Stochastic branching at the edge: Individual-based modeling of tumor cell proliferation

TL;DR

This paper introduces a stochastic individual-based model simulating tumor cell proliferation, capturing cell division and death dynamics, and establishes conditions for population size control over time.

Contribution

It proposes a novel stochastic branching model for tumor growth that incorporates cell traits, death, and division, with rigorous proof of population boundedness conditions.

Findings

Existence of a well-defined population evolution.

Condition for the mean population size to remain bounded.

Model captures key features of tumor cell proliferation.

Abstract

An individual-based model of stochastic branching is proposed and studied, in which point particles drift in $\bar{\mathds{R}}_{+}:=[0,+\infty)$ towards the origin (edge) with unit speed, where each of them splits into two particles that instantly appear in $\bar{\mathds{R}}_{+}$ at random positions. During their drift the particles are subject to a random disappearance (death). The model is intended to capture the main features of the proliferation of tumor cells, in which trait $x\in \bar{\mathds{R}}_{+}$ of a given cell is time to its division and the death is caused by therapeutic factors. The main result of the paper is proving the existence of an honest evolution of this kind and finding a condition that involves the death rate and cell cycle distribution parameters, under which the mean size of the population remains bounded in time.