Gonçalves Inês G, García-Aznar José Manuel
Multiscale in Mechanical and Biological Engineering, Department of Mechanical Engineering, Aragon Institute of Engineering Research (I3A), University of Zaragoza, Zaragoza 50018, Aragon, Spain.
Comput Struct Biotechnol J. 2023 Feb 1;21:1262-1271. doi: 10.1016/j.csbj.2023.01.044. eCollection 2023.
Cancer cells metabolize glucose through metabolic pathways that differ from those used by healthy and differentiated cells. In particular, tumours have been shown to consume more glucose than their healthy counterparts and to use anaerobic metabolic pathways, even under aerobic conditions. Nevertheless, scientists have still not been able to explain why cancer cells evolved to present an altered metabolism and what evolutionary advantage this might provide them. Experimental and computational models have been increasingly used in recent years to understand some of these biological questions. Multicellular tumour spheroids are effective experimental models as they replicate the initial stages of avascular solid tumour growth. Furthermore, these experiments generate data which can be used to calibrate and validate computational studies that aim to simulate tumour growth. Hybrid models are of particular relevance in this field of research because they model cells as individual agents while also incorporating continuum representations of the substances present in the surrounding microenvironment that may participate in intracellular metabolic networks as concentration or density distributions. Henceforth, in this review, we explore the potential of computational modelling to reveal the role of metabolic reprogramming in tumour growth.
癌细胞通过与健康分化细胞不同的代谢途径代谢葡萄糖。特别是，已表明肿瘤比其健康对应物消耗更多的葡萄糖，并且即使在有氧条件下也使用无氧代谢途径。然而，科学家们仍然无法解释癌细胞为何进化出改变的代谢方式，以及这可能为它们提供何种进化优势。近年来，实验模型和计算模型越来越多地用于理解其中一些生物学问题。多细胞肿瘤球体是有效的实验模型，因为它们复制了无血管实体肿瘤生长的初始阶段。此外，这些实验产生的数据可用于校准和验证旨在模拟肿瘤生长的计算研究。混合模型在这一研究领域特别相关，因为它们将细胞建模为个体代理，同时还纳入了周围微环境中可能作为浓度或密度分布参与细胞内代谢网络的物质的连续表示。从今以后，在本综述中，我们探讨计算建模揭示代谢重编程在肿瘤生长中的作用的潜力。
