⚡ Quick Summary
This study investigates the role of per- and polyfluoroalkyl substances (PFAS), particularly PFOA and PFOS, in the development of hepatocellular carcinoma (HCC) using a comprehensive multi-omics approach. The research identifies six key genes associated with PFAS exposure that could serve as potential prognostic biomarkers for HCC.
🔍 Key Details
- 📊 Study Focus: PFAS and their link to hepatocellular carcinoma
- 🔬 Methods: Multi-omics, machine learning, single-cell RNA sequencing, spatial transcriptomics
- 🧬 Key Genes Identified: APOA1, ESR1, IGF1, PPARGC1A, SERPINE1, PON1
- ⚙️ Validation Techniques: RT-qPCR, immunohistochemical staining, molecular docking simulations
🔑 Key Takeaways
- 🔍 PFAS exposure is increasingly linked to liver toxicity and HCC development.
- 🧬 Six core genes were identified as significant in PFAS-related HCC progression.
- 📈 The PFAS-related HCC signature (PFASRHSig) was developed as a survival risk model.
- 🔬 Multi-omics approaches provide a comprehensive understanding of disease mechanisms.
- 💡 Molecular docking simulations confirmed strong binding affinities between PFAS and target proteins.
- 🌱 Findings offer potential therapeutic targets for mitigating health risks associated with PFAS exposure.
- 📊 The study utilized publicly available transcriptomic data from multiple HCC cohorts.
- 🌍 Insights gained could advance clinical applications and improve patient outcomes.
📚 Background
Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals widely used in various industries due to their water- and grease-resistant properties. However, their environmental persistence and potential health risks have raised significant concerns. Recent studies have linked PFAS exposure to various health issues, including hepatotoxicity and the development of hepatocellular carcinoma (HCC), a common type of liver cancer. Understanding the molecular mechanisms behind these associations is crucial for developing effective interventions.
🗒️ Study
This research employed a multi-omics approach to explore the mechanisms by which PFAS contribute to HCC. The study analyzed publicly available transcriptomic data from several HCC cohorts, utilizing techniques such as single-cell RNA sequencing and spatial transcriptomics to identify differential gene expression patterns. The integration of machine learning and network toxicology allowed for the construction of a protein-protein interaction (PPI) network and the development of the PFAS-related HCC signature (PFASRHSig) for prognostic biomarker identification.
📈 Results
The study identified six core genes—APOA1, ESR1, IGF1, PPARGC1A, SERPINE1, and PON1—that are significantly associated with PFAS exposure and HCC progression. Functional enrichment analyses indicated that these genes are involved in critical metabolic signaling pathways related to lipid and glucose metabolism. Validation through RT-qPCR and immunohistochemical staining confirmed the expression levels of these targets in both tumor and normal tissues, while molecular docking simulations demonstrated strong binding affinities between PFAS compounds and the identified target proteins.
🌍 Impact and Implications
The findings from this study provide valuable insights into the molecular targets and pathways involved in PFAS-induced liver carcinogenesis. By identifying key genes and developing a robust survival risk model, the research opens new avenues for potential therapeutic interventions aimed at mitigating the health risks associated with PFAS exposure. This work not only enhances our understanding of PFAS toxicity mechanisms but also contributes to advancing clinical applications in the field of oncology.
🔮 Conclusion
This study underscores the importance of a multi-omics approach in unraveling the complex interactions between environmental toxins like PFAS and cancer development. The identification of core genes associated with HCC progression offers promising targets for future research and therapeutic strategies. As we continue to explore the implications of PFAS exposure, it is essential to prioritize public health initiatives aimed at reducing these harmful substances in our environment.
💬 Your comments
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Decoding per- and polyfluoroalkyl substances (PFAS) in hepatocellular carcinoma: a multi-omics and computational toxicology approach.
Abstract
BACKGROUND: Per- and polyfluoroalkyl substances (PFAS), particularly perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS), are synthetic chemicals known for their widespread use and environmental persistence. These compounds have been increasingly linked to hepatotoxicity and the development of hepatocellular carcinoma (HCC). However, the molecular mechanisms by which PFAS contribute to HCC remain underexplored.
METHODS: This study employs a multi-omics approach that combines network toxicology, integrated machine learning, single-cell RNA sequencing, spatial transcriptomics, experimental validation, and molecular docking simulations to uncover the mechanisms through which PFAS exposure drives HCC. We analyzed publicly available transcriptomic data from several HCC cohorts and used differential gene expression analysis to identify targets associated with both PFAS exposure and HCC. We constructed a protein-protein interaction (PPI) network and a survival risk model, the PFAS-related HCC signature (PFASRHSig), based on integrated machine learning to identify prognostic biomarkers, with the goal of identifying core targets of PFAS in HCC progression and prognosis. RT-qPCR and immunohistochemical (IHC) staining were used to validate the expression levels of the targets in both tumor and normal tissues. Molecular docking simulations were conducted to assess the binding affinities between PFAS compounds and selected target proteins.
RESULTS: Functional enrichment studies revealed that PFAS targets were associated with metabolic signaling pathways, which are actively involved in lipid, glucose, drug metabolism, etc. Through integrated machine learning and PPI network analysis, we identified six genes, APOA1, ESR1, IGF1, PPARGC1A, SERPINE1, and PON1, that serve as core targets of PFAS in both HCC progression and prognosis. These targets were further validated via bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics, which revealed differential expression patterns across various cell types in the HCC tumor microenvironment. The results of RT-qPCR and IHC staining were consistent with the in silico findings. Molecular docking simulations revealed strong binding affinities between PFAS compounds and these core targets, supporting their potential roles in PFAS-induced hepatocarcinogenesis.
CONCLUSIONS: Our study highlights key molecular targets and pathways involved in PFAS-induced liver carcinogenesis and proposes a robust survival risk model (PFASRHSig) for HCC. These findings provide new insights into PFAS toxicity mechanisms and offer potential therapeutic targets for mitigating the health risks associated with PFAS exposure. Collectively, our findings help in advancing clinical applications by providing insights into disease mechanisms and potential therapeutic interventions.
Author: [‘Hong Y’, ‘Wang D’, ‘Liu Z’, ‘Chen Y’, ‘Wang Y’, ‘Li J’]
Journal: J Transl Med
Citation: Hong Y, et al. Decoding per- and polyfluoroalkyl substances (PFAS) in hepatocellular carcinoma: a multi-omics and computational toxicology approach. Decoding per- and polyfluoroalkyl substances (PFAS) in hepatocellular carcinoma: a multi-omics and computational toxicology approach. 2025; 23:504. doi: 10.1186/s12967-025-06517-z