Novel Methods to localize protein-protein interactions in fixed cells and tissues

定位固定细胞和组织中蛋白质-蛋白质相互作用的新方法

• 批准号: 7613514
• 负责人: Seema Agarwal
• 金额: $ 22.34万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-11 至 2012-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7613514
• 关键词: Basic Science; Biological Markers; Cells; DNA; Development; Diagnostic; Engineering; Evolution; Goals; Human; In Situ; In Vitro; Individual; Location; Malignant Neoplasms; Measurement; Measures; Metabolic; Methods; Molecular; Monoclonal Antibodies; Outcome; Patients; Pharmaceutical Preparations; Phenotype; Play; Process; Proteins; Role; Sampling; Solutions; Specimen; Speed; Testing; Tissue Sample; Tissues; carcinogenesis; cell fixing; cell type; improved; neoplastic cell; novel; prognostic; protein expression; protein protein interaction; response; tumor

DESCRIPTION (provided by applicant): Although analyses of DNA, RNA, and protein expression can elucidate the phenotype of a cell, ultimately it is the interactions between proteins that determine metabolic function. Understanding protein-protein interactions is vital to the study of cancer, and the aim of most new chemotherapeutic drugs is to disrupt aberrant interactions. Recent advances in the quantification of tumor biomarkers in patient samples show great promise in predicting patient outcome and response to treatment. However, there is no good way to assess the co-localization of proteins in tissue samples. The successful evolution of bio-specific therapies and associated pharmaco-diagnostics may ultimately require quantitative measures of protein-protein interactions within each patient's tumor. From the basic science perspective, new methods in co-localizing proteins in tumor samples will advance the understanding of carcinogenesis and the subsequent development of targeted therapies. We hypothesize that engineering robust methods for assessing protein-protein interactions in human tumor samples will significantly improve the analysis of patient specimens and ultimately speed the development of targeted patient-specific therapies. Protein interactions are the gears which drive cells. In tumor cells, many of these processes are corrupted. Today, we can study the expression of individual proteins in patient tumor samples; however, we cannot look at the interactions between these proteins in patient tumors. Our goal is to create new methods for recognizing and studying such interactions. We hope that these methods will improve our understanding of cancer and provide means to assess which tumors will respond to specific therapies.

描述（由申请人提供）：尽管DNA、RNA和蛋白质表达的分析可以阐明细胞的表型，但最终是蛋白质之间的相互作用决定代谢功能。了解蛋白质-蛋白质相互作用对癌症的研究至关重要，大多数新的化疗药物的目的是破坏异常的相互作用。患者样本中肿瘤生物标志物定量的最新进展在预测患者结局和治疗反应方面显示出巨大的前景。然而，没有好的方法来评估组织样品中蛋白质的共定位。生物特异性治疗和相关药物诊断的成功发展可能最终需要定量测量每个患者肿瘤内的蛋白质-蛋白质相互作用。从基础科学的角度来看，在肿瘤样品中共定位蛋白质的新方法将促进对癌症发生的理解和随后的靶向治疗的发展。我们假设，设计用于评估人类肿瘤样本中蛋白质-蛋白质相互作用的强大方法将显着改善患者样本的分析，并最终加速靶向患者特异性治疗的发展。蛋白质相互作用是驱动细胞的齿轮。在肿瘤细胞中，许多这些过程都被破坏了。今天，我们可以研究单个蛋白质在患者肿瘤样本中的表达;然而，我们不能研究这些蛋白质在患者肿瘤中的相互作用。我们的目标是创造新的方法来识别和研究这种相互作用。我们希望这些方法将提高我们对癌症的理解，并提供评估哪些肿瘤对特定疗法有反应的方法。