Quantitative analysis of epithelial cell scatter

描述（由申请人提供）：拟议工作的主要目的是发展对上皮细胞散射的定量理解，这一过程与癌症发展的晚期转移阶段密切相关。在转移过程中，上皮组织结构被明显破坏，上皮细胞从原发部位逃逸并侵入周围组织。一个有效的体外转移模型涉及细胞分散。上皮细胞在体外成簇生长，使人想起它们在体内的单层、致密的形态。与转移相关的遗传扰动促使细胞从集群中“剥离”并分散到周围区域。因此，细胞分散试验已被用于鉴定可能在转移中起作用的癌基因（OGs）和肿瘤抑制基因（TSGs）。然而，目前的方法仅限于定性描述，难以评估特定OG/TSG的效力以及哪种组合表现出最大的协同作用。这些问题的答案可以指导我们选择最有效的药物靶点，并可以帮助我们设计最有效的联合治疗。此外，为了更深入地了解OG/ tsg如何定量地影响群体水平的表型，有必要研究导致多细胞分散的细胞水平过程。这些细胞水平的特性包括单个细胞和多细胞群的迁移。此外，迁移的细胞会发生碰撞。这些碰撞是否会重新形成小簇，或者碰撞细胞是否会“弹开”（类似于弹性碰撞），都会影响细胞散射的程度和动态。目前量化这些细胞水平特性的技术过于繁琐，无法对大量OG/ tsg的影响进行定量、系统规模的分析。在提出的工作中，我们试图解决这些挑战，以阐明粘附微环境和OG/TSGs对细胞散射的定量影响。我们将使用集成自动化高通量成像和微模式的多方面策略来量化细胞散射的细胞和种群水平方面。具体目标是：1。开发定量的自动化方法来测量细胞水平的运动特性。2. 阐明黏附微环境对多细胞散射的定量影响及其潜在的细胞水平特性。3. 阐明转移基因对多细胞分散和潜在细胞水平特性的定量贡献和协同作用。这项工作的结果将提供更深入的定量理解OG/TSGs和粘附微环境如何影响细胞水平的运动特性和多细胞散射，这是一个与转移密切相关的过程。

DESCRIPTION (provided by applicant): 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.