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癌症中的信号转导网络:定量参数影响网络拓扑。

Signal transduction networks in cancer: quantitative parameters influence network topology.

机构信息

Department of Chemical Engineering, West Virginia University, Morgantown, West Virginia 26506, USA.

出版信息

Cancer Res. 2010 Mar 1;70(5):1773-82. doi: 10.1158/0008-5472.CAN-09-3234. Epub 2010 Feb 23.

Abstract

Networks of fixed topology are used to summarize the collective understanding of the flow of signaling information within a cell (i.e., canonical signaling networks). Moreover, these canonical signaling networks are used to interpret how observed oncogenic changes in protein activity or expression alter information flow in cancer cells. However, creating a novel branch within a signaling network (i.e., a noncanonical edge) provides a mechanism for a cell to acquire the hallmark characteristics of cancer. The objective of this study was to assess the existence of a noncanonical edge within a receptor tyrosine kinase (RTK) signaling network based upon variation in protein expression alone, using a mathematical model of the early signaling events associated with epidermal growth factor receptor 1 (ErbB1) signaling network as an illustrative example. The abundance of canonical protein-RTK complexes (e.g., growth factor receptor bound protein 2-ErbB1 and Src homology 2 domain containing transforming protein 1-ErbB1) were used to establish a threshold that was correlated with ligand-dependent changes in cell proliferation. Given the available data, the uncertainty associated with this threshold was estimated using an empirical Bayesian approach. Using the variability in protein expression observed among a collection of breast cancer cell lines, this model was used to assess whether a noncanonical edge (e.g., Irs1-ErbB1) exceeds the threshold and to identify cell lines where this noncanonical edge is likely to be observed. Taken together, the simulations suggest that the topology of signal transduction networks within cells is influenced by quantitative parameters, such as protein expression and binding affinity. Moreover, forming this noncanonical pathway was not due solely to overexpression of the cell surface receptor but was influenced by overexpression of all members of the multiprotein complex. Multivariate alterations in expression of signaling proteins in cancer cells may activate noncanonical pathways and may rewire the signaling network within a cell.

摘要

固定拓扑网络用于总结细胞内信号信息流动的集体理解(即,典型信号网络)。此外,这些典型信号网络用于解释观察到的蛋白质活性或表达的致癌变化如何改变癌细胞中的信息流。然而,在信号网络中创建新分支(即非典型边缘)为细胞提供了获得癌症标志性特征的机制。本研究的目的是评估基于蛋白质表达的变化,在受体酪氨酸激酶(RTK)信号网络中是否存在非典型边缘,使用表皮生长因子受体 1(ErbB1)信号网络的早期信号事件的数学模型作为说明性示例。典型的蛋白-RTK 复合物(例如生长因子受体结合蛋白 2-ErbB1 和含 SH2 结构域的转化蛋白 1-ErbB1)的丰度用于建立与配体依赖性细胞增殖变化相关的阈值。鉴于现有数据,使用经验贝叶斯方法估计与该阈值相关的不确定性。利用一系列乳腺癌细胞系中观察到的蛋白质表达变异性,该模型用于评估非典型边缘(例如 Irs1-ErbB1)是否超过阈值,并识别可能观察到该非典型边缘的细胞系。总之,模拟表明细胞内信号转导网络的拓扑结构受定量参数的影响,例如蛋白质表达和结合亲和力。此外,形成这种非典型途径不仅仅是由于细胞表面受体的过表达,而是受到多蛋白复合物所有成员过表达的影响。癌细胞中信号蛋白表达的多变量改变可能会激活非典型途径,并可能重新布线细胞内的信号网络。

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