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首页> 外文会议>IEEE International Conference on BioInformatics and BioEngineering >Translating Multiscale Cancer Models into Clinical Trials: Simulating Breast Cancer Tumor Dynamics within the Framework of the 'Trial of Principle' Clinical Trial and the ACGT Project
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Translating Multiscale Cancer Models into Clinical Trials: Simulating Breast Cancer Tumor Dynamics within the Framework of the 'Trial of Principle' Clinical Trial and the ACGT Project

机译：将MultiSscale癌症模型转化为临床试验：在“原理试验”临床试验和ACGT项目的框架内模拟乳腺癌肿瘤动态

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The potential of cancer multilevel modeling has been particularly emphasized over the past years. Integration of multiscale experimental and clinical information pertaining to cancer via advanced computer models seems to considerably accelerate optimization of cancer treatment in the patient individualized context. However, a sine qua non prerequisite for such models to reach clinical practice is to be thoroughly tested through clinical trials for validation and optimization purposes. This is one of the major goals of the European Commission funded "Advancing Clinico-Genomic Trials on Cancer" (ACGT) project. This paper presents a discrete state based, four dimensional, multiscale tumor dynamics model that has been specially developed by the In Silico Oncology Group in order to mimick the Trial Of Principle (TOP) clinical trial concerning breast cancer treated with epirubicin. The TOP trial constitutes one of the ACGT clinical trials. A substantial part of the model can address other tumor types as well. The actual pseudoanonymized imaging, histopathological, molecular and clinical data of the patient are exploited. Special emphasis is put on the effect of cancer stem/clonogenic, progenitor, differentiated and dead cells, the cell category transition rates and the cell category relative populations within the tumor from the treatment baseline onwards. The importance of adaptation of the cell category relative populations to the cell category transition rates for free tumor growth is revealed and the concept of a pertinent nomogram is introduced. A method which ensures adaptation of these two sets of entities at the beginning of the simulation execution is proposed and subsequently successfully applied. Convergence and code checking issues are addressed. Indicative parametric/sensitivity studies are presented along with specific numerical findings. The model's behavior substantiates its potential to serve as the basis of a treatment optimization system following an eventually succesful completion of the clinical validation and optimization process.
机译：在过去几年中特别强调了癌症多级建模的潜力。通过先进的计算机模型与癌症有关的多尺度实验和临床信息的整合似乎在患者个性化背景下大大加速了癌症治疗的优化。然而，通过临床试验彻底测试临床实践的这种模型的正弦值，以验证和优化目的进行彻底测试。这是欧盟委员会资助的主要目标之一“推进癌症临床 - 基因组试验”（ACGT）项目。本文介绍了基于离散的状态，四维多尺度肿瘤动力学模型，该模型由Silico肿瘤学组专门开发，以模仿原则（顶部）临床试验的试验，该试验有关于与表腹酸处理的乳腺癌。最高试验构成了ACGT临床试验之一。模型的大部分也可以解决其他肿瘤类型。利用患者的实际假匿的成像，组织病理学，分子和临床数据。特别强调癌症茎/克隆因，祖细胞，分化和死细胞，细胞类转换率和肿瘤内的细胞类别相对群体的影响，从治疗基线开始。揭示了细胞类别相对群体对细胞类别转变率的自由肿瘤生长的重要性，并介绍了相关的NOM图的概念。提出了一种方法，其在模拟执行开始时确保了这两组实体的调整，并随后成功应用了。融合和代码检查问题已解决。表明参数/敏感性研究以及特定的数值发现呈现。该模型的行为证实其潜力作为在最终成功完成临床验证和优化过程之后作为治疗优化系统的基础。

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