Computational model for migration of a cell cluster in three-dimensional matrices.
Computational model for migration of a cell cluster in three-dimensional matrices.
复制标题
三维矩阵中细胞簇迁移的计算模型。
DOI：
10.1007/s10439-011-0290-9
复制
发表时间：
2011
影响因子：
3.8
通讯作者：
Zaman,MuhammadH
中科院分区：
文献类型：
--
作者：
Vargas,DiegoA;Zaman,MuhammadH
本文提出了第一个基于力的细胞群在模仿细胞外基质的3D环境中集体移动的动力学计算机模型。一般来说，集体细胞迁移是组织修复、形态发生和癌症侵袭机制的相关部分。特别是在癌症中，侵袭通过多细胞3D链以及集体细胞簇发生。由于癌症是一个缓慢的过程，这些集群尚未被仔细观察。然而，这种细胞运动机制的普遍性使其成为研究的目标。由于这种运动涉及不同的分子机制，而且它们之间的关系非常复杂，因此计算机模型将非常有用。这里提出的模型考虑到配体浓度，基质金属蛋白酶的活性，并根据实验结果和实验验证的单细胞计算机模型集群的几何形状，从而将隐含不同的基础分子特性。记录并分析了细胞团的速度分布。特别是七个不同的配置文件观察到的基础上不同的参与的配体，蛋白酶，和机械力。该模型成功地显示了改变运动细胞系统中单个变量的潜在影响。特别强调的是未来的改进方向和变量可能被调制，以模拟特定的生理条件。
This paper presents a first forced-based dynamics computer model of a cell cluster moving collectively in a 3D environment mimicking the extracellular matrix. In general, collective cell migration is a relevant part of the mechanisms for tissue repair, morphogenesis, and cancer invasion. Particularly in cancer, invasion occurs through multicellular 3D strands as well as collective cell clusters. Because cancer is a slow process, these clusters have not been carefully observed. However, the prevalence of this mechanism of cell locomotion makes it a target for study. Due to the different molecular mechanisms involved in this movement and the complex relations among them, a computer model would be of great use. The model presented here takes into account ligand concentration, matrix metalloproteinase activity, and cluster geometry based on experimental findings and experimentally validated single cell computer models; thus incorporating implicitly different underlying molecular properties. The velocity profiles of the cell clusters were recorded and analyzed. In particular seven different profiles are observed based on different participation of ligands, proteinases, and mechanical forces involved. The model is successful in showing potential effects of altering single variables in a system of cells in motion. Special emphasis is made on future directions for improvement and the variables to be potentially modulated to simulate particular physiological conditions.