In Vivo Multiphoton Based Imaging of Complex Cancer Cell Behavior

基于体内多光子的复杂癌细胞行为成像

• 批准号: 8231689
• 负责人: Vladislav Verkhusha
• 金额: $ 79.96万
• 依托单位: ALBERT EINSTEIN COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-21 至 2016-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8231689
• 关键词: Advanced Development; Affect; Animals; Automobile Driving; Behavior; Cells; Collection; Color; Complex; Data; Distant; Fluorescent Probes; Gene Mutation; Genes; Genetic; Hypoxia; Image; Immunoglobulin Somatic Hypermutation; Individual; Label; Light; Longevity; Lung; Malignant Neoplasms; Mammary Neoplasms; Maps; Methodology; Methods; Microscopy; Modeling; Molecular Evolution; Molecular Profiling; Mutagenesis; N-terminal; Neoplasm Metastasis; Oranges; Organ; Pathway interactions; Pattern; Phenotype; Photons; Play; Population; Primary Neoplasm; Protein Engineering; Proteins; Regulation; Resolution; Role; Screening procedure; Set protein; Specific qualifier value; Staging; Stress; System; Systems Biology; Techniques; Technology; Testing; Theoretical Studies; Time; Tissues; Variant; base; cancer cell; cell behavior; cell motility; cytotoxicity; design; in vivo; insight; malignant breast neoplasm; neoplastic cell; new technology; novel; tumor; tumor progression; two-photon

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.

描述（由申请人提供）：最近的结果导致许多人提出了一种依赖于微环境的模型，用于在原发性肿瘤和靶器官内启动迁移和播散性肿瘤细胞行为，这种行为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。该模型的测试在一定程度上受到了缺乏高分辨率体内显微镜方法和用于肿瘤深组织成像的基因编码荧光探针的阻碍，这些探针可以明确识别启动迁移和传播肿瘤细胞表型所涉及的微环境。同样存在问题的是表达谱标准分析的局限性。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识别受影响网络内的基因组，但我们之前的理论结果表明，主要扰动（其中癌症就是其中之一）导致的表达变化远远超出了所涉及的途径。至关重要的是，这些更遥远的变化将根据遗传背景而变化很大，因此预计个体之间的肿瘤表达谱会有很大差异。利用这一假设，我们提出了一种新的癌症系统级分析（SLAC），它根据表达变异性的增加来识别关键基因，进而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途径相互作用的可能性。通过将具有宽范围激发波长的多光子高分辨率显微镜与所提出的与传统 GFP 一样通用的多色远红荧光探针相结合，我们将推进体内肿瘤细胞动力学的深层组织细胞标记和成像。这种方法将使肿瘤研究中同时进行多达六种基因编码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表达模式区分并随后分离多种转移表型的肿瘤细胞的方法。通过将单细胞水平的多光子成像获得的迁移和传播肿瘤细胞的行为和命运与这些细胞表达谱的 SLAC 分析相关联，我们将确定驱动涉及转移（例如细胞迁移和传播）的肿瘤细胞行为的关键基因。