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.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117 Front+Genet
2016 ; 7
(ä): 79
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Cartography of Pathway Signal Perturbations Identifies Distinct Molecular
Pathomechanisms in Malignant and Chronic Lung Diseases
#MMPMID27200087
Arakelyan A
; Nersisyan L
; Petrek M
; Löffler-Wirth H
; Binder H
Front Genet
2016[]; 7
(ä): 79
PMID27200087
show ga
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.
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