Protein Localization: Multi-aperture Near-Field Optics

描述(由申请人提供)： 这项研究的目标是开发一种新形式的显微镜， 表面等离子体增强显微镜(SPEM)。SPEM达到35 nm的分辨率 旨在用于多种蛋白质在细胞中的定位和 确定患者的分子签名？肿瘤。SPEM系统生成 细胞内蛋白质位置的数据库，参照的是 细胞特征(例如，细胞膜和核膜、细胞器)。SPEM可以是 用于基于蛋白质表达识别癌症的分子特征 级别和位置。随着时间的推移，预计SPEM图像的数据库 将被组装起来，作为癌症诊断的参考 在分子水平上。SPEM被设计为无缝集成到 临床病理实验室。实施SPEM所需的步骤 分析是：(1)对玻片进行染色(2)病理学家阅读玻片并 标记要进行分子分析的细胞(使用数字坐标系 结合到SPEM显微镜中)是理想的(3)SPEM 属性自动生成本地化和表达级别数据。 标记的细胞，以及(4)病理学家结合 现有的免疫组织化学和形态数据来确定 病人？预测预后，选择合适的治疗方法。在R21研究中 系统的光学性能将被表征，并且 将演示石蜡包埋组织样本的适用性。在……里面 将开发全显微镜R33研究并用于生成 组织中多个蛋白质的蛋白质定位和表达数据 样本。

DESCRIPTION (provided by applicant): The objective for this research is to develop a new form of microscopy, Surface Plasmon Enhanced Microscopy (SPEM). SPEM achieves resolution of 35 nm and is intended to be used for localization of multiple proteins in cells and determine molecular signatures of patients? tumors. The SPEM system generates a database of protein locations within a cell referenced to the position of cellular features (e.g., cell and nuclear membranes, organelles). SPEM can be used to identify molecular signatures of cancer based on protein expression levels and locations. Over time it is expected that a database of SPEM images will be assembled that will serve as a reference for the diagnosis of cancer at the molecular level. SPEM has been designed to seamlessly integrate into the clinical pathology laboratory. The steps required to implement a SPEM analysis are: (1) stain the slide (2) the pathologist reads the slide and marks cells for which a molecular analysis (using a digital coordinate system that is incorporated into the SPEM microscope) is desired (3) SPEM automatically generates the localization and expression level data for the marked cells, and (4) the pathologist analyzes the results in conjunction with the existing immunohistochemical and morphological data to determine the patients? prognoses and select the appropriate therapy. In the R21 research the optical performance of the system will be characterized and the applicability to paraffin-embedded tissue specimens will be demonstrated. In the R33 research the full microscope will be develop and used to generate protein localization and expression data for multiple proteins in a tissue sample.