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首页> 外文期刊>Cancer research: The official organ of the American Association for Cancer Research, Inc >Mathematical Modeling Predicts Synergistic Antitumor Effects of Combining a Macrophage-Based, Hypoxia-Targeted Gene Therapy with Chemotherapy.
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Mathematical Modeling Predicts Synergistic Antitumor Effects of Combining a Macrophage-Based, Hypoxia-Targeted Gene Therapy with Chemotherapy.

机译:数学建模预测结合基于巨噬细胞,低氧靶向基因疗法和化疗的协同抗肿瘤作用。

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摘要

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. Cancer Res; 71(8); 2826-37. (c)2011 AACR.
机译:肿瘤缺氧与细胞增殖率低和药物递送不良有关,从而限制了许多传统疗法如化学疗法的功效。因为许多巨噬细胞聚集在肿瘤的低氧区域,所以靶向这些区域中的肿瘤细胞的一种方法可能是使用经过基因工程改造的巨噬细胞,这些巨噬细胞在暴露于低氧时会表达治疗基因。通过用纳米磁体预加载治疗性巨噬细胞并向肿瘤部位施加磁场,也可以增强这类治疗性巨噬细胞的全身递送。在这里,我们使用一种新的数学模型将常规环磷酰胺疗法的效果与巨噬细胞用于递送缺氧诱导的细胞色素P450以局部激活环磷酰胺的效果进行了比较。我们的数学模型描述了血管肿瘤生长的时空动态,并将细胞视为不同的实体。模型模拟预测,将传统疗法与基于巨噬细胞的疗法相结合将产生协同作用,比每种疗法的相加作用产生更大的抗肿瘤作用。我们发现,在这种联合治疗方法中,定时是至关重要的,当在化疗之前或同时进行基于巨噬细胞的低氧靶向治疗时,疗效最高。最后,我们表明,通过使用上述磁性方法,基因工程巨噬细胞的治疗显着增强,并且这种增强主要取决于所施加磁场的强度,而不是方向。这种见解在非浅表性肿瘤的治疗中可能很重要,因为在这种情况下,产生磁场的特定方向可能很困难。总之,我们证明了数学建模可以用来设计和最大化组合治疗方法在癌症中的功效。癌症研究; 71(8); 2826-37。 (c)2011年美国机修协会。

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