Integrating network toxicology, machine learning, and experimental evidence reveals candidate targets and pathways in PCDD/F-related colon cancer.

Previous studies have suggested that exposure to carcinogenic polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) pollutants may increase the risk of colon cancer, their underlying molecular mechanisms remain unclear. In this study, we employed a multidisciplinary approach integrating network toxicology, machine learning, molecular docking, molecular dynamics (MD) simulations and in vivo experiments to investigate how PCDD/Fs may promote colon carcinogenesis. Machine learning algorithms converged on MMP7 as a core target, MMP7 expression was upregulated in colon cancer tissues and was associated with immune cell infiltration. Molecular docking and MD simulations further suggested stable interactions between the five representative PCDD/F congeners and the target proteins (MMP7, SRC, and HSP90AA1), supporting their potential involvement in disease progression. Consistent with these in silico findings, exposure of mice to 24 μg/kg TCDF significantly increased the expression of Mmp7 and Hsp90aa1 in murine colonic tissues, increased the levels of proinflammatory cytokines Ifn-γ, Il-1β, and Il-6, and downregulated the expression of Mucin 2 (MUC2). Connectivity Map analysis based on the PCDD/F-related gene signature identified five candidate compounds targeting MMP7 and HSP90AA1, of which four HSP90 inhibitors (tanespimycin, alvespimycin, NVP-AUY922 and AT-13387) showed negative connectivity scores, suggesting potential to reverse the pollutant-induced expression profile.