Phenotypic heterogeneity in modeling cancer evolution

TL;DR

This paper develops a mathematical model to understand how phenotypic heterogeneity influences cancer evolution, revealing how differentiation, dedifferentiation, and microenvironmental plasticity affect mutant fixation and malignancy progression.

Contribution

It introduces an exact analytical framework for mutant fixation probabilities in heterogeneous stem cell populations, incorporating plasticity and environmental effects.

Findings

Plastic mutants have higher fixation probabilities and are more aggressive.

Decreasing stem-differentiated cell polarity reduces malignancy risk for non-plastic mutants.

The model applies broadly to population genetics and ecological systems.

Abstract

The unwelcome evolution of malignancy during cancer progression emerges through a selection process in a complex heterogeneous population structure. In the present work, we investigate evolutionary dynamics in a phenotypically heterogeneous population of stem cells (SCs) and their associated progenitors. The fate of a malignant mutation is determined not only by overall stem cell and differentiated cell growth rates but also differentiation and dedifferentiation rates. We investigate the effect of such a complex population structure on the evolution of malignant mutations. We derive exact analytic results for the fixation probability of a mutant arising in each of the subpopulations. The analytic results are in almost perfect agreement with the numerical simulations. Moreover, a condition for evolutionary advantage of a mutant cell versus the wild type population is given in the present study. We also show that microenvironment-induced plasticity in invading mutants leads to more aggressive mutants with higher fixation probability. Our model predicts that decreasing polarity between stem and differentiated cells turnover would raise the survivability of non-plastic mutants; while it would suppress the development of malignancy for plastic mutants. We discuss our model in the context of colorectal/intestinal cancer (at the epithelium). This novel mathematical framework can be applied more generally to a variety of problems concerning selection in heterogeneous populations, in other contexts such as population genetics, and ecology.