Dynamic evolution of memory-induced tumor cell development

In the report, the tumor cell growth model with non-Markovian characteristics was studied, and the memory scales were defined to characterize the non-Markovian dependence of tumor cell evolution. Firstly, the existence of an effective metastasis rate in the evolutionary process of tumor cells was demonstrated; secondly, the equivalence between memory networks and Markov networks was demonstrated. The equivalence depended on the controllability of memory scale, which induced the fluctuations of the growth process of tumor cells and normalized the theoretical expression of the noise in the tumor cell growth during the different processes. The numerical simulation results indicated that the memory scale in the cell mutations amplifies the noise level expressed by tumor cells; on the contrary, the memory scale during the phagocytosis process suppresses the noise of tumor progression, which suggested that the evolution of tumor cells is influenced by the dual effects of the memory levels.