2026-10-14T14:10:31Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34030385 2026-09-30T07:00:07Z category_146 category_13 category_14 category_734 category_931 category_64 portal_87 item_type_3 month_year_09_2026

Network toxicology and machine learning analysis of MC-LR-associated hepatocellular carcinoma Zhipeng Xu (198453) Ji Luo (312306) Jiaming Liang (7236017) Jianwen Deng (2207002) Minju He (25142252) Tongfen Cao (25142255) Guangzhao Chen (4498513) Space Science Genetics Molecular Biology Biological Sciences not elsewhere classified Information Systems not elsewhere classified Cancer Microcystin-LR network toxicology hepatocellular carcinoma machine learning molecular docking <p>Microcystin-LR (MC-LR), a hepatotoxic aquatic contaminant classified by IARC as a Group 2B carcinogen, was investigated using an integrated network toxicology and machine learning framework to explore potential molecular mechanisms underlying MC-LR-related hepatocarcinogenesis. By integrating GEO transcriptomic datasets, differential expression analysis, WGCNA, and predicted MC-LR targets, we identified 24 candidate genes potentially associated with MC-LR-related HCC. Functional enrichment analyses implicated these genes mainly in complement and coagulation cascades and metabolic processes. Machine learning consensus analysis prioritized five core genes—AKR1C3, FABP5, CA2, ADH1B, and EPHX2—each showing an AUC greater than 0.79 and suggesting moderate discriminatory potential. Single-gene GSEA linked these genes mainly to ribosome-related pathways, while single-cell transcriptomic analysis revealed cell-type-specific expression heterogeneity within the HCC microenvironment. Molecular docking provided exploratory structural evidence for possible in silico compatibility between MC-LR and the encoded proteins. However, further experimental validation is required to confirm this hypothesis. Overall, these findings establish a multidimensional framework for investigating MC-LR-associated hepatotoxicity and nominate candidate molecular nodes for future biomarker assessment, functional validation, and environment-related HCC risk evaluation.</p> 2026-09-30T07:00:07Z Dataset Dataset 10.6084/m9.figshare.34030385.v1 https://figshare.com/articles/dataset/Network_toxicology_and_machine_learning_analysis_of_MC-LR-associated_hepatocellular_carcinoma/34030385 CC BY 4.0