EGFR and IGF1R pathways play a key role in various human cancers and are crucial for tumour transformation and survival of malignant cells. High EGFR and IGF1R expression and activity has been associated with multiple aspects of cancer progression including tumourigenesis, metastasis, resistance to chemotherapeutics and other molecularly targeted drugs. Here, the biological relationship between the proteins involved in EGFR and IGF1R pathways and the downstream MAPK and PIK3 networks has been modelled to study the time behaviour of the overall system, and the functional interdependencies among the receptors, the proteins and kinases involved.
This model is described in the article:
Abstract:
In this paper we propose a Systems Biology approach to understand the molecular biology of the Epidermal Growth Factor Receptor (EGFR, also known as ErbB1/HER1) and type 1 Insulin-like Growth Factor (IGF1R) pathways in non-small cell lung cancer (NSCLC). This approach, combined with Translational Oncology methodologies, is used to address the experimental evidence of a close relationship among EGFR and IGF1R protein expression, by immunohistochemistry (IHC) and gene amplification, by in situ hybridization (FISH) and the corresponding ability to develop a more aggressive behavior. We develop a detailed in silico model, based on ordinary differential equations, of the pathways and study the dynamic implications of receptor alterations on the time behavior of the MAPK cascade down to ERK, which in turn governs proliferation and cell migration. In addition, an extensive sensitivity analysis of the proposed model is carried out and a simplified model is proposed which allows us to infer a similar relationship among EGFR and IGF1R activities and disease outcome.
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Computational model of EGFR and IGF1R pathways in lung cancer: a Systems Biology approach for Translational Oncology.
- Fortunato Bianconi, Elisa Baldelli, Vienna Ludovini, Lucio Crinò, Antonella Flacco, Paolo Valigi
- Biotechnology advances , 0/ 2012 , Volume 30 , Issue 1 , pages: 142-153 , PubMed ID: 21620944
- Department of Electronic and Information Engineering, Perugia University, Italy. fortunato.bianconi@diei.unipg.it
- In this paper we propose a Systems Biology approach to understand the molecular biology of the Epidermal Growth Factor Receptor (EGFR, also known as ErbB1/HER1) and type 1 Insulin-like Growth Factor (IGF1R) pathways in non-small cell lung cancer (NSCLC). This approach, combined with Translational Oncology methodologies, is used to address the experimental evidence of a close relationship among EGFR and IGF1R protein expression, by immunohistochemistry (IHC) and gene amplification, by in situ hybridization (FISH) and the corresponding ability to develop a more aggressive behavior. We develop a detailed in silico model, based on ordinary differential equations, of the pathways and study the dynamic implications of receptor alterations on the time behavior of the MAPK cascade down to ERK, which in turn governs proliferation and cell migration. In addition, an extensive sensitivity analysis of the proposed model is carried out and a simplified model is proposed which allows us to infer a similar relationship among EGFR and IGF1R activities and disease outcome.
Submitter of this revision: Lucian Smith
Curator: Lucian Smith
Modeller: Fortunato Bianconi
Metadata information
isDescribedBy (1 statement)
hasTaxon (1 statement)
isPartOf (3 statements)
Gene Ontology insulin-like growth factor receptor signaling pathway
Pathway Ontology lung cancer pathway
isVersionOf (2 statements)
Gene Ontology regulation of ERK1 and ERK2 cascade
hasVersion (1 statement)
hasProperty (1 statement)
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