Integrative analysis using Mendelian randomization and network toxicology reveals genetic support and potential mechanisms of atrazine in breast cancer

OBJECTIVE: Breast cancer (BC) is the leading cause of cancer-related mortality in women. Atrazine, a prevalent herbicide, is a persistent environmental pollutant with bioaccumulative potential. This study investigated the potential mechanisms underlying the association between atrazine exposure and BC. METHODS: We integrated potential common targets of atrazine in BC through multiple databases (e.g., PubChem, CTD, GeneCards, OMIM). Genetically supported target-level associations were assessed using Mendelian randomization (MR). The protein-protein interaction (PPI) network was constructed via the STRING database, and potential core targets were identified using Cytoscape. Gene ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) enrichment analyses were performed with R packages. Molecular docking simulations evaluated atrazine's binding affinity to the core candidate targets. RESULTS: We identified 1267 candidate targets potentially involved in atrazine-related BC processes. Based on single nucleotide polymorphism (SNP)-based selection criteria, genetic instruments derived from 1047 potential targets were included in the MR analysis, which further prioritized 164 targets with genetically supported associations with BC risk. PPI network analysis refined these to 38 computationally prioritized candidates. GO/KEGG enrichment suggested that the core candidate targets are predominantly enriched in cancer-related signaling and cellular stress/proliferation regulatory processes. Molecular docking demonstrated that the top five candidate proteins (AKT1, CASP3, HSPA4, CCND1, and MAPK3) exhibit potential binding affinity with atrazine. CONCLUSIONS: This study suggests that atrazine-related targets may be associated with BC risk through pathways involving cellular senescence, human T-cell leukemia virus 1 (HTLV-1) infection, and small cell lung cancer pathways, with AKT1, CASP3, HSPA4, CCND1, and MAPK3 as candidate targets. Overall, we provide a molecular framework for understanding genetically supported target-level associations between atrazine-related genes and BC risk, and an integrated approach to assessing toxicological effects of environmental pollutants.