非小细胞肺癌模型的跨尺度敏感性分析：分子信号特性与细胞行为的联系
Cross-Scale Sensitivity Analysis of a Non-Small Cell Lung Cancer Model: Linking Molecular Signaling Properties to Cellular Behavior
摘要：
敏感性分析是一种有效的工具，系统地确定特定的参数扰动，有显着影响的行为，一个给定的生物系统，在调查的规模。在这项工作中，使用一个二维的，多尺度的非小细胞肺癌（NSCLC）模型，我们研究了扰动的影响，系统参数跨越分子和细胞水平，即跨尺度的利益。这是通过首先将分子和细胞活动联系起来，然后评估分子水平上的参数对肿瘤时空扩张速率的影响来实现的，肿瘤时空扩张速率用作细胞水平上的输出行为。总体而言，该算法在大多数参数的相对较大变化下可靠地运行，因此证实了模型的稳健性。然而，三个途径组件（蛋白质PKC，MEK和ERK）和11个反应步骤被确定为至关重要的，通过采用灵敏度系数作为评价指标。这些敏感参数中的每一个都表现出类似的变化模式，因为其值的相对较大的增加或减少导致对系统的蜂窝性能的影响较小。这项研究提供了一种新的跨尺度的方法来分析计算模型参数的灵敏度，并提出了其跨学科的生物标志物研究的应用。
英文摘要：
Sensitivity analysis is an effective tool for systematically identifying specific perturbations in parameters that have significant effects on the behavior of a given biosystem, at the scale investigated. In this work, using a two-dimensional, multiscale non-small cell lung cancer (NSCLC) model, we examine the effects of perturbations in system parameters which span both molecular and cellular levels, i.e. across scales of interest. This is achieved by first linking molecular and cellular activities and then assessing the influence of parameters at the molecular level on the tumor's spatio-temporal expansion rate, which serves as the output behavior at the cellular level. Overall, the algorithm operated reliably over relatively large variations of most parameters, hence confirming the robustness of the model. However, three pathway components (proteins PKC, MEK, and ERK) and eleven reaction steps were determined to be of critical importance by employing a sensitivity coefficient as an evaluation index. Each of these sensitive parameters exhibited a similar changing pattern in that a relatively larger increase or decrease in its value resulted in a lesser influence on the system's cellular performance. This study provides a novel cross-scaled approach to analyzing sensitivities of computational model parameters and proposes its application to interdisciplinary biomarker studies.
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