Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA.
Department of Biomedical Engineering, Boston University, Boston, MA, USA.
J R Soc Interface. 2018 Aug;15(145). doi: 10.1098/rsif.2018.0243.
Angiogenesis is a crucial step in tumour progression, as this process allows tumours to recruit new blood vessels and obtain oxygen and nutrients to sustain growth. Therefore, inhibiting angiogenesis remains a viable strategy for cancer therapy. However, anti-angiogenic therapy has not proved to be effective in reducing tumour growth across a wide range of tumours, and no reliable predictive biomarkers have been found to determine the efficacy of anti-angiogenic treatment. Using our previously established computational model of tumour-bearing mice, we sought to determine whether tumour growth kinetic parameters could be used to predict the outcome of anti-angiogenic treatment. A model trained with datasets from six mice studies was used to generate a randomized tumour-bearing mouse population. We analysed tumour growth in untreated mice (control) and mice treated with an anti-angiogenic agent and determined the Kaplan-Meier survival estimates based on simulated tumour volume data. We found that the ratio between two kinetic parameters, and , which characterize the tumour's exponential and linear growth rates, as well as alone, can be used as prognostic biomarkers of the population survival outcome. Our work demonstrates a robust, quantitative approach for identifying tumour growth kinetic parameters as prognostic biomarkers and serves as a template that can be used to identify other biomarkers for anti-angiogenic treatment.
血管生成是肿瘤进展的关键步骤，因为这个过程允许肿瘤招募新的血管，并获得氧气和营养物质来维持生长。因此，抑制血管生成仍然是癌症治疗的一种可行策略。然而，抗血管生成疗法在减少广泛的肿瘤生长方面并没有被证明是有效的，也没有找到可靠的预测生物标志物来确定抗血管生成治疗的疗效。我们使用之前建立的荷瘤小鼠计算模型，试图确定肿瘤生长动力学参数是否可以用于预测抗血管生成治疗的结果。一个用来自六只小鼠研究的数据训练的模型被用来生成一个随机的荷瘤小鼠群体。我们分析了未经治疗的小鼠（对照组）和用抗血管生成剂治疗的小鼠的肿瘤生长情况，并根据模拟的肿瘤体积数据确定了 Kaplan-Meier 生存估计。我们发现，两个动力学参数之间的比率， 和 ，分别描述了肿瘤的指数和线性增长率，以及 本身，可以作为群体生存结果的预后生物标志物。我们的工作证明了一种强大的、定量的方法，可以将肿瘤生长动力学参数作为预后生物标志物进行识别，并为识别其他抗血管生成治疗的生物标志物提供了模板。
