Oscillations of the number of immune system cells in a space-velocity thermostatted kinetic theory model of tumor growth
L\'eon Masurel, Carlo Bianca, and Annie Lemarchand

TL;DR
This study models tumor-immune interactions using a thermostatted kinetic theory, revealing oscillatory behaviors in immune cell populations that depend on system parameters, and reproducing key features of immunotherapy outcomes.
Contribution
It introduces a kinetic Monte Carlo model of tumor-immune dynamics incorporating cell activity fluctuations and stochastic velocity changes, capturing oscillations and therapy-like phenomena.
Findings
Oscillations of immune cells depend on activity fluctuation strength.
High thermalization controls tumor growth effectively.
Critical parameters reproduce immunotherapy features.
Abstract
The competition between cancer cells and immune system cells in inhomogeneous conditions is described at cell scale within the framework of the thermostatted kinetic theory. Cell learning is reproduced by increased cell activity during favorable interactions. The cell activity fluctuations are controlled by a thermostat. The direction of cell velocity is changed according to stochastic rules mimicking a dense fluid. We develop a kinetic Monte Carlo algorithm inspired from the direct simulation Monte Carlo (DSMC) method initially used for dilute gases. The evolution of an initially localized tumor is analyzed. Qualitatively different behaviors are observed as the field regulating activity fluctuations decreases. For high field values, i.e. efficient thermalization, cancer is controlled. For small field values, cancer rapidly and monotonously escapes from immunosurveillance. For the…
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Taxonomy
TopicsMathematical Biology Tumor Growth · Advanced Thermodynamics and Statistical Mechanics · Gene Regulatory Network Analysis
