High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response
High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response
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DOI：
10.1038/nm.3954
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发表时间：
2015-11-01
期刊：
影响因子：
82.9
通讯作者：
Sellers, William R.
中科院分区：
文献类型：
--
作者：
Gao, Hui;Korn, Joshua M.;Sellers, William R.
在临床前开发期间使用有限的癌症模型来分析候选疗法会阻碍临床疗效的预测以及识别导致患者选择策略的患者反应不均匀的因素。我们建立了类似于1，000例患者来源的肿瘤异种移植模型（PDX），具有不同的驱动突变。使用这些PDX，我们使用1 x 1 x 1实验设计（PDX临床试验或PCT）进行体内化合物筛选，以评估对6种适应症中62种治疗的群体反应。我们通过鉴定基因型和药物反应之间的关联以及建立的耐药机制来证明这种方法的可重复性和临床可转化性。此外，我们的研究结果表明，PCTs可能是一个更准确的方法比细胞系模型评估的临床潜力，一些治疗方式。因此，我们提出，这种实验范式可能会改善临床前评估的治疗方式，并提高我们的能力，预测临床试验的反应。
Profiling candidate therapeutics with limited cancer models during preclinical development hinders predictions of clinical efficacy and identifying factors that underlie heterogeneous patient responses for patient-selection strategies. We established similar to 1,000 patient-derived tumor xenograft models (PDXs) with a diverse set of driver mutations. With these PDXs, we performed in vivo compound screens using a 1 x 1 x 1 experimental design (PDX clinical trial or PCT) to assess the population responses to 62 treatments across six indications. We demonstrate both the reproducibility and the clinical translatability of this approach by identifying associations between a genotype and drug response, and established mechanisms of resistance. In addition, our results suggest that PCTs may represent a more accurate approach than cell line models for assessing the clinical potential of some therapeutic modalities. We therefore propose that this experimental paradigm could potentially improve preclinical evaluation of treatment modalities and enhance our ability to predict clinical trial responses.