4.6 Article

Mathematical modeling of tumor surface growth with necrotic kernels

Journal

MATHEMATICAL METHODS IN THE APPLIED SCIENCES
Volume 44, Issue 17, Pages 12688-12706

Publisher

WILEY
DOI: 10.1002/mma.7571

Keywords

global continuation; Hopf bifurcation; stability; surface contact; tumor-immune model

Funding

  1. Foundation for Innovation at HIT
  2. National Institutes of Health [U54CA132383]
  3. National Science Foundation of US [DMS-1446139]

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This paper investigates a two-dimensional tumor-immune model with time delay in the adaptive immune response, showing through qualitative and numerical analysis the impact of the immune system on tumors. The positive equilibrium is locally asymptotically stable when the ratio of immune killing rate to tumor volume growth rate is less than a critical value. The results suggest that the time taken for the adaptive immune system to respond to tumors can lead to oscillation dynamics and impact patient survival time.
A two-dimensional tumor-immune model with the time delay of the adaptive immune response is considered in this paper. The model is designed to account for the interaction between cytotoxic T lymphocytes (CTLs) and cancer cells on the surface of a solid tumor. The model considers the surface growth as a major growth pattern of solid tumors in order to describe the existence of necrotic kernels. The qualitative analysis shows that the immune-free equilibrium is unstable, and the behavior of positive equilibrium is closely related to the ratio of the immune killing rate to tumor volume growth rate. The positive equilibrium is locally asymptotically stable when the ratio is smaller than a critical value. Otherwise, the occurrence of the delay-driven Hopf bifurcation at the positive equilibrium is proved. Applying the center manifold reduction and normal form method, we obtain explicit formulas to determine the properties of the Hopf bifurcation. The global continuation of a local Hopf bifurcation is investigated based on the coincidence degree theory. The results reveal that the time of the adaptive immune system taken to response to tumors can lead to oscillation dynamics. We also carry out detailed numerical analysis for parameters and numerical simulations to illustrate our qualitative analysis. Numerically, we find that shorter immune response time can lead to longer patient survival time, and the period and amplitude of a stable periodic solution increase with the increasing immune response time. When CTLs recruitment rate and death rate vary, we show how the ratio of the immune killing rate to tumor volume growth rate and the first bifurcation value change numerically, which yields further insights to the tumor-immune dynamics.

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