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数学模型预测,将基于巨噬细胞的、缺氧靶向基因治疗与化疗相结合具有协同抗肿瘤作用。

Mathematical modeling predicts synergistic antitumor effects of combining a macrophage-based, hypoxia-targeted gene therapy with chemotherapy.

机构信息

Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, UK.

出版信息

Cancer Res. 2011 Apr 15;71(8):2826-37. doi: 10.1158/0008-5472.CAN-10-2834. Epub 2011 Mar 1.

Abstract

Tumor hypoxia is associated with low rates of cell proliferation and poor drug delivery, limiting the efficacy of many conventional therapies such as chemotherapy. Because many macrophages accumulate in hypoxic regions of tumors, one way to target tumor cells in these regions could be to use genetically engineered macrophages that express therapeutic genes when exposed to hypoxia. Systemic delivery of such therapeutic macrophages may also be enhanced by preloading them with nanomagnets and applying a magnetic field to the tumor site. Here, we use a new mathematical model to compare the effects of conventional cyclophosphamide therapy with those induced when macrophages are used to deliver hypoxia-inducible cytochrome P450 to locally activate cyclophosphamide. Our mathematical model describes the spatiotemporal dynamics of vascular tumor growth and treats cells as distinct entities. Model simulations predict that combining conventional and macrophage-based therapies would be synergistic, producing greater antitumor effects than the additive effects of each form of therapy. We find that timing is crucial in this combined approach with efficacy being greatest when the macrophage-based, hypoxia-targeted therapy is administered shortly before or concurrently with chemotherapy. Last, we show that therapy with genetically engineered macrophages is markedly enhanced by using the magnetic approach described above, and that this enhancement depends mainly on the strength of the applied field, rather than its direction. This insight may be important in the treatment of nonsuperficial tumors, where generating a specific orientation of a magnetic field may prove difficult. In conclusion, we demonstrate that mathematical modeling can be used to design and maximize the efficacy of combined therapeutic approaches in cancer.

摘要

肿瘤缺氧与细胞增殖率低和药物输送不良有关,限制了许多常规疗法(如化疗)的疗效。由于许多巨噬细胞在肿瘤的缺氧区域积聚,一种靶向这些区域肿瘤细胞的方法可能是使用表达治疗基因的基因工程巨噬细胞,当暴露于缺氧时。通过预先用纳米磁铁加载这些治疗性巨噬细胞,并将磁场应用于肿瘤部位,也可以增强这种治疗性巨噬细胞的全身递送。在这里,我们使用新的数学模型比较了常规环磷酰胺治疗与巨噬细胞用于局部诱导缺氧诱导型细胞色素 P450 以激活环磷酰胺时所诱导的治疗效果。我们的数学模型描述了血管肿瘤生长的时空动力学,并将细胞视为不同的实体。模型模拟预测,将常规治疗与基于巨噬细胞的治疗相结合将具有协同作用,产生比每种治疗形式的累加效果更大的抗肿瘤作用。我们发现,在这种联合方法中,时间至关重要,当基于巨噬细胞的、针对缺氧的治疗在化疗之前或同时进行时,疗效最大。最后,我们表明,使用上述磁性方法可以显著增强基因工程巨噬细胞的治疗效果,并且这种增强主要取决于施加磁场的强度,而不是其方向。这一见解对于治疗非浅表肿瘤可能很重要,因为在这种肿瘤中,产生特定的磁场方向可能很困难。总之,我们证明了数学建模可用于设计和最大化癌症联合治疗方法的疗效。

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