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DOI 10.1016/j.compbiolchem.2026.109107

Медицинская библиотека · Computational biology and chemistry · 2026

Integration of network toxicology, WGCNA, and explainable machine learning to decipher the toxic molecular basis underlying DEGDB plasticizer-induced clear cell renal cell carcinoma (ccRCC) progression.

Yanping Ma, Guolin Tian, Tao Yang, Angyang Du, Jiaxin Li, Bo Tao, Yajie Li, Yaodong Jia, Yuelong Feng, Hao Yang, Lihong Nie, Ruining Zhao

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Аннотация

Diethylene glycol dibenzoate (DEGDB), an emerging eco-friendly plasticizer, remains critically understudied with mechanistic and molecular-level evidence linking it to clear cell renal cell carcinoma (ccRCC) progression, representing a major knowledge gap. To fill this gap, we conducted a cross-scale investigation using network toxicology, WGCNA, machine learning, SHAP explainable modeling, and molecular docking as methodological tools to elucidate DEGDB‑induced ccRCC progression. By jointly mining the ChEMBL, PubChem, SwissADME, STRING, and GEO repositories, we rigorously distilled a high-confidence set of 42 target genes, among which TSHR, ADORA2B, ANPEP, CA9, CYP3A4, JUN, NR1I3, and PHGDH were highlighted. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that DEGDB may propel ccRCC progression by disrupting neuro-endocrine-immune network regulation, activating chemical carcinogenesis-related receptors, and perturbing metabolic-degradation pathways such as nitrogen metabolism and lysosomal signaling. Subsequently, 113 machine-learning algorithms were leveraged to construct predictive models, and SHAP-based interpretation pinpointed five core genes-CA9, NR1I3, PHGDH, GABRA2, and ANPEP. Validation against The Cancer Genome Atlas (TCGA) datasets demonstrated that CA9 exhibits marked expression divergence in ccRCC (box-plot analysis) and is strongly associated with unfavorable prognosis (Kaplan-Meier survival curves). Molecular-docking simulations further confirmed robust binding affinities between DEGDB and all five core target proteins (binding energies < -5 kcal/mol). In vitro assays additionally revealed that DEGDB significantly promotes 786-O and A498 proliferation and up-regulates CA9 protein expression. Collectively, our findings indicate that DEGDB accelerates ccRCC progression via the orchestrated modulation of cellular proliferation, disruption of neuro-endocrine-immune homeostasis, and activation of oncogenic receptors. This study provides a theoretical framework for assessing the environmentally relevant health risks posed by emerging plasticizers and for devising preventive strategies against DEGDB‑induced ccRCC under real‑world exposure scenarios.

Для цитирования: Yanping Ma, Guolin Tian, Tao Yang, Angyang Du, Jiaxin Li, Bo Tao, Yajie Li, Yaodong Jia, Yuelong Feng, Hao Yang, Lihong Nie, Ruining Zhao. Integration of network toxicology, WGCNA, and explainable machine learning to decipher the toxic molecular basis underlying DEGDB plasticizer-induced clear cell renal cell carcinoma (ccRCC) progression.. Computational biology and chemistry. 2026. DOI: 10.1016/j.compbiolchem.2026.109107.

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