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3D Bioprinted Omentum tissue to model ovarian cancer metastasis

3D Bioprinted Omentum tissue to model ovarian cancer metastasis
3D 生物打印网膜组织用于模拟卵巢癌转移
批准号：
10255275
负责人：
Marc Ferrer-Alegre
金额：
$72.57万
依托单位：
NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
--
资助国家：
美国
项目状态：
未结题
起止时间：
至
来源：
https://reporter.nih.gov/project-details/10255275
关键词：
3-DimensionalAnimal ModelAntineoplastic AgentsBiological AssayBlood VesselsCancer Cell GrowthCell LineCell modelCell-Matrix JunctionCellsDevelopmentEndothelial CellsFibroblastsFluorescence MicroscopyFunctional disorderGenetically Engineered MouseGoalsGrowthHumanImmunodeficient MouseIn VitroLabelLocationMalignant NeoplasmsMalignant neoplasm of ovaryMesothelial CellMetastatic Malignant Neoplasm to the OvaryModelingMonitorMorphologyNeoplasm MetastasisOmentumPatientsPericytesPhysiologicalPhysiologyPreclinical TestingProductionProtocols documentationSiteSurfaceSuspensionsThree-Dimensional ImagingTissuesToxicity TestsXenograft procedurebiofabricationbioprintingcancer cellcell growthcellular imagingclinical efficacydrug developmentdrug discoveryefficacy testingmonolayerneoplastic cellnovel therapeuticsovarian neoplasmpredictive testpreventscreeningtumor

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中文摘要
翻译
我们已经开发了用于生产血管化网膜模型的生物纤维素方案，所述模型包括患者来源的成纤维细胞、内皮细胞和周细胞以及患者间皮细胞层。 患者细胞从我们的合作者Ernst Lengyel博士和Hilary Kenny获得。 将荧光标记的卵巢肿瘤细胞悬浮液添加到组织上的间皮细胞层的顶部，并使用荧光显微镜监测组织内的肿瘤形成。 已经开发了3D成像分析来量化肿瘤的大小和数量以及它们的位置。 这些分析将用于筛选一组集中的化合物，以防止组织中肿瘤形成。
英文摘要
We have developed biofabrication protocols for the production of vascularized omentum model that includes patient derived fibroblasts, endothelial cells and pericytes, and a layer of patient mesothelial cells. Patient cells were obtained from our collaborators Dr. Ernst Lengyel and Hilary Kenny. Addition of a suspension of fluorescently labeled ovarian tumor cells to the top of mesothelial cell layer on the tissue and used fluorescence microscopy to monitor tumor formation inside the tissue. 3D imaging analysis have been developed to quantiate size and number of tumors, and their location. These analytics will be used to screen a focused set of compounds for compounds that prevent tumor formation in the tissue.
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