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Modeling TGF-β signaling pathway in epithelial-mesenchymal transition
Author(s) -
Pasquale Laise,
Duccio Fanelli,
Píetro Lió,
Annarosa Arcangeli
Publication year - 2012
Publication title -
aip advances
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.421
H-Index - 58
ISSN - 2158-3226
DOI - 10.1063/1.3697962
Subject(s) - epithelial–mesenchymal transition , microbiology and biotechnology , markov chain monte carlo , tgf beta signaling pathway , mesenchymal stem cell , signal transduction , biology , transforming growth factor , chemistry , metastasis , computer science , cancer , bayesian probability , genetics , artificial intelligence
The epithelial-mesenchymal transition (EMT) consists in a morphological change in epithelial cells characterized by the loss of the cell adhesion and the acquisition of mesenchymal phenotype. This process plays a crucial role in the embryonic development and in regulating the tissue homeostasis in the adult, but it proves also fundamental for the development of cancer metastasis. Experimental evidences have shown that the EMT depends on the TGF-β signaling pathway, which in turn regulates the transcriptional cellular activity. In this work, a dynamical model of the TGF-β pathway is proposed and calibrated versus existing experimental data on lung cancer A549 cells. The analysis combines Bayesian Markov Chain Monte Carlo (MCMC) and standard Ordinary Differential Equations (ODEs) techniques to interpolate the gene expression data via an iterative adjustments of the parameters involved. The kinetic of the Smad proteins phosphorylation, as predicted within the model is found in excellent agreement with available experiments, an observation that confirms the adequacy of the proposed mathematical picture

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