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: 8336838
• 负责人: Vladislav Verkhusha
• 金额: $ 76.6万
• 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/8336838
• 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

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.

项目摘要 最近的结果使许多人提出了一种依赖于微环境的模型来启动 原发肿瘤和靶标内的迁移和播散性肿瘤细胞行为 基因突变不稳定且在时间和空间上短暂的器官。 这种观点被称为转移的微环境模型。该模型的测试有 部分由于缺乏高分辨率体内显微镜方法而受到阻碍 用于肿瘤深部组织成像的基因编码荧光探针，可以确定 识别参与启动迁移和传播的微环境 肿瘤细胞表型。同样存在问题的是标准表达分析的局限性 配置文件。癌症表达谱的标准分析涉及识别一致的上调 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，我们之前的理论结果表明，主要的扰动 （癌症就是其中之一）导致表达变化远远超出所涉及的途径。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有很大不同。使用这个 假设我们提出了一种新的癌症系统级分析（SLAC），它确定了关键的 基于表达变异性增加的基因，这反过来又提供了可能性 发现与微环境相关的高度非直观的途径相互作用 乳腺癌进展的调节。通过结合多光子高分辨率 具有宽范围激发波长的显微镜，具有所提出的多色远红光 荧光探针与传统 GFP 一样通用，我们将推进深层组织细胞标记 和体内肿瘤细胞动力学成像。这种方法将使活体内 在肿瘤研究中同时对多达六种基因编码颜色进行成像。这反过来又将 提供了一种区分并随后分离多发性转移瘤细胞的方法 基于荧光颜色编码表达模式的表型。通过关联 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，在单细胞水平上进行成像，我们将 识别驱动涉及转移（例如细胞迁移）的肿瘤细胞行为的关键基因 和传播。