Mathematical modeling of the cancer cell's control circuitry: Paving the way to individualized therapeutic strategies

R. P. Araujo*, E. F. Petricoin, L. A. Liotta

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

7 Scopus citations


Cancer is a disease of signal transduction in which the dysregulation of the network of intracellular and extracellular signaling cascades is sufficient to thwart the cell's finely-tuned biochemical control mechanisms. A keen interest in the mathematical modeling of cell signaling networks and the regulation of signal transduction has emerged in recent years, and has produced a glimmer of insight into the sophisticated feedback control and network regulation operating within cells. In this review, we present an overview of published theoretical studies on the control aspects of signal transduction, emphasizing the role and importance of mechanisms such as 'ultrasensitivity' and feedback loops. We emphasize that these exquisite and often subtle control strategies represent the key to orchestrating 'simple' signaling behaviors within the complex intracellular network, while regulating the trade-off between sensitivity and robustness to internal and external perturbations. Through a consideration of these apparent paradoxes, we explore how the basic homeostasis of the intracellular signaling network, in the face of carcinogenesis, can lead to neoplastic progression rather than cell death. A simple mathematical model is presented, furnishing a vivid illustration of how 'control-oriented' models of the deranged signaling networks in cancer cells may enucleate improved treatment strategies, including patient-tailored combination therapies, with the potential for reduced toxicity and more robust and potent antitumor activity.

Original languageEnglish
Pages (from-to)145-155
Number of pages11
JournalCurrent Signal Transduction Therapy
Issue number2
StatePublished - May 2007
Externally publishedYes


  • Combination therapies
  • Control theory
  • Molecular-targeted inhibitors
  • Proteomics
  • Signal transduction


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