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动态对比增强磁共振成像预测单克隆抗体肿瘤分布。

Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Prediction of Monoclonal Antibody Tumor Disposition.

机构信息

Department of Pharmaceutical Sciences, University at Buffalo, 450 Pharmacy Building, Buffalo, NY 14214, USA.

Buffalo Neuroimaging Analysis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY 14203, USA.

出版信息

Int J Mol Sci. 2022 Jan 8;23(2):679. doi: 10.3390/ijms23020679.

Abstract

The prediction of monoclonal antibody (mAb) disposition within solid tumors for individual patients is difficult due to inter-patient variability in tumor physiology. Improved a priori prediction of mAb pharmacokinetics in tumors may facilitate the development of patient-specific dosing protocols and facilitate improved selection of patients for treatment with anti-cancer mAb. Here, we report the use of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), with tumor penetration of the contrast agent gadobutrol used as a surrogate, to improve physiologically based pharmacokinetic model (PBPK) predictions of cetuximab pharmacokinetics in epidermal growth factor receptor (EGFR) positive xenografts. In the initial investigations, mice bearing Panc-1, NCI-N87, and LS174T xenografts underwent DCE-MRI imaging with the contrast agent gadobutrol, followed by intravenous dosing of an Iodine-labeled, non-binding mAb (8C2). Tumor concentrations of 8C2 were determined following the euthanasia of mice (3 h-6 days after 8C2 dosing). Potential predictor relationships between DCE-MRI kinetic parameters and 8C2 PBPK parameters were evaluated through covariate modeling. The addition of the DCE-MRI parameter K alone or K in combination with the DCE-MRI parameter Vp on the PBPK parameters for tumor blood flow (QTU) and tumor vasculature permeability (σ) led to the most significant improvement in the characterization of 8C2 pharmacokinetics in individual tumors. To test the utility of the DCE-MRI covariates on a priori prediction of the disposition of mAb with high-affinity tumor binding, a second group of tumor-bearing mice underwent DCE-MRI imaging with gadobutrol, followed by the administration of Iodine-labeled cetuximab (a high-affinity anti-EGFR mAb). The MRI-PBPK covariate relationships, which were established with the untargeted antibody 8C2, were implemented into the PBPK model with considerations for EGFR expression and cetuximab-EGFR interaction to predict the disposition of cetuximab in individual tumors (a priori). The incorporation of the K MRI parameter as a covariate on the PBPK parameters QTU and σ decreased the PBPK model prediction error for cetuximab tumor pharmacokinetics from 223.71 to 65.02%. DCE-MRI may be a useful clinical tool in improving the prediction of antibody pharmacokinetics in solid tumors. Further studies are warranted to evaluate the utility of the DCE-MRI approach to additional mAbs and additional drug modalities.

摘要

由于肿瘤生理学的个体间变异性,预测单克隆抗体(mAb)在实体瘤中的分布对于个体患者而言较为困难。对肿瘤中 mAb 药代动力学的预测的改进,可能有助于制定针对患者的给药方案,并有助于提高对接受抗癌 mAb 治疗的患者的选择。在这里,我们报告了使用动态对比增强磁共振成像(DCE-MRI),以肿瘤内对比剂钆布醇的穿透作为替代物,来改善表皮生长因子受体(EGFR)阳性异种移植物中西妥昔单抗药代动力学的基于生理学的药代动力学模型(PBPK)预测。在最初的研究中,携带 Panc-1、NCI-N87 和 LS174T 异种移植物的小鼠接受了 DCE-MRI 成像,随后静脉注射碘标记的非结合性 mAb(8C2)。在处死小鼠后(8C2 给药后 3 h-6 天),确定了 8C2 的肿瘤浓度。通过协变量建模评估了 DCE-MRI 动力学参数与 8C2 PBPK 参数之间的潜在预测关系。单独添加 DCE-MRI 参数 K 或 K 与 DCE-MRI 参数 Vp 组合,可使肿瘤血流量(QTU)和肿瘤血管通透性(σ)的 PBPK 参数的 8C2 药代动力学特征得到最大程度的改善。为了测试 DCE-MRI 协变量对高亲和力肿瘤结合的 mAb 处置的先验预测的效用,第二组携带肿瘤的小鼠接受了 DCE-MRI 成像,使用了钆布醇,随后给予碘标记的西妥昔单抗(高亲和力抗 EGFR mAb)。建立在非靶向抗体 8C2 上的 MRI-PBPK 协变量关系,考虑到 EGFR 表达和西妥昔单抗-EGFR 相互作用,被纳入 PBPK 模型中,以预测西妥昔单抗在各个肿瘤中的分布(先验)。将 K MRI 参数作为 PBPK 参数 QTU 和 σ 的协变量,可将西妥昔单抗肿瘤药代动力学的 PBPK 模型预测误差从 223.71 降低至 65.02%。DCE-MRI 可能是改善实体瘤中抗体药代动力学预测的有用临床工具。需要进一步的研究来评估 DCE-MRI 方法对其他 mAb 和其他药物模式的效用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ff8/8775965/f19e6390d65a/ijms-23-00679-g001.jpg

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