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肿瘤生长和治疗反应的计算模拟:高频低剂量药物方案和同时进行的血管正常化的益处。

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

机构信息

Edwin L. Steele Laboratories, Department of Radiation Oncology, Harvard Medical School and Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.

Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran.

出版信息

PLoS Comput Biol. 2023 Jun 8;19(6):e1011131. doi: 10.1371/journal.pcbi.1011131. eCollection 2023 Jun.

DOI:10.1371/journal.pcbi.1011131
PMID:37289729
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10249820/
Abstract

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.

摘要

实施有效的癌症治疗策略需要考虑肿瘤微环境(TME)中的时空异质性如何影响肿瘤进展和治疗反应。在这里,我们开发了一个 TME 的多尺度三维数学模型来模拟肿瘤生长和血管生成,然后利用该模型评估了一系列单一和联合治疗方法。治疗包括给予最大耐受剂量或节拍(即频繁给予低剂量)的抗癌药物联合抗血管生成治疗。结果表明,节拍治疗可使肿瘤血管正常化,从而改善药物输送,调节癌症代谢,降低细胞间质压力并减少癌细胞侵袭。此外,我们发现联合使用抗癌药物和抗血管生成治疗可增强肿瘤杀伤作用并减少药物在正常组织中的积累。我们还表明,联合使用抗血管生成和抗癌药物可以降低癌症侵袭性并使癌症代谢微环境正常化,从而减少缺氧和低血糖。我们的模型模拟表明,血管正常化联合节拍细胞毒性治疗通过增强肿瘤杀伤作用和限制正常组织毒性具有有益效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/f652327018e2/pcbi.1011131.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/7f1dd39a32af/pcbi.1011131.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/84eb637a701b/pcbi.1011131.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/ada1f53be59c/pcbi.1011131.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/1c5a530e9c74/pcbi.1011131.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/51561ab7e876/pcbi.1011131.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/eaaf7dd9a1a4/pcbi.1011131.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/613ac81aff94/pcbi.1011131.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/6fc55c5de718/pcbi.1011131.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/cc3d9d16a739/pcbi.1011131.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/f652327018e2/pcbi.1011131.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/7f1dd39a32af/pcbi.1011131.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/84eb637a701b/pcbi.1011131.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/ada1f53be59c/pcbi.1011131.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/1c5a530e9c74/pcbi.1011131.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/51561ab7e876/pcbi.1011131.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/eaaf7dd9a1a4/pcbi.1011131.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/613ac81aff94/pcbi.1011131.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/6fc55c5de718/pcbi.1011131.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/cc3d9d16a739/pcbi.1011131.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d0/10249820/f652327018e2/pcbi.1011131.g010.jpg

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