Abstract
Cancer cells frequently evade immune attack possibly by utilizing slow stochastic signaling through the mitochondrial cell death pathway and thus keeping apoptotic activation immunologically silent. A key goal of this computational work is to find optimal strategy to induce apoptosis selectively in cancer cells in a rapid and deterministic manner utilizing paralog selective BH3 mimetic ligands (as monotherapy agent or in combination therapy). A kinetic Monte Carlo based computational model is developed based on recently available data from cellular experiments and bioinformatic analysis. Results obtained from simulations capture single cell fluctuation effects and elucidate that certain ratio of anti- and pro- apoptotic proteins (such as Bcl2/Bax) control the extent of mitochondrial pore formation in cancer and healthy cells. This work also elucidates that combined use of affinity variant BH3 mimetic ligands and network based targeting could lead to rapid and selective apoptosis induction in cancer cells (with minimal cell-to-cell fluctuations). It is expected that such rapid induction of apoptosis would induce generation of immunogenic cell death signal (“danger” signal that could be recognized by the innate immune system for self/nonself discrimination).
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