Laser Capture For Macromolecular Analysis Of Development

激光捕获用于大分子分析的开发

• 批准号: 7201693
• 负责人: Robert F Bonner
• 金额: --
• 依托单位: EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7201693
• 关键词: biomarker; cell population study; diagnostic tests; gene expression; human tissue; laboratory mouse; laser capture microdissection; macromolecule; molecular pathology; technology /technique development

Integrative molecular biology requires understanding interactions of large numbers of pathways. Similarly molecular medicine increasingly relies on complex macromolecular diagnostics to guide therapeutic choices. A fundamental argument for laser capture microdissection (LCM) of tissues is that without separation of specific cell populations from complex tissues, we will miss critical control functions of thousands of regulated transcription factors, cell regulators, and receptors that are expressed at low copy number. Without detecting changes in many of these critical effectors, the integrative understanding of tissue function and pathology will not proceed effectively. In complex tissues - particularly among pathological variations - it is exceptionally difficult to measure the majority of molecules that are at low copy number per cell without first isolating specific cell populations. For example, among Cancer Genome Anatomy Project partially sequenced cDNA libraries, only LCM-dissected ovarian cancer cDNA libraries are exceptionally informative about ovarian cancer biology. After LCM isolation of pure target cells, the library construction protocol used had selectively amplified a small number of rarer transcripts to the level that allowed statistical comparison of their expression between highly purified low and high malignant potential cancer cells. Many of these ?overamplified? genes overexpressed in the high malignant potential compared to low malignant potential ovarian cancer libraries are known to be oncogenes, and genes associated with invasion and metastatic processes in other tissues. The LCM techniques that we started developing ten years ago are now widely used in molecular analysis of genetics and gene expression changes within target cells within complex tissues. However, in global proteomic and lipid studies without molecular amplification methods, the quantity of isolated cells sufficient to perform accurate characterization of less abundant species is problematic as the microscopic visualization, targeting, and isolation in laser microdissection has a maximal rate of about 1 to 20 cells per second depending on the cells? microscopic distribution within the tissues. Recently, in collaboration with NCI and CIT, we invented and are now refining an automatic ?target-directed microtransfer? technique based on macromolecule-specific labeling of cells not requiring user visualization or microscopic targeting and capable of much higher throughput rates. This technique (patent pending) is built on our solid physical understanding of thermoplastic microtransfer and uses a much simpler device and transfer films than commercial laser microdissection instruments. Our current prototype is capable of isolating all specifically immunolabeled cells or organelles within 1 cm2 region of a standard immunostained tissue section in about five seconds, which corresponds to specific separation from approximately 50,000 cells per second. With this technique we can exceed the cell separation rates of standard technologies such as fluorescence-activated cell sorting while preserving our ability to harvest directly from standard sections of complex tissues. This rapid, automated microtransfer method has improved spatial resolution (~1 micron) and is consequently particularly well-suited to isolate highly dispersed, specific cell populations (e.g., stem cells or only those neurons in the supra-optic nucleus that express vasopressin) or specific organelles (e.g., neuronal nuclei in the brain). The spatial relationships (morphology) among the specific cells in the tissue are preserved on the transfer film. As this technology becomes more robust, we will seek to integrate the microtransfer with molecular profiling of specific cells within tissues, including routine proteomic and lipidomic analyses, particularly for the large number of less abundant molecular species. If microdissection and molecular analysis can be made clinically practical, the expression levels of sets of approximately 20 to 100 critical, stage-specific disease markers within a selected cell population might provide reliable diagnosis and intermediate endpoints of response to molecular therapies in individual patients. Our analysis of large gene expression and protein databases suggests that a significant fraction of all genes is expressed in any specific cell type and that the levels of gene products universally exhibit a highly skewed power-law distribution similar to those characterizing many other complex systems. We have developed mathematical models for the evolution of such distributions that predict the observed distributions of genes, protein domains, and gene expression observed in species of increasing biological complexity. We foresee an evolution of molecular diagnosis from one based on the qualitative or quantitative analysis of a few key biomarker macromolecules to one in which special clustering algorithms analyze complex multivariate databases. Such analyses should permit a more complete identification of highly correlated clinical cases and allow us to characterize their response to molecular therapies specifically designed to prevent progression. We are attempting to develop new approaches for better integration of our thermoplastic microtransfer methods of microdissection with downstream macromolecular analysis to permit more routine and simpler multiplex molecular diagnostics. A key feature is using the polymer matrix in which target cells are embedded for affinity purification and then for direct optical detection within the transparent polymer. We are using a variety of microscopy techniques in our lab to quantitatively characterize protocols for incorporating affinity nanoparticles in the tissue and polymer matrix. In the longer term, we foresee using in situ optical labels to quantify the spatial distributions of specific molecules captured within the microtransfer and retained following simple purification steps. Coupling the robust and simple automatic microdissection with rapid purification and detection of species might provide unique abilities to follow macromolecular changes in normal tissue development and in pathologies such as cancer progression within prostate, colon, breast, lung, and ovary tissues. In continuing collaborations with NCI, we have developed standard procedures for the isolation of normal and pathological cells from clinical specimens. We have used our models of the statistics of expression levels in cell populations to identify genes differentially expressed in cancer progression. With future integration of microdissection and macromolecular analysis, we believe the critical role for many less abundantly expressed genes in determining normal function and pathological changes will be more easily studied and integrated into molecular diagnostics and selection of clinical therapies.

综合分子生物学需要了解大量途径的相互作用。同样，分子医学越来越依赖复杂的大分子诊断来指导治疗选择。激光捕获微分解（LCM）的基本论点是，如果不将特定细胞群体与复杂组织分开，我们将错过以低拷贝数表达的数千个受调节转录因子，细胞调节剂和受体的关键控制功能。如果不检测许多关键效应子的变化，对组织功能和病理学的综合理解将无法有效地进行。在复杂的组织中 - 尤其是在病理变化中 - 在没有先分离特定细胞群体的情况下，测量每个细胞拷贝数低的分子的大多数分子非常困难。例如，在癌症基因组解剖项目中部分测序的cDNA文库中，只有LCM截止的卵巢癌cDNA库对于卵巢癌生物学的信息非常丰富。 LCM分离纯目标细胞后，所使用的库构建方案选择性地将少数稀有的转录物放到了水平上，从而可以对其在高度纯化的低恶性和高恶性势癌细胞之间的表达进行统计比较。其中许多？与低恶性潜在的卵巢癌库相比，高恶性潜力过表达的基因已知是癌基因的，并且与其他组织中的侵袭和转移过程有关。 我们十年前开始开发的LCM技术现已广泛用于遗传学和基因表达在复杂组织内目标细胞内的变化。然而，在没有分子扩增方法的全球蛋白质组学和脂质研究中，由于显微镜可视化，靶向和分离的隔离细胞的数量足以对较少丰富的物种进行准确表征，这是有问题的。组织内的微观分布。最近，我们与NCI和CIT合作，我们发明了并正在完善自动目标定向的微转移？基于细胞大分子特异性标记的技术，不需要用户可视化或微观靶向，并且能够具有更高的吞吐率。该技术（专利待处理）建立在我们对热塑性微转移的牢固的物理理解上，并且使用了比商用激光微解剖仪器更简单的设备和传输膜。我们的当前原型能够在大约五秒钟内分离出标准免疫染色组织截面的1 CM2区域内的所有特定免疫标记的细胞或细胞器，这对应于每秒约50,000个细胞的特异性分离。通过这种技术，我们可以超过标准技术的细胞分离速率，例如荧光激活的细胞分选，同时保留我们直接从复杂组织的标准部分收获的能力。这种快速，自动化的微转移方法具有改进的空间分辨率（〜1微米），因此特别非常适合隔离高度分散的特定细胞群（例如，干细胞或仅表达加压素）或特定特定细胞器或特定细胞器（例如，神经元（例如神经元）的上型核中的神经元中的神经元（例如，神经元）。组织中特定细胞之间的空间关系（形态）保留在转移膜上。随着该技术变得越来越强大，我们将寻求将微转移与组织中特定细胞的分子分析相结合，包括常规蛋白质组学和脂肪组分析，尤其是对于大量较少的分子物种。 如果可以在临床上进行显微解剖和分子分析，则在选定的细胞群中，大约20至100个关键阶段特异性疾病标志物的表达水平可能会提供可靠的诊断和中间端点对个别患者分子疗法的反应。我们对大基因表达和蛋白质数据库的分析表明，所有基因的显着部分均在任何特定的细胞类型中表达，并且基因产物的水平普遍表现出与表征许多其他复杂系统相似的高度偏斜的幂律分布。我们已经开发了数学模型，用于预测基因，蛋白质结构域和基因表达的分布在增加生物学复杂性的物种中。我们预见了分子诊断的演变，该分子诊断是基于对几种关键生物标志物大分子的定性或定量分析，其中特殊聚类算法分析复杂的多变量数据库。这样的分析应允许对高度相关的临床病例进行更完整的识别，并允许我们表征它们对专门为预防进展而设计的分子疗法的反应。 我们正在尝试开发新方法，以更好地整合微型微型转移方法的微分解方法，并通过下游大分子分析来允许更多常规和更简单的多重分子诊断。一个关键特征是使用聚合物矩阵，其中靶细胞嵌入亲和力纯化，然后在透明聚合物内进行直接光学检测。我们在实验室中使用多种显微镜技术来定量表征将亲和力纳米颗粒掺入组织和聚合物基质中的方案。从长远来看，我们预见到使用原位光学标记来量化微转移中捕获的特定分子的空间分布，并按照简单的纯化步骤保留。耦合强大而简单的自动显微解剖与物种的快速纯化和检测可能会提供独特的能力，以遵循正常组织发育的大分子变化以及前列腺，结肠，乳腺癌，肺和卵巢组织中癌症进展的病理学的变化。在与NCI的持续合作中，我们开发了从临床标本中分离正常和病理细胞的标准程序。我们已经使用了细胞群体表达水平的统计模型来鉴定在癌症进展中差异表达的基因。随着微分解和大分子分析的未来整合，我们认为许多不太表达基因在确定正常功能和病理变化中的关键作用将更容易研究并整合到分子诊断和临床疗法的选择中。