Monte Carlo uncertainty quantification in modelling cell deformation during cancer metastasis
J. Chen (TU Delft - Numerical Analysis)
D Weihs (Technion Israel Institute of Technology)
F. J. Vermolen (TU Delft - Numerical Analysis)
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Abstract
During metastasis of cancer, cell migration plays a crucial role, which is normally accompanied by morphological evolution. To simulate cell deformation, we develop a phenomenological, computational model involving deformation of a cell as well as its nucleus. The migration of a single cell is orchestrated by a generic signal (e.g. a chemokine or a stiffness stimulus), the microvascular flow and stochastic processes, which are dealt with by using Green’s Fundamental solutions, Poisseuille flow and a vector Wiener process, respectively. Moreover, due to the uncertainties in the input variables, Monte Carlo simulations are carried out to evaluate the correlations between various parameters and quantitatively predict the likelihood of vessel transmigration of one cell during cancer metastasis.