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Lung immune signatures define two groups of end-stage IPF patients

BACKGROUND: The role of the immune system in the pathobiology of Idiopathic Pulmonary Fibrosis (IPF) is controversial. METHODS: To investigate it, we calculated immune signatures with Gene Set Variation Analysis (GSVA) and applied them to the lung transcriptome followed by unbiased cluster analysis...

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Autores principales: Cruz, Tamara, Mendoza, Núria, Casas-Recasens, Sandra, Noell, Guillaume, Hernandez-Gonzalez, Fernanda, Frino-Garcia, Alejandro, Alsina-Restoy, Xavi, Molina, María, Rojas, Mauricio, Agustí, Alvar, Sellares, Jacobo, Faner, Rosa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10540496/
https://www.ncbi.nlm.nih.gov/pubmed/37770891
http://dx.doi.org/10.1186/s12931-023-02546-8
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author Cruz, Tamara
Mendoza, Núria
Casas-Recasens, Sandra
Noell, Guillaume
Hernandez-Gonzalez, Fernanda
Frino-Garcia, Alejandro
Alsina-Restoy, Xavi
Molina, María
Rojas, Mauricio
Agustí, Alvar
Sellares, Jacobo
Faner, Rosa
author_facet Cruz, Tamara
Mendoza, Núria
Casas-Recasens, Sandra
Noell, Guillaume
Hernandez-Gonzalez, Fernanda
Frino-Garcia, Alejandro
Alsina-Restoy, Xavi
Molina, María
Rojas, Mauricio
Agustí, Alvar
Sellares, Jacobo
Faner, Rosa
author_sort Cruz, Tamara
collection PubMed
description BACKGROUND: The role of the immune system in the pathobiology of Idiopathic Pulmonary Fibrosis (IPF) is controversial. METHODS: To investigate it, we calculated immune signatures with Gene Set Variation Analysis (GSVA) and applied them to the lung transcriptome followed by unbiased cluster analysis of GSVA immune-enrichment scores, in 109 IPF patients from the Lung Tissue Research Consortium (LTRC). Results were validated experimentally using cell-based methods (flow cytometry) in lung tissue of IPF patients from the University of Pittsburgh (n = 26). Finally, differential gene expression and hypergeometric test were used to explore non-immune differences between clusters. RESULTS: We identified two clusters (C#1 and C#2) of IPF patients of similar size in the LTRC dataset. C#1 included 58 patients (53%) with enrichment in GSVA immune signatures, particularly cytotoxic and memory T cells signatures, whereas C#2 included 51 patients (47%) with an overall lower expression of GSVA immune signatures (results were validated by flow cytometry with similar unbiased clustering generation). Differential gene expression between clusters identified differences in cilium, epithelial and secretory cell genes, all of them showing an inverse correlation with the immune response signatures. Notably, both clusters showed distinct features despite clinical similarities. CONCLUSIONS: In end-stage IPF lung tissue, we identified two clusters of patients with very different levels of immune signatures and gene expression but with similar clinical characteristics. Weather these immune clusters differentiate diverse disease trajectories remains unexplored. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12931-023-02546-8.
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spelling pubmed-105404962023-09-30 Lung immune signatures define two groups of end-stage IPF patients Cruz, Tamara Mendoza, Núria Casas-Recasens, Sandra Noell, Guillaume Hernandez-Gonzalez, Fernanda Frino-Garcia, Alejandro Alsina-Restoy, Xavi Molina, María Rojas, Mauricio Agustí, Alvar Sellares, Jacobo Faner, Rosa Respir Res Research BACKGROUND: The role of the immune system in the pathobiology of Idiopathic Pulmonary Fibrosis (IPF) is controversial. METHODS: To investigate it, we calculated immune signatures with Gene Set Variation Analysis (GSVA) and applied them to the lung transcriptome followed by unbiased cluster analysis of GSVA immune-enrichment scores, in 109 IPF patients from the Lung Tissue Research Consortium (LTRC). Results were validated experimentally using cell-based methods (flow cytometry) in lung tissue of IPF patients from the University of Pittsburgh (n = 26). Finally, differential gene expression and hypergeometric test were used to explore non-immune differences between clusters. RESULTS: We identified two clusters (C#1 and C#2) of IPF patients of similar size in the LTRC dataset. C#1 included 58 patients (53%) with enrichment in GSVA immune signatures, particularly cytotoxic and memory T cells signatures, whereas C#2 included 51 patients (47%) with an overall lower expression of GSVA immune signatures (results were validated by flow cytometry with similar unbiased clustering generation). Differential gene expression between clusters identified differences in cilium, epithelial and secretory cell genes, all of them showing an inverse correlation with the immune response signatures. Notably, both clusters showed distinct features despite clinical similarities. CONCLUSIONS: In end-stage IPF lung tissue, we identified two clusters of patients with very different levels of immune signatures and gene expression but with similar clinical characteristics. Weather these immune clusters differentiate diverse disease trajectories remains unexplored. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12931-023-02546-8. BioMed Central 2023-09-28 2023 /pmc/articles/PMC10540496/ /pubmed/37770891 http://dx.doi.org/10.1186/s12931-023-02546-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Cruz, Tamara
Mendoza, Núria
Casas-Recasens, Sandra
Noell, Guillaume
Hernandez-Gonzalez, Fernanda
Frino-Garcia, Alejandro
Alsina-Restoy, Xavi
Molina, María
Rojas, Mauricio
Agustí, Alvar
Sellares, Jacobo
Faner, Rosa
Lung immune signatures define two groups of end-stage IPF patients
title Lung immune signatures define two groups of end-stage IPF patients
title_full Lung immune signatures define two groups of end-stage IPF patients
title_fullStr Lung immune signatures define two groups of end-stage IPF patients
title_full_unstemmed Lung immune signatures define two groups of end-stage IPF patients
title_short Lung immune signatures define two groups of end-stage IPF patients
title_sort lung immune signatures define two groups of end-stage ipf patients
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10540496/
https://www.ncbi.nlm.nih.gov/pubmed/37770891
http://dx.doi.org/10.1186/s12931-023-02546-8
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