Integrated computational analysis prioritizes candidate targets and pathways linking ochratoxin A exposure to hepatocellular carcinoma
- 1Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China
Abstract
Ochratoxin A (OTA), a food-borne mycotoxin, has been implicated in hepatotoxicity and potential carcinogenic processes, yet the molecular links between OTA exposure and hepatocellular carcinoma (HCC) remain incompletely understood. This study used an integrated computational workflow to prioritize candidate targets and pathways potentially linking OTA exposure with HCC. OTA-related and HCC-related targets were collected from public databases, intersected, and subjected to functional enrichment analysis. Transcriptomic data from the GSE36376 discovery dataset were analyzed to identify differentially expressed genes, followed by LASSO and SVM-RFE feature selection, immune-cell deconvolution, molecular docking, and molecular dynamics simulation. A total of 214 overlapping OTA-HCC-associated targets were identified and were enriched in pathways related to signal transduction, apoptosis, metabolism, and immune regulation. In GSE36376, 443 differentially expressed genes were identified using p < 0.05 and |log2 fold change| > 1, and overlap analysis yielded 13 shared target genes. Five candidate targets, CYP3A4, KIFC1, AKR1C3, CA2, and TTR, were further prioritized. KIFC1 and AKR1C3 were upregulated in HCC samples, whereas CYP3A4, CA2, and TTR were downregulated. These genes showed apparent discriminatory ability within the discovery dataset, with AUC values ranging from 0.866 to 0.958. Molecular docking predicted favorable OTA-target interactions, with docking energies ranging from −7.4 to −10.8 kcal/mol. CYP3A4 showed the lowest predicted docking energy (−10.8 kcal/mol) and was further evaluated by molecular dynamics simulation, with a protein-fitted OTA RMSD of 1.435 ± 0.097 nm and complex Rg of 2.308 ± 0.010 nm during the equilibrated 20–100 ns trajectory. Overall, this study provides a reproducible hypothesis-generating framework for exploring potential metabolic, genomic-instability-related, and immune-microenvironment links between OTA exposure and HCC. Future validation in independent datasets and experimental models will be important to further assess the biological relevance of these candidate targets and pathways.
Related
- Integrated GWAS and linkage mapping in a multi-parent population prioritizes candidate genes for kernel number per row in maize
- Computational prediction of a multi-epitope Human Metapneumovirus vaccine candidate through integrated reverse vaccinology and pan-genomic approaches
- REN-former prioritizes candidate regulators of kidney disease-state transitions through single-cell foundation modeling and human genetics
- Integrative single-cell and bulk transcriptomics with reverse network pharmacology prioritizes macrophage-associated candidate genes in Lyme arthritis
- Integrated Transcriptomic and CRISPR Dependency Analysis Prioritizes a CDK1-AURKB Mitotic Vulnerability Axis in Diffuse Intrinsic Pontine Glioma
BibTeX
@article{yang2026integrated,
title = {{Integrated computational analysis prioritizes candidate targets and pathways linking ochratoxin A exposure to hepatocellular carcinoma}},
author = {Shili Yang and Huaiquan Liu and Haiyang Kou and Lingyan Lai and Xinyan Zhang and Yunling Xu and Yu Sun and Bo Chen},
journal = {PLOS One},
year = {2026},
month = aug,
doi = {10.1371/journal.pone.0357594},
url = {https://doi.org/10.1371/journal.pone.0357594},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Integrated computational analysis prioritizes candidate targets and pathways linking ochratoxin A exposure to hepatocellular carcinoma
AU - Shili Yang
AU - Huaiquan Liu
AU - Haiyang Kou
AU - Lingyan Lai
AU - Xinyan Zhang
AU - Yunling Xu
AU - Yu Sun
AU - Bo Chen
PY - 2026
DA - 2026/08/31
JO - PLOS One
DO - 10.1371/journal.pone.0357594
UR - https://doi.org/10.1371/journal.pone.0357594
AB - Ochratoxin A (OTA), a food-borne mycotoxin, has been implicated in hepatotoxicity and potential carcinogenic processes, yet the molecular links between OTA exposure and hepatocellular carcinoma (HCC) remain incompletely understood. This study used an integrated computational workflow to prioritize candidate targets and pathways potentially linking OTA exposure with HCC. OTA-related and HCC-related targets were collected from public databases, intersected, and subjected to functional enrichment analysis. Transcriptomic data from the GSE36376 discovery dataset were analyzed to identify differentially expressed genes, followed by LASSO and SVM-RFE feature selection, immune-cell deconvolution, molecular docking, and molecular dynamics simulation. A total of 214 overlapping OTA-HCC-associated targets were identified and were enriched in pathways related to signal transduction, apoptosis, metabolism, and immune regulation. In GSE36376, 443 differentially expressed genes were identified using p < 0.05 and |log2 fold change| > 1, and overlap analysis yielded 13 shared target genes. Five candidate targets, CYP3A4, KIFC1, AKR1C3, CA2, and TTR, were further prioritized. KIFC1 and AKR1C3 were upregulated in HCC samples, whereas CYP3A4, CA2, and TTR were downregulated. These genes showed apparent discriminatory ability within the discovery dataset, with AUC values ranging from 0.866 to 0.958. Molecular docking predicted favorable OTA-target interactions, with docking energies ranging from −7.4 to −10.8 kcal/mol. CYP3A4 showed the lowest predicted docking energy (−10.8 kcal/mol) and was further evaluated by molecular dynamics simulation, with a protein-fitted OTA RMSD of 1.435 ± 0.097 nm and complex Rg of 2.308 ± 0.010 nm during the equilibrated 20–100 ns trajectory. Overall, this study provides a reproducible hypothesis-generating framework for exploring potential metabolic, genomic-instability-related, and immune-microenvironment links between OTA exposure and HCC. Future validation in independent datasets and experimental models will be important to further assess the biological relevance of these candidate targets and pathways.
SN - 1932-6203
ER -