RTB 2

实时出价2

基本信息

  • 批准号:
    10375195
  • 负责人:
  • 金额:
    $ 34.5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-12-01 至 2026-11-30
  • 项目状态:
    未结题

项目摘要

Metastasis requires fundamental changes in cell behavior and causes most cancer deaths. Metastasis is also an inherently 3D process involving interactions among diverse cancer cells and with the tumor microenvironment (TME). We developed innovative 3D assays to model each step in metastasis ex vivo. We use these assays to generate hypotheses about how cancer cells accomplish metastasis and which molecular signals should be targeted therapeutically. In vivo validation of these hypotheses is rate limiting, technically and conceptually. We can compare the effects of many perturbations in vitro, with real-time imaging and molecular readouts. In contrast, in vivo validation is generally limited to measurements of tumor diameter, CTC and metastasis numbers, and a few molecular markers in 2D sections. There is an urgent need to achieve a 3D understanding of metastasis, including the complex interactions among cell types and transitions between cell states. The 3D imaging and spatial multi-omics approaches in TECH1 and TECH2 are ideally suited to allow us to understand vascular invasion, the key transition from local to metastatic disease. Prior studies generally evaluated single cell types or a few markers, largely in 2D. CODA (TECH1) will enable us to classify cell types and their spatial relationships in 3D. DBiT-seq (TECH2) enables us to reconstruct the transcriptome and select proteome of high-resolution regions (~10 micron) across whole sections of human tumors. We will combine these techniques to achieve spatial multi-omics and resolve cancer cell state changes during breast cancer metastasis. Aim 1: Adapt CODA to murine models and human breast tumors, focusing on venous invasion. We will first supply archival human breast tumors to enable TECH to adapt their 3D deep learning algorithms to breast cancer. We will start with a existing series of 250 human breast tumors with digitized serial sections. We will then collect, fix, and section fresh human breast tumor samples, stained with immune and cancer cell markers. We will use CODA to reconstruct the 3D architecture of vascular invasion and associated stromal responses. We will also adapt CODA techniques for use with murine preclinical models. We will then leverage these insights to reconstitute the vascular invasion niche in vitro by adapting a novel microfluidic platform we developed. Aim 2: Adapt DBiT-seq for murine and human breast tumors, focusing on cancer cell state transitions. We will adapt DBiT-seq to 3D human breast tumor samples to understand spatial relationships among cancer cell states during vascular invasion. This analysis will be led from cell states and inferred state transitions we defined in vitro using single cell RNA-seq in our 3D metastasis assays. We will then collect a staged series of tumors and distant organs from GEMMs to define cell state transitions spatially across metastatic processes that are difficult to sample in humans. We will then use the transcriptional and signaling dynamics identified in vivo using DBiT-seq to identify candidate molecular regulators for functional validation in vascular invasion microfluidic devices in vitro. Validated candidates will then be tested in vivo in breast cancer GEMMs.
转移需要细胞行为的根本改变,并导致大多数癌症死亡。转移也是

项目成果

期刊论文数量(0)
专著数量(0)
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会议论文数量(0)
专利数量(0)

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Andrew Josef Ewald其他文献

Andrew Josef Ewald的其他文献

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{{ truncateString('Andrew Josef Ewald', 18)}}的其他基金

Mapping the single cell state basis of metastasis in space and time
绘制空间和时间转移的单细胞状态基础
  • 批准号:
    10738579
  • 财政年份:
    2023
  • 资助金额:
    $ 34.5万
  • 项目类别:
RTB 2
实时出价2
  • 批准号:
    10532387
  • 财政年份:
    2021
  • 资助金额:
    $ 34.5万
  • 项目类别:
Integrating bioinformatics into multiscale models for hepatocellular carcinoma
将生物信息学整合到肝细胞癌的多尺度模型中
  • 批准号:
    10372006
  • 财政年份:
    2018
  • 资助金额:
    $ 34.5万
  • 项目类别:
Integrating bioinformatics into multiscale models for hepatocellular carcinoma
将生物信息学整合到肝细胞癌的多尺度模型中
  • 批准号:
    10524181
  • 财政年份:
    2018
  • 资助金额:
    $ 34.5万
  • 项目类别:
Integrating bioinformatics into multiscale models for hepatocellular carcinoma
将生物信息学整合到肝细胞癌的多尺度模型中
  • 批准号:
    9490092
  • 财政年份:
    2018
  • 资助金额:
    $ 34.5万
  • 项目类别:
Integrating bioinformatics into multiscale models for hepatocellular carcinoma
将生物信息学整合到肝细胞癌的多尺度模型中
  • 批准号:
    9891969
  • 财政年份:
    2018
  • 资助金额:
    $ 34.5万
  • 项目类别:
Cancer Invasion and Metastasis
癌症侵袭和转移
  • 批准号:
    10409352
  • 财政年份:
    1997
  • 资助金额:
    $ 34.5万
  • 项目类别:
Cancer Invasion and Metastasis
癌症侵袭和转移
  • 批准号:
    10650408
  • 财政年份:
    1997
  • 资助金额:
    $ 34.5万
  • 项目类别:

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