J Transl Med. 2025 May 2;23(1):504. doi: 10.1186/s12967-025-06517-z.

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.

PMID:40317014 | PMC:PMC12049027 | DOI:10.1186/s12967-025-06517-z

Respir Res. 2025 Mar 26;26(1):115. doi: 10.1186/s12931-025-03185-x.

ABSTRACT

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of global mortality, with acute exacerbations of COPD (AECOPD) significantly increasing the disease's morbidity and mortality. Among the pathogens implicated in AECOPD, Pseudomonas aeruginosa (P. aeruginosa) is increasingly recognized as a major co-infecting bacterium. Despite its clinical importance, the molecular mechanisms and therapeutic targets underlying AECOPD with P. aeruginosa infection remain inadequately understood.

METHODS: We employed a multi-omics approach, integrating proteomic analyses of bronchoalveolar lavage fluid (BALF) and plasma with transcriptomic analysis of peripheral blood. A discovery cohort of 40 AECOPD with P. aeruginosa infection patients and 20 healthy controls was analyzed, followed by validation in an independent cohort of 20 patients and 10 controls. Differentially expressed proteins (DEPs) and genes (DEGs) were identified and subjected to protein-protein interaction (PPI) network analysis, weighted gene co-expression network analysis (WGCNA), and immune infiltration analysis. Molecular docking simulations were conducted to explore potential therapeutic agents.

RESULTS: Our integrative analysis identified key biomarkers, which played critical roles in oxidative stress and neutrophil extracellular trap (NET) formation, both of which were pivotal in the pathogenesis of AECOPD with P. aeruginosa infection. The combined analysis of BALF, plasma, and peripheral blood underscored the interplay between local lung changes and systemic immune responses. Functional enrichment analyses highlighted significant pathways related to bacterial defense, inflammation, and immune activation. Validation in an independent cohort confirmed the diagnostic value of three key proteins (AZU1, MPO, and RETN), with high area under the curve (AUC) values in ROC analyses. Molecular docking indicated strong binding affinities of these proteins with Pioglitazone and Rosiglitazone, suggesting potential therapeutic utility.

CONCLUSIONS: This study provides a comprehensive understanding of the molecular mechanisms underlying AECOPD with P. aeruginosa infection, highlighting the pivotal roles of oxidative stress and NET formation in disease progression. The identified biomarkers offer promising diagnostic and therapeutic targets. Our findings pave the way for novel strategies to improve outcomes for AECOPD patients with P. aeruginosa infection. While the study design limits our ability to establish causality, these results provide important insights that warrant further investigation, particularly through longitudinal studies, to confirm the specific contributions of P. aeruginosa in exacerbations.

CLINICAL TRIAL NUMBER: Not applicable.

PMID:40140846 | PMC:PMC11948814 | DOI:10.1186/s12931-025-03185-x