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Human disease: lung disease3
Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases.
LHA - Leipzig Health Atlas

Abstract (Expand)

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.

Authors: A. Arakelyan, L. Nersisyan, M. Petrek, H. Loffler-Wirth, H. Binder

Date Published: 21st May 2016

Publication Type: Not specified

Human Diseases: lung disease

Methylation associated pathway activity deregulation in lung adenocarcinoma
CapSys - Systems Medicine of Community Acquired Pneumonia

Abstract (Expand)

Methylation impairments are tightly associated with gene expression and molecular pathway deregulation in cancer development. However, other regulatory mechanisms exist, making it important to distinguish … those from methylation driven changes. Here we specifically assessed molecular pathway states associated with gene methylation in lung adenocarcinoma. Paired gene expression and methylation data (id:GSE32867) were obtained from Gene Expression Omnibus. Self organizing maps (Wirth, H. et al.BMC Bioinformatics 2011;12:306 ) and in-house pathway signal flow algorithms were applied to describe expression (PSF) and methylation (mPSF) states in KEGG pathways. 35 and 24 KEGG pathways had at least one branch deregulated at significance levels p<0.05 and 0.05<p < 0.1, respectively. Because many pathways are multibranch, our analysis totalled in 54 up- (PSF>1) and 73 down-regulated (PSF<1) branches. From these branches, 19 were positively (mPSF<0) or negatively (mPSF>0) correlated with methylation states (see table).

Authors: L. Nersisyan, Henry Löffler-Wirth, A. Gevorgyan, Hans Binder, A. Arakelyan

Date Published: 2014

Publication Type: Not specified

Human Diseases: lung disease

Mining common pathway deregulation profiles in lung diseases
CapSys - Systems Medicine of Community Acquired Pneumonia

Abstract (Expand)

This study is aimed at investigating lung diseases described by common pathomechanisms based on evaluation of gene expression profiles in molecular pathways. 16 datasets containing 428 samples for 22 … health conditions were taken from Gene Expression Omnibus. Self organizing maps (Wirth, H. et al.BMC Bioinformatics 2011;12:306) and cluster analysis with dynamic tree cut were used for gene expression based disease clustering. In-house pathway signal flow algorithm and phylogenetic analysis were applied to find common pathway deregulation patterns in clusters. Analysis resulted in grouping the 22 conditions into 5 clusters (fig.1). PSF and phylogenetic analysis identified unique pathway deregulation patterns for each cluster (fig.2).

Authors: A. Arakelyan, L. Nersisyan, Henry Löffler-Wirth, Hans Binder

Date Published: 2014

Publication Type: Not specified

Human Diseases: lung disease

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