Authors
Changhui Lang, Jieling Wu, Nuoxin Wang
Published in
Molecular genetics and genomics : MGG. Volume 301. Issue 1. Jul 14, 2026. Epub Jul 14, 2026.
Abstract
Neutrophil extracellular traps (NETs) facilitate inflammation and epithelial-mesenchymal transition (EMT), promoting the progression of pulmonary fibrosis. Various machine learning methods were used to screen for prognostic genes. Based on prognostic genes, a risk model was constructed to assess their ability for prognosis prediction of idiopathic pulmonary fibrosis (IPF). Mendelian Randomization (MR) analysis evaluated causal associations between IPF and prognostic genes, while GSE122960 examined cell-type-specific expression. A bleomycin-induced pulmonary fibrosis mouse was established, collagen deposition was assessed by Masson and Picrosirius Red staining, the expression of prognostic genes were validated by Reverse Transcription quantitative Polymerase Chain Reaction (RT-qPCR) and Western blot (WB), and NETs-related protein ( Cith3 and MPO ) were evaluated by immunofluorescence. A comprehensive analysis resulted in the identification of 3 prognostic genes (MMP1, CXCR7, and TPST1), followed by the development of a NET-inflammation-associated prognostic model, which well predicted the prognosis of IPF. Moreover, exploratory MR analysis suggested possible positive associations between genetically predicted MMP1 and TPST1 expression and IPF risk. Single-cell analysis revealed the expression of MMP1 and TPST1 differed significantly in monocytes between IPF patients and controls. Furthermore, significant differences were identified in functional pathways and immune cell infiltration between risk groups. Masson and Picrosirius Red staining confirmed collagen deposition in the bleomycin-induced pulmonary fibrosis mouse model. RT-qPCR and WB showed higher expression of MMP1, CXCR7, and TPST1 in pulmonary fibrosis mice than in controls. Cith3 + MPO double immunofluorescence staining showed increased NETs-related signals in the model group than the control. These findings provide potential prognostic markers for IPF patients and may enhance comprehension of the disease's underlying inflammatory and fibrotic processes.
PMID:
42446678
Bibliographic data and abstract were imported from PubMed on 14 Jul 2026.
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