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. We focus in particular 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.
Sevecka M, Wolf-Yadlin A*, MacBeath G. “Lysate Microarrays Enable High-throughput, Quantitative Investigations of Cellular Signaling”. Submitted.
Locasale JW, Wolf-Yadlin, A. “Maximum entropy reconstructions of dynamic signaling networks from quantitative proteomics data”. PLoS One. 2009 Aug 26; 4(8):e6522.
Wolf-Yadlin A, Sevecka M, MacBeath G. “Dissecting Protein Function and Signaling Using Protein Microarrays”. Curr. Opin. Chem. Biol. 2009; 13(4):398-405. Epub 2009 Aug 5.
Gordus A, Krall JA, Beyer EM, Kaushansky A, Wolf-Yadlin A, Sevecka M, Chang BH, Rush J, MacBeath G. “Linear combinations of docking affinities explain quantitative differences in RTK signaling”. Mol Syst
Biol. 2009; 5:235. Epub 2009 Jan 20.
Wolf-Yadlin A, Hautaniemi S, Lauffenburger DA, White FM. “Multiple Reaction Monitoring for Robust Quantitative Proteomic Analysis of Cellular Signaling Networks”. Proc Natl Acad Sci U S A. 2007; 104(14):5860-5. Epub 2007 Mar 26.
Zhang Y, Wolf-Yadlin A*, White FM. “Quantitative Proteomic Analysis of Phosphotyrosine-Mediated Cellular Signaling Networks”. Methods Mol Biol. 2007; 359(14):203-212.
Kumar N, Wolf-Yadlin A, White FM, Lauffenburger DA. “Modeling HER2 Effects on Cell Behavior from Mass Spectrometry Phosphotyrosine Data”. PLoS Comput Biol. 2007; 3(1):e4. Epub 2006 Nov 21.
Wolf-Yadlin A, Kumar N, Zhang Y, Hautaniemi S, Zaman M, Kim HD, Grantcharova V, Lauffenburger DA, White FM. “Effects of HER2 overexpression on cell signaling networks governing proliferation and migration”. Mol Syst Biol. 2006; 2:54. Epub 2006 Oct 3.
Zhang Y, Wolf-Yadlin A*, Ross PL, Pappin DJ, Rush J, Lauffenburger DA, White FM. “ Time-resolved mass spectrometry of tyrosine phosphorylation sites in the EGF receptor signaling network reveals dynamic modules”. Mol Cell Proteomics. 2005; 4(9):1240-50. Epub 2005
* Co-first author