An integrative phenotype-structured partial differential equation model for the population dynamics of epithelial-mesenchymal transition

TL;DR

This paper introduces a PDE-based model to understand how intracellular regulation, stochastic transitions, and cell growth collectively influence epithelial-mesenchymal heterogeneity, relevant to cancer progression.

Contribution

It presents a novel integrative PDE model capturing multi-scale cellular processes affecting E-M phenotypic dynamics in cell populations.

Findings

Population distribution affected by regulatory networks and stochastic fluctuations.

Linear growth rate dependence explains faster in vivo growth of heterogeneous subclones.

Model enhances understanding of intracellular and population-level dynamics in E-M heterogeneity.

Abstract

Phenotypic heterogeneity along the epithelial-mesenchymal (E-M) axis contributes to cancer metastasis and drug resistance. Recent experimental efforts have collated detailed time-course data on the emergence and dynamics of E-M heterogeneity in a cell population. However, it remains unclear how different possible processes interplay in shaping the dynamics of E-M heterogeneity: a) intracellular regulatory interaction among biomolecules, b) cell division and death, and c) stochastic cell-state transition (biochemical reaction noise and asymmetric cell division). Here, we propose a Cell Population Balance (Partial Differential Equation (PDE)) based model that captures the dynamics of cell population density along the E-M phenotypic axis due to abovementioned multi-scale cellular processes. We demonstrate how population distribution resulting from intracellular regulatory networks driving cell-state transition gets impacted by stochastic fluctuations in E-M regulatory biomolecules, differences in growth rates among cell subpopulations, and initial population distribution. Further, we reveal that a linear dependence of the cell growth rate on the population heterogeneity is sufficient to recapitulate the faster in vivo growth of orthotopic injected heterogeneous E-M subclones reported before experimentally. Overall, our model contributes to the combined understanding of intracellular and cell-population levels dynamics in the emergence of E-M heterogeneity in a cell population.