Evolution and controllability of cancer networks: a boolean perspective

Srihari, Sriganesh, Raman, Venkatesh, Leong, Hon Wai and Ragan, Mark A. (2013) Evolution and controllability of cancer networks: a boolean perspective. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11 1: 83-94. doi:10.1109/TCBB.2013.128


Author Srihari, Sriganesh
Raman, Venkatesh
Leong, Hon Wai
Ragan, Mark A.
Title Evolution and controllability of cancer networks: a boolean perspective
Journal name IEEE/ACM Transactions on Computational Biology and Bioinformatics   Check publisher's open access policy
ISSN 1545-5963
1557-9964
Publication date 2013-10-22
Year available 2013
Sub-type Article (original research)
DOI 10.1109/TCBB.2013.128
Volume 11
Issue 1
Start page 83
End page 94
Total pages 13
Place of publication New York, United States
Publisher Association for Computing Machinery
Collection year 2014
Language eng
Abstract Cancer forms a robust system and progresses as stages over time typically with increasing aggressiveness and worsening prognosis. Characterizing these stages and identifying the genes driving transitions between them is critical to understand cancer progression and to develop effective anti-cancer therapies. Here, we propose a novel model of the 'cancer system' as a Boolean state space in which a Boolean network, built from protein-interaction and gene-expression data from different stages of cancer, transits between Boolean satisfiability states by "editing" interactions and "flipping" genes. The application of our model (called BoolSpace) on three case studies - pancreatic and breast tumours in human and post spinal-cord injury in rats – reveals valuable insights into the phenomenon of cancer progression. In particular, we notice that several of the genes flipped are serine/threonine kinases which act as natural cellular switches and that different sets of genes are flipped during the initial and final stages indicating a pattern to tumour progression. We hypothesize that robustness of cancer partly stems from "passing of the baton" between genes at different stages, and therefore an effective therapy should target a "cover set" of these genes. A C/C++ implementation of BoolSpace is freely available at: http://www.bioinformatics.org.au/tools-data
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Published online ahead of print 23 October 2013.

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2014 Collection
Institute for Molecular Bioscience - Publications
 
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Created: Mon, 16 Dec 2013, 15:08:00 EST by Susan Allen on behalf of Institute for Molecular Bioscience