Microprinted tumor spheroids enable anti-cancer drug screening
Pradip Shahi Thakuri, Stephanie L. Ham, Hossein Tavana
- 发表年份
- 2016
- 引用次数
- 7
摘要
Spheroids present a biologically relevant model of avascular tumors and a unique tool for discovery of anti-cancer drugs. Despite being used in research laboratories for several decades, spheroids are not routinely used for drug discovery primarily due to the difficulty of mass-producing uniformly-sized spheroids and intense labor involved in handling, drug treatment, and analyzing them. We overcome this barrier using a novel technology to robotically microprint spheroids in standard 384-well plates. An aqueous drop containing cancer cells is dispensed into a bath of a second, immiscible aqueous phase. The drop maintains cells in close proximity to aggregate into a single spheroid. Using U-87 MG brain cancer cells, we show that this approach produces spheroids of well-defined size with ~10% deviation from their mean diameter. We demonstrate the feasibility of robotic, high throughput compound screening against tumor spheroids using a collection of 25 standard chemotherapeutics and molecular inhibitors against U-87 MG spheroids. Each drug is used in a wide range of concentrations. Viability of cancer cells in drug-treated spheroids is measured using a PrestoBlue assay. Morphological changes are used as a secondary measure for analysis of drug effect. We identify several compounds that effectively inhibit growth of spheroids. To generate a scoring system for effectiveness of drugs, we use half-maximum inhibitory concentration (IC50), maximum inhibition (Emax), and area under the dose-response curve (AUC) to present a multi-parametric approach that takes into account both potency and efficacy of drugs. Our robotic technology offers a low cost and convenient platform for screening large collections of chemical compounds against realistic tumor models prior to expensive and tedious in vivo tests, dramatically improving testing throughput and efficiency, and reducing costs.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992