An intra-vital metabolic microscope to reveal the mechanisms of radiation resistance in head and neck carcinomas

活体代谢显微镜揭示头颈癌的抗辐射机制

基本信息

  • 批准号:
    10271869
  • 负责人:
  • 金额:
    $ 30.4万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-03-01 至 2026-12-31
  • 项目状态:
    未结题

项目摘要

PROJECT SUMMARY Given the clinical importance of radio-resistance in head and neck squamous cell cancer (HNSCC), understanding how radio-resistant tumors rewire their metabolic pathways and vascular network to escape radiotherapy (RT) is critical towards developing strategies to eliminate residual tumor cells and/or prevent subsequent recurrence. Currently, no techniques are available to provide a systems level approach to image the major axes of metabolism and the associated vasculature at a spatial resolution that can elucidate the modulation of cancer cell metabolism or vascular reprogramming in vivo. Our technological goal is to create innovative solutions in microscopy, automated algorithms and experimental strategies to image tumor metabolism, vascular function and architecture at a spatial resolution that allows for visualization of primary tumors, residual disease and recurrence following RT to facilitate the understanding of tumor biology and function, assessment of recurrence risk and design of therapies to mitigate residual disease and/or recurrence altogether in pre-clinical models. Our technological approach fills an important gap that exists between in vitro cell studies and whole- body imaging, and is complementary to metabolomics and immunohistochemistry. The Specific Aims of this proposal are to develop a portable multi-parametric microscope that combines structured illumination microscopy and dark field microscopy in a re-emission geometry to image key metabolic and vascular endpoints simultaneously (Specific Aim 1); and use the technology with in vivo HNSCC orthotropic models to test the novel hypothesis that RT-induced hypoxia-inducible factors (HIF-1α and HIF-2α) expression and subsequent changes in metabolism/vasculature underlie HNSCC radio-resistance (Specific Aim 2). This proposal will set the foundation for translating our technology to patient-derived xenograft models that have been shown to faithfully recapitulate many of the micro-environmental features of patient tumors, allowing us to move our technique forward towards translational pharmaceutical research.
项目总结 鉴于头颈部鳞状细胞癌(HNSCC)放射抵抗的临床重要性, 了解放射耐药肿瘤如何重新连接代谢途径和血管网络以逃脱 放射治疗(RT)对于制定消除残留肿瘤细胞和/或预防的策略至关重要。 随后复发。目前,还没有可用的技术来提供系统级的方法来映像 新陈代谢的主轴和相关的血管系统在空间分辨率上可以解释这种调节 体内癌细胞新陈代谢或血管重编程的研究。我们的技术目标是创造创新 在显微镜、自动化算法和实验策略方面的解决方案,以成像肿瘤代谢、血管 空间分辨率的功能和架构,允许可视化原发肿瘤、残留疾病 放射治疗后的复发,以促进对肿瘤生物学和功能的了解,评估 临床前完全减轻残留疾病和/或复发的复发风险和治疗设计 模特们。我们的技术方法填补了体外细胞研究和整体细胞研究之间存在的一个重要空白。 身体成像,是对代谢组学和免疫组织化学的补充。这样做的具体目的是 建议开发一种结合结构照明显微镜的便携式多参数显微镜 和暗视野显微镜在再发射几何成像关键代谢和血管终点 同时(特定目标1);并使用体内HNSCC正交各向异性模型来测试 RT诱导低氧诱导因子(HIF-1α和HIF-2α)表达及随后的新假说 代谢/血管系统的改变是HNSCC放射抵抗的基础(特定目标2)。这项提案将设立 将我们的技术转化为患者衍生的异种移植模型的基础已被证明 忠实地概括了患者肿瘤的许多微环境特征,使我们能够移动我们的 技术向转化型药学研究迈进。

项目成果

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Caigang Zhu其他文献

Caigang Zhu的其他文献

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{{ truncateString('Caigang Zhu', 18)}}的其他基金

Point-of-care optical spectroscopy platform and novel ratio-metric algorithms for rapid and systematic functional characterization of biological models in vivo
即时光学光谱平台和新颖的比率度量算法,可快速、系统地表征体内生物模型的功能
  • 批准号:
    10655174
  • 财政年份:
    2023
  • 资助金额:
    $ 30.4万
  • 项目类别:
Non-destructive optical spectroscopic assay for high-throughput metabolic characterization of in vitro cell models and patient-derived organoids
用于体外细胞模型和患者来源类器官高通量代谢表征的无损光学光谱测定
  • 批准号:
    10348268
  • 财政年份:
    2022
  • 资助金额:
    $ 30.4万
  • 项目类别:
Non-destructive optical spectroscopic assay for high-throughput metabolic characterization of in vitro cell models and patient-derived organoids
用于体外细胞模型和患者来源类器官高通量代谢表征的无损光学光谱测定
  • 批准号:
    10666355
  • 财政年份:
    2022
  • 资助金额:
    $ 30.4万
  • 项目类别:
An intra-vital metabolic microscope to reveal the mechanisms of radiation resistance in head and neck carcinomas
活体代谢显微镜揭示头颈癌的抗辐射机制
  • 批准号:
    10573171
  • 财政年份:
    2017
  • 资助金额:
    $ 30.4万
  • 项目类别:

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