Ponce-de-Leon Miguel, Montagud Arnau, Akasiadis Charilaos, Schreiber Janina, Ntiniakou Thaleia, Valencia Alfonso
Barcelona Supercomputing Center (BSC), Barcelona, Spain.
Institute of Informatics and Telecommunications, NCSR "Demokritos", Agia Paraskevi, Greece.
Front Mol Biosci. 2022 Apr 6;9:836794. doi: 10.3389/fmolb.2022.836794. eCollection 2022.
The emergence of cell resistance in cancer treatment is a complex phenomenon that emerges from the interplay of processes that occur at different scales. For instance, molecular mechanisms and population-level dynamics such as competition and cell-cell variability have been described as playing a key role in the emergence and evolution of cell resistances. Multi-scale models are a useful tool for studying biology at very different times and spatial scales, as they can integrate different processes occurring at the molecular, cellular, and intercellular levels. In the present work, we use an extended hybrid multi-scale model of 3T3 fibroblast spheroid to perform a deep exploration of the parameter space of effective treatment strategies based on TNF pulses. To explore the parameter space of effective treatments in different scenarios and conditions, we have developed an HPC-optimized model exploration workflow based on EMEWS. We first studied the effect of the cells' spatial distribution in the values of the treatment parameters by optimizing the supply strategies in 2D monolayers and 3D spheroids of different sizes. We later study the robustness of the effective treatments when heterogeneous populations of cells are considered. We found that our model exploration workflow can find effective treatments in all the studied conditions. Our results show that cells' spatial geometry and population variability should be considered when optimizing treatment strategies in order to find robust parameter sets.
癌症治疗中细胞耐药性的出现是一种复杂的现象，它源于不同尺度上发生的过程之间的相互作用。例如，分子机制以及群体水平的动态变化，如竞争和细胞间变异性，被认为在细胞耐药性的出现和演变中起着关键作用。多尺度模型是在非常不同的时间和空间尺度上研究生物学的有用工具，因为它们可以整合在分子、细胞和细胞间水平上发生的不同过程。在本研究中，我们使用3T3成纤维细胞球体的扩展混合多尺度模型，对基于肿瘤坏死因子（TNF）脉冲的有效治疗策略的参数空间进行深入探索。为了探索不同场景和条件下有效治疗的参数空间，我们基于EMEWS开发了一种高性能计算（HPC）优化的模型探索工作流程。我们首先通过优化不同大小的二维单层和三维球体中的给药策略，研究了细胞空间分布对治疗参数值的影响。随后，我们研究了考虑细胞异质性群体时有效治疗的稳健性。我们发现，我们的模型探索工作流程能够在所有研究条件下找到有效的治疗方法。我们的结果表明，在优化治疗策略时应考虑细胞的空间几何形状和群体变异性，以便找到稳健的参数集。
