Phase transitions of biological phenotypes by means of a prototypical PDE model
The basic investigation is the existence and the (numerical) observability of propagating fronts in the framework of the so-called Epithelial-to-Mesenchymal Transition and its reverse Mesenchymal-to-Epithelial Transition, which are known to play a crucial role in tumor development. To this aim, we p...
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doaj-c8a4e6fd2c6841a29a38d5e85b543ddf2021-09-06T19:22:00ZengSciendoCommunications in Applied and Industrial Mathematics2038-09092020-01-0111111710.2478/caim-2020-0001caim-2020-0001Phase transitions of biological phenotypes by means of a prototypical PDE modelMascia C.0Moschetta P.1Simeoni C.2Department of Mathematics G. Castelnuovo, Sapienza University of Rome, ItalyDepartment of Mathematics G. Castelnuovo, Sapienza University of Rome, ItalyLaboratoire J.A. Dieudonné, University of Nice Sophia Antipolis, FranceThe basic investigation is the existence and the (numerical) observability of propagating fronts in the framework of the so-called Epithelial-to-Mesenchymal Transition and its reverse Mesenchymal-to-Epithelial Transition, which are known to play a crucial role in tumor development. To this aim, we propose a simplified one-dimensional hyperbolic-parabolic PDE model composed of two equations, one for the representative of the epithelial phenotype, and the second describing the mesenchymal phenotype. The system involves two positive constants, the relaxation time and a measure of invasiveness, moreover an essential feature is the presence of a nonlinear reaction function, typically assumed to be S-shaped. An identity characterizing the speed of propagation of the fronts is proven, together with numerical evidence of the existence of traveling waves. The latter is obtained by discretizing the system by means of an implicit-explicit finite difference scheme, then the algorithm is validated by checking the capability of the so-called LeVeque–Yee formula to reproduce the value of the speed furnished by the above cited identity. Once such justification has been achieved, we concentrate on numerical experiments relative to Riemann initial data connecting two stable stationary states of the underlying ODE model. In particular, we detect an explicit transition threshold separating regression regimes from invasive ones, which depends on critical values of the invasiveness parameter. Finally, we perform an extensive sensitivity analysis with respect to the system parameters, exhibiting a subtle dependence for those close to the threshold values, and we postulate some conjectures on the propagating fronts.https://doi.org/10.2478/caim-2020-0001phase transitionsreaction-diffusion systemspropagating frontsfinite difference schemeswave speed approximations |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mascia C. Moschetta P. Simeoni C. |
spellingShingle |
Mascia C. Moschetta P. Simeoni C. Phase transitions of biological phenotypes by means of a prototypical PDE model Communications in Applied and Industrial Mathematics phase transitions reaction-diffusion systems propagating fronts finite difference schemes wave speed approximations |
author_facet |
Mascia C. Moschetta P. Simeoni C. |
author_sort |
Mascia C. |
title |
Phase transitions of biological phenotypes by means of a prototypical PDE model |
title_short |
Phase transitions of biological phenotypes by means of a prototypical PDE model |
title_full |
Phase transitions of biological phenotypes by means of a prototypical PDE model |
title_fullStr |
Phase transitions of biological phenotypes by means of a prototypical PDE model |
title_full_unstemmed |
Phase transitions of biological phenotypes by means of a prototypical PDE model |
title_sort |
phase transitions of biological phenotypes by means of a prototypical pde model |
publisher |
Sciendo |
series |
Communications in Applied and Industrial Mathematics |
issn |
2038-0909 |
publishDate |
2020-01-01 |
description |
The basic investigation is the existence and the (numerical) observability of propagating fronts in the framework of the so-called Epithelial-to-Mesenchymal Transition and its reverse Mesenchymal-to-Epithelial Transition, which are known to play a crucial role in tumor development. To this aim, we propose a simplified one-dimensional hyperbolic-parabolic PDE model composed of two equations, one for the representative of the epithelial phenotype, and the second describing the mesenchymal phenotype. The system involves two positive constants, the relaxation time and a measure of invasiveness, moreover an essential feature is the presence of a nonlinear reaction function, typically assumed to be S-shaped. An identity characterizing the speed of propagation of the fronts is proven, together with numerical evidence of the existence of traveling waves. The latter is obtained by discretizing the system by means of an implicit-explicit finite difference scheme, then the algorithm is validated by checking the capability of the so-called LeVeque–Yee formula to reproduce the value of the speed furnished by the above cited identity. Once such justification has been achieved, we concentrate on numerical experiments relative to Riemann initial data connecting two stable stationary states of the underlying ODE model. In particular, we detect an explicit transition threshold separating regression regimes from invasive ones, which depends on critical values of the invasiveness parameter. Finally, we perform an extensive sensitivity analysis with respect to the system parameters, exhibiting a subtle dependence for those close to the threshold values, and we postulate some conjectures on the propagating fronts. |
topic |
phase transitions reaction-diffusion systems propagating fronts finite difference schemes wave speed approximations |
url |
https://doi.org/10.2478/caim-2020-0001 |
work_keys_str_mv |
AT masciac phasetransitionsofbiologicalphenotypesbymeansofaprototypicalpdemodel AT moschettap phasetransitionsofbiologicalphenotypesbymeansofaprototypicalpdemodel AT simeonic phasetransitionsofbiologicalphenotypesbymeansofaprototypicalpdemodel |
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