Influence of non-Gaussian noise on a tumor growth system under immune surveillance

In this paper, the stationary probability distribution (SPD) function and the mean first passage time (MFPT) are investigated in a tumor growth model driven by non-Gaussian noise which is introduced to mimic random fluctuations in the levels of the immune system. Results demonstrate the different transitions induced by the strength of non-Gaussian noise under different immune coefficients and the dual roles of non-Gaussian noise in promoting host protection against cancer and in facilitating tumor escape from immune destruction. Additionally, it can be discovered that increases in noise strength, the degree of departure from Gaussian noise, and the immune coefficient can accelerate the extinction of tumor cells. Numerical simulations are performed, and their results present good agreement with the theoretical results.