Grizzi Fabio, Di Ieva Antonio, Russo Carlo, Frezza Eldo E, Cobos Everardo, Muzzio Pier Carlo, Chiriva-Internati Maurizio
Laboratories of Quantitative Medicine, Istituto Clinico Humanitas IRCCS, Via Manzoni 56, 20089 Rozzano, Milan, Italy.
Theor Biol Med Model. 2006 Oct 17;3:37. doi: 10.1186/1742-4682-3-37.
Cancer remains one of the most complex diseases affecting humans and, despite the impressive advances that have been made in molecular and cell biology, how cancer cells progress through carcinogenesis and acquire their metastatic ability is still widely debated.
There is no doubt that human carcinogenesis is a dynamic process that depends on a large number of variables and is regulated at multiple spatial and temporal scales. Viewing cancer as a system that is dynamically complex in time and space will, however, probably reveal more about its underlying behavioural characteristics. It is encouraging that mathematicians, biologists and clinicians continue to contribute together towards a common quantitative understanding of cancer complexity. This way of thinking may further help to clarify concepts, interpret new and old experimental data, indicate alternative experiments and categorize the acquired knowledge on the basis of the similarities and/or shared behaviours of very different tumours.
癌症仍然是影响人类的最复杂疾病之一，尽管在分子和细胞生物学方面已经取得了令人瞩目的进展，但癌细胞如何通过致癌作用发展并获得转移能力仍存在广泛争议。
毫无疑问，人类致癌作用是一个动态过程，它取决于大量变量，并在多个空间和时间尺度上受到调节。然而，将癌症视为一个在时间和空间上动态复杂的系统，可能会揭示更多关于其潜在行为特征的信息。令人鼓舞的是，数学家、生物学家和临床医生继续共同努力，以实现对癌症复杂性的共同定量理解。这种思维方式可能进一步有助于澄清概念、解释新旧实验数据、指明替代实验，并根据非常不同肿瘤的相似性和/或共同行为对所获得的知识进行分类。
