Spatial simulation of autologous cell defection for cancer treatment.

Cancer cells are highly cooperative in a nepotistic way and evolutionarily dynamic. Present cancer treatments often overlook these aspects, inducing the selection of resistant cancer cells and the corresponding relapse. As an alternative method of cancer elimination, autologous cell defection (ACD) was suggested by which modified cancer cells parasitically reliant on other cancer cells are implemented to the cancer cluster. Specifically, modified cancer cells should not produce costly growth factors that promote the growth of other cancer cells while receiving the benefit of exposure to such growth factors. Analytical models and rudimentary experiments up to date provide the medical feasibility of this method. In this study, I built comprehensive spatial simulation models by embracing the effects of the multiple growth factors, the Warburg effect, mutations and immunity. The simulation results based on planar spatial structures indicate that implementation of the defective modified tumours may replace the existing cancer cluster and defective cells would later collapse by themselves. Furthermore, I built a mathematical model that compares the fitness of the cells adjacent to the hypertumour-cancer interface. I also calculated whether anticancer drugs that reduce the effects of the growth factors promote or demote the utility of ACD under diverse fitness functions. The computational examination implies that anticancer drugs may impede the therapeutic effect of ACD when there is a strong concavity in the fitness function. The analysis results could work as a general guidance for effective ACD that may expand the paradigm of cancer treatment.