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）是将上皮细胞转化为间充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前景。我们在景观上确定了四个稳态吸引子，分别描述了抗转移（A），转移（M）和另外两个中间（I1和I2）细胞状态的特征。四稳态态势和中间状态的存在与最近的单细胞测量一致。我们将两个中间状态I1之一确定为EMT状态。通过MAP方法，我们发现，对于转移性进展，细胞需要首先经历EMT（进入I1状态），然后变为转移性（从I1状态转换为M状态）。具体而言，对于转移性进展，应在转移基因（例如BACH1）之前激活EMT基因（例如ZEB）。这表明时间顺序对于激活生物系统中的细胞程序很重要，并提供了促进EMT促进癌症转移的可能机制。为了从这种景观角度确定可能的治疗目标，我们对单个分子因素进行了敏感性分析，并确定了景观控制的最佳干预措施。我们发现，与单因素敏感性分析相比，最小化过渡动作可以更有效地识别诱导吸引物之间过渡的目标最佳组合。