Department of Oncology, Georgetown University Medical Center, 3970 Reservoir Rd NW, Washington, DC, 20057, USA.
Hormel Institute and Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Austin, MN, 55912, USA.
Cancer Metastasis Rev. 2020 Sep;39(3):903-918. doi: 10.1007/s10555-020-09921-7. Epub 2020 Aug 10.
Total metastatic burden is the primary cause of death for many cancer patients. While the process of metastasis has been studied widely, much remains to be understood. Moreover, few agents have been developed that specifically target the major steps of the metastatic cascade. Many individual genes and pathways have been implicated in metastasis but a holistic view of how these interact and cooperate to regulate and execute the process remains somewhat rudimentary. It is unclear whether all of the signaling features that regulate and execute metastasis are yet fully understood. Novel features of a complex system such as metastasis can often be discovered by taking a systems-based approach. We introduce the concepts of systems modeling and define some of the central challenges facing the application of a multidisciplinary systems-based approach to understanding metastasis and finding actionable targets therein. These challenges include appreciating the unique properties of the high-dimensional omics data often used for modeling, limitations in knowledge of the system (metastasis), tumor heterogeneity and sampling bias, and some of the issues key to understanding critical features of molecular signaling in the context of metastasis. We also provide a brief introduction to integrative modeling that focuses on both the nodes and edges of molecular signaling networks. Finally, we offer some observations on future directions as they relate to developing a systems-based model of the metastatic cascade.
总的转移负担是许多癌症患者死亡的主要原因。虽然转移过程已经被广泛研究,但仍有许多问题需要了解。此外,开发出专门针对转移级联主要步骤的药物很少。许多单个基因和途径都与转移有关,但对于这些基因和途径如何相互作用和合作来调节和执行该过程的整体观点仍然有些初步。目前尚不清楚是否已经完全了解调节和执行转移的所有信号特征。复杂系统(如转移)的新特征通常可以通过系统方法来发现。我们介绍了系统建模的概念,并定义了应用多学科系统方法来理解转移并在其中找到可操作的靶点所面临的一些核心挑战。这些挑战包括理解通常用于建模的高维组学数据的独特性质、对系统(转移)的知识有限、肿瘤异质性和采样偏差,以及理解转移背景下分子信号关键特征的一些关键问题。我们还简要介绍了关注分子信号网络节点和边缘的综合建模。最后,我们就与开发转移级联系统模型相关的未来方向提出了一些观察意见。