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Computational model of EGFR and IGF1R pathways in lung cancer: A Systems Biology approach for Translational Oncology

Paper ID Volume ID Publish Year Pages File Format Full-Text
14591 1232 2012 12 PDF Available
Title
Computational model of EGFR and IGF1R pathways in lung cancer: A Systems Biology approach for Translational Oncology
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.

Keywords
Systems Biology; Translation Oncology; EGFR; IGF1R; Mathematical modeling; Survival analysis
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Publisher
Database: Elsevier - ScienceDirect
Journal: Biotechnology Advances - Volume 30, Issue 1, January–February 2012, Pages 142–153
Authors
, , , , , ,
Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us