Novel Approach to High-Throughput Identification and Characterization of Neoantigen-Specific T-Cell Receptors to Guide Immunotherapy Development.

高通量鉴定和表征新抗原特异性 T 细胞受体的新方法,以指导免疫疗法的开发。

基本信息

  • 批准号:
    10007685
  • 负责人:
  • 金额:
    $ 39.98万
  • 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
  • 起止时间:
    2020-06-15 至 2022-05-31
  • 项目状态:
    已结题

项目摘要

PROJECT SUMMARY Newly developed immunotherapies have shown great promise for the management and treatment of various types of cancer. Among these new strategies, the development of T-cell Receptor engineered T-cells (TCR T- cells) targeting tumor specific neoantigens has arisen as a promising approach to improve efficacy, decrease toxicity and overcome acquired resistance. However, the multiplicity of mutations in cancer and the lack of high- throughput methods to identify neoantigen-specific TCRs is preventing the wide implementation of TCR T-cells therapies. Flexomics is developing an integrated platform harnessing recent advances in single cell genomics, immunoassays and microfluidics for the high-throughput characterization of antigen-specific TCRs. Our proprietary approach is designed to identify T-cell activation in response to specific antigen exposure at single cell level for 100,000s T-cells while simultaneously capturing phenotypic and genotypic information in the form of expression of key marker genes and full-length TCR sequence identification. To demonstrate the feasibility of our method we propose to: (1) track functional responses from single T-cells to cognate antigen-exposure by measuring their cytokine secretion in our novel high-density picowell plate that allows us to co-capture 100,000s pairs of Antigen Presenting Cell (APC) / T-cell, (2) retrieve and link TCR sequence and expression for 20 phenotypic markers to each individual T-cell thanks to our unique barcoding system, (3) demonstrate end-to-end workflow and recapitulate previously discovered antigen-specific TCR sequence for a well characterized neoantigen. At the end of our Phase I grant, we will have demonstrated a concrete example of how our platform allows the screening and characterization of antigen-TCR interactions at unprecedented scale. We will also have all processes in place to start screening other neoantigens and further refine our workflow. Screening and discovery of neoantigen-specific T-cell response and TCR is critical to the future progress of cancer immunotherapies. Our technology has been developed specifically to support and accelerate the development of personalized treatments by providing a rapid and cost-effective method to identify immunogenic neoantigens and characterize their associated antigen-specific TCRs.
项目概要 新开发的免疫疗法在各种疾病的管理和治疗方面显示出巨大的前景 癌症的类型。在这些新策略中,T细胞受体工程化T细胞(TCR T- 细胞)靶向肿瘤特异性新抗原已成为一种有前途的方法,可以提高疗效,减少 毒性并克服获得性耐药性。然而,癌症突变的多样性以及高水平突变的缺乏 识别新抗原特异性 TCR 的通量方法阻碍了 TCR T 细胞的广泛应用 疗法。 Flexomics 正在开发一个综合平台,利用单细胞基因组学的最新进展, 用于抗原特异性 TCR 的高通量表征的免疫测定和微流体。我们的 专有方法旨在识别 T 细胞激活,以响应单次特定抗原暴露 100,000 个 T 细胞的细胞水平,同时以表格形式捕获表型和基因型信息 关键标记基因的表达和全长TCR序列鉴定。为证明可行性 我们建议的方法是:(1) 跟踪单个 T 细胞对同源抗原暴露的功能反应 在我们的新型高密度皮孔板中测量它们的细胞因子分泌,使我们能够共同捕获 100,000 个细胞因子 抗原呈递细胞 (APC)/T 细胞对,(2) 检索并链接 20 个的 TCR 序列和表达 得益于我们独特的条形码系统,每个 T 细胞的表型标记,(3) 展示端到端 工作流程并概括先前发现的抗原特异性 TCR 序列,以得到充分表征的 新抗原。在第一阶段资助结束时,我们将展示一个具体示例,说明我们的平台如何 允许以前所未有的规模筛选和表征抗原-TCR 相互作用。我们还将有 所有流程均已到位,开始筛选其他新抗原并进一步完善我们的工作流程。筛选和 新抗原特异性 T 细胞反应和 TCR 的发现对于癌症的未来进展至关重要 免疫疗法。我们的技术是专门为支持和加速发展而开发的 通过提供快速且经济高效的方法来识别免疫原性新抗原,实现个性化治疗 并表征其相关的抗原特异性 TCR。

项目成果

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Magali Soumillon其他文献

Magali Soumillon的其他文献

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{{ truncateString('Magali Soumillon', 18)}}的其他基金

Novel Approach to High-Throughput Identification and Characterization of Neoantigen-Specific T-Cell Receptors to Guide Immunotherapy Development.
高通量鉴定和表征新抗原特异性 T 细胞受体的新方法,以指导免疫疗法的开发。
  • 批准号:
    10652632
  • 财政年份:
    2020
  • 资助金额:
    $ 39.98万
  • 项目类别:
Novel Approach to High-Throughput Identification and Characterization of Neoantigen-Specific T-Cell Receptors to Guide Immunotherapy Development.
高通量鉴定和表征新抗原特异性 T 细胞受体的新方法,以指导免疫疗法的开发。
  • 批准号:
    10546726
  • 财政年份:
    2020
  • 资助金额:
    $ 39.98万
  • 项目类别:

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