The major aim of the proposed work is to develop a quantitative understanding of epithelial cell scatter, a process that is closely linked to late metastatic stages of cancer development. During metastasis, epithelial tissue structure is significantly disrupted as epithelial cells escape from their primary site and invade surrounding tissue. An effective ex vivo model of metastasis involves cell scatter. Epithelial cells grow in clusters ex vivo, reminiscent of their monolayer, well-packed morphology in vivo. Metastasis-associated genetic perturbations promote cells to "peel away" from clusters and scatter into the surrounding region. Thus, the cell scatter assay has been used to identify oncogenes (OGs) and tumor suppressor genes (TSGs) that may play a role in metastasis. However, current approaches are limited to qualitative characterizations from which it is difficult to assess how potent a particular OG/TSG might be and which combinations exhibit the most synergism. Answers to such questions can guide us to the most potent choice of drug targets and could help us design the most effective combination treatments. Furthermore, to understand more deeply how OG/TSGs quantitatively affect population-level phenotype, it is essential to examine the cell-level processes that contribute to multicellular scatter. These cell-level properties include the migration of individual cells and multicellular groups. In addition, migrating cells will collide. Whether these collisions re-seed small clusters or whether colliding cells "bounce apart" (akin to an elastic collision) will affect the extent and dynamics of cell scatter. Current techniques to quantify these cell-level properties are too cumbersome to permit quantitative, systems-scale analysis of the effects of numerous OG/TSGs. In the proposed work, we seek to address these challenges in order to elucidate the quantitative effects of the adhesive microenvironment and OG/TSGs on cell scatter. We will quantify both the cell- and population-level aspects of cell scatter using a multi-faceted strategy that integrates automated high-throughput imaging and micropatterning.
The Specific Aims are: 1. To develop quantitative automated methods for measuring cell-level motility properties. 2. To elucidate the quantitative effect of the adhesive microenvironment on multicellular scatter and the underlying cell-level properties. 3. To elucidate the quantitative contributions and synergisms of metastatic genes to multicellular scatter and to the underlying cell-level properties. Results from the proposed work will provide a deeper quantitative understanding of how OG/TSGs and the adhesive microenvironment affect cell-level motile properties and multicellular scatter, a process closely related to metastasis.

Public Health Relevance

The majority of human cancers occurs in epithelial tissues, and the disease enters a lethal metastatic phase when cancer cells escape from well-ordered epithelial tissues and infiltrate into surrounding areas. The proposed work will provide a deeper quantitative understanding of how genetic changes induce cells to scatter from their neighbors, a core aspect of metastasis. These quantitative insights will point us to the most potent scatter-inducing genes, highlighting potentially more effective drug targets to curb metastatic processes.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Modeling and Analysis of Biological Systems Study Section (MABS)
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Li, Jerry
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Northeastern University
Engineering (All Types)
Schools of Engineering
United States
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