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Integrative analysis of lung molecular signatures reveals key drivers of idiopathic pulmonary fibrosis

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a devastating disease with a high clinical burden. The molecular signatures of IPF were analyzed to distinguish molecular subgroups and identify key driver genes and therapeutic targets. METHODS: Thirteen datasets of lung tissue transcriptomics incl...

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Autores principales: Kim, Sung Kyoung, Jung, Seung Min, Park, Kyung-Su, Kim, Ki-Jo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8650281/
https://www.ncbi.nlm.nih.gov/pubmed/34876074
http://dx.doi.org/10.1186/s12890-021-01749-3
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author Kim, Sung Kyoung
Jung, Seung Min
Park, Kyung-Su
Kim, Ki-Jo
author_facet Kim, Sung Kyoung
Jung, Seung Min
Park, Kyung-Su
Kim, Ki-Jo
author_sort Kim, Sung Kyoung
collection PubMed
description BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a devastating disease with a high clinical burden. The molecular signatures of IPF were analyzed to distinguish molecular subgroups and identify key driver genes and therapeutic targets. METHODS: Thirteen datasets of lung tissue transcriptomics including 585 IPF patients and 362 normal controls were obtained from the databases and subjected to filtration of differentially expressed genes (DEGs). A functional enrichment analysis, agglomerative hierarchical clustering, network-based key driver analysis, and diffusion scoring were performed, and the association of enriched pathways and clinical parameters was evaluated. RESULTS: A total of 2,967 upregulated DEGs was filtered during the comparison of gene expression profiles of lung tissues between IPF patients and healthy controls. The core molecular network of IPF featured p53 signaling pathway and cellular senescence. IPF patients were classified into two molecular subgroups (C1, C2) via unsupervised clustering. C1 was more enriched in the p53 signaling pathway and ciliated cells and presented a worse prognostic score, while C2 was more enriched for cellular senescence, profibrosing pathways, and alveolar epithelial cells. The p53 signaling pathway was closely correlated with a decline in forced vital capacity and carbon monoxide diffusion capacity and with the activation of cellular senescence. CDK1/2, CKDNA1A, CSNK1A1, HDAC1/2, FN1, VCAM1, and ITGA4 were the key regulators as evidence by high diffusion scores in the disease module. Currently available and investigational drugs showed differential diffusion scores in terms of their target molecules. CONCLUSIONS: An integrative molecular analysis of IPF lungs identified two molecular subgroups with distinct pathobiological characteristics and clinical prognostic scores. Inhibition against CDKs or HDACs showed great promise for controlling lung fibrosis. This approach provided molecular insights to support the prediction of clinical outcomes and the selection of therapeutic targets in IPF patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-021-01749-3.
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spelling pubmed-86502812021-12-07 Integrative analysis of lung molecular signatures reveals key drivers of idiopathic pulmonary fibrosis Kim, Sung Kyoung Jung, Seung Min Park, Kyung-Su Kim, Ki-Jo BMC Pulm Med Research BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a devastating disease with a high clinical burden. The molecular signatures of IPF were analyzed to distinguish molecular subgroups and identify key driver genes and therapeutic targets. METHODS: Thirteen datasets of lung tissue transcriptomics including 585 IPF patients and 362 normal controls were obtained from the databases and subjected to filtration of differentially expressed genes (DEGs). A functional enrichment analysis, agglomerative hierarchical clustering, network-based key driver analysis, and diffusion scoring were performed, and the association of enriched pathways and clinical parameters was evaluated. RESULTS: A total of 2,967 upregulated DEGs was filtered during the comparison of gene expression profiles of lung tissues between IPF patients and healthy controls. The core molecular network of IPF featured p53 signaling pathway and cellular senescence. IPF patients were classified into two molecular subgroups (C1, C2) via unsupervised clustering. C1 was more enriched in the p53 signaling pathway and ciliated cells and presented a worse prognostic score, while C2 was more enriched for cellular senescence, profibrosing pathways, and alveolar epithelial cells. The p53 signaling pathway was closely correlated with a decline in forced vital capacity and carbon monoxide diffusion capacity and with the activation of cellular senescence. CDK1/2, CKDNA1A, CSNK1A1, HDAC1/2, FN1, VCAM1, and ITGA4 were the key regulators as evidence by high diffusion scores in the disease module. Currently available and investigational drugs showed differential diffusion scores in terms of their target molecules. CONCLUSIONS: An integrative molecular analysis of IPF lungs identified two molecular subgroups with distinct pathobiological characteristics and clinical prognostic scores. Inhibition against CDKs or HDACs showed great promise for controlling lung fibrosis. This approach provided molecular insights to support the prediction of clinical outcomes and the selection of therapeutic targets in IPF patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-021-01749-3. BioMed Central 2021-12-07 /pmc/articles/PMC8650281/ /pubmed/34876074 http://dx.doi.org/10.1186/s12890-021-01749-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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
Kim, Sung Kyoung
Jung, Seung Min
Park, Kyung-Su
Kim, Ki-Jo
Integrative analysis of lung molecular signatures reveals key drivers of idiopathic pulmonary fibrosis
title Integrative analysis of lung molecular signatures reveals key drivers of idiopathic pulmonary fibrosis
title_full Integrative analysis of lung molecular signatures reveals key drivers of idiopathic pulmonary fibrosis
title_fullStr Integrative analysis of lung molecular signatures reveals key drivers of idiopathic pulmonary fibrosis
title_full_unstemmed Integrative analysis of lung molecular signatures reveals key drivers of idiopathic pulmonary fibrosis
title_short Integrative analysis of lung molecular signatures reveals key drivers of idiopathic pulmonary fibrosis
title_sort integrative analysis of lung molecular signatures reveals key drivers of idiopathic pulmonary fibrosis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8650281/
https://www.ncbi.nlm.nih.gov/pubmed/34876074
http://dx.doi.org/10.1186/s12890-021-01749-3
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