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Predicting biomarkers of progressive pulmonary fibrosis: morphological, cytokine profile, and clinical portrait
Predicting biomarkers of progressive pulmonary fibrosis: morphological, cytokine profile, and clinical portrait
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Predicting biomarkers of progressive pulmonary fibrosis: morphological, cytokine profile, and clinical portrait
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Predicting biomarkers of progressive pulmonary fibrosis: morphological, cytokine profile, and clinical portrait
Predicting biomarkers of progressive pulmonary fibrosis: morphological, cytokine profile, and clinical portrait
Journal Article

Predicting biomarkers of progressive pulmonary fibrosis: morphological, cytokine profile, and clinical portrait

2025
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Overview
The term progressive pulmonary fibrosis (PPF) refers to a specific disorder that becomes worse despite optimal treatment. The pathogenic explanation of this progressive worsening is still to be found. In this study, we explored whether any histological, molecular, radiological, or clinical features could predict a progressive phenotype in patients with fibrotic interstitial lung diseases. Two hundred and fifteen patients with PPF other than idiopathic pulmonary fibrosis (IPF) and connective tissue disease-associated ILD (CTD-ILD) were followed in our ILD clinic between January 2016 and May 2023. Based on tissue block availability, 48 patients were definitively enrolled. Progression was defined according to the most recent guidelines. Clinical, radiological, and functional data were also collected retrospectively and correlated with tissue morphological and molecular cytokine profiles. Fifteen patients were classified as progressors (PPF) and 33 as non-progressors (nPPF) with similar age at diagnosis and gender. PPF showed a higher prevalence of traction bronchiectasis (80% vs. 27%; p=<0.001) at CT scan and lower functional parameters [FVC: 2.42 L vs. 3.37 L; p=0.004; TLC: 3.83 L vs. 4.65 L; p=0.027] at diagnosis. Lung specimens revealed a significant overexpression of IL9 in the PPF compared to the nPPF group (p=0.049). Boruta algorithm analysis showed that lymphoid aggregates and traction bronchiectasis at diagnosis are the most important variables in determining the PPF status. The present results increase the understanding of the pathological mechanisms of PPF, offering potential avenues for improved prognostication and therapeutic intervention.