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Peer-reviewedCC BYPLOS One

Elucidating the toxicogenomic mechanisms of DBP exposure on Hepatocellular carcinoma through network toxicology and molecular docking analysis

  • Dafei Dai1,2
  • Nianzhao Yang1,2
  • Fubao Liu1
  • Xiaopeng Chen2
  1. 1Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
  2. 2Department of General Surgery, The First Affiliated Hospital of Wannan Medical College (Yijishan Hospital of Wannan Medical College), Wuhu, Anhui, China.
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Abstract

Backgroud: This study explored the molecular mechanisms by which dibutyl phthalate (DBP) contributes to hepatocellular carcinoma (HCC) pathogenesis using integrated network toxicology and bioinformatics. Methods: DBP’s carcinogenic potential was evaluated with ADMETLAB 3.0 and ProTox3. DBP-related targets were obtained from ChEMBL, SwissTargetPrediction, and PharmMapper; HCC-related targets from GeneCards and OMIM. Overlapping genes were identified by Venn analysis. A protein-protein interaction (PPI) network was constructed using STRING and analyzed with Cytoscape to identify hub genes. Functional enrichment analysis (GO/KEGG) was performed with DAVID. Expression validation and survival analysis used TCGA-LIHC and GEO (GSE39791) data. A prognostic nomogram integrating gene expression and clinical variables was developed. Single-cell RNA sequencing (GSE299340) was analyzed with Seurat to examine hub gene expression. Molecular docking and dynamics simulations investigated DBP interactions with core targets. Results: A total of 242 overlapping genes between DBP-associated and HCC-associated targets were identified. PPI network analysis revealed seven hub genes: KRAS, GRB2, ESR1, HSP90AA1, SRC, EGFR, and TP53. Enrichment analysis indicated significant involvement in cancer-related pathways. Expression analysis in TCGA and GEO datasets confirmed significant dysregulation of GRB2, ESR1, HSP90AA1, and SRC in HCC tissues, which correlated with patient survival outcomes. The prognostic model incorporating these genes showed good predictive accuracy. Single-cell analysis indicated distinct expression patterns of ESR1 (hepatocytes) and HSP90AA1 (immune cells) in HCC. Molecular docking demonstrated stable binding of DBP to ESR1 and HSP90AA1 with favorable binding energies (−6.8 and −6.1 kcal/mol, respectively). Molecular dynamics simulations supported the stability of these complexes, with van der Waals interactions being the primary binding force. Conclusions: This integrative analysis suggests that DBP exposure may contribute to HCC pathogenesis by modulating core genes and pathways, although these findings are associative and require experimental confirmation. Hub genes, especially ESR1 and HSP90AA1, are potential biomarkers and targets. Direct DBP-protein interactions provide mechanistic insights into HCC etiology.

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Cite

BibTeXRIS
BibTeX
@article{dai2026elucidating,
  title = {{Elucidating the toxicogenomic mechanisms of DBP exposure on Hepatocellular carcinoma through network toxicology and molecular docking analysis}},
  author = {Dafei Dai and Nianzhao Yang and Fubao Liu and Xiaopeng Chen},
  journal = {PLOS One},
  year = {2026},
  month = oct,
  doi = {10.1371/journal.pone.0359516},
  url = {https://doi.org/10.1371/journal.pone.0359516},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Elucidating the toxicogenomic mechanisms of DBP exposure on Hepatocellular carcinoma through network toxicology and molecular docking analysis
AU  - Dafei Dai
AU  - Nianzhao Yang
AU  - Fubao Liu
AU  - Xiaopeng Chen
PY  - 2026
DA  - 2026/10/28
JO  - PLOS One
DO  - 10.1371/journal.pone.0359516
UR  - https://doi.org/10.1371/journal.pone.0359516
AB  - Backgroud: This study explored the molecular mechanisms by which dibutyl phthalate (DBP) contributes to hepatocellular carcinoma (HCC) pathogenesis using integrated network toxicology and bioinformatics. Methods: DBP’s carcinogenic potential was evaluated with ADMETLAB 3.0 and ProTox3. DBP-related targets were obtained from ChEMBL, SwissTargetPrediction, and PharmMapper; HCC-related targets from GeneCards and OMIM. Overlapping genes were identified by Venn analysis. A protein-protein interaction (PPI) network was constructed using STRING and analyzed with Cytoscape to identify hub genes. Functional enrichment analysis (GO/KEGG) was performed with DAVID. Expression validation and survival analysis used TCGA-LIHC and GEO (GSE39791) data. A prognostic nomogram integrating gene expression and clinical variables was developed. Single-cell RNA sequencing (GSE299340) was analyzed with Seurat to examine hub gene expression. Molecular docking and dynamics simulations investigated DBP interactions with core targets. Results: A total of 242 overlapping genes between DBP-associated and HCC-associated targets were identified. PPI network analysis revealed seven hub genes: KRAS, GRB2, ESR1, HSP90AA1, SRC, EGFR, and TP53. Enrichment analysis indicated significant involvement in cancer-related pathways. Expression analysis in TCGA and GEO datasets confirmed significant dysregulation of GRB2, ESR1, HSP90AA1, and SRC in HCC tissues, which correlated with patient survival outcomes. The prognostic model incorporating these genes showed good predictive accuracy. Single-cell analysis indicated distinct expression patterns of ESR1 (hepatocytes) and HSP90AA1 (immune cells) in HCC. Molecular docking demonstrated stable binding of DBP to ESR1 and HSP90AA1 with favorable binding energies (−6.8 and −6.1 kcal/mol, respectively). Molecular dynamics simulations supported the stability of these complexes, with van der Waals interactions being the primary binding force. Conclusions: This integrative analysis suggests that DBP exposure may contribute to HCC pathogenesis by modulating core genes and pathways, although these findings are associative and require experimental confirmation. Hub genes, especially ESR1 and HSP90AA1, are potential biomarkers and targets. Direct DBP-protein interactions provide mechanistic insights into HCC etiology.
SN  - 1932-6203
ER  -