Cargando…
Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases
Lung diseases are described by a wide variety of developmental mechanisms and clinical manifestations. Accurate classification and diagnosis of lung diseases are the bases for development of effective treatments. While extensive studies are conducted toward characterization of various lung diseases...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4859092/ https://www.ncbi.nlm.nih.gov/pubmed/27200087 http://dx.doi.org/10.3389/fgene.2016.00079 |
_version_ | 1782430909499179008 |
---|---|
author | Arakelyan, Arsen Nersisyan, Lilit Petrek, Martin Löffler-Wirth, Henry Binder, Hans |
author_facet | Arakelyan, Arsen Nersisyan, Lilit Petrek, Martin Löffler-Wirth, Henry Binder, Hans |
author_sort | Arakelyan, Arsen |
collection | PubMed |
description | Lung diseases are described by a wide variety of developmental mechanisms and clinical manifestations. Accurate classification and diagnosis of lung diseases are the bases for development of effective treatments. While extensive studies are conducted toward characterization of various lung diseases at molecular level, no systematic approach has been developed so far. Here we have applied a methodology for pathway-centered mining of high throughput gene expression data to describe a wide range of lung diseases in the light of shared and specific pathway activity profiles. We have applied an algorithm combining a Pathway Signal Flow (PSF) algorithm for estimation of pathway activity deregulation states in lung diseases and malignancies, and a Self Organizing Maps algorithm for classification and clustering of the pathway activity profiles. The analysis results allowed clearly distinguish between cancer and non-cancer lung diseases. Lung cancers were characterized by pathways implicated in cell proliferation, metabolism, while non-malignant lung diseases were characterized by deregulations in pathways involved in immune/inflammatory response and fibrotic tissue remodeling. In contrast to lung malignancies, chronic lung diseases had relatively heterogeneous pathway deregulation profiles. We identified three groups of interstitial lung diseases and showed that the development of characteristic pathological processes, such as fibrosis, can be initiated by deregulations in different signaling pathways. In conclusion, this paper describes the pathobiology of lung diseases from systems viewpoint using pathway centered high-dimensional data mining approach. Our results contribute largely to current understanding of pathological events in lung cancers and non-malignant lung diseases. Moreover, this paper provides new insight into molecular mechanisms of a number of interstitial lung diseases that have been studied to a lesser extent. |
format | Online Article Text |
id | pubmed-4859092 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-48590922016-05-19 Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases Arakelyan, Arsen Nersisyan, Lilit Petrek, Martin Löffler-Wirth, Henry Binder, Hans Front Genet Genetics Lung diseases are described by a wide variety of developmental mechanisms and clinical manifestations. Accurate classification and diagnosis of lung diseases are the bases for development of effective treatments. While extensive studies are conducted toward characterization of various lung diseases at molecular level, no systematic approach has been developed so far. Here we have applied a methodology for pathway-centered mining of high throughput gene expression data to describe a wide range of lung diseases in the light of shared and specific pathway activity profiles. We have applied an algorithm combining a Pathway Signal Flow (PSF) algorithm for estimation of pathway activity deregulation states in lung diseases and malignancies, and a Self Organizing Maps algorithm for classification and clustering of the pathway activity profiles. The analysis results allowed clearly distinguish between cancer and non-cancer lung diseases. Lung cancers were characterized by pathways implicated in cell proliferation, metabolism, while non-malignant lung diseases were characterized by deregulations in pathways involved in immune/inflammatory response and fibrotic tissue remodeling. In contrast to lung malignancies, chronic lung diseases had relatively heterogeneous pathway deregulation profiles. We identified three groups of interstitial lung diseases and showed that the development of characteristic pathological processes, such as fibrosis, can be initiated by deregulations in different signaling pathways. In conclusion, this paper describes the pathobiology of lung diseases from systems viewpoint using pathway centered high-dimensional data mining approach. Our results contribute largely to current understanding of pathological events in lung cancers and non-malignant lung diseases. Moreover, this paper provides new insight into molecular mechanisms of a number of interstitial lung diseases that have been studied to a lesser extent. Frontiers Media S.A. 2016-05-06 /pmc/articles/PMC4859092/ /pubmed/27200087 http://dx.doi.org/10.3389/fgene.2016.00079 Text en Copyright © 2016 Arakelyan, Nersisyan, Petrek, Löffler-Wirth and Binder. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Arakelyan, Arsen Nersisyan, Lilit Petrek, Martin Löffler-Wirth, Henry Binder, Hans Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases |
title | Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases |
title_full | Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases |
title_fullStr | Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases |
title_full_unstemmed | Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases |
title_short | Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases |
title_sort | cartography of pathway signal perturbations identifies distinct molecular pathomechanisms in malignant and chronic lung diseases |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4859092/ https://www.ncbi.nlm.nih.gov/pubmed/27200087 http://dx.doi.org/10.3389/fgene.2016.00079 |
work_keys_str_mv | AT arakelyanarsen cartographyofpathwaysignalperturbationsidentifiesdistinctmolecularpathomechanismsinmalignantandchroniclungdiseases AT nersisyanlilit cartographyofpathwaysignalperturbationsidentifiesdistinctmolecularpathomechanismsinmalignantandchroniclungdiseases AT petrekmartin cartographyofpathwaysignalperturbationsidentifiesdistinctmolecularpathomechanismsinmalignantandchroniclungdiseases AT lofflerwirthhenry cartographyofpathwaysignalperturbationsidentifiesdistinctmolecularpathomechanismsinmalignantandchroniclungdiseases AT binderhans cartographyofpathwaysignalperturbationsidentifiesdistinctmolecularpathomechanismsinmalignantandchroniclungdiseases |