Institute for Systems Biology, Seattle WA, USA.
Semin Cancer Biol. 2013 Aug;23(4):270-8. doi: 10.1016/j.semcancer.2013.06.003. Epub 2013 Jun 20.
The increasingly evident limitations of target-selective cancer therapy has stimulated a flurry of ideas for overcoming the development of resistance and recurrence - the near universal reason for therapy failure from which target-selective drugs are not exempt. A widely proposed approach to conquer therapy resistance is to depart from the myopic focus on individual causal pathways and instead target multiple nodes in the cancer cell's gene regulatory network. However, most ideas rely on a simplistic conceptualization of networks: utilizing solely their topology and treating it as a display of causal interactions, while ignoring the integrated dynamics in state space. Here, we review the more encompassing formal framework of global network dynamics in which cancer cells, like normal cell types, are high-dimensional attractor states. Then therapy is represented by the network perturbation that will promote the exit from such cancer attractors and reentering a normal attractor. We show in this qualitative and accessible discussion how the idea of a quasi-potential landscape and the theory of least-action-path offer a new formal understanding for computing the set of network nodes (molecular targets) that need to be targeted in concert in order to exit the cancer attractor. But targeting cancer cells based on the network configuration of an "average" cancer cell, however precise, may not suffice to eradicate all tumor cells because of the dynamic non-genetic heterogeneity of cancer cell populations that makes them moving targets and drives the replenishment of the cancer attractor with surviving, non-responsive cells from neighboring abnormal attractors.
日益明显的肿瘤靶向治疗局限性，刺激了人们提出各种想法来克服耐药性和复发的问题——这几乎是靶向药物治疗失败的普遍原因。克服耐药性的一种广泛提出的方法是，不局限于对单一因果途径的短视关注，而是针对癌细胞基因调控网络中的多个节点。然而，大多数想法依赖于对网络的简单概念化：仅利用其拓扑结构，并将其视为因果相互作用的显示，而忽略了状态空间中的综合动态。在这里，我们回顾了更全面的全局网络动态形式框架，其中癌细胞与正常细胞类型一样，是高维吸引子状态。然后，治疗由网络扰动表示，该扰动将促进从这种癌细胞吸引子中退出并重新进入正常吸引子。在这个定性和易于理解的讨论中，我们展示了准势能景观的思想和最小作用量路径理论如何为计算需要协同靶向的网络节点（分子靶标）集提供新的形式理解，以便从癌细胞吸引子中退出。但是，基于“平均”癌细胞的网络配置来靶向癌细胞，无论多么精确，可能不足以消除所有肿瘤细胞，因为癌细胞群体的动态非遗传异质性使它们成为移动目标，并驱动具有生存能力、无反应性的细胞从相邻异常吸引子中补充癌细胞吸引子。
