计算生物学
分子生物标志物
邻苯二甲酸盐
致癌物
污染物
基因
对接(动物)
生物
化学
毒理
遗传学
医学
肿瘤科
生态学
护理部
有机化学
作者
Chenyu Liang,Wei‐Cheng Tian,H. Zeng,Ziyang Xia,Zijie Luo,Yue Zhuo,Min Pan,Kaifu Wu,Siyu Xiong,Xuejing Lin,Xinchun Li,Jiaxi Yu
摘要
ABSTRACT Mono(2‐ethylhexyl) phthalate (MEHP) is a ubiquitous environmental contaminant and endocrine‐disrupting chemical (EDC), identified as a potential carcinogen. Emerging studies have begun to elucidate the impact of MEHP on prostate cancer (PCa), yet its pathogenic effects and the underlying molecular mechanisms remain unclear. This study seeks to explore the molecular basis through which MEHP affects the onset and progression of PCa. Using network toxicology and bioinformatics, we identified MEHP‐related pathogenic genes in PCa. An innovative predictive model was developed by employing multiple machine learning ensemble algorithms, and its performance was validated using the area under the receiver operating characteristic (ROC) curve. Furthermore, at the single‐cell resolution, the role of key MEHP‐associated molecules, including several critical genes, in the oncogenic progression of PCa was identified. Through the construction of an environmental pollutant–key gene–PCa network, we investigated the interactions between environmental pollutants and the key genes VGF , ASPN , FOXS1 , APLN , and AMH . Molecular docking studies demonstrated that the APLN , FOXS1 , and ASPN genes exhibited favorable binding energies and high affinities for MEHP. The findings of this study provide a theoretical foundation for understanding the pathogenic role of MEHP in PCa and its potential molecular mechanisms. They also promote the application of network toxicology, molecular docking, machine learning, and single‐cell analysis in the study of environmental pollutants.
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