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Therapeutic Implications from Sensitivity Analysis of Tumor Angiogenesis Models

机译:肿瘤血管生成模型敏感性分析的治疗意义

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摘要

Anti-angiogenic cancer treatments induce tumor starvation and regression by targeting the tumor vasculature that delivers oxygen and nutrients. Mathematical models prove valuable tools to study the proof-of-concept, efficacy and underlying mechanisms of such treatment approaches. The effects of parameter value uncertainties for two models of tumor development under angiogenic signaling and anti-angiogenic treatment are studied. Data fitting is performed to compare predictions of both models and to obtain nominal parameter values for sensitivity analysis. Sensitivity analysis reveals that the success of different cancer treatments depends on tumor size and tumor intrinsic parameters. In particular, we show that tumors with ample vascular support can be successfully targeted with conventional cytotoxic treatments. On the other hand, tumors with curtailed vascular support are not limited by their growth rate and therefore interruption of neovascularization emerges as the most promising treatment target.
机译:抗血管生成性癌症治疗通过靶向输送氧气和营养的肿瘤血管来诱导肿瘤饥饿和消退。数学模型证明是有价值的工具,可用于研究此类治疗方法的概念验证,功效和潜在机制。研究了参数值不确定性对血管生成信号和抗血管生成治疗下两种肿瘤发展模型的影响。进行数据拟合以比较两个模型的预测并获得名义参数值以进行灵敏度分析。敏感性分析表明,不同癌症治疗方法的成功取决于肿瘤大小和肿瘤内在参数。尤其是,我们显示,具有常规血管毒性治疗可以成功靶向具有充足血管支持的肿瘤。另一方面,血管支持减少的肿瘤不受其生长速率的限制,因此中断新血管形成成为最有希望的治疗目标。

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