Laboratory of Biological Chemistry, Medical School, Aristotle University of Thessaloniki 54124, Thessaloniki, Greece.
Cancer Med. 2013 Apr;2(2):164-77. doi: 10.1002/cam4.62. Epub 2013 Feb 17.
Complex phenotypes emerge from the interactions of thousands of macromolecules that are organized in multimolecular complexes and interacting functional modules. In turn, modules form functional networks in health and disease. Omics approaches collect data on changes for all genes and proteins and statistical analysis attempts to uncover the functional modules that perform the functions that characterize higher levels of biological organization. Systems biology attempts to transcend the study of individual genes/proteins and to integrate them into higher order information. Cancer cells exhibit defective genetic and epigenetic networks formed by altered complexes and network modules arising in different parts of tumor tissues that sustain autonomous cell behavior which ultimately lead tumor growth. We suggest that an understanding of tumor behavior must address not only molecular but also, and more importantly, tumor cell heterogeneity, by considering cancer tissue genetic and epigenetic networks, by characterizing changes in the types, composition, and interactions of complexes and networks in the different parts of tumor tissues, and by identifying critical hubs that connect them in time and space.
复杂的表型是由数千种大分子相互作用而产生的，这些大分子在多分子复合物和相互作用的功能模块中进行组织。反过来，模块在健康和疾病中形成功能网络。组学方法收集所有基因和蛋白质变化的数据，统计分析试图揭示执行特征更高层次生物组织功能的功能模块。系统生物学试图超越对单个基因/蛋白质的研究，并将它们整合到更高阶的信息中。癌细胞表现出缺陷的遗传和表观遗传网络，这些网络由肿瘤组织不同部位产生的改变的复合物和网络模块形成，这些复合物和网络模块维持自主的细胞行为，最终导致肿瘤生长。我们认为，对肿瘤行为的理解不仅必须考虑分子，而且更重要的是，还必须考虑肿瘤细胞异质性，这可以通过考虑肿瘤组织的遗传和表观遗传网络，通过描述肿瘤组织不同部位复合物和网络的类型、组成和相互作用的变化，以及通过识别将它们在时间和空间上连接起来的关键枢纽来实现。
