Identifying prognostic biomarkers and immune interactions in ovarian cancer associated with perfluorooctanoic acid exposure: Insights from comparative toxicogenomics and molecular docking studies

全氟辛酸 毒理基因组学 计算生物学 卵巢癌 对接(动物) 分子生物标志物 生物 免疫系统 化学 生物信息学 癌症 医学 肿瘤科 生物化学 遗传学 基因 基因表达 护理部
作者
Jianing Li,Xiaofeng Bian,Caixia Zhang,Yirong Chen,Shijia Huang,Shuli Zhao,Yanchuan Li
出处
期刊:Ecotoxicology and Environmental Safety [Elsevier BV]
卷期号:291: 117831-117831 被引量:7
标识
DOI:10.1016/j.ecoenv.2025.117831
摘要

BACKGROUND: Perfluorooctanoic acid (PFOA) exposure has been implicated in various health issues. This study aims to identify common genes associated with PFOA exposure and ovarian cancer, elucidate their biological functions, and explore their prognostic significance. METHODS: We identified common genes linked to PFOA exposure and ovarian cancer using the Comparative Toxicogenomics Database. Protein-protein interaction and functional enrichment analyses were performed via Metascape. A PFOA-related risk model was developed using TCGA data and LASSO regression. Survival and expression analyses were conducted, and a prognostic nomogram was created. Tumor immune microenvironment interactions were investigated using ESTIMATE and ssGSEA methods. Molecular docking studies assessed the binding affinities between PFOA and target proteins. RESULTS: Utilizing the Comparative Toxicogenomics Database, we identified 229 common genes linked to both PFOA exposure and ovarian cancer. A comprehensive protein-protein interaction (PPI) network analysis revealed distinct functional modules. Enrichment analysis indicated significant involvement of these genes in pathways like the PI3K-Akt signaling pathway and focal adhesion. Lasso regression identified seven key prognostic genes (ERBB2, CCNH, PDE2A, CXCL11, TIAM1, SLC9A1, and EPHA2), with survival analysis demonstrating that PFOA-related high risk group exhibited significantly worse overall survival. Expression analysis showed the dysregulation of key prognostic genes in tumor tissues, while immune correlation analysis indicated significant associations with the tumor microenvironment. Molecular docking and molecular dynamics simulations revealed strong binding affinities between PFOA and the PDE2A. CONCLUSION: Overall, this research contributes to a deeper understanding of the health risks associated with PFOA exposure and highlights the importance of continued monitoring and regulation of environmental pollutants to safeguard public health.
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