Evidence map›Paper›PMID 42672059›Full record

ArticlePloS one2026

Integrated computational analysis prioritizes candidate targets and pathways linking ochratoxin A exposure to hepatocellular carcinoma.

Shili Yang, Huaiquan Liu, Haiyang Kou, Lingyan Lai, Xinyan Zhang, Yunling Xu, Yu Sun, Bo Chen

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Shili YangGuizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China.ORCID https://orcid.org/0009-0009-4125-3323
Huaiquan LiuGuizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China.
Haiyang KouGuizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China.
Lingyan LaiGuizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China.
Xinyan ZhangGuizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China.
Yunling XuGuizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China.
Yu SunGuizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China.
Bo ChenGuizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China.ORCID https://orcid.org/0009-0003-1150-727X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Carcinoma, HepatocellularComputational BiologyLiver NeoplasmsOchratoxinsGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMolecular Docking SimulationMolecular Dynamics SimulationSignal Transductionochratoxin AOchratoxins

Identifiers

PMID42672059
PMCPMC13529001

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.