A mathematical model quantifies proliferation and motility effects of TGF--$\beta$ on cancer cells

TL;DR

This paper develops a mathematical model combining Fisher-Kolmogorov equations with experimental data to quantify how TGF-β influences cancer cell proliferation and motility, revealing its dual role in tumor suppression and promotion.

Contribution

It introduces a novel parametrization procedure for the Fisher-Kolmogorov model to accurately reflect TGF-β effects on cancer cells, integrating experimental validation.

Findings

TGF-β doubles cell motility in vitro.

TGF-β halves cell proliferation in vitro.

Model accurately predicts TGF-β effects on cell behavior.

Abstract

Transforming growth factor (TGF) $\beta$ is known to have properties of both a tumor suppressor and a tumor promoter. While it inhibits cell proliferation, it also increases cell motility and decreases cell--cell adhesion. Coupling mathematical modeling and experiments, we investigate the growth and motility of oncogene--expressing human mammary epithelial cells under exposure to TGF--$\beta$. We use a version of the well--known Fisher--Kolmogorov equation, and prescribe a procedure for its parametrization. We quantify the simultaneous effects of TGF--$\beta$ to increase the tendency of individual cells and cell clusters to move randomly and to decrease overall population growth. We demonstrate that in experiments with TGF--$\beta$ treated cells \textit{in vitro}, TGF--$\beta$ increases cell motility by a factor of 2 and decreases cell proliferation by a factor of 1/2 in comparison with untreated cells.