Disentangling the Behavioural Variability of Confined Cell Migration

TL;DR

This study investigates the variability in confined cell migration of breast cancer cells, revealing distinct behavioral classes and the roles of aging and heterogeneity in migration dynamics using a dynamical systems approach.

Contribution

It introduces a novel framework combining stochastic modeling and subpopulation analysis to characterize behavioral variability in cell migration.

Findings

Behavioral variance exceeds population-averaged model predictions.

Heterogeneity includes slow and fast cell subpopulations.

Migration behaviors range from bistable to limit cycle dynamics.

Abstract

Cell-to-cell variability is inherent to numerous biological processes, including cell migration. Quantifying and characterizing the variability of migrating cells is challenging, as it requires monitoring many cells for long time windows under identical conditions. Here, we observe the migration of single human breast cancer cells (MDA-MB-231) in confining two-state micropatterns. To describe the stochastic dynamics of this confined migration, we employ a dynamical systems approach. We identify statistics to measure the behavioural variance of the migration, which significantly exceed those predicted by a population-averaged stochastic model. This additional variance can be explained by the combination of an 'aging' process and population heterogeneity. To quantify population heterogeneity, we decompose the cells into subpopulations of slow and fast cells, revealing the presence of distinct classes of dynamical systems describing the migration, ranging from bistable to limit cycle behaviour. Our findings highlight the breadth of migration behaviours present in cell populations.