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Building microenvironment-containing organoids from patient samples with single-cell precision

Building microenvironment-containing organoids from patient samples with single-cell precision
以单细胞精度从患者样本中构建含有微环境的类器官
批准号:
10225309
负责人:
SCOTT R MANALIS
金额:
$20.67万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2022-11-30

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中文摘要
翻译
总结 类器官模型最近已经作为一种替代的、更现实的体外表达而出现, 与传统的2D培养方法相比,在功能水平上,类器官 已经证明可用作离体药物测试的真实肿瘤模型。虽然类器官 模型通常可以准确地概括肿瘤的空间组织,它们通常是 来源于单细胞类型(例如,肿瘤细胞或多能干细胞)和现有的用于 制备具有明确组成的类器官是有限的。为了解决这个问题,我们建议制定 用于构建由主要肿瘤、间质和免疫细胞组成的类器官共培养物的仪器 细胞类型先前显示在多发性骨髓瘤的耐药性中发挥作用,通过荧光 标记细胞并将它们从患者样品中分配到培养威尔斯孔中。通过 监测这些类器官的生长和活力,并对它们进行药物测试,我们将 确定足以概括主要肿瘤间质的最小功能单位 多发性骨髓瘤骨髓小生境的相互作用。如果成功,我们设想, 患者来源的类器官模型可以导致改进的功能测定,以测试 患者样本的癌症治疗,与潜在的目标,使用这些测定,以指导 治疗决定。
英文摘要
Summary Organoid models have recently emerged as an alternative, more realistic in vitro representation of patient tumors when compared to traditional 2D culture approaches. At a functional level, organoids have proven useful as realistic tumor model to be used for ex vivo drug testing. Although organoid models can often accurately recapitulate the spatial organization of the tumor, they are typically derived from a single cell type (e.g., tumor cells or pluripotent stem cells) and existing tools for making organoids with well-defined compositions are limited. To address this, we propose to develop an instrument for building organoid co-cultures consisting of the major tumor, stromal, and immune cell types previously shown to play a role in drug resistance in multiple myeloma, by fluorescently labeling cells and dispensing them from patient samples into culture wells in a single step. By monitoring the growth and viability of these organoids and subjecting them to drug testing, we will determine the minimal functional unit that is sufficient to recapitulate the major tumor-stroma interactions of the multiple myeloma bone marrow niche. If successful, we envision that more realistic patient-derived organoid models could lead to improved functional assays to test the susceptibility of patient samples to cancer therapeutics, with the potential goal of using these assays to guide treatment decisions.
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