Receptor tyrosine kinase (RTK) signaling is crucial for many cellular processes, including proliferation, differentiation, cell metabolism, survival and apoptosis. Alterations in growth factor signaling networks can play a pivotal role in carcinogenesis. Despite an explosive growth of our knowledge of protein and lipid components involved in the epidermal growth factor receptor (EGFR) and insulin receptor (IR) signaling, an integrative, quantitative picture of responses of the signaling networks and their control at the cellular level remains poorly understood. The response of hepatocytes to growth factors is the consequence of a complex interplay of multiple protein-protein and protein-lipid interactions, subcellular relocation of signaling proteins and phosphorylation/dephosphorylation reactions. During the previous period of support, our work has demonstrated the considerable potential of a novel cross-disciplinary approach that combines experimental studies with nonlinear systems analysis and interacting computational models to achieve a quantitative understanding of the EGFR and IR signaling networks in hepatocytes. In this application we seek continued support to validate feasible hypotheses suggested by computational modeling, determine the molecular and kinetic factors controlling the different response patterns to EGF and insulin, and understand how cells interpret signals in a context-dependent manner. This knowledge will provide a powerful tool to predict and manipulate critical cellular decisions, which determine cell fate and may, thereby, assist in the development of improved drug therapies.
The Specific Aims are: (1) To extend the quantitative analysis of the EGFR signaling network to multiple downstream branches including the Ras/Raf/MEK/ERK pathway in freshly isolated hepatocytes; (2) To modify the EGFR network by the conditional expression of key signaling proteins to desired levels and systematically quantify the impact on EGF-induced signaling in a model cell line; (3) To integrate the insulin receptor (IR) signaling network in the experimental and computational analysis and characterize its interaction with the EGFR pathways in hepatocytes.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM059570-04
Application #
6617237
Study Section
Cell Development and Function Integrated Review Group (CDF)
Program Officer
Ikeda, Richard A
Project Start
2000-06-01
Project End
2007-05-31
Budget Start
2003-06-01
Budget End
2004-05-31
Support Year
4
Fiscal Year
2003
Total Cost
$302,600
Indirect Cost
Name
Thomas Jefferson University
Department
Pathology
Type
Schools of Medicine
DUNS #
053284659
City
Philadelphia
State
PA
Country
United States
Zip Code
19107
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