Computational simulations of tumor growth and treatment response: Benefits of high-frequency, low-dose drug regimens and concurrent vascular normalization.

Computational simulations of tumor growth and treatment response: Benefits of high-frequency, low-dose drug regimens and concurrent vascular normalization.
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DOI:
10.1371/journal.pcbi.1011131
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发表时间:
2023-06
影响因子:
4.3
通讯作者:
--
中科院分区:
生物学2区
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--
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实施有效的癌症治疗策略需要考虑肿瘤微环境(TME)内的时空异质性如何影响肿瘤的进展和治疗反应。在这里,我们开发了一个多尺度的TME三维数学模型来模拟肿瘤的生长和血管生成,然后使用该模型来评估一系列单一和联合治疗方法。治疗包括最大耐受量或节律(即频繁的低剂量)抗癌药物联合抗血管生成治疗。结果表明,节律疗法使肿瘤血管正常化,从而改善药物输送,调节肿瘤新陈代谢,降低间质液体压力,减少癌细胞侵袭。此外,我们发现,将抗癌药物与抗血管生成治疗结合起来,可以增强肿瘤杀伤力,减少药物在正常组织中的积聚。我们还发现,联合应用抗血管生成药物和抗癌药物可以降低肿瘤的侵袭性,使肿瘤代谢微环境正常化,从而减少缺氧和低血糖。我们的模型模拟表明,血管正常化与节律性细胞毒治疗相结合,通过增强肿瘤杀伤力和限制正常组织毒性具有有益的效果。注射药物有效治疗实体瘤需要癌细胞充分暴露于细胞毒药物中。然而,不均匀和功能不佳的血管使这一点变得困难。到达给定癌细胞的药物数量取决于许多因素,包括药物的化学成分、其在血液循环中的寿命、其穿过血管壁进入组织的能力,以及注射的时间表。我们提出了一个关于肿瘤生长、血管生成、新陈代谢和药物运输的数学模型,该模型研究了这些过程如何影响治疗反应。我们发现,低剂量、高频率(节律)治疗使肿瘤血管正常化,以改善药物输送,并且将抗癌药物与特定增强血管功能的药物相结合,可增加肿瘤杀伤率,减少药物在正常组织中的积聚。我们的模型模拟表明,血管正常化与节律性细胞毒治疗相结合,通过增强肿瘤杀伤力和限制正常组织毒性具有有益的效果。
Implementation of effective cancer treatment strategies requires consideration of how the spatiotemporal heterogeneities within the tumor microenvironment (TME) influence tumor progression and treatment response. Here, we developed a multi-scale three-dimensional mathematical model of the TME to simulate tumor growth and angiogenesis and then employed the model to evaluate an array of single and combination therapy approaches. Treatments included maximum tolerated dose or metronomic (i.e., frequent low doses) scheduling of anti-cancer drugs combined with anti-angiogenic therapy. The results show that metronomic therapy normalizes the tumor vasculature to improve drug delivery, modulates cancer metabolism, decreases interstitial fluid pressure and decreases cancer cell invasion. Further, we find that combining an anti-cancer drug with anti-angiogenic treatment enhances tumor killing and reduces drug accumulation in normal tissues. We also show that combined anti-angiogenic and anti-cancer drugs can decrease cancer invasiveness and normalize the cancer metabolic microenvironment leading to reduced hypoxia and hypoglycemia. Our model simulations suggest that vessel normalization combined with metronomic cytotoxic therapy has beneficial effects by enhancing tumor killing and limiting normal tissue toxicity. Effective treatment of solid tumors with injected drugs requires that sufficient exposure of cancer cells to the cytotoxic drugs. However, non-uniform and poorly functioning blood vessels make this difficult. The amount of drug that reaches a given cancer cells depends on many factors, including the drug chemistry, its lifetime in the blood circulation, its ability to cross the blood vessel wall and enter the tissue, and the schedule of the injections. We present a mathematical model of tumor growth, angiogenesis, metabolism and drug transport that examines how these processes affect the response to treatment. We find that low dose, high frequency (metronomic) therapy normalizes the tumor vasculature to improve drug delivery and that combining an anti-cancer drug with a drug that specifically enhances vascular function increases tumor killing and reduces drug accumulation in normal tissues. Our model simulations suggest that vessel normalization combined with metronomic cytotoxic therapy has beneficial effects by enhancing tumor killing and limiting normal tissue toxicity.
DOI: 10.1016/j.jtbi.2010.02.036
发表时间: 2010-06-21
影响因子: 2
作者:
Frieboes, Hermann B.;Jin, Fang;Chuang, Yao-Li;Wise, Steven M.;Lowengrub, John S.;Cristini, Vittorio
通讯作者: Cristini, Vittorio
DOI: 10.1152/physrev.00038.2010
发表时间: 2011-07
影响因子: 33.6
作者:
Goel S;Duda DG;Xu L;Munn LL;Boucher Y;Fukumura D;Jain RK
通讯作者: Jain RK
DOI: 10.1111/j.1600-0463.2008.01148.x
发表时间: 2008-07
期刊: APMIS : acta pathologica, microbiologica, et immunologica Scandinavica
影响因子: --
作者:
Fukumura D;Jain RK
通讯作者: Jain RK
DOI: 10.1186/1742-4682-6-5
发表时间: 2009-04-16
影响因子: --
作者:
Buchwald, Peter
通讯作者: Buchwald, Peter
DOI: 10.1002/jcb.21187
发表时间: 2007-07-01
影响因子: 4
作者:
Fukumura, Dai;Jain, Rakesh K.
通讯作者: Jain, Rakesh K.