Letter abstract


Nature Biotechnology 27, 199 - 204 (2009)
Published online: 1 February 2009 | doi:10.1038/nbt.1522

Dynamic modularity in protein interaction networks predicts breast cancer outcome

Ian W Taylor1,2, Rune Linding1,3, David Warde-Farley4,5, Yongmei Liu1, Catia Pesquita6, Daniel Faria6, Shelley Bull1,5, Tony Pawson1,2, Quaid Morris4 & Jeffrey L Wrana1,2

Top

Changes in the biochemical wiring of oncogenic cells drives phenotypic transformations that directly affect disease outcome. Here we examine the dynamic structure of the human protein interaction network (interactome) to determine whether changes in the organization of the interactome can be used to predict patient outcome. An analysis of hub proteins identified intermodular hub proteins that are co-expressed with their interacting partners in a tissue-restricted manner and intramodular hub proteins that are co-expressed with their interacting partners in all or most tissues. Substantial differences in biochemical structure were observed between the two types of hubs. Signaling domains were found more often in intermodular hub proteins, which were also more frequently associated with oncogenesis. Analysis of two breast cancer patient cohorts revealed that altered modularity of the human interactome may be useful as an indicator of breast cancer prognosis.

Top
  1. Samuel Lunenfeld Research Institute, Mount Sinai Hospital, 600 University Ave., Toronto, Ontario M5G 1X5, Canada.
  2. Department of Molecular Genetics, University of Toronto, 1 King's College Circle, Room 4396, Toronto, Ontario M5S 1A8, Canada.
  3. Cellular & Molecular Logic Team, Institute of Cancer Research (ICR), Section of Cell, Molecular & Systems Section, 237 Fulham Road, London, SW3 6JB, UK.
  4. The Terrence Donnelly Centre for Cellular and Biomolecular Research, 160 College St., Toronto, Ontario M5S 3E1, Canada.
  5. Department of Computer Science, University of Toronto, 10 King's College Road, Room 3303, Toronto, Ontario M5S 3G4, Canada.
  6. Faculty of Sciences, University of Lisbon, Campo Grande, 1749-016, Lisbon, Portugal.
  7. Dalla Lana, School of Public Health, University of Toronto, 155 College St., Toronto, ON M5T 3M7, Canada.

Correspondence to: Jeffrey L Wrana1,2 e-mail: wrana@lunenfeld.ca



MORE ARTICLES LIKE THIS

These links to content published by NPG are automatically generated.

NEWS AND VIEWS

Complex networks Role model for modules

Nature Physics News and Views (01 Jan 2007)


Extra navigation

Open Innovation Challenges

ADVERTISEMENT