在实现固体肿瘤功能精准医疗的成功中，至关重要的是在外体条件下对患者源性癌细胞（PDCs）进行药物测试。虽然高通量（HT）药物筛选方法已经取得了在二维（2D）格​​式下培养的细胞方面良好的建立，但这种方法在预测临床反应方面可能具有有限的价值。在本文中，我们描述了在三维（3D）生长支持基质中高通量模式下（3D-DSRT）优化药物敏感性和抗药性测试（DSRT）的结果，以肝细胞线（HepG2）为例。支持基质包括广泛应用的动物源性Matrigel和纤维素基GrowDex，后者早已被证明支持细胞系和干细胞的三维生长。此外，在功能精准医疗研究中包括两名患者的卵巢癌PDCs的敏感性针对52种药物在5种不同浓度下进行3D-DSRT测试。简言之，在优化的方案中，PDCs嵌入基质并种植到384孔板中，以允许形成球体，然后在纳升级声学分配器中加入药物。球体对药物治疗的敏感性是通过细胞活力读数来衡量的（这里在药物加入72小时后）。质量控制和数据分析是使用公开可用的Breeze软件执行的。我们展示了两种基质在已建立的3D-DSRT中的可用性，并报告了卵巢癌PDCs对MEK抑制剂和细胞毒性药物敏感性的2D与3D生长条件相关的差异。这项研究提供了在3D-DSRT中稳健且快速筛选PDCs药物敏感性的概念证明，这对于药物发现和个性化的外体药物测试在功能精准医疗研究中都非常重要。这些发现表明，比较2D和3D-DSRT的结果对于理解药物机制并选择最有效的治疗方案对患者有着关键意义。版权 © 2023 Elsevier Inc. 发表。

Central to the success of functional precision medicine of solid tumors is to perform drug testing of patient-derived cancer cells (PDCs) in tumor-mimicking ex vivo conditions. While high throughput (HT) drug screening methods have been well-established for cells cultured in two-dimensional (2D) format, this approach may have limited value in predicting clinical responses. Here, we describe the results of the optimization of drug sensitivity and resistance testing (DSRT) in three-dimensional (3D) growth supporting matrices in a HT mode (3D-DSRT) using the hepatocyte cell line (HepG2) as an example. Supporting matrices included widely used animal-derived Matrigel and cellulose-based hydrogel, GrowDex, which has earlier been shown to support 3D growth of cell lines and stem cells. Further, the sensitivity of ovarian cancer PDCs, from two patients included in the functional precision medicine study, was tested for 52 drugs in 5 different concentrations using 3D-DSRT. Shortly, in the optimized protocol, the PDCs are embedded with matrices and seeded to 384-well plates to allow the formation of the spheroids prior to the addition of drugs in nanoliter volumes with acoustic dispenser. The sensitivity of spheroids to drug treatments is measured with cell viability readout (here, 72 h after addition of drugs). The quality control and data analysis are performed with openly available Breeze software. We show the usability of both matrices in established 3D-DSRT, and report 2D vs 3D growth condition dependent differences in sensitivities of ovarian cancer PDCs to MEK-inhibitors and cytotoxic drugs. This study provides a proof-of-concept for robust and fast screening of drug sensitivities of PDCs in 3D-DSRT, which is important not only for drug discovery but also for personalized ex vivo drug testing in functional precision medicine studies. These findings suggest that comparing results of 2D- and 3D-DSRT is essential for understanding drug mechanisms and for selecting the most effective treatment for the patient.Copyright © 2023. Published by Elsevier Inc.