In Vivo Multiphoton Based Imaging of Complex Cancer Cell Behavior

描述(申请人提供)：最近的结果导致许多人提出了一个微环境依赖的模型，用于在原发肿瘤和靶器官中启动肿瘤细胞的迁移和传播行为，这种行为不是由基因突变稳定地指定的，并且在时间和空间上是瞬时的。这一观点被称为转移的微环境模型。这一模型的测试在一定程度上受到缺乏高分辨率活体显微镜方法和用于肿瘤深层组织成像的基因编码荧光探针的阻碍，这些方法和探针允许最终识别启动肿瘤细胞迁移和扩散的微环境。同样有问题的是对表达谱进行标准分析的局限性。癌症表达谱的标准分析涉及识别持续上调和下调的基因。虽然这些技术可能直接在受影响的网络中识别一组基因，但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，这些更远距离的变化将取决于遗传背景的高度可变，因此肿瘤的表达谱预计在个体之间会有很大的不同。利用这一假设，我们提出了一种新的癌症系统水平分析(SLAC)，它基于表达可变性的增加来识别关键基因，并反过来提供了发现与乳腺癌进展的微环境调节相关的高度非直观的途径相互作用的可能性。通过将具有宽激发波长范围的多光子高分辨率显微镜与所提出的与传统绿色荧光蛋白一样通用的多色远红荧光探针相结合，我们将推进深层次组织细胞标记和体内肿瘤细胞动力学的成像。这种方法将使在肿瘤研究中同时进行多达六种基因编码的颜色的活体成像成为可能。这反过来将提供一种基于荧光颜色编码的表达模式来区分和随后分离多种转移表型的肿瘤细胞的方法。通过在单细胞水平上通过多光子成像获得的肿瘤细胞的迁移和扩散的行为和命运与这些细胞的表达谱的SLAC分析相关联，我们将找出驱动肿瘤细胞行为的关键基因，如细胞迁移和转移。

DESCRIPTION (provided by applicant): 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.