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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:
10660980
负责人:
Alexander R. Ivanov
金额:
$41.18万
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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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:
    10388993
  • 项目类别:
  • 资助金额:
    $1.26万
  • 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:
    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:
海外基金