  Cancer cells are widely known to be protected from apoptosis, which is a
major hurdle to successful anti-cancer 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.
