Work

Assessing the carcinogenic potential and molecular mechanisms of arecoline in human lungs: from in silico methods to in vitro validation

Year: 2025

Type: article

Abstract: OBJECTIVE: Despite the globally recognized carcinogenic potential of arecoline, the primary active compound in areca nut, the molecular mechanisms underlying its role in lung adenocarcinoma (LUAD) have yet to be fully understood. This study aims to bridge this gap by integrating network toxicology, molecular docking and dynamics simulation, tumor bioinformatics, and in vitro assays to elucidate the molecular mechanisms through which arecoline contributes to LUAD development. METHODS: We first utilized disease-related databases and compound databases to identify arecoline-targeted LUAD-relevant proteins and constructed an interaction network using Cytoscape to screen core proteins based on topological analysis. Subsequently, we performed molecular docking and dynamics simulation, along with surface plasmon resonance assay to examine and validate the interactions between arecoline and core proteins. Next, we utilized these proteins for functional enrichment analyses to explore their correlation with cancer. Ultimately, we detected the expression and prognosis of core genes and constructed a prognostic model to examine its relationship with immune infiltration and immunotherapy. RESULTS: Arecoline targets 106 LUAD-relevant proteins, including 24 core proteins. The stable interactions of arecoline and core proteins (especially PTGS2) greatly support the carcinogenic toxicity of arecoline in human lungs. These target proteins influence the occurrence, progression, and immune infiltration of LUAD by participating in pathways related to cancer and immunity, thereby affecting the prognosis and immunotherapy of LUAD patients. CONCLUSION: This study elucidates the molecular mechanism underlying arecoline-induced LUAD, introducing a novel approach for assessing food safety and presenting innovative and promising targets and strategies for cancer intervention and therapy.

Source: Ecotoxicology and Environmental Safety

DOI: 10.1016/j.ecoenv.2025.118108

Author: Wenwen Wang

Institutions: Westlake University, Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,650