Li Chunhe, Balazsi Gabor
1Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China.
2Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
NPJ Syst Biol Appl. 2018 Aug 23;4:34. doi: 10.1038/s41540-018-0068-x. eCollection 2018.
The epithelial-mesenchymal transition (EMT) is a basic developmental process that converts epithelial cells to mesenchymal cells. Although EMT might promote cancer metastasis, the molecular mechanisms for it remain to be fully clarified. To address this issue, we constructed an EMT-metastasis gene regulatory network model and quantified the potential landscape of cancer metastasis-promoting system computationally. We identified four steady-state attractors on the landscape, which separately characterize anti-metastatic (A), metastatic (M), and two other intermediate (I1 and I2) cell states. The tetrastable landscape and the existence of intermediate states are consistent with recent single-cell measurements. We identified one of the two intermediate states I1 as the EMT state. From a MAP approach, we found that for metastatic progression cells need to first undergo EMT (enter the I1 state), and then become metastatic (switch from the I1 state to the M state). Specifically, for metastatic progression, EMT genes (such as ZEB) should be activated before metastasis genes (such as BACH1). This suggests that temporal order is important for the activation of cellular programs in biological systems, and provides a possible mechanism of EMT-promoting cancer metastasis. To identify possible therapeutic targets from this landscape view, we performed sensitivity analysis for individual molecular factors, and identified optimal interventions for landscape control. We found that minimizing transition actions more effectively identifies optimal combinations of targets that induce transitions between attractors than single-factor sensitivity analysis. Overall, the landscape view not only suggests that intermediate states increase plasticity during cell fate decisions, providing a possible source for tumor heterogeneity that is critically important in metastatic progress, but also provides a way to identify therapeutic targets for preventing cancer progression.
上皮-间质转化（EMT）是一个将上皮细胞转化为间质细胞的基本发育过程。尽管EMT可能促进癌症转移，但其分子机制仍有待充分阐明。为了解决这个问题，我们构建了一个EMT-转移基因调控网络模型，并通过计算量化了癌症转移促进系统的潜在态势。我们在该态势上识别出四个稳态吸引子，它们分别表征抗转移（A）、转移（M）以及另外两种中间（I1和I2）细胞状态。四稳态态势以及中间状态的存在与最近的单细胞测量结果一致。我们将两个中间状态之一的I1识别为EMT状态。从映射方法来看，我们发现对于转移进展，细胞需要首先经历EMT（进入I1状态），然后变为转移状态（从I1状态切换到M状态）。具体而言，对于转移进展，EMT基因（如ZEB）应在转移基因（如BACH1）之前被激活。这表明时间顺序对于生物系统中细胞程序的激活很重要，并提供了一种EMT促进癌症转移的可能机制。为了从这种态势视角识别可能的治疗靶点，我们对各个分子因素进行了敏感性分析，并确定了用于态势控制的最佳干预措施。我们发现，与单因素敏感性分析相比，最小化转变作用能更有效地识别诱导吸引子之间转变的靶点最佳组合。总体而言，这种态势视角不仅表明中间状态在细胞命运决定过程中增加了可塑性，为转移进展中至关重要的肿瘤异质性提供了一个可能来源，还提供了一种识别预防癌症进展治疗靶点的方法。
