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One of the most important questions in modern biology is how cells maintain their identity and what are the genomic and proteomic changes that drive the transition of cells from a healthy to a diseased state. Deregulation of receptor tyrosine kinase (RTK) signaling, often a consequence of receptor mutation or aberrant expression, has been shown to play an important role in cancer progression and the onset of other diseases. Therefore, it is essential to understand how different RTKs interact with their downstream pathways to produce diverse cellular behavior such as growth, proliferation, migration and differentiation. While traditional biochemical techniques have allowed us to understand how different components of the cell behave individually, a systems-level approach is required to understand how these components interact with each other, and how they function in the context of biological complexity.
The goal of our lab is to understand the mechanism of RTK-mediated signaling at a systems level. Currently we focus on TRKB - an RTK whose deregulation has been implicated in several types of cancer, most notably neuroblastoma, as well as in various diseases of the nervous system such as schizophrenia and Alzheimer's disease. The approach we are taking involves the development and application of novel mass spectrometry- and microarray-based methodologies to quantitatively measure dynamic changes of large numbers of signaling proteins of interest. In combination with systematic perturbations of protein expression and function, these tools allow us to use a global approach to determine the connectivity of the RTK-mediated signaling networks and the dynamics of their signaling. In addditon, we draw on well-established high-throughput gene expresion profiling and phenotypic measurements to examine the relationships between signaling dynamics, gene expression, cellular phenotype and disease progression. We then use these quantitative data to develop computational models of cellular signaling and to explore correlations between protein activity and phenotype. Ultimately, we envision that these efforts will allow us to not only elucidate the topology of signaling networks, but to make informed predictions about the most beneficial intervention strategies to regulate a phenotype or ablate a disease.
Copyright © 2003-2013 Molecular & Cellular Biology Program, University of Washington
Fred Hutchison Cancer Research Center | University of Washington
Institute for Systems Biology | Seattle Biomed