{"title":"TGF-β1在肺纤维化中的三维肺泡类器官药物筛选模型。","authors":"Hyeong-Jun Han, Hyunyoung Kim","doi":"10.1016/j.bbrep.2025.102191","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":8771,"journal":{"name":"Biochemistry and Biophysics Reports","volume":"43 ","pages":"102191"},"PeriodicalIF":2.2000,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12358629/pdf/","citationCount":"0","resultStr":"{\"title\":\"3D alveolar organoid drug screening model for targeting TGF-β1 in pulmonary fibrosis.\",\"authors\":\"Hyeong-Jun Han, Hyunyoung Kim\",\"doi\":\"10.1016/j.bbrep.2025.102191\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":8771,\"journal\":{\"name\":\"Biochemistry and Biophysics Reports\",\"volume\":\"43 \",\"pages\":\"102191\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12358629/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biochemistry and Biophysics Reports\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.bbrep.2025.102191\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/9/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biochemistry and Biophysics Reports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.bbrep.2025.102191","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/9/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
3D alveolar organoid drug screening model for targeting TGF-β1 in pulmonary fibrosis.
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.
期刊介绍:
Open access, online only, peer-reviewed international journal in the Life Sciences, established in 2014 Biochemistry and Biophysics Reports (BB Reports) publishes original research in all aspects of Biochemistry, Biophysics and related areas like Molecular and Cell Biology. BB Reports welcomes solid though more preliminary, descriptive and small scale results if they have the potential to stimulate and/or contribute to future research, leading to new insights or hypothesis. Primary criteria for acceptance is that the work is original, scientifically and technically sound and provides valuable knowledge to life sciences research. We strongly believe all results deserve to be published and documented for the advancement of science. BB Reports specifically appreciates receiving reports on: Negative results, Replication studies, Reanalysis of previous datasets.