Linh T Ngo, Michaella J Rekowski, Devin C Koestler, Takafumi Yorozuya, Atsushi Saito, Imaan Azeem, Alexis Harrison, M Kristen Demoruelle, Jonathan Boomer, Bryant R England, Paul Wolters, Philip L Molyneaux, Mario Castro, Joyce S Lee, Joshua J Solomon, Koji Koronuma, Michael P Washburn, Scott M Matson
{"title":"支气管肺泡灌洗液的蛋白质组分析发现了与特发性间质性肺病存活率相关的蛋白质群。","authors":"Linh T Ngo, Michaella J Rekowski, Devin C Koestler, Takafumi Yorozuya, Atsushi Saito, Imaan Azeem, Alexis Harrison, M Kristen Demoruelle, Jonathan Boomer, Bryant R England, Paul Wolters, Philip L Molyneaux, Mario Castro, Joyce S Lee, Joshua J Solomon, Koji Koronuma, Michael P Washburn, Scott M Matson","doi":"10.1183/23120541.00192-2024","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Idiopathic interstitial pneumonias (IIPs), such as idiopathic pulmonary fibrosis and interstitial pneumonia with autoimmune features, present diagnostic and therapeutic challenges due to their heterogeneous nature. This study aimed to identify intrinsic molecular signatures within the lung microenvironment of these IIPs through proteomic analysis of bronchoalveolar lavage fluid (BALF).</p><p><strong>Methods: </strong>Patients with IIP (n=23) underwent comprehensive clinical evaluation including pre-treatment bronchoscopy and were compared with controls without lung disease (n=5). Proteomic profiling of BALF was conducted using label-free quantitative methods. Unsupervised cluster analyses identified protein expression profiles that were then analysed to predict survival outcomes and investigate associated pathways.</p><p><strong>Results: </strong>Proteomic profiling successfully differentiated IIP from controls. k-means clustering based on protein expression revealed three distinct IIP clusters, which were not associated with age, smoking history, or baseline pulmonary function. These clusters had unique survival trajectories and provided more accurate survival predictions than the Gender Age Physiology index (concordance index 0.794 <i>versus</i> 0.709). The cluster with the worst prognosis featured decreased inflammatory signalling and complement activation, with pathway analysis highlighting altered immune response pathways related to immunoglobulin production and B-cell-mediated immunity.</p><p><strong>Conclusions: </strong>The unsupervised clustering of BALF proteomics provided a novel stratification of IIP patients, with potential implications for prognostic and therapeutic targeting. The identified molecular phenotypes underscore the diversity within the IIP classification and the potential importance of personalised treatments for these conditions. Future validation in larger, multi-ethnic cohorts is essential to confirm these findings and to explore their utility in clinical decision-making for patients with IIP.</p>","PeriodicalId":11739,"journal":{"name":"ERJ Open Research","volume":"10 6","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11647942/pdf/","citationCount":"0","resultStr":"{\"title\":\"Proteomic profiling of bronchoalveolar lavage fluid uncovers protein clusters linked to survival in idiopathic forms of interstitial lung disease.\",\"authors\":\"Linh T Ngo, Michaella J Rekowski, Devin C Koestler, Takafumi Yorozuya, Atsushi Saito, Imaan Azeem, Alexis Harrison, M Kristen Demoruelle, Jonathan Boomer, Bryant R England, Paul Wolters, Philip L Molyneaux, Mario Castro, Joyce S Lee, Joshua J Solomon, Koji Koronuma, Michael P Washburn, Scott M Matson\",\"doi\":\"10.1183/23120541.00192-2024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Idiopathic interstitial pneumonias (IIPs), such as idiopathic pulmonary fibrosis and interstitial pneumonia with autoimmune features, present diagnostic and therapeutic challenges due to their heterogeneous nature. This study aimed to identify intrinsic molecular signatures within the lung microenvironment of these IIPs through proteomic analysis of bronchoalveolar lavage fluid (BALF).</p><p><strong>Methods: </strong>Patients with IIP (n=23) underwent comprehensive clinical evaluation including pre-treatment bronchoscopy and were compared with controls without lung disease (n=5). Proteomic profiling of BALF was conducted using label-free quantitative methods. Unsupervised cluster analyses identified protein expression profiles that were then analysed to predict survival outcomes and investigate associated pathways.</p><p><strong>Results: </strong>Proteomic profiling successfully differentiated IIP from controls. k-means clustering based on protein expression revealed three distinct IIP clusters, which were not associated with age, smoking history, or baseline pulmonary function. These clusters had unique survival trajectories and provided more accurate survival predictions than the Gender Age Physiology index (concordance index 0.794 <i>versus</i> 0.709). The cluster with the worst prognosis featured decreased inflammatory signalling and complement activation, with pathway analysis highlighting altered immune response pathways related to immunoglobulin production and B-cell-mediated immunity.</p><p><strong>Conclusions: </strong>The unsupervised clustering of BALF proteomics provided a novel stratification of IIP patients, with potential implications for prognostic and therapeutic targeting. The identified molecular phenotypes underscore the diversity within the IIP classification and the potential importance of personalised treatments for these conditions. Future validation in larger, multi-ethnic cohorts is essential to confirm these findings and to explore their utility in clinical decision-making for patients with IIP.</p>\",\"PeriodicalId\":11739,\"journal\":{\"name\":\"ERJ Open Research\",\"volume\":\"10 6\",\"pages\":\"\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11647942/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERJ Open Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1183/23120541.00192-2024\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/11/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"RESPIRATORY SYSTEM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERJ Open Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1183/23120541.00192-2024","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"RESPIRATORY SYSTEM","Score":null,"Total":0}
Proteomic profiling of bronchoalveolar lavage fluid uncovers protein clusters linked to survival in idiopathic forms of interstitial lung disease.
Background: Idiopathic interstitial pneumonias (IIPs), such as idiopathic pulmonary fibrosis and interstitial pneumonia with autoimmune features, present diagnostic and therapeutic challenges due to their heterogeneous nature. This study aimed to identify intrinsic molecular signatures within the lung microenvironment of these IIPs through proteomic analysis of bronchoalveolar lavage fluid (BALF).
Methods: Patients with IIP (n=23) underwent comprehensive clinical evaluation including pre-treatment bronchoscopy and were compared with controls without lung disease (n=5). Proteomic profiling of BALF was conducted using label-free quantitative methods. Unsupervised cluster analyses identified protein expression profiles that were then analysed to predict survival outcomes and investigate associated pathways.
Results: Proteomic profiling successfully differentiated IIP from controls. k-means clustering based on protein expression revealed three distinct IIP clusters, which were not associated with age, smoking history, or baseline pulmonary function. These clusters had unique survival trajectories and provided more accurate survival predictions than the Gender Age Physiology index (concordance index 0.794 versus 0.709). The cluster with the worst prognosis featured decreased inflammatory signalling and complement activation, with pathway analysis highlighting altered immune response pathways related to immunoglobulin production and B-cell-mediated immunity.
Conclusions: The unsupervised clustering of BALF proteomics provided a novel stratification of IIP patients, with potential implications for prognostic and therapeutic targeting. The identified molecular phenotypes underscore the diversity within the IIP classification and the potential importance of personalised treatments for these conditions. Future validation in larger, multi-ethnic cohorts is essential to confirm these findings and to explore their utility in clinical decision-making for patients with IIP.
期刊介绍:
ERJ Open Research is a fully open access original research journal, published online by the European Respiratory Society. The journal aims to publish high-quality work in all fields of respiratory science and medicine, covering basic science, clinical translational science and clinical medicine. The journal was created to help fulfil the ERS objective to disseminate scientific and educational material to its members and to the medical community, but also to provide researchers with an affordable open access specialty journal in which to publish their work.