Unraveling the Carcinogenic Mechanisms of Food contaminants through Network Toxicology, Machine Learning, and Molecular Docking

Food contamination is a significant global health threat, with carcinogenic potential, yet the molecular pathways linking contaminants to cancer remain poorly understood. This study aimed to identify key molecular targets mediating the carcinogenic effects of food contaminants. We utilized multiple online databases to identify target genes associated with nine prevalent dietary contaminants (Glyphosate, Perfluorooctane sulfonate, Nitrosamines, Pentabromodiphenyl ethers, Methylmercury, Dioxins, Acrylamide, Pyrrolizidine Alkaloids, and Aflatoxin) and pan-cancer. Protein-protein interaction (PPI) analysis and visualization were conducted on intersecting genes, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses to uncover potential mechanisms. We focused on breast (BRCA), prostate (PRAD), and colon (COAD) carcinomas due to their significant pathway associations. Hub genes were prioritized using an integrative strategy combining topological algorithms in Cytoscape (Centiscape, MCODE, and cytohubba's MCC), machine learning validation, and Weighted Gene Co-expression Network Analysis (WGCNA). Molecular docking simulations were performed to examine interactions between contaminants and hub genes. We identified 69 pan-cancer-intersected targets. Comprehensive enrichment analyses revealed significant cancer-associated pathways. Hub gene prioritization identified JUN in BRCA, CDC42 in COAD, and MAPK14 in PRAD as critical regulatory targets. Validation using The Cancer Genome Atlas (TCGA) data confirmed statistically significant differential expression patterns (p < 0.05) for these targets across respective malignancies. Gene Set Enrichment Analysis (GSEA) delineated pathway activation profiles consistent with tumor progression mechanisms. Molecular docking simulations demonstrated robust binding affinities (binding energy ≤-5.0 kcal/mol) between contaminants and structural domains of identified hub targets, suggesting direct mechanistic interactions. Our study elucidates the molecular mechanisms underlying dietary carcinogens, identifies potential therapeutic targets, and highlights the need for enhanced food safety policies. This integrative approach combining molecular and clinical insights may inform precision public health interventions.