MSM Mapping and Modeling ErbB Receptor Membrane Topogra*

University Of New Mexico, Albuquerque NM

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Abstract

[unreadable] DESCRIPTION (provided by applicant): [unreadable] Our goal is to understand the topographical regulation of ErbB signaling in endometrial cancer, a disease where amplification of ErbB1 (the EGFR) and ErbB2 genes is associated with poor outcome. Specifically, we propose: 1) to map the topography of ErbB receptors and their associated signaling molecules using innovative electron microscopy techniques; 2) to apply rigorous biochemical and statistical analyses to [unreadable] establish quantities of signaling molecules, their distributions and their relationships; and 3) to use these spatial and quantitative data as a framework for multiscale simulations of the signaling process. Preliminary data show that, when expressed at modest levels, ErbB receptors are preclustered in the membranes of endometrial epithelial cells. We hypothesize that signal transduction by these preformed clusters is held in check by the low probability of interactions between receptors in the open, signaling-competent [unreadable] conformation. When ligand addition is simulated, the preclustered state accelerates dimerization, leading to trans-phosphorylation and activation. We predict that overexpression of ErbB receptors in cancer promotes the formation of large, mixed clusters that increase the probability of ligand-independent, productive dimerization. We further predict that the spatial relationships of receptors to downstream signaling [unreadable] molecules has profound effects on ErbB signaling to critical MAP kinase and AKT pathways. To test this, we will map steady-state distributions of ErbB1 and Erb2 under defined combinations of wildtype and mutant receptors. Ligand-induced changes in receptor distributions will be documented, focusing on cluster size and co-clustering, localization to caveolae and uptake by clathrin-coated pits. Double-labeling protocols will map receptor proximity to downstream signaling molecules. Effects of kinase inhibitors on receptor distributions will be determined. Our image processing and statistical toolbox will be applied to establish receptor distribution patterns, as well as estimates of relative concentrations of receptors and downstream components within signaling domains. We will simulate diffusion, clustering and internalization of receptors and signaling molecules using Monte Carlo and agent-based approaches. Spatially realistic simulations will [unreadable] predict rates of ErbB receptor homo and heterodimerization, and the efficiency of receptor-effector coupling. The model will fully explore the spatial and temporal aspects of ErbB signaling. [unreadable] [unreadable]