In Vivo Multiphoton Based Imaging of Complex Cancer Cell Behavior

项目摘要 最近的结果导致许多人提出了一个微环境依赖的模型来启动 肿瘤细胞在原发灶和靶区的迁移和扩散行为 不稳定的由基因突变确定的器官，在时间和空间上是暂时的。 这一观点被称为转移的微环境模型。该模型的测试已经 部分原因是缺乏高分辨率的活体显微镜方法和 用于肿瘤深层组织成像的基因编码的荧光探针，允许最终 确定启动迁徙和传播的微环境 肿瘤细胞表型。同样有问题的是对表达的标准分析的局限性 配置文件。癌症表达谱的标准分析涉及识别持续的UP-1。 和下调的基因。虽然这些技术很可能直接识别出一组基因 在受影响的网络中，我们之前的理论结果表明，主要的扰动 (癌症是其中之一)引起的表达变化远远超出了所涉及的途径。至关重要的是， 这些更远的变化将是高度可变的，取决于遗传背景，因此 预计不同个体之间的肿瘤表达谱有很大的不同。使用这个 假设我们提出了一种新的系统级癌症分析(SLAC)，它识别关键 基于表达可变性增加的基因，这反过来又提供了 发现与微环境相关的高度非直观的路径交互作用 乳腺癌进展的调控。通过结合多光子高分辨率 具有宽激发波长范围的显微镜，所建议的多色远红 像传统绿色荧光蛋白一样通用的荧光探针我们将推进深层组织细胞标记 以及体内肿瘤细胞动力学的成像。这种方法将使生命中的 在肿瘤研究中同时成像多达六种遗传编码的颜色。这反过来又会 提供了一种鉴别和随后分离多发转移的肿瘤细胞的方法 基于荧光颜色编码的表达模式的表型。通过将 多光子获得的肿瘤细胞迁移和扩散的行为和命运 通过对这些细胞的表达谱进行SLAC分析，我们将在单细胞水平进行成像 确定驱动肿瘤细胞行为的关键基因，如细胞迁移 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.