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肿瘤的侵袭和转移行为,常常是导致病人的死亡的原因.而人们对这些由复杂的肿瘤-宿主以及肿瘤细胞与细胞之间相互作用而产生的群体性行为知之甚少.对这一过程了解的加深,需要多学科间的合作.在本篇文章中,作者将简要回顾肿瘤物理领域的一种新手段,即近年来由作者参与的通过元胞自动机(CA)模型来研究微环境促进的实体瘤侵袭性生长的研究,该模型整合了一系列微观的肿瘤宿主相互作用,包含了肿瘤细胞对细胞外基质的降解,肿瘤细胞趋向养分的迁移,肿瘤生长导致的局部组织压力累积以及该压力对局部的肿瘤-宿主界面稳定性的影响,并且,肿瘤生长时细胞间的粘连也被明确地考虑进来.该元胞自动机模型能成功地重现出一系列的标志性的肿瘤侵袭行为,这有力地表明出该模型的有效性和预测能力.这一模型,如果能与临床数据结合,理论上能够拓展从医学数据中得到的现有结论,帮助设计新的实验,检验假说,并且在实验难以检测到的情形下,预测肿瘤的行为,协助癌症的早期诊断和预后,并针对不同病人,提出最优的个体化医疗方案.
Tumor invasion and metastasis are often the causes of patient deaths, and little is known about the collective behavior of these complex tumor-host and tumor cell-cell interactions. In this article, the authors will briefly review a new tool in the field of oncology, in which the author has participated in recent years to study the effects of microenvironment promotion through the cellular automata (CA) model The model incorporates a series of microscopic tumor host-host interactions that include degradation of extracellular matrix by tumor cells, migration of tumor cells to nutrients, accumulation of local tissue pressure due to tumor growth, and Pressure on the local tumor-host interface stability, and cell adhesion is also explicitly taken into account during tumor growth.The cellular automata model successfully reproduces a series of landmark tumor invasion behaviors , Which effectively shows the effectiveness of the model and predictive ability of this model, if combined with clinical data, in theory, be able to expand from the medical According to the available findings, it helps to design new experiments, test hypotheses and predict tumor behavior in experiments that are difficult to detect, assist in the early diagnosis and prognosis of cancer, and propose optimal individuals for different patients Medical programs.