Mathematical modeling of PDGF-driven glioblastoma reveals optimized radiation dosing schedules.

Mathematical modeling of PDGF-driven glioblastoma reveals optimized radiation dosing schedules.
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DOI:
10.1016/j.cell.2013.12.029
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发表时间:
2014-01-30
期刊:
影响因子:
64.5
通讯作者:
Michor F
Michor F
中科院分区:
生物学1区
文献类型:
--
作者:
Leder K;Pitter K;LaPlant Q;Hambardzumyan D;Ross BD;Chan TA;Holland EC;Michor F

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胶质母细胞瘤(GBM)是最常见和最恶性的原发脑肿瘤,通常采用手术、化疗和放射治疗。尽管进行了这种治疗,复发是不可避免的,在过去的50年里,存活率有了很小的改善。最近的研究表明,基底膜表现出分化状态的异质性和不稳定性,以及这些状态对辐射的不同敏感性。在这里,我们采用了一种迭代的理论和实验相结合的策略,该策略考虑了肿瘤细胞的异质性和动态获得的放射抗性来预测不同放射治疗方案的有效性。使用这个模型,我们确定了两个预计将显著提高疗效的递送计划,利用辐射抵抗的动态不稳定性。这些时间表使小鼠的存活率更高。我们的跨学科方法也可能适用于其他接受放射治疗的人类癌症类型,因此,可能为显著提高肿瘤治疗的主要有效性奠定基础。
Glioblastomas (GBMs) are the most common and malignant primary brain tumors and are aggressively treated with surgery, chemotherapy, and radiotherapy. Despite this treatment, recurrence is inevitable and survival has improved minimally over the last 50 years. Recent studies have suggested that GBMs exhibit both heterogeneity and instability of differentiation states and varying sensitivities of these states to radiation. Here, we employed an iterative combined theoretical and experimental strategy that takes into account tumor cellular heterogeneity and dynamically acquired radioresistance to predict the effectiveness of different radiation schedules. Using this model, we identified two delivery schedules predicted to significantly improve efficacy by taking advantage of the dynamic instability of radioresistance. These schedules led to superior survival in mice. Our interdisciplinary approach may also be applicable to other human cancer types treated with radiotherapy and, hence, may lay the foundation for significantly increasing the effectiveness of a mainstay of oncologic therapy.
肿瘤基因对神经元和星形胶质细胞的去分化会在小鼠中诱导神经胶质瘤。
DOI: 10.1126/science.1226929
发表时间: 2012-11-23
期刊: Science (New York, N.Y.)
影响因子: --
作者:
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DOI: 10.1371/journal.pone.0035857
发表时间: 2012
期刊: PloS one
影响因子: 3.7
作者:
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