Cancer onset and progression: A genome-wide, nonlinear dynamical systems perspective on onconetworks

Date

2007-05-21

Author

Qu, K.
Haidar, A. Abi
Fan, J.
Ensman, L.
Tuncay, Kağan
Jolly, M.
Ortoleva, P.

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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It is hypothesized that the many human cell types corresponding to multiple states is supported by an underlying nonlinear dynamical system (NDS) of transcriptional regulatory network (TRN) processes. This hypothesis is validated for epithelial cells whose TRN is found to support an extremely complex array of states that we term a "bifurcation nexus", for which we introduce a quantitative measure of complexity. The TRN used is constructed and analyzed by integrating a database of TRN information, cDNA microarray data analyzers, bioinformatics modules, a transcription/transiation/post-translation kinetic model, and NDS analysis software. Results of this genome-wide approach suggest that a cell can be induced to persist in one state or to transition between distinct states; apparently irreversible transitions can be reversed when the high dimensional space of extracellular and intracellular parameters is understood. As conditions change, certain cellular states (cell lines) are no longer supported, new ones emerge, and transitions (cell differentiation or death) occur. The accumulation of simulated point mutations (minor changes which individually are insignificant) lead to occasional dramatic transitions. The genome-wide scope of many of these transitions is shown to arise from the cross-linked TRN structure. These notions imply that studying individual oncogenes may not be sufficient to understand cancer; rather, "onconetworks" (subsets of strongly coupled genes supporting multiple cell states) should be considered. Our approach reveals several epithelial onconetworks, each involving oncogenes and anti-tumor and supporting genes.

Subject Keywords

General Biochemistry, Genetics and Molecular Biology, Modelling and Simulation, Statistics and Probability, General Immunology and Microbiology, Applied Mathematics, General Agricultural and Biological Sciences, General Medicine

URI

https://hdl.handle.net/11511/42957

Journal

JOURNAL OF THEORETICAL BIOLOGY

DOI

https://doi.org/10.1016/j.jtbi.2006.12.002

Collections

Department of Civil Engineering, Article

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Citation Formats

K. Qu et al., “Cancer onset and progression: A genome-wide, nonlinear dynamical systems perspective on onconetworks,” JOURNAL OF THEORETICAL BIOLOGY, pp. 234–244, 2007, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/42957.