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Meta-Analysis of Genetic Programs between Idiopathic Pulmonary Fibrosis and Sarcoidosis
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) and pulmonary sarcoidosis are typical interstitial lung diseases with unknown etiology that cause lethal lung damages. There are notable differences between these two pulmonary disorders, although they do share some similarities. Gene expression profil...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3743918/ https://www.ncbi.nlm.nih.gov/pubmed/23967151 http://dx.doi.org/10.1371/journal.pone.0071059 |
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author | Leng, Dong Huan, Caijuan Xie, Ting Liang, Jiurong Wang, Jun Dai, Huaping Wang, Chen Jiang, Dianhua |
author_facet | Leng, Dong Huan, Caijuan Xie, Ting Liang, Jiurong Wang, Jun Dai, Huaping Wang, Chen Jiang, Dianhua |
author_sort | Leng, Dong |
collection | PubMed |
description | BACKGROUND: Idiopathic pulmonary fibrosis (IPF) and pulmonary sarcoidosis are typical interstitial lung diseases with unknown etiology that cause lethal lung damages. There are notable differences between these two pulmonary disorders, although they do share some similarities. Gene expression profiles have been reported independently, but differences on the transcriptional level between these two entities have not been investigated. METHODS/RESULTS: All expression data of lung tissue samples for IPF and sarcoidosis were from published datasets in the Gene Expression Omnibus (GEO) repository. After cross platform normalization, the merged sample data were grouped together and were subjected to statistical analysis for finding discriminate genes. Gene enrichments with their corresponding functions were analyzed by the online analysis engine “Database for Annotation, Visualization and Integrated Discovery” (DAVID) 6.7, and genes interactions and functional networks were further analyzed by STRING 9.0 and Cytoscape 3.0.0 Beta1. One hundred and thirty signature genes could potentially differentiate one disease state from another. Compared with normal lung tissue, tissue affected by IPF and sarcoidosis displayed similar signatures that concentrated on proliferation and differentiation. Distinctly expressed genes that could distinguish IPF from sarcoidosis are more enriched in processes of cilium biogenesis or degradation and regulating T cell activations. Key discriminative network modules involve aspects of bone morphogenetic protein receptor two (BMPR2) related and v-myb myeloblastosis viral oncogene (MYB) related proliferation. CONCLUSIONS: This study is the first attempt to examine the transcriptional regulation of IPF and sarcoidosis across different studies based on different working platforms. Groups of significant genes were found to clearly distinguish one condition from the other. While IPF and sarcoidosis share notable similarities in cell proliferation, differentiation and migration, remarkable differences between the diseases were found at the transcription level, suggesting that the two diseases are regulated by overlapping yet distinctive transcriptional networks. |
format | Online Article Text |
id | pubmed-3743918 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-37439182013-08-21 Meta-Analysis of Genetic Programs between Idiopathic Pulmonary Fibrosis and Sarcoidosis Leng, Dong Huan, Caijuan Xie, Ting Liang, Jiurong Wang, Jun Dai, Huaping Wang, Chen Jiang, Dianhua PLoS One Research Article BACKGROUND: Idiopathic pulmonary fibrosis (IPF) and pulmonary sarcoidosis are typical interstitial lung diseases with unknown etiology that cause lethal lung damages. There are notable differences between these two pulmonary disorders, although they do share some similarities. Gene expression profiles have been reported independently, but differences on the transcriptional level between these two entities have not been investigated. METHODS/RESULTS: All expression data of lung tissue samples for IPF and sarcoidosis were from published datasets in the Gene Expression Omnibus (GEO) repository. After cross platform normalization, the merged sample data were grouped together and were subjected to statistical analysis for finding discriminate genes. Gene enrichments with their corresponding functions were analyzed by the online analysis engine “Database for Annotation, Visualization and Integrated Discovery” (DAVID) 6.7, and genes interactions and functional networks were further analyzed by STRING 9.0 and Cytoscape 3.0.0 Beta1. One hundred and thirty signature genes could potentially differentiate one disease state from another. Compared with normal lung tissue, tissue affected by IPF and sarcoidosis displayed similar signatures that concentrated on proliferation and differentiation. Distinctly expressed genes that could distinguish IPF from sarcoidosis are more enriched in processes of cilium biogenesis or degradation and regulating T cell activations. Key discriminative network modules involve aspects of bone morphogenetic protein receptor two (BMPR2) related and v-myb myeloblastosis viral oncogene (MYB) related proliferation. CONCLUSIONS: This study is the first attempt to examine the transcriptional regulation of IPF and sarcoidosis across different studies based on different working platforms. Groups of significant genes were found to clearly distinguish one condition from the other. While IPF and sarcoidosis share notable similarities in cell proliferation, differentiation and migration, remarkable differences between the diseases were found at the transcription level, suggesting that the two diseases are regulated by overlapping yet distinctive transcriptional networks. Public Library of Science 2013-08-14 /pmc/articles/PMC3743918/ /pubmed/23967151 http://dx.doi.org/10.1371/journal.pone.0071059 Text en © 2013 Leng et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Leng, Dong Huan, Caijuan Xie, Ting Liang, Jiurong Wang, Jun Dai, Huaping Wang, Chen Jiang, Dianhua Meta-Analysis of Genetic Programs between Idiopathic Pulmonary Fibrosis and Sarcoidosis |
title | Meta-Analysis of Genetic Programs between Idiopathic Pulmonary Fibrosis and Sarcoidosis |
title_full | Meta-Analysis of Genetic Programs between Idiopathic Pulmonary Fibrosis and Sarcoidosis |
title_fullStr | Meta-Analysis of Genetic Programs between Idiopathic Pulmonary Fibrosis and Sarcoidosis |
title_full_unstemmed | Meta-Analysis of Genetic Programs between Idiopathic Pulmonary Fibrosis and Sarcoidosis |
title_short | Meta-Analysis of Genetic Programs between Idiopathic Pulmonary Fibrosis and Sarcoidosis |
title_sort | meta-analysis of genetic programs between idiopathic pulmonary fibrosis and sarcoidosis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3743918/ https://www.ncbi.nlm.nih.gov/pubmed/23967151 http://dx.doi.org/10.1371/journal.pone.0071059 |
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