Advanced Development of Primary Pancreatic Organoid Tumor Models for High-Throughput Phenotypic Drug Screening.

Advanced Development of Primary Pancreatic Organoid Tumor Models for High-Throughput Phenotypic Drug Screening.
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DOI:
10.1177/2472555218766842
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发表时间:
2018-07
期刊:
SLAS discovery : advancing life sciences R & D
影响因子:
--
通讯作者:
Spicer TP
Spicer TP
中科院分区:
其他
文献类型:
--
作者:
Hou S;Tiriac H;Sridharan BP;Scampavia L;Madoux F;Seldin J;Souza GR;Watson D;Tuveson D;Spicer TP

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在肿瘤学中,传统的高通量药物筛选通常依赖于二维(2D)细胞模型,这不能充分概括癌症的生理背景。三维(3D)细胞模型被认为能更好地模拟体内肿瘤的复杂性。已经描述了许多培养3D有机物的方法,但大多数方法不均匀且成本高昂,因此不适用于高通量筛选(HTS)目的。在这里,我们描述了一种与HTS兼容的方法,通过结合使用细胞排斥表面和结合磁力的生物打印技术,能够在标准平底384和1536孔板中一致地生产有机物。我们通过评估具有良好特性的抗癌药物对四种患者来源的胰腺癌KRAS突变相关原代细胞的影响来验证这一同质性过程,其中包括癌症相关的成纤维细胞。这项技术通过完成对约3300种批准药物的细胞毒性中试筛选,测试了其与HTS自动化的兼容性。为了突出3D格式的好处,我们在2D和3D测试中并行执行了这个试点屏幕。这些数据表明,这项技术可以很容易地应用于支持依赖于临床相关的、直接从患者身上获得的体外3D肿瘤模型的大规模药物筛选,这是迈向个性化药物的一个重要里程碑。
Traditional high-throughput drug screening in oncology routinely relies on two-dimensional (2D) cell models, which inadequately recapitulate the physiologic context of cancer. Three-dimensional (3D) cell models are thought to better mimic the complexity of in vivo tumors. Numerous methods to culture 3D organoids have been described, but most are nonhomogeneous and expensive, and hence impractical for high-throughput screening (HTS) purposes. Here we describe an HTS-compatible method that enables the consistent production of organoids in standard flat-bottom 384- and 1536-well plates by combining the use of a cell-repellent surface with a bioprinting technology incorporating magnetic force. We validated this homogeneous process by evaluating the effects of well-characterized anticancer agents against four patient-derived pancreatic cancer KRAS mutant-associated primary cells, including cancer-associated fibroblasts. This technology was tested for its compatibility with HTS automation by completing a cytotoxicity pilot screen of ~3300 approved drugs. To highlight the benefits of the 3D format, we performed this pilot screen in parallel in both the 2D and 3D assays. These data indicate that this technique can be readily applied to support large-scale drug screening relying on clinically relevant, ex vivo 3D tumor models directly harvested from patients, an important milestone toward personalized medicine.
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