1668P - Systems biology in translational oncology: computational and experimental study of EGFR and IGF1R pathways in NSCLC cell lines

Date 30 September 2012
Event ESMO Congress 2012
Session Poster presentation II
Topics Basic Science
Lung and other Thoracic Tumours
Presenter Fortunato Bianconi
Authors F. Bianconi1, K. Perruccio2, V. Ludovini3, E. Baldelli3, G. Bellezza4, A. Flacco2, P. Valigi5, L. Crinò6
  • 1University of Perugia, 06036 - Perugia/IT
  • 2Medical Oncology Division, S. Maria della Misericordia Hospital,, 06132 - Perugia/IT
  • 3Medical Oncology, S. Maria della Misericordia Hospital, 06132 - Perugia/IT
  • 4University Of Perugia, Institute of Pathological Anatomy and Histology, University of Perugia, Perugia, Italy, 06132 - Perugia/IT
  • 5Department Of Electronic And Information Engineering, University of Perugia, Perugia/IT
  • 6Oncologia Medica, S. Maria della Misericordia Hospital, 06132 - Perugia/IT

Abstract

Background

The epidermal growth factor receptor (EGFR) and type 1 insulin-like growth factor receptor (IGF1R) pathways are complex networks involving interactions between membrane-bound receptors, ligands, binding proteins, downstream effectors and mutual interactions. In this study we have designed a computational model of EGFR and IGF1R pathways in NSCLC and we validated their dynamic responses in several tumor cell lines.

Materials and methods

EGFR and IGF1R pathways and the downstream MAPK and PIK3 networks have been modeled by means a mathematical model based on ODE. A549, H1299, H1675 and H1650 tumor cell lines were stimulated by EGF, IGF-I, EGF/IGF-I and without ligands. For these induction conditions we quantified at 0, 2, 5, 10, 20, 30, 40, 50, 60 minutes by western blotting the following proteins: phospho-AKT, AKT, phospho-EGFR, EGFR, phospho-p44/42 MAPK(ERK 1/2), p44/42 MAPK(ERK1/2), phospho-IGF1R and IGF1R. Model simulations and experiment data have been combined together.

Results

The time series performed in all cell lines under the four induction conditions allowed us to characterize the signal transduction through EGFR and IGF1R pathways. Our model has reproduced proteins behavior of A549, H1299, H1675 and H1650 cell lines and also the robustness of the network has been confirmed.

Conclusions

We propose a Systems Biology approach, combined with Translational Oncology tolls, to understand the interaction between EGFR and IGF1R pathways in NSCLC cell lines and validate model predictions. Future work will investigate the effect of drugs action on cell lines.

Disclosure

All authors have declared no conflicts of interest.