Crown Bioscience Inc., Suzhou, Jiangsu, P.R. China.
Cancer Res Commun. 2023 Oct 23;3(10):2146-2157. doi: 10.1158/2767-9764.CRC-23-0243.
Drug combination therapy is a promising strategy for treating cancer; however, its efficacy and synergy require rigorous evaluation in preclinical studies before going to clinical trials. Existing methods have limited power to detect synergy in animal studies. Here, we introduce a novel approach to assess in vivo drug synergy with high sensitivity and low false discovery rate. It can accurately estimate combination index and synergy score under the Bliss independence model and the highest single agent (HSA) model without any assumption on tumor growth kinetics, study duration, data completeness and balance for tumor volume measurement. We show that our method can effectively validate in vitro drug synergy discovered from cell line assays in in vivo xenograft experiments, and can help to elucidate the mechanism of action for immune checkpoint inhibitors in syngeneic mouse models by combining an anti-PD-1 antibody and several tumor-infiltrating leukocytes depletion treatments. We provide a unified view of in vitro and in vivo synergy by presenting a parallelism between the fixed-dose in vitro and the 4-group in vivo combination studies, so they can be better designed, analyzed, and compared. We emphasize that combination index, when defined here via relative survival of tumor cells, is both dose and time dependent, and give guidelines on designing informative in vivo combination studies. We explain how to interpret and apply Bliss and HSA synergies. Finally, we provide an open-source software package named invivoSyn that enables automated analysis of in vivo synergy using our method and several other existing methods.
This work presents a general solution to reliably determine in vivo drug synergy in single-dose 4-group animal combination studies.
药物联合治疗是治疗癌症的一种有前途的策略；然而，在临床试验之前，需要在临床前研究中严格评估其疗效和协同作用。现有的方法在动物研究中检测协同作用的能力有限。在这里，我们引入了一种新的方法，可以高灵敏度和低假发现率评估体内药物协同作用。它可以在 Bliss 独立性模型和最高单药（HSA）模型下准确估计组合指数和协同评分，而无需对肿瘤生长动力学、研究持续时间、数据完整性和肿瘤体积测量的平衡进行任何假设。我们表明，我们的方法可以有效地验证来自细胞系测定的体外药物协同作用在体内异种移植实验中，并通过结合抗 PD-1 抗体和几种肿瘤浸润白细胞耗竭治疗，有助于阐明免疫检查点抑制剂在同源小鼠模型中的作用机制。我们通过展示固定剂量体外和 4 组体内组合研究之间的平行性，提供了一种统一的体外和体内协同作用的观点，因此它们可以更好地设计、分析和比较。我们强调，这里通过肿瘤细胞的相对存活率定义的组合指数既取决于剂量又取决于时间，并给出了设计信息丰富的体内组合研究的指南。我们解释了如何解释和应用 Bliss 和 HSA 协同作用。最后，我们提供了一个名为 invivoSyn 的开源软件包，该软件包允许使用我们的方法和其他几种现有方法自动分析体内协同作用。
这项工作为在单次剂量 4 组动物组合研究中可靠地确定体内药物协同作用提供了一种通用解决方案。
