title: A network model for angiogenesis in ovarian cancer.
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.
authors.affiliation: Dana-Farber Cancer Institute, Boston, MA, USA. rekrg@channing.harvard.edu.|Harvard School of Public Health, Boston, MA, USA. rekrg@channing.harvard.edu.|Brigham and Women's Hospital, Boston, MA, USA. rekrg@channing.harvard.edu.
authors.forename: Kimberly
authors.initials: K
authors.lastname: Glass
authors.affiliation: Dana-Farber Cancer Institute, Boston, MA, USA. johnq@jimmy.harvard.edu.|Harvard School of Public Health, Boston, MA, USA. johnq@jimmy.harvard.edu.
authors.forename: John
authors.initials: J
authors.lastname: Quackenbush
authors.affiliation: Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA. dspentzo@bidmc.harvard.edu.
authors.forename: Dimitrios
authors.initials: D
authors.lastname: Spentzos
authors.affiliation: Princess Margaret Cancer Center, University Health Network, Toronto, ON, M5G 2M9, Canada. bhaibeka@uhnresearch.ca.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Haibe-Kains
authors.affiliation: Dana-Farber Cancer Institute, Boston, MA, USA. gcyuan@jimmy.harvard.edu.|Harvard School of Public Health, Boston, MA, USA. gcyuan@jimmy.harvard.edu.
authors.forename: Guo-Cheng
authors.initials: GC
authors.lastname: Yuan
mesh_terms: D000970:Antineoplastic Agents / Q000627:therapeutic use; D003627:Data Interpretation, Statistical; D057890:Epigenomics; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D006801:Humans; D015233:Models, Statistical; D009389:Neovascularization, Pathologic / Q000235:genetics*; D010051:Ovarian Neoplasms / Q000098:blood supply* / Q000188:drug therapy / Q000235:genetics*; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D000970:Antineoplastic Agents; D014157:Transcription Factors