ArticleBiochemistry and biophysics reports2025
3D alveolar organoid drug screening model for targeting TGF-β1 in pulmonary fibrosis.
Article in Biochemistry and biophysics reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Stem cell-based therapies for silicosis: mechanisms, sources, clinical translation, and emerging strategies.Frontiers in immunology · 2026Review
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2 authors.
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Abstract
Idiopathic pulmonary fibrosis (IPF) is a prototype of chronic, progressive, and fibrotic lung disease. Excessive deposition of extracellular matrix (ECM) results in fibrotic remodeling, alveolar destruction, and irreversible lung dysfunction. In addition to myofibroblast activation and ECM deposition, repetitive lung epithelial cell damage and reprogramming areconsidered to be closely involved in IPF pathogenesis. Transforming growth factor (TGF)-β1 plays an important role in IPF and cancer; it is a major pro-fibrotic cytokine, and is a potential target for treating fibrotic diseases.TGF-β1 binds to TGF-βRII, phosphorylating TGF-βRI, and enhances ECM expression via the suppressor of mothers against decapentaplegic (SMAD) phosphorylation signaling pathway. Current medical interventions for IPF are predominantly anti-fibrotic medications such as pirfenidone and nintedanib, which are effective in delaying lung function deterioration, reducing acute symptom exacerbations, and increasing overall life expectancy. However, these pharmaceutical agents cannot repair fibrotic pulmonary tissues or impede disease progression. To bridge this gap, we constructed a model of TGF-β1-induced fibrosis and screened for potential drugs. From 320 anti-fibrotic drugs, 9 hits were found in the TGF-β1-induced fibrosis model, and after validation, the final 7 hits were identified as TGF-β1 inhibitors. All the 7 hits were confirmed as TGF-βRI inhibitors, which showed that the model could quickly and easily discover new compounds that can act as TGF-β1 inhibitors. This study is significantbecausewe useda 3D model to swiftly and precisely identify TGF-β1 inhibitors, potentially accelerating the clinical translation of TGF-β1-targeted therapies for fibrotic diseases.
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