High-Throughput 3D Tumor Spheroid Screening Method for Cancer Drug Discovery Using Celigo Image Cytometry
High-Throughput 3D Tumor Spheroid Screening Method for Cancer Drug Discovery Using Celigo Image Cytometry
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DOI：
10.1177/2211068216652846
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发表时间：
2017-08-01
期刊：
影响因子：
2.7
通讯作者：
Chan, Leo Li-Ying
中科院分区：
文献类型：
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作者：
Kessel, Sarah;Cribbes, Scott;Chan, Leo Li-Ying
肿瘤学家已经研究了蛋白质或基于化学的化合物对癌细胞的影响，以确定潜在的候选药物。传统上，药物的生长抑制和细胞毒作用首先在2D体外模型中测量，然后在3D体内异种移植模型中进一步测试。虽然候选药物在2D环境中可以表现出良好的抑制或细胞毒性结果，但在3D环境中可能不会观察到类似的效果。在这项工作中，我们开发了一种基于图像的高通量筛选三维肿瘤球体的方法，使用Calio图像细胞仪。首先，通过对人脑胶质母细胞瘤细胞系U87 MG的种植密度的研究，确定了形成肿瘤球体的最佳种植密度。接下来，测量17-AAG对球体大小和存活率的剂量-反应效应，以确定IC50值。最后，开发的高通量方法被用来测量四种药物(17-AAG、紫杉醇、TMZ和阿霉素)相对于球体大小和生存能力的剂量反应。每个实验都在2D模型中同时进行，以进行比较。这种检测方法允许更有效的过程来确定高质量的候选药物，这可能会减少将药物带入临床试验所需的总体时间。
Oncologists have investigated the effect of protein or chemical-based compounds on cancer cells to identify potential drug candidates. Traditionally, the growth inhibitory and cytotoxic effects of the drugs are first measured in 2D in vitro models, and then further tested in 3D xenograft in vivo models. Although the drug candidates can demonstrate promising inhibitory or cytotoxicity results in a 2D environment, similar effects may not be observed under a 3D environment. In this work, we developed an image-based high-throughput screening method for 3D tumor spheroids using the Celigo image cytometer. First, optimal seeding density for tumor spheroid formation was determined by investigating the cell seeding density of U87MG, a human glioblastoma cell line. Next, the dose-response effects of 17-AAG with respect to spheroid size and viability were measured to determine the IC50 value. Finally, the developed high-throughput method was used to measure the dose response of four drugs (17-AAG, paclitaxel, TMZ, and doxorubicin) with respect to the spheroid size and viability. Each experiment was performed simultaneously in the 2D model for comparison. This detection method allowed for a more efficient process to identify highly qualified drug candidates, which may reduce the overall time required to bring a drug to clinical trial.