Systematic Exploration of Potential Toxicity Targets and Molecular Mechanisms of Emerging Short-Chain PFAS Substitutes: PFBA- and PFBS-Induced Hepatocellular Carcinoma Based on Toxicity Network Analysis, Machine Learning, and Biomimetic Calculations.

Journal: Journal of applied toxicology : JAT
Published Date: May 30, 2025

Abstract

Perfluorobutanoic acid (PFBA) and perfluorobutanesulfonic acid (PFBS) are short-chain alternatives to traditional perfluoroalkyl and polyfluoroalkyl substances (PFASs). Long-term exposure to these pollutants is closely associated with hepatocellular carcinoma (HCC). However, the toxic targets and mechanisms underlying PFBA- and PFBS-induced HCC remain unclear. To address this knowledge gap, this study employed a multifaceted approach encompassing network toxicology, molecular docking, and molecular dynamic simulation. Thirty-six core targets associated with PFBA- and PFBS-induced HCC were identified, and 12 key genes were initially screened through network toxicity analysis. Subsequently, based on the TCGA and ICGC datasets, three classical algorithms were applied to screen key genes: PPARG, ESR1, and ALB. Further exploration of the HCC-related dataset from the GEO database identified six critical genes: PPARG, ESR1, CD36, ABCA1, ACACA, and ALB. Survival analysis and ROC analysis based on the TCGA dataset revealed and validated the strong association between the expression levels of key genes (PPARG, ESR1, and ACACA). Single-gene GSEA showed that these three key genes may induce HCC through multiple biological pathways via interfering with the normal growth and development of hepatocytes and promoting inflammation and cell proliferation. Ultimately, molecular dynamics demonstrated the strong binding affinities between PFBA, PFBS, and the three protein receptors, with the best stability and flexibility of the interaction between PFBS and PPARG. These findings provide insights into the theoretical foundation for applying network toxicology, molecular docking, and molecular dynamic simulations in environmental pollutant research.

Authors

  • Zirui Zhang
    Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China.
  • Jin Wang
    Cells Vision (Guangzhou) Medical Technology Inc., Guangzhou, China. Electronic address: wangjin@cellsvision.com.
  • Zhongyi Zhang
    Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, China.
  • Qianrong Gan
    Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
  • Yunliang He
    Institute of Traditional Chinese Medicine, Sichuan Academy of Chinese Medicine Sciences, Chengdu, Sichuan, China.
  • Donghui Chen
    Institute of Traditional Chinese Medicine, Sichuan Academy of Chinese Medicine Sciences, Chengdu, Sichuan, China.
  • Yong Zhang
    Outpatient Department of Hepatitis, The Sixth Affiliated People's Hospital of Dalian Medical University, Dalian, Liaoning, China.
  • Mei Zhao
    College of Materials Science and Engineering, Qingdao University of Science and Technology, Qingdao 266042, China. Electronic address: zhaomei@qust.edu.cn.

Keywords

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