Integrators of Metastatic Potential

转移潜能积分器

基本信息

  • 批准号:
    10599845
  • 负责人:
  • 金额:
    $ 17.97万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-03-01 至 2025-02-28
  • 项目状态:
    未结题

项目摘要

ABSTRACT One key goal of the NCI Precision Medicine Initiative focuses on development of new tools to tailor cancer therapy to disease status and risk of metastasis-- Patients at high risk for metastatic disease would receive aggressive, frequently molecularly-targeted therapy, whereas those with low risk for metastatic disease would be treated with appropriate local therapies, sparing them toxic side effects of therapy while maintaining high likelihood for cure. One of the main challenges preventing implementation of precision medicine for metastasis is limited understanding of signaling molecules and pathways that confer high metastatic potential to a small subset of cancer cells within a larger, heterogeneous tumor. Consequently, molecular imaging of metastatic ‘potential’ is an unvanquished challenge. To engineer biosensors that can detect and measure metastatic 'potential' of single living cancer cells, we carried out a comprehensive analysis of the pan-cancer phosphoproteome to search for actin-remodelers required for cell migration, that are enriched in cancers, but excluded in normal cells. Only one phosphoprotein emerged, tyr-phosphorylated CCDC88A (GIV/Girdin), a bona-fide metastasis-related protein across a variety of solid tumors. We designed multi-modular biosensors that are partly derived from GIV, and because GIV integrates pro-metastatic signaling by multiple oncogenic receptors, we named them ‘Integrator-of-Metastatic- Potential (IMP)'. It is hypothesized that single cell imaging of GIV activation using IMPs, rather than simply levels of GIV expression, will detect the subset of metastasis-initiating cells that must be eliminated to prevent metastatic disease. Preliminary experiments demonstrate that IMPs captured the heterogeneity of metastatic potential within primary lung and breast tumors at steady-state, detected those few cells which have acquired the highest metastatic potential and tracked their enrichment during metastasis. These findings provide proof- of-concept that IMPs can measure the diversity and plasticity of metastatic potential of tumor cells in a sensitive and unbiased way. Going forward, IMPs will be optimized and validated for use as tools for molecular imaging of metastasis-initiating cells via 3 goals: 1) Image metastatic potential of single breast cancer cells; 2) Image GIV activation as a marker of Metastasis Initiating Cells (MICs); and 3) Image metastatic potential in patient- derived xenografts. To accomplish these goals, this multi PD/PI proposal capitalizes on synergy of non- overlapping expertise of two PIs and two animal model systems (zebrafish and mice), in-depth biology of a novel signaling pathway, and cutting-edge technology of in vivo imaging. Success in detecting metastasis-initiating cells will be a transformative advance for cancer cell biology. It will pave the path for the development of personalized screening platforms to assess the effectiveness of anti- cancer drugs in killing the highly tumorigenic cells within any given tumor, and ultimately enable clinical implementation of precision cancer therapy to improve treatment and quality of life for patients.
摘要 NCI精准医学倡议的一个关键目标是开发新的工具来定制癌症 对疾病状态和转移风险的治疗--转移疾病的高危患者将接受 积极的,经常是分子靶向的治疗,而那些转移疾病风险较低的人会 接受适当的局部治疗,避免治疗的毒副作用,同时保持较高的 治愈的可能性。阻止实施精准转移医学的主要挑战之一 对赋予小细胞肺癌高转移潜能的信号分子和信号通路的了解有限 一个较大的、异质肿瘤内的癌细胞亚群。因此,转移瘤的分子成像 “潜力”是一个不可战胜的挑战。 为了设计生物传感器,可以检测和测量单个活癌细胞的转移潜力, 我们对泛癌磷酸蛋白质组进行了全面的分析,以寻找肌动蛋白重构体。 是细胞迁移所必需的,在癌症中丰富,但在正常细胞中被排除在外。只有一种磷蛋白 出现了酪氨酸磷酸化的CCDC88A(GIV/Girdin),它是一种真正的转移相关蛋白,跨多种 实体瘤。我们设计了部分源自GIV的多模块生物传感器,因为GIV 整合了多个癌基因受体的促转移信号,我们将其命名为转移整合因子- 潜力(IMP)‘。假设使用IMPS的GIV激活的单细胞成像,而不是简单地 GIV表达水平,将检测必须消除的启动转移的细胞子集,以防止 转移性疾病。初步实验表明,IMPS捕捉到了转移瘤的异质性。 原发肺癌和乳腺肿瘤内的潜能处于稳定状态,检测到那些已经获得的少数细胞 最高的转移潜能,并跟踪它们在转移过程中的丰富。这些发现提供了证据-- 概念上,IMPS可以测量肿瘤细胞转移潜能的多样性和可塑性 和不偏不倚的方式。展望未来,IMPS将作为分子成像工具进行优化和验证。 通过3个目标研究转移启动细胞:1)单个乳腺癌细胞的转移潜能的图像;2)图像 GIV激活作为转移起始细胞(MICs)的标志;以及3)患者的图像转移潜能- 衍生异种移植物。为了实现这些目标,该多PD/PI提案充分利用了非 两个PI和两个动物模型系统(斑马鱼和老鼠)的交叉专业知识,深入研究一种新的生物学 信号通路,以及体内成像的前沿技术。 成功检测到启动转移的细胞将是癌细胞生物学的一个变革性进展。 这将为个性化筛查平台的发展铺平道路,以评估抗击艾滋病的效果 抗癌药物可以杀死任何特定肿瘤内的高致瘤性细胞,并最终使临床 实施癌症精准治疗,提高患者治疗和生活质量。

项目成果

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Pradipta Ghosh其他文献

Pradipta Ghosh的其他文献

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{{ truncateString('Pradipta Ghosh', 18)}}的其他基金

Integrators of Metastatic Potential
转移潜能积分器
  • 批准号:
    10372682
  • 财政年份:
    2021
  • 资助金额:
    $ 17.97万
  • 项目类别:
Precision therapeutics of inflammatory bowel disease guided by Boolean logic
布尔逻辑指导的炎症性肠病精准治疗
  • 批准号:
    10709716
  • 财政年份:
    2020
  • 资助金额:
    $ 17.97万
  • 项目类别:
Macrophage Polarization in Response to Infections and Inflammation
巨噬细胞极化对感染和炎症的反应
  • 批准号:
    10685988
  • 财政年份:
    2020
  • 资助金额:
    $ 17.97万
  • 项目类别:
Macrophage Polarization in Response to Infections and Inflammation
巨噬细胞极化对感染和炎症的反应
  • 批准号:
    10463749
  • 财政年份:
    2020
  • 资助金额:
    $ 17.97万
  • 项目类别:
Modulation of Macrophage Polarization by Heterotrimeric G proteins: Implications of Gastrointestinal Inflammation
异源三聚体 G 蛋白对巨噬细胞极化的调节:胃肠道炎症的影响
  • 批准号:
    10628032
  • 财政年份:
    2019
  • 资助金额:
    $ 17.97万
  • 项目类别:
Integrators of Metastatic Potential
转移潜能积分器
  • 批准号:
    10357854
  • 财政年份:
    2019
  • 资助金额:
    $ 17.97万
  • 项目类别:
Integrators of Metastatic Potential
转移潜能积分器
  • 批准号:
    10112849
  • 财政年份:
    2019
  • 资助金额:
    $ 17.97万
  • 项目类别:
Modulation of Macrophage Polarization by Heterotrimeric G proteins: Implications of Gastrointestinal Inflammation
异源三聚体 G 蛋白对巨噬细胞极化的调节:胃肠道炎症的影响
  • 批准号:
    10152363
  • 财政年份:
    2019
  • 资助金额:
    $ 17.97万
  • 项目类别:
Modulation of Macrophage Polarization by Heterotrimeric G proteins: Implications of Gastrointestinal Inflammation
异源三聚体 G 蛋白对巨噬细胞极化的调节:胃肠道炎症的影响
  • 批准号:
    10397537
  • 财政年份:
    2019
  • 资助金额:
    $ 17.97万
  • 项目类别:
G Protein pathways as Novel Therapeutic and Diagnostic Targets in Liver Fibrosis
G 蛋白通路作为肝纤维化的新治疗和诊断靶点
  • 批准号:
    8689692
  • 财政年份:
    2014
  • 资助金额:
    $ 17.97万
  • 项目类别:

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