No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.
Modeling TGF-β signaling pathway in epithelial-mesenchymal transition
1. Jean Paul Thiery, Hervé Acloque, Rubi Y. J. Huang, and M. Angela Nieto, “Epithelial-mesenchymal transition in development and disease,” Cell 21, 166–176 (2009).
2. JCarl-Henrik Heldin, Maréne Landström, and Aristidis Moustakas, “Mechanism of TGF-β signaling to growth arrest, apoptosis, and epithelial mesenchymal transition,” Current Opinion in Cell Biology 21, 166–176 (2009).
3. Bernhard Schmierer, Alexander L. Tournier, Paul A. Bates, and Caroline S. Hill, “Mathematical modeling identifies Smad nucleocytoplasmic shuttling as a dynamic signal-interpreting system,” PNAS 105 no. 18, 6608–6613 (2008).
7. Linsey E. Lindley and Karoline J. Briegel, “Molecular characterization of TGFb-induced epithelial-mesenchymal transition in normal finite lifespan human mammary epithelial cells,” Biochemical and Biophysical Research Communications 399, 659–664 (2010).
8. Mark Schena, Dari Shalon, Ronald W. Davis, and Patrick O. Brown, “Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray,” Science 270 no. 5235, 467–470 (1995).
10. Jin J. Y., Richard R. Almon, Debra C. Dubois, and William J. Jusko, “Modeling of Corticosteroid Pharmacogenomics in Rat Liver Using Gene Microarrays,” The journal of pharmacology and experimental therapeutics 307 no. 1, 93–109 (2003).
11. Zhenling Yao, Eric P. Hoffman, Svetlana Ghimbovschi, Debra C. DuBois, Richard R. Almon, and William J. Jusko, “Mathematical Modeling of Corticosteroid Pharmacogenomics in Rat Muscle following Acute and Chronic Methylprednisolone Dosing,” Molecular Pharmaceutics 5 no. 2, 328–339 (2008).
13. Venkateshwar G. Keshamouni, George Michailidis, Catherine S. Grasso, Shalini Anthwal, John R. Strahler, Angela Walker, Douglas A. Arenberg, Raju C. Reddy, Sudhakar Akulapalli, Victor J. Thannickal, Theodore J. Standiford, Philip C. Andrews, and Gilbert S. Omenn, “Differential Protein Expression Profiling by iTRAQ-2DLC-MS/MS of Lung Cancer Cells Undergoing Epithelial-Mesenchymal Transition Reveals a Migratory/Invasive Phenotype,” Journal of Proteome Research 5, 1143–1154 (2006).
16. Incidentally, we are now in a position to clarify why the families of fixed points (i), (ii), (iii) are not compatible with the selected initial data. First, let us note that TGF-β and R get progressively consumed at exactly the same pace, see the first two equations of system (7), as they are both implicated in the creation of the R* species. However, at t = 0, the quota of free receptors R is significantly larger than the number of injected TGF-β molecules (R(t = 0) = 1nM vs. TGF-β(t = 0) = 0.113nM). As a consequence, and because R and TGF-β obey to an identical kinetic, it is the TGF-β that vanish first, reaching its asymptotic state TGF-β = 0 when a residual quota of R is still present. From here on, the receptors R cannot be mutated in R* any longer and are therefore indefinitely frozen to the asymptotic value R(t = 0) − TGF-β(t = 0), which is positive and different from zero. Both solutions (i) and (ii) are therefore to be rejected because they require R = 0. A similar reasoning can be invoked to exclude solution (iii). This latter would in fact imply Sc = 0. However, as it can be readily appreciated by inspection of system (7), the rate of loss of both R* and Sc is governed by the same term, namely −kp[R*][Sc]. The maximum amount of bound receptors R* is equal to the number of TGF-β(t = 0) molecules, while the Sc elements at time t = 0 are definitely many more (121.1nM). Moreover, the population of Sc gets also re-integrated, via a source term controlled by the reaction rate kexp, which acts as long as Sn is different from zero. Based on the above, we can therefore conclude that Sc molecules are still present when R* becomes zero. From here on the Sc cannot decrease any longer and stay frozen to the value that they have eventually attained when the condition R* = 0 is met. Hence, solution (iii) cannot apply to the scrutinized setting, as it assumes the asymptotic condition Sc = 0.
18. Andreas Wagner, “Robustness and Evolvability in Living Systems,” Princeton University Press (2007).
19. Karline Soetaert and Thomas Petzoldt, “Inverse Modelling, Sensitivity and Monte Carlo Analysis in R Using Package FME,” Journal of Statistical Software 33(3), 1–28 (2010).
R Development Core Team, Vienna, Austria, “R: A Language and Environment for statistical Computing,” ISBN 3-900051-07-0, (http://www.R-project.org
21. Daniel Sorensen and Daniel Gianola, “Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics,” Springer, New York (2002).
22. Kornelia Polyak and Robert A. Weinberg, “Transitions between epithelial and mesenchymal states: acquisition of malignant and stem cell traits,” Nature Reviews 9, 265–273 (2009).
Article metrics loading...
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 cancermetastasis. 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.
Full text loading...
Most read this month