Network toxicology and multi-omics analyses identify diagnostic genes and elucidate underlying mechanisms of 6PPDQ-induced hepatocellular carcinoma.

With the rapid expansion of tire production, the antioxidant N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD) and its transformation product, 6PPD-quinone (6PPDQ), have emerged as widespread environmental contaminants with demonstrated toxicity. Here, we employed an integrated network toxicology and computational framework to elucidate the mechanisms by which 6PPDQ may contribute to hepatocellular carcinoma (HCC). Transcriptomic data from four GEO datasets were normalized and analyzed using differential expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA), identifying 923 HCC-associated genes. Intersection with 3844 predicted 6PPDQ targets resulted in 148 candidate mediators. GO and KEGG analyses revealed enrichment in xenobiotic metabolism, redox regulation, and oncogenic pathways (e.g., PI3K-Akt, TNF, p53). Subsequent machine learning analysis identified nine hub genes, among which CHST4, SLC26A6, LY6E, and FAM13A formed a robust diagnostic signature (AUC = 0.999; Hosmer-Lemeshow P = 1.0). Single-sample gene set enrichment analysis (ssGSEA) and single-cell RNA sequencing (scRNA-seq) confirmed their cell type-specific expression and associations with altered immune infiltration. Molecular docking and 100 ns dynamics simulations demonstrated stable high-affinity binding between 6PPDQ and CHST4 (ΔG = -9.1 kcal/mol). Finally, we constructed an adverse outcome pathway (AOP) linking 6PPDQ exposure to immune dysregulation and HCC initiation. This multi-omics and in silico study reveals a mechanistic network by which 6PPDQ promotes hepatic carcinogenesis, highlights four candidate biomarkers for early detection, and provides a conceptual AOP framework for future toxicological and therapeutic investigations.