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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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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. |
format | Online Article Text |
id | pubmed-4408593 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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