Breast cancer
Potential Molecular Links Between Benzophenone-3 and Breast Cancer: Network Toxicology, Machine Learning, Molecular Modeling, and Gene Expression Validation
By Wang Z, Wang Y, Cao Z and 1 others.
Abstract
Purpose
Benzophenone-3 (BP-3) is a widely used ultraviolet filter with potential carcinogenic concern, but its molecular link with breast cancer remains unclear. This study aimed to identify candidate targets and potential molecular links between BP-3 and breast cancer using toxicological prediction, machine learning, molecular modeling, and gene expression analysis.
Methods
The ADMET and toxicity profiles of BP-3 were evaluated using PubChem, ADMETlab 3.0, ProTox 3.0, and pkCSM. BP-3-related targets were predicted from ChEMBL, STITCH, and SwissTargetPrediction, while breast cancer-related differentially expressed genes were obtained from GEO datasets. Candidate targets were screened by intersection analysis and examined using GO/KEGG enrichment and PPI networks. Core genes were identified using 127 machine learning model combinations and SHAP interpretation. GSVA, GSEA, TIMER2.0, molecular docking, molecular dynamics simulations, MM-GBSA calculations, and qRT-PCR were used for validation.