A hybrid multiscale model for investigating tumor angiogenesis and its response to cell-based therapy.

Q2 Medicine In Silico Biology Pub Date : 2019-01-01 DOI:10.3233/ISB-170469
Melisa Hendrata, Janti Sudiono
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引用次数: 6

Abstract

Angiogenesis, a formation of blood vessels from an existing vasculature, plays a key role in tumor growth and its progression into cancer. The lining of blood vessels consists of endothelial cells (ECs) which proliferate and migrate, allowing the capillaries to sprout towards the tumor to deliver the needed oxygen. Various treatments aiming to suppress or even inhibit angiogenesis have been explored. Mesenchymal stem cells (MSCs) have recently been undergoing development in cell-based therapy for cancer due to their ability to migrate towards the capillaries and induce the apoptosis of the ECs, causing capillary degeneration. However, further investigations in this direction are needed as it is usually difficult to preclinically assess the efficacy of such therapy. We develop a hybrid multiscale model that integrates molecular, cellular, tissue and extracellular components of tumor system to investigate angiogenesis and tumor growth under MSC-mediated therapy. Our simulations produce angiogenesis and vascular tumor growth profiles as observed in the experiments. Furthermore, the simulations show that the effectiveness of MSCs in inducing EC apoptosis is density dependent and its full effect is reached within several days after MSCs application. Quantitative agreements with experimental data indicate the predictive potential of our model for evaluating the efficacy of cell-based therapies targeting angiogenesis.

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研究肿瘤血管生成及其对细胞治疗反应的混合多尺度模型。
血管生成是一种由现有血管系统形成的血管,在肿瘤生长及其发展为癌症的过程中起着关键作用。血管内壁由内皮细胞(ECs)组成,这些细胞增殖和迁移,使毛细血管向肿瘤生长,以输送所需的氧气。各种旨在抑制甚至抑制血管生成的治疗方法已经被探索。由于间充质干细胞(MSCs)能够向毛细血管迁移并诱导内皮细胞凋亡,导致毛细血管变性,因此最近在基于细胞的癌症治疗中得到了发展。然而,由于通常难以临床前评估这种治疗的疗效,因此需要在这方面进行进一步的研究。我们开发了一个混合多尺度模型,整合了肿瘤系统的分子、细胞、组织和细胞外成分,以研究msc介导治疗下的血管生成和肿瘤生长。我们的模拟产生了实验中观察到的血管生成和血管肿瘤生长概况。此外,模拟结果表明,MSCs诱导EC凋亡的有效性与密度有关,并且在应用MSCs后几天内达到完全效果。与实验数据的定量一致表明,我们的模型在评估以血管生成为目标的细胞为基础的治疗效果方面具有预测潜力。
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来源期刊
In Silico Biology
In Silico Biology Computer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍: The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.
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