Selected aspects of avascular tumor growth reproduced by a hybrid model of cell dynamics and chemical kinetics

IF 1.9 4区 数学 Q2 BIOLOGY
Marco Scianna
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引用次数: 0

Abstract

We here propose a hybrid computational framework to reproduce and analyze aspects of the avascular progression of a generic solid tumor. Our method first employs an individual-based approach to represent the population of tumor cells, which are distinguished in viable and necrotic agents. The active part of the disease is in turn differentiated according to a set of metabolic states. We then describe the spatio-temporal evolution of the concentration of oxygen and of tumor-secreted proteolytic enzymes using partial differential equations (PDEs). A differential equation finally governs the local degradation of the extracellular matrix (ECM) by the malignant mass. Numerical realizations of the model are run to reproduce tumor growth and invasion in a number scenarios that differ for cell properties (adhesiveness, duplication potential, proteolytic activity) and/or environmental conditions (level of tissue oxygenation and matrix density pattern). In particular, our simulations suggest that tumor aggressiveness, in terms of invasive depth and extension of necrotic tissue, can be reduced by (i) stable cell–cell contact interactions, (ii) poor tendency of malignant agents to chemotactically move upon oxygen gradients, and (iii) presence of an overdense matrix, if coupled by a disrupted proteolytic activity of the disease.

细胞动力学和化学动力学混合模型再现无血管肿瘤生长的某些方面
我们在此提出一种混合计算框架,用于再现和分析一般实体瘤无血管进展的各个方面。我们的方法首先采用基于个体的方法来表示肿瘤细胞群,并将其区分为有活力的细胞和坏死的细胞。疾病的活跃部分又根据一组代谢状态加以区分。然后,我们使用偏微分方程(PDEs)来描述氧气浓度和肿瘤分泌的蛋白水解酶的时空演变。最后,一个微分方程控制着恶性肿块对细胞外基质(ECM)的局部降解。通过对模型进行数值模拟,可以在不同细胞特性(粘附性、复制潜能、蛋白水解活性)和/或环境条件(组织氧合水平和基质密度模式)的情况下再现肿瘤的生长和侵袭。特别是,我们的模拟表明,肿瘤的侵袭性(就侵袭深度和坏死组织的扩展范围而言)可通过以下方式降低:(i) 稳定的细胞-细胞接触相互作用;(ii) 恶性病原体在氧梯度上的趋化性较差;(iii) 过密基质的存在,如果再加上疾病的蛋白水解活性受到破坏。
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来源期刊
Mathematical Biosciences
Mathematical Biosciences 生物-生物学
CiteScore
7.50
自引率
2.30%
发文量
67
审稿时长
18 days
期刊介绍: Mathematical Biosciences publishes work providing new concepts or new understanding of biological systems using mathematical models, or methodological articles likely to find application to multiple biological systems. Papers are expected to present a major research finding of broad significance for the biological sciences, or mathematical biology. Mathematical Biosciences welcomes original research articles, letters, reviews and perspectives.
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