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A network model for angiogenesis in ovarian cancer

BACKGROUND: We recently identified two robust ovarian cancer subtypes, defined by the expression of genes involved in angiogenesis, with significant differences in clinical outcome. To identify potential regulatory mechanisms that distinguish the subtypes we applied PANDA, a method that uses an inte...

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Autores principales: Glass, Kimberly, Quackenbush, John, Spentzos, Dimitrios, Haibe-Kains, Benjamin, Yuan, Guo-Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4408593/
https://www.ncbi.nlm.nih.gov/pubmed/25888305
http://dx.doi.org/10.1186/s12859-015-0551-y
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author Glass, Kimberly
Quackenbush, John
Spentzos, Dimitrios
Haibe-Kains, Benjamin
Yuan, Guo-Cheng
author_facet Glass, Kimberly
Quackenbush, John
Spentzos, Dimitrios
Haibe-Kains, Benjamin
Yuan, Guo-Cheng
author_sort Glass, Kimberly
collection PubMed
description BACKGROUND: We recently identified two robust ovarian cancer subtypes, defined by the expression of genes involved in angiogenesis, with significant differences in clinical outcome. To identify potential regulatory mechanisms that distinguish the subtypes we applied PANDA, a method that uses an integrative approach to model information flow in gene regulatory networks. RESULTS: We find distinct differences between networks that are active in the angiogenic and non-angiogenic subtypes, largely defined by a set of key transcription factors that, although previously reported to play a role in angiogenesis, are not strongly differentially-expressed between the subtypes. Our network analysis indicates that these factors are involved in the activation (or repression) of different genes in the two subtypes, resulting in differential expression of their network targets. Mechanisms mediating differences between subtypes include a previously unrecognized pro-angiogenic role for increased genome-wide DNA methylation and complex patterns of combinatorial regulation. CONCLUSIONS: The models we develop require a shift in our interpretation of the driving factors in biological networks away from the genes themselves and toward their interactions. The observed regulatory changes between subtypes suggest therapeutic interventions that may help in the treatment of ovarian cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0551-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-44085932015-04-25 A network model for angiogenesis in ovarian cancer Glass, Kimberly Quackenbush, John Spentzos, Dimitrios Haibe-Kains, Benjamin Yuan, Guo-Cheng BMC Bioinformatics Research Article BACKGROUND: We recently identified two robust ovarian cancer subtypes, defined by the expression of genes involved in angiogenesis, with significant differences in clinical outcome. To identify potential regulatory mechanisms that distinguish the subtypes we applied PANDA, a method that uses an integrative approach to model information flow in gene regulatory networks. RESULTS: We find distinct differences between networks that are active in the angiogenic and non-angiogenic subtypes, largely defined by a set of key transcription factors that, although previously reported to play a role in angiogenesis, are not strongly differentially-expressed between the subtypes. Our network analysis indicates that these factors are involved in the activation (or repression) of different genes in the two subtypes, resulting in differential expression of their network targets. Mechanisms mediating differences between subtypes include a previously unrecognized pro-angiogenic role for increased genome-wide DNA methylation and complex patterns of combinatorial regulation. CONCLUSIONS: The models we develop require a shift in our interpretation of the driving factors in biological networks away from the genes themselves and toward their interactions. The observed regulatory changes between subtypes suggest therapeutic interventions that may help in the treatment of ovarian cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0551-y) contains supplementary material, which is available to authorized users. BioMed Central 2015-04-11 /pmc/articles/PMC4408593/ /pubmed/25888305 http://dx.doi.org/10.1186/s12859-015-0551-y Text en © Glass et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Glass, Kimberly
Quackenbush, John
Spentzos, Dimitrios
Haibe-Kains, Benjamin
Yuan, Guo-Cheng
A network model for angiogenesis in ovarian cancer
title A network model for angiogenesis in ovarian cancer
title_full A network model for angiogenesis in ovarian cancer
title_fullStr A network model for angiogenesis in ovarian cancer
title_full_unstemmed A network model for angiogenesis in ovarian cancer
title_short A network model for angiogenesis in ovarian cancer
title_sort network model for angiogenesis in ovarian cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4408593/
https://www.ncbi.nlm.nih.gov/pubmed/25888305
http://dx.doi.org/10.1186/s12859-015-0551-y
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