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Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway
BACKGROUND: 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 alteration...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2764635/ https://www.ncbi.nlm.nih.gov/pubmed/19804630 http://dx.doi.org/10.1186/1752-0509-3-100 |
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author | Orton, Richard J Adriaens, Michiel E Gormand, Amelie Sturm, Oliver E Kolch, Walter Gilbert, David R |
author_facet | Orton, Richard J Adriaens, Michiel E Gormand, Amelie Sturm, Oliver E Kolch, Walter Gilbert, David R |
author_sort | Orton, Richard J |
collection | PubMed |
description | BACKGROUND: 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. RESULTS: 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. CONCLUSION: 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. |
format | Text |
id | pubmed-2764635 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-27646352009-10-21 Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway Orton, Richard J Adriaens, Michiel E Gormand, Amelie Sturm, Oliver E Kolch, Walter Gilbert, David R BMC Syst Biol Research Article BACKGROUND: 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. RESULTS: 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. CONCLUSION: 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. BioMed Central 2009-10-05 /pmc/articles/PMC2764635/ /pubmed/19804630 http://dx.doi.org/10.1186/1752-0509-3-100 Text en Copyright © 2009 Orton et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Orton, Richard J Adriaens, Michiel E Gormand, Amelie Sturm, Oliver E Kolch, Walter Gilbert, David R Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway |
title | Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway |
title_full | Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway |
title_fullStr | Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway |
title_full_unstemmed | Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway |
title_short | Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway |
title_sort | computational modelling of cancerous mutations in the egfr/erk signalling pathway |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2764635/ https://www.ncbi.nlm.nih.gov/pubmed/19804630 http://dx.doi.org/10.1186/1752-0509-3-100 |
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