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探索利用细胞状态可塑性的新型胶质母细胞瘤放射治疗方案的 I 期研究。

Phase I study of a novel glioblastoma radiation therapy schedule exploiting cell-state plasticity.

机构信息

Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.

Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, USA.

出版信息

Neuro Oncol. 2023 Jun 2;25(6):1100-1112. doi: 10.1093/neuonc/noac253.

DOI:10.1093/neuonc/noac253
PMID:36402744
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10237407/
Abstract

BACKGROUND

Glioblastomas comprise heterogeneous cell populations with dynamic, bidirectional plasticity between treatment-resistant stem-like and treatment-sensitive differentiated states, with treatment influencing this process. However, current treatment protocols do not account for this plasticity. Previously, we generated a mathematical model based on preclinical experiments to describe this process and optimize a radiation therapy fractionation schedule that substantially increased survival relative to standard fractionation in a murine glioblastoma model.

METHODS

We developed statistical models to predict the survival benefit of interventions to glioblastoma patients based on the corresponding survival benefit in the mouse model used in our preclinical study. We applied our mathematical model of glioblastoma radiation response to optimize a radiation therapy fractionation schedule for patients undergoing re-irradiation for glioblastoma and developed a first-in-human trial (NCT03557372) to assess the feasibility and safety of administering our schedule.

RESULTS

Our statistical modeling predicted that the hazard ratio when comparing our novel radiation schedule with a standard schedule would be 0.74. Our mathematical modeling suggested that a practical, near-optimal schedule for re-irradiation of recurrent glioblastoma patients was 3.96 Gy × 7 (1 fraction/day) followed by 1.0 Gy × 9 (3 fractions/day). Our optimized schedule was successfully administered to 14/14 (100%) patients.

CONCLUSIONS

A novel radiation therapy schedule based on mathematical modeling of cell-state plasticity is feasible and safe to administer to glioblastoma patients.

摘要

背景

胶质母细胞瘤由具有动态、双向可塑性的治疗抵抗性干细胞样和治疗敏感性分化状态的异质细胞群体组成,治疗会影响这一过程。然而,目前的治疗方案并没有考虑到这种可塑性。此前,我们基于临床前实验生成了一个数学模型来描述这一过程,并优化了放射治疗分割方案,与小鼠胶质母细胞瘤模型中的标准分割方案相比,该方案大大提高了生存率。

方法

我们开发了统计模型,根据我们在临床前研究中使用的小鼠模型中相应的生存获益,预测干预胶质母细胞瘤患者的生存获益。我们将我们的胶质母细胞瘤放射反应数学模型应用于优化接受再放射治疗的胶质母细胞瘤患者的放射治疗分割方案,并开展了首例人体试验(NCT03557372),以评估我们方案的可行性和安全性。

结果

我们的统计建模预测,比较我们的新放射方案与标准方案时,危害比为 0.74。我们的数学建模表明,对于复发性胶质母细胞瘤患者再放疗的一种实用、近乎最佳的方案是 3.96 Gy×7(每天 1 次分割),随后是 1.0 Gy×9(每天 3 次分割)。我们的优化方案成功地用于 14/14(100%)患者。

结论

基于细胞状态可塑性的数学建模的新型放射治疗方案对胶质母细胞瘤患者是可行且安全的。

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Mathematical modeling of radiotherapy: impact of model selection on estimating minimum radiation dose for tumor control.放射治疗的数学建模:模型选择对估计肿瘤控制所需最小辐射剂量的影响。
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Glioblastoma in adults: a Society for Neuro-Oncology (SNO) and European Society of Neuro-Oncology (EANO) consensus review on current management and future directions.成人脑胶质母细胞瘤:神经肿瘤学会(SNO)和欧洲神经肿瘤学会(EANO)关于当前管理和未来方向的共识综述。
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