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World J Clin Oncol. Nov 10, 2010; 1(1): 24-28
Published online Nov 10, 2010. doi: 10.5306/wjco.v1.i1.24
How can we kill cancer cells: Insights from the computational models of apoptosis
Subhadip Raychaudhuri
Subhadip Raychaudhuri, Department of Biomedical Engineering, Biophysics Graduate Group, Graduate Group in Immunology, and Graduate Group in Applied Mathematics, University of California, Davis, CA 95616, United States
Author contributions: Raychaudhuri S wrote the manuscript.
Correspondence to: Subhadip Raychaudhuri, PhD, Department of Biomedical Engineering, Biophysics Graduate Group, Graduate Group in Immunology, and Graduate Group in Applied Mathematics, University of California, Davis, CA 95616, United States. raychaudhuri@ucdavis.edu
Telephone: +1-530-7546716 Fax: +1-530-7545739
Received: May 31, 2010
Revised: July 28, 2010
Accepted: August 4, 2010
Published online: November 10, 2010
Abstract

Cancer cells are widely known to be protected from apoptosis, a phenomenon that is a major hurdle to successful anticancer therapy. Over-expression of several anti-apoptotic proteins, or mutations in pro-apoptotic factors, has been recognized to confer such resistance. Development of new experimental strategies, such as in silico modeling of biological pathways, can increase our understanding of how abnormal regulation of apoptotic pathway in cancer cells can lead to tumour chemoresistance. Monte Carlo simulations are in particular well suited to study inherent variability, such as spatial heterogeneity and cell-to-cell variations in signaling reactions. Using this approach, often in combination with experimental validation of the computational model, we observed that large cell-to-cell variability could explain the kinetics of apoptosis, which depends on the type of pathway and the strength of stress stimuli. Most importantly, Monte Carlo simulations of apoptotic signaling provides unexpected insights into the mechanisms of fractional cell killing induced by apoptosis-inducing agents, showing that not only variation in protein levels, but also inherent stochastic variability in signaling reactions, can lead to survival of a fraction of treated cancer cells.

Keywords: Apoptosis; Cell death; Cancer; Computational modeling; Monte Carlo simulations