A network model for angiogenesis in ovarian cancer. Issue 1 (December 2015)

• Record Type: Journal Article
• Authors: Glass, Kimberly; Quackenbush, John; Spentzos, Dimitrios; Haibe-Kains, Benjamin; Yuan, Guo-Cheng
• Is Part Of: BMC bioinformatics. Volume 16:Issue 1(2015)
• Page Start: 1
• Page End: 17
• Publication Date: 2015-12
• Subjects: Network modeling -- Gene regulation -- Regulatory networks -- Ovarian cancer -- Cancer subtypes -- Angiogenesis; Bioinformatics -- Periodicals; Computational biology -- Periodicals; 570.285
• DOI: 10.1186/s12859-015-0551-y
• Languages: English
• ISSNs: 1471-2105

Abstract

Abstract 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.