A stochastic cellular automata model of growth of avascular tumor with immune response and immunotherapy. (2018) - Shahmoradi, Shiva; Rahatabad, Fereidoun Nowshiravan; Maghooli, Keivan
Abstract: In this paper, a stochastic cellular automata model is presented to investigate the immunotherapy effects on avascular tumor treatment. In this model, the influence of the extracellular matrix on tumor growth is explored. To investigate the immunotherapy effect, first, the model tumor is first allowed to grow in a natural way. Then, immunotherapy is applied by increasing/decreasing the main parameters of the model, based on a threshold number of immune system cells. During the therapy period, the proliferation and escape rates of the cancer cells are decreased, with a constant step. In addition, the rate of cancer cell lysis and the rate of the binding of cancer cells are increased. These changes are continued until the number of immune cells reaches the given threshold. Results show that with a low threshold value, the tumor cell population does not change much. Moreover, by increasing the threshold value, the tumor enters the dormant state, and for the extreme threshold value, a long-term eradication of the tumor would be possible. These results are consistent with those captured by the ordinary differential equation (ODE) based models and also with experimental observations, where it has been shown that many patients can be in complete remission for 7–91 months.