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

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 questionable 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) in cancer cell populations. 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 the reversible 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. Moreover, it still does not show as rich dynamics as the reversible model in capturing the overshoots of both CSCs and non-CSCs. By comparison, it is more likely for the reversible model to correctly predict the stability of the phenotypic mixture and various types of overshoot behavior.

Phenotypic Switching Resulting From Developmental Plasticity: Fixed or Reversible?

“…Having made a case for reversible (correctable) phenotype switching enabled by developmental phenotypic plasticity, what might we speculate to be the selection pressures leading to its evolution? Advantages to mature organisms of reversible phenotype switching, as well as its evolution, have received considerable attention -for an entry into the literature see Gabriel (2005), Gabriel (2006), Piersma and van Gils (2010), Berman (2016), Chen et al (2016), Pfab et al (2016), Lazaro et al (2019), and Ratikainen and Kokko (2019). Yet, as Beaman et al (2016) state, ".…”

A Bayesian statistical analysis of stochastic phenotypic plasticity model of cancer cells

“…Some other researches laid emphasis on the role of the phenotypic plasticity in transient dynamics. It was shown that an interesting overshoot phenomenon of CSCs observed in experiment can be well explained by de-differentiation from non-CSCs to CSCs [17,18]. Besides, Leder et al studied mathematical models of pdgf-driven glioblastoma and revealed that the effectiveness of radiotherapy is quite sensitive to the capability of de-differentiation from differentiated sensitive cells to stemlike resistant cells [19]; Jilkine and Gutenkunst studied the effect of de-differentiation on time to mutation acquisition in cancers [20]; Chen et al studied transition model between endocrine therapy responsive and resistant states in breast cancer by Landscape Theory [21]; Dhawan et al showed with mathematical modeling that exposure to hypoxia enhanced the plasticity and heterogeneity of cancer cell populations [22]; Tonekaboi et al investigated how cellular plasticity behaves differently in small and large cancer cell populations [23].…”

Alternative models of cancer stem cells: The stemness phenotype model, 10 years later

“…These findings clearly demonstrated that cancer cells are actually extremely plastic and that microenvironmental conditions can influence and drive the bidirectional interconversion between CSCs and non-CSCs phenotypes. Recently several theoretical multi-phenotypic models that include, interconversion and cellular plasticity has been useful in predicting and validating this new paradigm[ 58 - 60 ].…”