In Vivo Multiphoton Based Imaging of Complex Cancer Cell Behavior

项目摘要 最近的研究结果使许多人提出了一个微环境依赖的模型，用于启动 原发肿瘤和靶内的迁移和播散肿瘤细胞行为 器官不是由基因突变稳定指定的，并且在时间和空间上是短暂的。 这种观点被称为转移的微环境模型。该模型的测试 部分原因是缺乏高分辨率的体内显微镜方法， 用于肿瘤深层组织成像的基因编码荧光探针， 识别参与启动迁移和传播的微环境 肿瘤细胞表型同样成问题的是对表达的标准分析的局限性 数据区.癌症表达谱的标准分析包括鉴定一致的上调- 和下调的基因。虽然这些技术可能直接识别基因组， 在受影响的网络中，我们以前的理论结果表明， (of癌症是其中之一）导致表达变化远远超出所涉及的途径。最关键的是， 这些更远的变化将取决于遗传背景， 预期个体之间的肿瘤表达谱是非常不同的。使用此 假设我们提出了一种新的系统水平的癌症分析（SLAC），它确定了关键 基因的基础上增加表达变异性，这反过来又提供了可能性， 发现与微环境有关的高度非直观的通路相互作用 调节乳腺癌的进展。通过结合多光子高分辨率 具有宽范围的激发波长的显微镜， 荧光探针作为通用的传统绿色荧光蛋白，我们将推进深层组织细胞标记 以及体内肿瘤细胞动态成像。这种方法将使活体内 在肿瘤研究中同时成像多达六种遗传编码的颜色。这反过来将 提供了一种区分并随后分离多个转移性肿瘤细胞的方法， 基于荧光颜色编码的表达模式的表型。通过关联 通过多光子获得的迁移和播散肿瘤细胞的行为和命运 在单细胞水平成像与SLAC分析这些细胞的表达谱，我们将 确定驱动肿瘤细胞转移行为（如细胞迁移）的关键基因 和传播。

PROJECT ABSTRACT Recent results have led many to propose a microenvironment-dependent model for initiation of migratory and disseminating tumor cell behavior at both the primary tumor and within target organs that is not stably specified by genetic mutation and that is transient in time and space. This view is called the microenvironment model of metastasis. The testing of this model has been hampered in part by the lack of high-resolution in vivo microscopy methods and genetically-encoded fluorescent probes for tumor deep-tissue imaging that allow definitive identification of the microenvironments involved in initiating the migratory and disseminating tumor cell phenotype. Equally problematic are the limitations of standard analyses of expression profiles. Standard analysis of expression profiles in cancer involves identifying consistently up- and down- regulated genes. While these techniques are likely to identify sets of genes directly within affected networks, our previous theoretical results have shown that major perturbations (of which cancer is one) cause expression changes far beyond the pathway involved. Crucially, these more distant changes will be highly variable depending on the genetic background, thus tumor expression profiles are expected to be greatly dissimilar between individuals. Using this hypothesis we propose a novel systems-level analysis of cancer (SLAC), which identifies key genes based upon increase in expression variability, and which in turn offers the possibility of discovering highly non-intuitive pathway interactions connected with microenvironment regulation of breast cancer progression. By combining the multiphoton high-resolution microscopy having the wide range of excitation wavelengths with the proposed multicolor far-red fluorescent probes as versatile as conventional GFP we will advance deep-tissue cell labeling and imaging of tumor cells dynamics in vivo. This approach will make possible the intravital imaging of simultaneously up to six genetically-encoded colors in tumor studies. This in turn will provide a way to discriminate and subsequently isolate the tumor cells of multiple metastatic phenotypes based on the fluorescent color-encoded expression patterns. By correlating the behavior and fate of migrating and disseminating tumor cells obtained by the multiphoton imaging at a single-cell level with SLAC analysis of expression profiles of these cells, we will identify the key genes driving tumor cell behaviors involved in metastasis such as cell migration and dissemination.