Basic ingredients for mathematical modeling of tumor growth in vitro: Cooperative effects and search for space


Autoria(s): Costa, F. H S; Campos, M.; Aiéllo, O. E.; da Silva, M. A A
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

27/05/2014

27/05/2014

01/11/2013

Resumo

Based on the literature data from HT-29 cell monolayers, we develop a model for its growth, analogous to an epidemic model, mixing local and global interactions. First, we propose and solve a deterministic equation for the progress of these colonies. Thus, we add a stochastic (local) interaction and simulate the evolution of an Eden-like aggregate by using dynamical Monte Carlo methods. The growth curves of both deterministic and stochastic models are in excellent agreement with the experimental observations. The waiting times distributions, generated via our stochastic model, allowed us to analyze the role of mesoscopic events. We obtain log-normal distributions in the initial stages of the growth and Gaussians at long times. We interpret these outcomes in the light of cellular division events: in the early stages, the phenomena are dependent each other in a multiplicative geometric-based process, and they are independent at long times. We conclude that the main ingredients for a good minimalist model of tumor growth, at mesoscopic level, are intrinsic cooperative mechanisms and competitive search for space. © 2013 Elsevier Ltd.

Formato

24-29

Identificador

http://dx.doi.org/10.1016/j.jtbi.2013.07.030

Journal of Theoretical Biology, v. 337, p. 24-29.

0022-5193

1095-8541

http://hdl.handle.net/11449/76899

10.1016/j.jtbi.2013.07.030

WOS:000325955000003

2-s2.0-84883207249

2-s2.0-84883207249.pdf

Idioma(s)

eng

Relação

Journal of Theoretical Biology

Direitos

openAccess

Palavras-Chave #Dynamical Monte Carlo #Mathematical modeling #Tumor growth #cell organelle #epidemic #Monte Carlo analysis #numerical model #stochasticity #tumor #cell division #growth curve #in vitro study #mathematical computing #mathematical model #Monte Carlo method #normal distribution #priority journal #simulation #stochastic model #tumor growth #tumor model
Tipo

info:eu-repo/semantics/article