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Updated: Mar 3, 2026

Mapping Dysfunctional Protein-Protein Interactions in Disease
Published on: October 24, 2025
Unraveling the PFOS-NSCLC axis: integrated network toxicology, machine learning, and causal inference identify
Ting Huang1, Huaxin Pang2, Jundan Wang1
1Department of Oncology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Zhejiang, Hangzhou, China.
Background:
Perfluorooctanesulfonic acid (PFOS) is a persistent environmental pollutant with suspected carcinogenic potential; however, the molecular mechanisms driving PFOS-associated non-small cell lung cancer (NSCLC) remain obscure. In particular, the interplay between chemical exposure, oncogenic signaling nodes, and tumor microenvironment (TME) remodeling is poorly defined. This study integrates systems toxicology with multi-omics to elucidate the role of EIF4EBP1 as a mechanistic bridge connecting PFOS exposure to NSCLC pathogenesis.
Methods:
We synthesized chemical-protein interactions from toxicological databases (ChEMBL, STITCH, and SwissTargetPrediction) and disease-associated genes to map the PFOS-NSCLC intersection. Robust feature selection, utilizing LASSO and SVM-RFE algorithms, was applied to transcriptomic data from the GSE33532 discovery cohort to identify core targets. Key findings were substantiated through external validation in The Cancer Genome Atlas (TCGA) dataset, including differential expression and survival analyses. Causal associations were investigated via two-sample Mendelian randomization (MR), and the immune landscape was characterized using the CIBERSORT algorithm. Molecular docking simulations and an adverse outcome pathway (AOP) framework were further employed to assess mechanistic plausibility.
Results:
Network analysis identified 41 shared targets significantly enriched in PPAR signaling and xenobiotic metabolism. Machine learning consensus prioritized EIF4EBP1 as a critical hub gene. EIF4EBP1 was significantly upregulated in both the discovery (AUC = 0.936) and TCGA validation cohorts. Clinical analysis revealed subtype-specific prognostic value, where high EIF4EBP1 expression correlated with poor survival in lung adenocarcinoma (LUAD) but favorable outcomes in squamous cell carcinoma (LUSC). Immunologically, EIF4EBP1 expression tracked with an adaptive immune-skewed profile, characterized by increased plasma cell and activated CD4 + memory T cell infiltration. MR analysis indicated a potential causal effect of genetically predicted EIF4EBP1 expression on increased LUAD risk (OR = 4.196, 95% CI: 1.209-14.565), but not squamous cell carcinoma. Structural docking confirmed a stable, non-covalent interaction between PFOS and the EIF4EBP1 binding pocket (-7.2 kcal/mol).
Conclusion:
This study identifies EIF4EBP1 as a putative molecular initiating node linking PFOS exposure to LUAD susceptibility and immune modulation. The constructed AOP framework suggests a mechanism wherein PFOS-mediated translational dysregulation contributes to subtype-specific carcinogenesis. These findings provide a data-driven rationale for risk assessment and warrant further experimental verification in toxicological models.
Insights
Perfluorooctanesulfonic acid (PFOS) exposure is linked to lung cancer through EIF4EBP1, a key gene influencing tumor development and immune response. This study reveals EIF4EBP1 as a potential bridge connecting PFOS to lung adenocarcinoma risk.
Area of Science:
- Environmental Toxicology
- Cancer Genomics
- Systems Biology
Background:
- Perfluorooctanesulfonic acid (PFOS) is a persistent pollutant with suspected carcinogenicity.
- Molecular mechanisms linking PFOS to non-small cell lung cancer (NSCLC) are not well understood.
- The interplay between chemical exposure, oncogenic signaling, and tumor microenvironment remodeling in PFOS-associated NSCLC requires elucidation.
Purpose of the Study:
- To identify molecular mechanisms connecting PFOS exposure to NSCLC pathogenesis.
- To elucidate the role of EIF4EBP1 as a mechanistic link between PFOS and NSCLC.
- To investigate the impact of PFOS on the tumor microenvironment and oncogenic signaling.
Main Methods:
- Integrated systems toxicology and multi-omics analyses.
- Network analysis of chemical-protein interactions and disease-associated genes.
- Machine learning (LASSO, SVM-RFE) for feature selection in transcriptomic data.
- External validation using The Cancer Genome Atlas (TCGA) dataset.
- Mendelian randomization (MR) for causal inference and CIBERSORT for immune landscape characterization.
- Molecular docking and Adverse Outcome Pathway (AOP) framework for mechanistic assessment.
Main Results:
- Identified 41 shared targets between PFOS and NSCLC, enriched in PPAR signaling and xenobiotic metabolism.
- Prioritized EIF4EBP1 as a critical hub gene, significantly upregulated in discovery and validation cohorts.
- EIF4EBP1 exhibited subtype-specific prognostic value in lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC).
- EIF4EBP1 expression correlated with an adaptive immune-skewed profile.
- MR analysis suggested a potential causal effect of EIF4EBP1 expression on LUAD risk.
- Molecular docking confirmed a stable interaction between PFOS and EIF4EBP1.
Conclusions:
- EIF4EBP1 is identified as a putative molecular node linking PFOS exposure to LUAD susceptibility and immune modulation.
- A constructed AOP framework suggests PFOS-mediated translational dysregulation contributes to subtype-specific carcinogenesis.
- Findings provide a data-driven rationale for risk assessment and warrant further experimental validation.
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