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Robust ultra-high sensitivity proteomic technologies for limited samples

Robust ultra-high sensitivity proteomic technologies for limited samples
适用于有限样品的稳健超高灵敏度蛋白质组技术
批准号:
10388993
负责人:
Alexander R. Ivanov
金额:
$1.26万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-07-01 至 2025-06-30

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中文摘要
翻译
项目摘要 大多数高度多样化的生物过程是通过蛋白质,蛋白质翻译后 修饰/蛋白质形式,蛋白质相互作用,PI(例如,蛋白质-蛋白质,PPI,蛋白质-配体,PLI),和 这种相互作用的丰度、活性、功能和完整性的异常可导致严重的疾病, 包括癌症此外,通过新的靶向疗法破坏这些基于蛋白质的特征, 可以是个体化治疗方法中对这些药物反应的重要生物标志物。临床 生物标本的数量往往有限,这极大地阻碍了 诊断、治疗开发和生物医学研究。显微活检和液体活检含有罕见的 细胞群如循环肿瘤细胞、造血干细胞(HSC)和免疫细胞可 仅包含几千或几百个细胞并且是异质的。传统技术研究 蛋白质组学谱、蛋白质形式、蛋白质复合物和PPI(例如,常规蛋白质组学、核磁共振、X射线 晶体学、酵母双杂交筛选和免疫亲和纯化(IP),然后质谱 (MS))不能容易地用于分析小细胞群、显微镜临床样品和 这主要是由于灵敏度的限制。因此,许多生物学和临床相关研究 由于缺乏这种低水平样品的技术,因此没有进行。在此,我们建议 开发分析平台,以便能够对稀缺样品进行高灵敏度分析, 蛋白酶体、完整蛋白酶体和天然复合物。这就要求小说的发展 样品制备方法,超低流量液相分离与MS接口,MS数据 采集和数据分析。开发这种新的方法来彻底分析微尺度样品 并将其集成到创新的“即插即用”自动化平台中, 通过MS表征完整的蛋白质型、蛋白质复合物和PTM对于获得 对疾病分子机制的生物学见解和治疗靶点的发现, 用于诊断和预后目的的生物标志物。开发的平台将使用良好的- 控制模型系统,并应用于最临床相关的设置,以检查(1)模型系统, 细胞分化和活化;(2)转录因子STAT 3的相互作用和生物学作用 其在绝大多数卵巢癌细胞系和原代样品中异常活化;和(2) MHC相关的促凋亡肽。
英文摘要
PROJECT SUMMARY The majority of highly diverse biological processes are enabled through proteins, protein post-translational modifications/proteoforms, protein interactions, PIs (e.g., protein-protein, PPIs, protein- ligand, PLIs), and aberrations of abundances, activities, functions, and integrity of such interactions can lead to severe diseases, including cancer. Furthermore, disruption of these protein-based characteristics by novel targeted therapies can be an important biomarker for the response to these drugs in personalized medicine approaches. Clinical and biological specimens are often available in limited amounts, which greatly hampers the progress in diagnostics, therapy development, and biomedical research. Microbiopsy and liquid biopsies containing rare cell populations such as circulating tumor cells, hematopoietic stem cells (HSCs) and immune cells may contain only low thousands or hundreds of cells and be heterogeneous. Traditional techniques to study proteomic profiles, proteoforms, protein complexes, and PPIs (e.g., conventional proteomics, NMR, X-ray crystallography, yeast two-hybrid screening and immunoaffinity purification (IP) followed by mass spectrometry (MS)) cannot be readily used for the analysis of small cell populations, microscopic clinical samples and individual cells mainly due to limitations in sensitivity. Therefore, many biological and clinically relevant studies are not undertaken because of the lack of technology for such low level samples. Here, we propose to develop analytical platforms that will enable high sensitivity analysis of scarce samples at the level of digests, intact proteoforms, and native complexes. This task will demand the development of novel approaches in sample preparation, ulra-low flow liquid phase separations interfaced with MS, MS data acquisition, and data analysis. Developing such novel methods for thorough profiling of microscale samples and integrating them in innovative “plug-and-play” automated platforms capable of efficient and high sensitivity characterization of intact proteoforms, protein complexes and PTMs by MS will be highly desirable for gaining biological insights into molecular mechanisms of the disease and discovery of therapeutic targets and biomarkers for diagnostic and prognostic purposes. The developed platforms will be evaluated using well- controlled model systems and applied in the most clinically relevant settings to examine (1) model systems for cell differentiation and activation; (2) the interactome and biological role of STAT3, the transcription factor which is aberrantly activated in the vast majority of ovarian cancer cell lines and primary samples; and (2) MHC-associated neontigenic peptides.
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Robust ultra-high sensitivity proteomic technologies for limited samples
  • 批准号:
    10202666
  • 项目类别:
  • 资助金额:
    $41.18万
  • 财政年份:
    2020
  • 负责人:
    Alexander R. Ivanov
  • 依托单位:
Robust ultra-high sensitivity proteomic technologies for limited samples
  • 批准号:
    10448500
  • 项目类别:
  • 资助金额:
    $41.18万
  • 财政年份:
    2020
  • 负责人:
    Alexander R. Ivanov
  • 依托单位:
Robust ultra-high sensitivity proteomic technologies for limited samples
  • 批准号:
    10580146
  • 项目类别:
  • 资助金额:
    $24.1万
  • 财政年份:
    2020
  • 负责人:
    Alexander R. Ivanov
  • 依托单位:
Robust ultra-high sensitivity proteomic technologies for limited samples
  • 批准号:
    10660980
  • 项目类别:
  • 资助金额:
    $41.18万
  • 财政年份:
    2020
  • 负责人:
    Alexander R. Ivanov
  • 依托单位:
海外基金