Gene Network Rewiring to Study Melanoma Stage Progression and Elements Essential for Driving Melanoma.

Metastatic melanoma patients have a poor prognosis, mainly attributable to the underlying heterogeneity in melanoma driver genes and altered gene expression profiles. These characteristics of melanoma also make the development of drugs and identification of novel drug targets for metastatic melanoma...

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Main Authors: Abhinav Kaushik, Yashuma Bhatia, Shakir Ali, Dinesh Gupta
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4641706?pdf=render
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spelling doaj-c5843142f38d4129bd34ced106349b6e2020-11-25T01:52:38ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-011011e014244310.1371/journal.pone.0142443Gene Network Rewiring to Study Melanoma Stage Progression and Elements Essential for Driving Melanoma.Abhinav KaushikYashuma BhatiaShakir AliDinesh GuptaMetastatic melanoma patients have a poor prognosis, mainly attributable to the underlying heterogeneity in melanoma driver genes and altered gene expression profiles. These characteristics of melanoma also make the development of drugs and identification of novel drug targets for metastatic melanoma a daunting task. Systems biology offers an alternative approach to re-explore the genes or gene sets that display dysregulated behaviour without being differentially expressed. In this study, we have performed systems biology studies to enhance our knowledge about the conserved property of disease genes or gene sets among mutually exclusive datasets representing melanoma progression. We meta-analysed 642 microarray samples to generate melanoma reconstructed networks representing four different stages of melanoma progression to extract genes with altered molecular circuitry wiring as compared to a normal cellular state. Intriguingly, a majority of the melanoma network-rewired genes are not differentially expressed and the disease genes involved in melanoma progression consistently modulate its activity by rewiring network connections. We found that the shortlisted disease genes in the study show strong and abnormal network connectivity, which enhances with the disease progression. Moreover, the deviated network properties of the disease gene sets allow ranking/prioritization of different enriched, dysregulated and conserved pathway terms in metastatic melanoma, in agreement with previous findings. Our analysis also reveals presence of distinct network hubs in different stages of metastasizing tumor for the same set of pathways in the statistically conserved gene sets. The study results are also presented as a freely available database at http://bioinfo.icgeb.res.in/m3db/. The web-based database resource consists of results from the analysis presented here, integrated with cytoscape web and user-friendly tools for visualization, retrieval and further analysis.http://europepmc.org/articles/PMC4641706?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Abhinav Kaushik
Yashuma Bhatia
Shakir Ali
Dinesh Gupta
spellingShingle Abhinav Kaushik
Yashuma Bhatia
Shakir Ali
Dinesh Gupta
Gene Network Rewiring to Study Melanoma Stage Progression and Elements Essential for Driving Melanoma.
PLoS ONE
author_facet Abhinav Kaushik
Yashuma Bhatia
Shakir Ali
Dinesh Gupta
author_sort Abhinav Kaushik
title Gene Network Rewiring to Study Melanoma Stage Progression and Elements Essential for Driving Melanoma.
title_short Gene Network Rewiring to Study Melanoma Stage Progression and Elements Essential for Driving Melanoma.
title_full Gene Network Rewiring to Study Melanoma Stage Progression and Elements Essential for Driving Melanoma.
title_fullStr Gene Network Rewiring to Study Melanoma Stage Progression and Elements Essential for Driving Melanoma.
title_full_unstemmed Gene Network Rewiring to Study Melanoma Stage Progression and Elements Essential for Driving Melanoma.
title_sort gene network rewiring to study melanoma stage progression and elements essential for driving melanoma.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2015-01-01
description Metastatic melanoma patients have a poor prognosis, mainly attributable to the underlying heterogeneity in melanoma driver genes and altered gene expression profiles. These characteristics of melanoma also make the development of drugs and identification of novel drug targets for metastatic melanoma a daunting task. Systems biology offers an alternative approach to re-explore the genes or gene sets that display dysregulated behaviour without being differentially expressed. In this study, we have performed systems biology studies to enhance our knowledge about the conserved property of disease genes or gene sets among mutually exclusive datasets representing melanoma progression. We meta-analysed 642 microarray samples to generate melanoma reconstructed networks representing four different stages of melanoma progression to extract genes with altered molecular circuitry wiring as compared to a normal cellular state. Intriguingly, a majority of the melanoma network-rewired genes are not differentially expressed and the disease genes involved in melanoma progression consistently modulate its activity by rewiring network connections. We found that the shortlisted disease genes in the study show strong and abnormal network connectivity, which enhances with the disease progression. Moreover, the deviated network properties of the disease gene sets allow ranking/prioritization of different enriched, dysregulated and conserved pathway terms in metastatic melanoma, in agreement with previous findings. Our analysis also reveals presence of distinct network hubs in different stages of metastasizing tumor for the same set of pathways in the statistically conserved gene sets. The study results are also presented as a freely available database at http://bioinfo.icgeb.res.in/m3db/. The web-based database resource consists of results from the analysis presented here, integrated with cytoscape web and user-friendly tools for visualization, retrieval and further analysis.
url http://europepmc.org/articles/PMC4641706?pdf=render
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