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靶向放射性核素与 CAR-T 细胞联合治疗的数学建模方法

英文原题:A Mathematical Modeling Approach for Targeted Radionuclide and Chimeric Antigen Receptor T Cell Combination Therapy.

查看英文原题

A Mathematical Modeling Approach for Targeted Radionuclide and Chimeric Antigen Receptor T Cell Combination Therapy.

PubMed 2021/10/15(内容时间) Cancers (Basel) Q2 · IF 4.8(JCR 2025)

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中文摘要

靶向放射性核素治疗(TRT)近来随着放射性核素偶联小分子和抗体的应用而日益流行。同样,免疫治疗也显示出令人鼓舞的结果,例如CAR-T 细胞疗法在血液系统恶性肿瘤中的应用。此外,TRT和CAR-T 疗法具有独特的特征,在确定给药剂量以及联合治疗的时间和顺序时需要特别考虑,包括TRT剂量在体内的分布、放射性核素的衰变率以及CAR-T 细胞的增殖和持久性。这些特征使联合治疗的相加或协同效应变得复杂,因此需要进行数学处理,将这些动力学与靶肿瘤细胞的增殖和清除率相关联。在此,我们将先前发表的两个数学模型相结合,探讨在多发性骨髓瘤背景下TRT和CAR-T 细胞疗法的剂量、时机和顺序的影响。我们发现,对于固定的TRT和CAR-T 细胞剂量,肿瘤增殖率是决定TRT和CAR-T 治疗最佳时机的最重要参数。

展开英文摘要原文

Targeted radionuclide therapy (TRT) has recently seen a surge in popularity with the use of radionuclides conjugated to small molecules and antibodies. Similarly, immunotherapy also has shown promising results, an example being chimeric antigen receptor T cell (CAR-T) therapy in hematologic malignancies.

Moreover, TRT and CAR-T therapies possess unique features that require special consideration when determining how to dose as well as the timing and sequence of combination treatments including the distribution of the TRT dose in the body, the decay rate of the radionuclide, and the proliferation and persistence of the CAR-T cells.

These characteristics complicate the additive or synergistic effects of combination therapies and warrant a mathematical treatment that includes these dynamics in relation to the proliferation and clearance rates of the target tumor cells.

Here, we combine two previously published mathematical models to explore the effects of dose, timing, and sequencing of TRT and CAR-T cell-based therapies in a multiple myeloma setting.

We find that, for a fixed TRT and CAR-T cell dose, the tumor proliferation rate is the most important parameter in determining the best timing of TRT and CAR-T therapies.

论文信息

作者
Adhikarla V、Awuah D、Brummer AB、Caserta E、Krishnan A、Pichiorri F、Minnix M、Shively JE
单位
Division of Mathematical Oncology, Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA.United States
期刊
Cancers2021 Oct 15
原文标识
PubMed 34680320 · DOI 10.3390/cancers13205171