数学建模揭示血癌放射性核素靶向治疗的优化策略

IF 3.3 Q3 ONCOLOGY
Maxim Kuznetsov, Vikram Adhikarla, Enrico Caserta, Xiuli Wang, John E Shively, Flavia Pichiorri, Russell C Rockne
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引用次数: 0

摘要

放射性核素靶向治疗是通过注射与放射性核素结合的癌症特异性分子来实现的。尽管这种治疗方法具有特异性,但也并非没有副作用,这限制了它的使用,尤其是对血液灌注良好的快速增殖器官(如骨髓)有害。考虑到毒性限制因素,优化放射性缀合物的用药可提高疗效。根据我们对使用 225Ac-DOTA-daratumumab 治疗播散性多发性骨髓瘤小鼠模型的实验,我们建立了一个数学模型,该模型的研究强调了优化放射性核素靶向治疗的以下原则。1) 核素与抗体比的重要性。癌细胞上放射性结合剂的密度决定了沉积在癌细胞中的辐射能量密度。低标记比以及未标记抗体和衰变产物抗体在血液中的积累,可减轻因缺乏放射性核素的抗体过度占据特定受体而造成的癌症辐射损伤。2) 基于癌症结合能力的剂量。癌细胞上特异性受体的总数是优化治疗的关键因素,通过估算可以使治疗效果接近理论极限。应避免注射明显超过癌症结合能力的剂量,因为残留在血液中的放射性结合剂的疗效和毒性比微乎其微。3) 以粒子范围为导向的多重剂量。使用短程粒子发射器和高亲和性抗体可通过癌症结合能力的初始饱和来实现稳健的治疗优化,从而使进一步注射的放射性缀合物和沉积剂量重新分配到继续表达特定受体的仍有活力的细胞中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mathematical Modeling Unveils Optimization Strategies for Targeted Radionuclide Therapy of Blood Cancers.

Significance: Mathematical modeling yields general principles for optimization of TRT in mouse models of multiple myeloma that can be extrapolated to other cancer models and clinical settings.

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