Dataset Information

Sasagawa2005_MAPK

ABSTRACT: This a model from the article: Prediction and validation of the distinct dynamics of transient and sustained ERK activation. Sasagawa S, Ozaki Y, Fujita K, Kuroda S Nat. Cell Biol.[2005 Apr; Volume: 7 (Issue: 4 )]: 365-73 15793571, Abstract: To elucidate the hidden dynamics of extracellular-signal-regulated kinase (ERK) signalling networks, we developed a simulation model of ERK signalling networks by constraining in silico dynamics based on in vivo dynamics in PC12 cells. We predicted and validated that transient ERK activation depends on rapid increases of epidermal growth factor and nerve growth factor (NGF) but not on their final concentrations, whereas sustained ERK activation depends on the final concentration of NGF but not on the temporal rate of increase. These ERK dynamics depend on Ras and Rap1 dynamics, the inactivation processes of which are growth-factor-dependent and -independent, respectively. Therefore, the Ras and Rap1 systems capture the temporal rate and concentration of growth factors, and encode these distinct physical properties into transient and sustained ERK activation, respectively. Dynamics of active Ras, active Rap1 and phosphorylated ERK were correctly reproduced with CellDesigner 3.0 This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2012 The BioModels.net Team. For more information see the terms of use. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

SUBMITTER: Shinya Kuroda

PROVIDER: BIOMD0000000049 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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Dataset's files

Source:

			Action	DRS
	BIOMD0000000049?filename=BIOMD0000000049-biopax2.owl	Owl
	BIOMD0000000049?filename=BIOMD0000000049-biopax3.owl	Owl
	BIOMD0000000049?filename=BIOMD0000000049-matlab.m	Other
	BIOMD0000000049?filename=BIOMD0000000049.m	Other
	BIOMD0000000049?filename=BIOMD0000000049.ode	Other

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Prediction and validation of the distinct dynamics of transient and sustained ERK activation.

Sasagawa Satoru S Ozaki Yu-ichi Y Fujita Kazuhiro K Kuroda Shinya S

Nature cell biology 20050327 4

To elucidate the hidden dynamics of extracellular-signal-regulated kinase (ERK) signalling networks, we developed a simulation model of ERK signalling networks by constraining in silico dynamics based on in vivo dynamics in PC12 cells. We predicted and validated that transient ERK activation depends on rapid increases of epidermal growth factor and nerve growth factor (NGF) but not on their final concentrations, whereas sustained ERK activation depends on the final concentration of NGF but not o ...[more]

PMID: 15793571

Publication: 1/4

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Project description:Orton2009 - Modelling cancerous mutations in the EGFR/ERK pathway - EGF Model This model studies the aberrations in ERK signalling for different cancer mutations. The authors alter a previously existing EGF model (Brown et al 2004) to include new interactions that better fit empirical data. Predictions show that the ERK signalling is a robust mechanism taking different courses for different cancer mutations. Most parameter values are used from the previous model and the new parameters are estimated using experimental data performed by the authors on PC12 cells (adrenal gland, rat). The authors provide an SBML version of the model in the paper. This model is described in the article: Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway. Orton RJ, Adriaens ME, Gormand A, Sturm OE, Kolch W, Gilbert DR. BMC Syst Biol 2009 Oct; 3: 100 Abstract: The Epidermal Growth Factor Receptor (EGFR) activated Extracellular-signal Regulated Kinase (ERK) pathway is a critical cell signalling pathway that relays the signal for a cell to proliferate from the plasma membrane to the nucleus. Deregulation of the EGFR/ERK pathway due to alterations affecting the expression or function of a number of pathway components has long been associated with numerous forms of cancer. Under normal conditions, Epidermal Growth Factor (EGF) stimulates a rapid but transient activation of ERK as the signal is rapidly shutdown. Whereas, under cancerous mutation conditions the ERK signal cannot be shutdown and is sustained resulting in the constitutive activation of ERK and continual cell proliferation. In this study, we have used computational modelling techniques to investigate what effects various cancerous alterations have on the signalling flow through the ERK pathway.We have generated a new model of the EGFR activated ERK pathway, which was verified by our own experimental data. We then altered our model to represent various cancerous situations such as Ras, B-Raf and EGFR mutations, as well as EGFR overexpression. Analysis of the models showed that different cancerous situations resulted in different signalling patterns through the ERK pathway, especially when compared to the normal EGF signal pattern. Our model predicts that cancerous EGFR mutation and overexpression signals almost exclusively via the Rap1 pathway, predicting that this pathway is the best target for drugs. Furthermore, our model also highlights the importance of receptor degradation in normal and cancerous EGFR signalling, and suggests that receptor degradation is a key difference between the signalling from the EGF and Nerve Growth Factor (NGF) receptors.Our results suggest that different routes to ERK activation are being utilised in different cancerous situations which therefore has interesting implications for drug selection strategies. We also conducted a comparison of the critical differences between signalling from different growth factor receptors (namely EGFR, mutated EGFR, NGF, and Insulin) with our results suggesting the difference between the systems are large scale and can be attributed to the presence/absence of entire pathways rather than subtle difference in individual rate constants between the systems. This model is hosted on BioModels Database and identified by: BIOMD0000000623. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.