ArticleBMC pharmacology & toxicology2025
Integrative analysis reveals key molecular mechanisms and prognostic model for Ethylnitrosourea-induced gliomagenesis.
Article in BMC pharmacology & toxicology, 2025. 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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Abstract
backgroundEthylnitrosourea (ENU) is a potent mutagen that induces gliomas in experimental models. Understanding the molecular mechanisms underlying ENU-induced gliomagenesis can provide insights into glioma pathogenesis and potential therapeutic targets.
methodsWe analyzed gene expression data from GSE16011 and GSE4290 datasets to identify differentially expressed genes (DEGs) associated with gliomagenesis. Comparative Toxicogenomics Database (CTD) was used to identify potential ENU targets. Protein-protein interaction (PPI) network, enrichment analysis, and Cox regression analysis were employed to elucidate key genes and pathways. A risk model was constructed using the TCGA dataset by LASSO analysis, and nomogram and immuno-infiltration analyses were performed.
resultsWe identified 71 common genes potentially in ENU-induced gliomas. Key hub genes, including TP53, MCL1, CCND1, and PTEN, were highlighted in the PPI network. Enrichment analysis revealed significant GO terms and KEGG pathways, such as "Neuroactive ligand-receptor interaction" and "Glioma." A risk model based on 11 prognostic genes was constructed, effectively stratifying patients into low and high-risk groups, with significant differences in overall survival. The model demonstrated high predictive accuracy. The nomogram constructed from ENU-related risk scores showed good calibration and clinical utility. Immuno-infiltration analysis indicated higher immune cell infiltration in high-risk patients. Molecular docking suggested strong binding affinities of ENU with MGMT and CA12.
conclusionOur integrative analysis identified key genes and pathways implicated in ENU-induced gliomagenesis. The ENU-related risk model and nomogram provide significant prognostic value, offering potential tools for clinical assessment and targeted therapies in glioma patients.
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