The overshoot and phenotypic equilibrium in characterizing cancer dynamics of reversible phenotypic plasticity

TL;DR

This paper compares hierarchical and reversible models of cancer cell phenotypic plasticity, demonstrating that the reversible model more accurately predicts long-term stability and transient dynamics like overshoot in cancer cell populations.

Contribution

It provides a comparative analysis showing the reversible model's superiority over the hierarchical model in capturing cancer cell dynamics and phenotypic equilibrium.

Findings

Reversible model predicts phenotypic equilibrium and overshoot.

Hierarchical model fails under certain conditions to predict these dynamics.

Reversible model better captures transient and long-term cancer cell behaviors.

Abstract

The paradigm of phenotypic plasticity indicates reversible relations of different cancer cell phenotypes, which extends the cellular hierarchy proposed by the classical cancer stem cell (CSC) theory. Since it is still question able if the phenotypic plasticity is a crucial improvement to the hierarchical model or just a minor extension to it, it is worthwhile to explore the dynamic behavior characterizing the reversible phenotypic plasticity. In this study we compare the hierarchical model and the reversible model in predicting the cell-state dynamics observed in biological experiments. Our results show that the hierarchical model shows significant disadvantages over the reversible model in describing both long-term stability (phenotypic equilibrium) and short-term transient dynamics (overshoot) of cancer cells. In a very specific case in which the total growth of population due to each cell type is identical, the hierarchical model predicts neither phenotypic equilibrium nor overshoot, whereas thereversible model succeeds in predicting both of them. Even though the performance of the hierarchical model can be improved by relaxing the specific assumption, its prediction to the phenotypic equilibrium strongly depends on a precondition that may be unrealistic in biological experiments, and it also fails to capture the overshoot of CSCs. By comparison, it is more likely for the reversible model to correctly describe the stability of the phenotypic mixture and various types of overshoot behavior.