 182 overlapping targets associated with lung cancer. GO analysis revealed that these targets were primarily involved in biological processes such as cell proliferation, response to stimuli, and metabolic processes. KEGG pathway analysis indicated that these targets were mainly enriched in the p53 signaling pathway, ErbB signaling pathway, and PI3K-Akt signaling pathway. PPI network analysis identified key targets including MAPK1, AKT1, SRC, MAPK3, and p53. Molecular docking screened coumestrol as a molecule capable of binding to human estrogen receptor 2 (ESR2), and its inhibitory effect on the proliferation of A549 and H460 cells was experimentally validated(P＜0.000 1). Conclusions The active components in tea may intervene in the development and progression of lung cancer through a multi-component, multi-target, and multi-pathway mechanism, The results suggests potential components against lung cancer in tea, which may be applied in the prevention of human lung cancer.

Key words: tea, lung cancer, network pharmacology, protein-protein interaction network