MASS SPECTROMETRY SHARED RESOURCE

描述：（申请人的描述）癌症的一个主要科学挑战 生物学是在分子水平上鉴定和表征 各种肿瘤性疾病的细胞变化。成功的关键 这一奋进是开发和实施新的工具， 敏感的蛋白质鉴定和表征， 翻译修饰质谱（MS）的高灵敏度 成为此类研究的宝贵工具。拟议的主要目标 “NCI质谱共享资源蛋白质组学和蛋白质分析”是 来扩大和提升我们的质谱仪的容量和灵敏度 设施，并将最先进的MS技术应用于关键蛋白质 参与癌症研究的分析，加强癌症研究计划， 西奈山。 该共享资源的具体目标是： 1. 为NCI提供快速、经济、高质量的MS服务 以及西奈山和其他NCI的其他癌症研究人员， 资助调查人员在纽约市，以执行切割- 边缘研究，其中使用新的质谱技术， 解决重要的生物化学和生物医学问题。 2. 将我的研究实验室新开发的质谱技术转移到 NCI共享资源，扩大容量，升级 质谱技术的灵敏度，以协助国家癌症研究所资助， 其他癌症研究者。 3. 为了教育国家癌症研究所资助的研究人员，其他癌症导向的科学家， 和他们的工作人员在癌症生物学中使用MS进行蛋白质分析。

DESCRIPTION: (Applicant's Description) A major scientific challenge in cancer biology is the identification and characterization at molecular level of the cellular changes in various neoplastic diseases. Critical to the success of this endeavor is the development and implementation of new tools for rapid and sensitive protein identification and characterization of their post- translational modifications. High sensitivity of mass spectrometry (MS) has become an invaluable tool for such studies. The major goal of the proposed "NCI Mass Spectrometry Shared Resource for Proteomics and Protein Analysis" is to expand and upgrade the capacity and sensitivity of our mass spectrometry facility and to apply state-of-the-art MS technologies to critical protein analysis involved in cancer research, strengthening cancer research program at Mount Sinai. The specific aims of this Shared Resource are: 1. To provide rapid, cost-effective, and high-quality MS service for NCI and other cancer-oriented investigators at Mount Sinai and other NCI- funded investigators in the New York City in order to perform cutting- edge research in which new mass spectrometric technologies are used to solve important biochemical and biomedical problems. 2. To transfer newly developed MS technology from my research laboratory to the NCI Shared Resource and expand the capacity and upgrade the sensitivity of mass spectrometry techniques for assisting NCI-funded and other cancer-oriented investigators. 3. To educate NCI-funded investigators, other cancer-oriented scientists, and their staffs on using MS for protein analysis in cancer biology.