Identifying core gene modules in glioblastoma based on multilayer factor-mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data

The driver genetic aberrations collectively regulate core cellular processes underlying cancer development. However, identifying the modules of driver genetic alterations and characterizing their functional mechanisms are still major challenges for cancer studies. Here, we developed an integrative m...

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Main Authors:	Ping, Yanyan, Deng, Yulan, Wang, Li, Zhang, Hongyi, Zhang, Yong, Xu, Chaohan, Zhao, Hongying, Fan, Huihui, Yu, Fulong, Xiao, Yun, Li, Xia
Format:	Online
Language:	English
Published:	Oxford University Press 2015
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4344511/

id	pubmed-4344511
recordtype	oai_dc
spelling	pubmed-43445112015-03-17 Identifying core gene modules in glioblastoma based on multilayer factor-mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data Ping, Yanyan Deng, Yulan Wang, Li Zhang, Hongyi Zhang, Yong Xu, Chaohan Zhao, Hongying Fan, Huihui Yu, Fulong Xiao, Yun Li, Xia Computational Biology The driver genetic aberrations collectively regulate core cellular processes underlying cancer development. However, identifying the modules of driver genetic alterations and characterizing their functional mechanisms are still major challenges for cancer studies. Here, we developed an integrative multi-omics method CMDD to identify the driver modules and their affecting dysregulated genes through characterizing genetic alteration-induced dysregulated networks. Applied to glioblastoma (GBM), the CMDD identified a core gene module of 17 genes, including seven known GBM drivers, and their dysregulated genes. The module showed significant association with shorter survival of GBM. When classifying driver genes in the module into two gene sets according to their genetic alteration patterns, we found that one gene set directly participated in the glioma pathway, while the other indirectly regulated the glioma pathway, mostly, via their dysregulated genes. Both of the two gene sets were significant contributors to survival and helpful for classifying GBM subtypes, suggesting their critical roles in GBM pathogenesis. Also, by applying the CMDD to other six cancers, we identified some novel core modules associated with overall survival of patients. Together, these results demonstrate integrative multi-omics data can identify driver modules and uncover their dysregulated genes, which is useful for interpreting cancer genome. Oxford University Press 2015-02-27 2015-02-04 /pmc/articles/PMC4344511/ /pubmed/25653168 http://dx.doi.org/10.1093/nar/gkv074 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Ping, Yanyan Deng, Yulan Wang, Li Zhang, Hongyi Zhang, Yong Xu, Chaohan Zhao, Hongying Fan, Huihui Yu, Fulong Xiao, Yun Li, Xia
spellingShingle	Ping, Yanyan Deng, Yulan Wang, Li Zhang, Hongyi Zhang, Yong Xu, Chaohan Zhao, Hongying Fan, Huihui Yu, Fulong Xiao, Yun Li, Xia Identifying core gene modules in glioblastoma based on multilayer factor-mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data
author_facet	Ping, Yanyan Deng, Yulan Wang, Li Zhang, Hongyi Zhang, Yong Xu, Chaohan Zhao, Hongying Fan, Huihui Yu, Fulong Xiao, Yun Li, Xia
author_sort	Ping, Yanyan
title	Identifying core gene modules in glioblastoma based on multilayer factor-mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data
title_short	Identifying core gene modules in glioblastoma based on multilayer factor-mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data
title_full	Identifying core gene modules in glioblastoma based on multilayer factor-mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data
title_fullStr	Identifying core gene modules in glioblastoma based on multilayer factor-mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data
title_full_unstemmed	Identifying core gene modules in glioblastoma based on multilayer factor-mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data
title_sort	identifying core gene modules in glioblastoma based on multilayer factor-mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data
description	The driver genetic aberrations collectively regulate core cellular processes underlying cancer development. However, identifying the modules of driver genetic alterations and characterizing their functional mechanisms are still major challenges for cancer studies. Here, we developed an integrative multi-omics method CMDD to identify the driver modules and their affecting dysregulated genes through characterizing genetic alteration-induced dysregulated networks. Applied to glioblastoma (GBM), the CMDD identified a core gene module of 17 genes, including seven known GBM drivers, and their dysregulated genes. The module showed significant association with shorter survival of GBM. When classifying driver genes in the module into two gene sets according to their genetic alteration patterns, we found that one gene set directly participated in the glioma pathway, while the other indirectly regulated the glioma pathway, mostly, via their dysregulated genes. Both of the two gene sets were significant contributors to survival and helpful for classifying GBM subtypes, suggesting their critical roles in GBM pathogenesis. Also, by applying the CMDD to other six cancers, we identified some novel core modules associated with overall survival of patients. Together, these results demonstrate integrative multi-omics data can identify driver modules and uncover their dysregulated genes, which is useful for interpreting cancer genome.
publisher	Oxford University Press
publishDate	2015
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4344511/
_version_	1613193534724112384

Identifying core gene modules in glioblastoma based on multilayer factor-mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data

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