Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences (A.P.S., L.G., A.V., H.-P.C., D.K.S.), Center for Hearing and Deafness, SUNY Eye Institute (G.M.S.), and Department of Biological Sciences (G.G.-L.W.), The State University of New York at Buffalo, Buffalo, New York
Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences (A.P.S., L.G., A.V., H.-P.C., D.K.S.), Center for Hearing and Deafness, SUNY Eye Institute (G.M.S.), and Department of Biological Sciences (G.G.-L.W.), The State University of New York at Buffalo, Buffalo, New York.
J Pharmacol Exp Ther. 2020 Jul;374(1):184-199. doi: 10.1124/jpet.119.262287. Epub 2020 Apr 9.
The objective of this work was to develop a systems pharmacokinetics-pharmacodynamics (PK-PD) model that can characterize in vivo bystander effect of antibody-drug conjugate (ADC) in a heterogeneous tumor. To accomplish this goal, a coculture xenograft tumor with 50% GFP-MCF7 (HER2-low) and 50% N87 (HER2-high) cells was developed. The relative composition of a heterogeneous tumor for each cell type was experimentally determined by immunohistochemistry analysis. Trastuzumab-vc-MMAE (T-vc-MMAE) was used as a tool ADC. Plasma and tumor PK of T-vc-MMAE was analyzed in N87, GFP-MCF7, and coculture tumor-bearing mice. In addition, tumor growth inhibition (TGI) studies were conducted in all three xenografts at different T-vc-MMAE dose levels. To characterize the PK of ADC in coculture tumors, our previously published tumor distribution model was evolved to account for different cell populations. The evolved tumor PK model was able to a priori predict the PK of all ADC analytes in the coculture tumors reasonably well. The tumor PK model was subsequently integrated with a PD model that used intracellular tubulin occupancy to drive ADC efficacy in each cell type. The final systems PK-PD model was able to simultaneously characterize all the TGI data reasonably well, with a common set of parameters for MMAE-induced cytotoxicity. The model was later used to simulate the effect of different dosing regimens and tumor compositions on the bystander effect of ADC. The model simulations suggested that dose-fractionation regimen may further improve overall efficacy and bystander effect of ADCs by prolonging the tubulin occupancy in each cell type. SIGNIFICANCE STATEMENT: A PK-PD analysis is presented to understand bystander effect of Trastuzumab-vc-MMAE ADC in antigen (Ag)-low, Ag-high, and coculture (i.e., Ag-high + Ag-low) xenograft mice. This study also describes a novel single cell-level systems PK-PD model to characterize in vivo bystander effect of ADCs. The proposed model can serve as a platform to mathematically characterize multiple cell populations and their interactions in tumor tissues. Our analysis also suggests that fractionated dosing regimen may help improve the bystander effect of ADCs.
这项工作的目的是开发一种能够描述抗体药物偶联物（ADC）在异质性肿瘤中体内旁观者效应的系统药代动力学-药效学（PK-PD）模型。为了实现这一目标，开发了一种共培养异种移植肿瘤，其中 50% GFP-MCF7（HER2-低）和 50% N87（HER2-高）细胞。通过免疫组织化学分析实验确定了异质性肿瘤中每种细胞类型的相对组成。曲妥珠单抗-vc-MMAE（T-vc-MMAE）被用作工具 ADC。在 N87、GFP-MCF7 和共培养肿瘤荷瘤小鼠中分析了 T-vc-MMAE 的血浆和肿瘤 PK。此外，在所有三种异种移植物中进行了不同 T-vc-MMAE 剂量水平的肿瘤生长抑制（TGI）研究。为了描述共培养肿瘤中 ADC 的 PK，我们之前发表的肿瘤分布模型进行了改进，以考虑不同的细胞群体。改进后的肿瘤 PK 模型能够很好地预先预测共培养肿瘤中所有 ADC 分析物的 PK。随后，将肿瘤 PK 模型与使用细胞内微管蛋白占有率来驱动每种细胞类型中 ADC 疗效的 PD 模型进行了整合。最终的系统 PK-PD 模型能够很好地同时描述所有 TGI 数据，使用共同的一组参数来描述 MMAE 诱导的细胞毒性。该模型后来被用于模拟不同给药方案和肿瘤组成对 ADC 旁观者效应的影响。模型模拟表明，分次给药方案通过延长每种细胞类型中的微管蛋白占有率，可能进一步提高 ADC 的总体疗效和旁观者效应。意义：进行 PK-PD 分析以了解曲妥珠单抗-vc-MMAE ADC 在抗原（Ag）低、Ag 高和共培养（即 Ag 高+Ag 低）异种移植小鼠中的旁观者效应。本研究还描述了一种新的单细胞水平系统 PK-PD 模型，用于描述 ADC 的体内旁观者效应。所提出的模型可以作为一个平台，用于数学描述肿瘤组织中的多个细胞群体及其相互作用。我们的分析还表明，分次给药方案可能有助于提高 ADC 的旁观者效应。
