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首页> 外文期刊>Journal of Clinical Bioinformatics >A dynamic model for tumour growth and metastasis formation
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A dynamic model for tumour growth and metastasis formation

机译：肿瘤生长和转移形成的动力学模型

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A simple and fast computational model to describe the dynamics of tumour growth and metastasis formation is presented. The model is based on the calculation of successive generations of tumour cells and enables one to describe biologically important entities like tumour volume, time point of 1st metastatic growth or number of metastatic colonies at a given time. The model entirely relies on the chronology of these successive events of the metastatic cascade. The simulation calculations were performed for two embedded growth models to describe the Gompertzian like growth behaviour of tumours. The initial training of the models was carried out using an analytical solution for the size distribution of metastases of a hepatocellular carcinoma. We then show the applicability of our models to clinical data from the Munich Cancer Registry. Growth and dissemination characteristics of metastatic cells originating from cells in the primary breast cancer can be modelled thus showing its ability to perform systematic analyses relevant for clinical breast cancer research and treatment. In particular, our calculations show that generally metastases formation has already been initiated before the primary can be detected clinically.
机译：提供了一个简单而快速的计算模型来描述肿瘤生长和转移形成的动力学。该模型基于对肿瘤细胞连续世代的计算，并能够描述生物学上重要的实体，例如肿瘤体积，第一个转移性生长的时间点或给定时间的转移菌落数。该模型完全依赖于转移级联的这些连续事件的时间顺序。对两个嵌入式生长模型进行了模拟计算，以描述类似Gompertzian的肿瘤生长行为。使用肝细胞癌转移灶大小分布的分析解决方案对模型进行初始训练。然后，我们展示了我们的模型对慕尼黑癌症登记处临床数据的适用性。可以对原发性乳腺癌细胞中转移细胞的生长和扩散特性进行建模，从而显示其进行与临床乳腺癌研究和治疗相关的系统分析的能力。特别是，我们的计算结果表明，通常在临床上可以检测到原发灶之前，已经开始形成转移灶。

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