School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona, United States of America.
Key Laboratory of Systems Biology, Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China.
PLoS Comput Biol. 2020 Mar 10;16(3):e1007682. doi: 10.1371/journal.pcbi.1007682. eCollection 2020 Mar.
Epithelial-to-mesenchymal transition (EMT) is a fundamental cellular process and plays an essential role in development, tissue regeneration, and cancer metastasis. Interestingly, EMT is not a binary process but instead proceeds with multiple partial intermediate states. However, the functions of these intermediate states are not fully understood. Here, we focus on a general question about how the number of partial EMT states affects cell transformation. First, by fitting a hidden Markov model of EMT with experimental data, we propose a statistical mechanism for EMT in which many unobservable microstates may exist within one of the observable macrostates. Furthermore, we find that increasing the number of intermediate states can accelerate the EMT process and that adding parallel paths or transition layers may accelerate the process even further. Last, a stabilized intermediate state traps cells in one partial EMT state. This work advances our understanding of the dynamics and functions of EMT plasticity during cancer metastasis.
上皮-间充质转化（EMT）是一种基本的细胞过程，在发育、组织再生和癌症转移中起着至关重要的作用。有趣的是，EMT 不是一个二元过程，而是经历了多个部分中间状态。然而，这些中间状态的功能尚未完全理解。在这里，我们关注一个关于部分 EMT 状态数量如何影响细胞转化的一般问题。首先，通过用实验数据拟合 EMT 的隐马尔可夫模型，我们提出了一个 EMT 的统计机制，其中在一个可观察的宏观状态中可能存在许多不可观察的微观状态。此外，我们发现增加中间状态的数量可以加速 EMT 过程，并且添加并行路径或过渡层甚至可以进一步加速该过程。最后，一个稳定的中间状态会将细胞困在一个部分 EMT 状态中。这项工作推进了我们对癌症转移过程中 EMT 可塑性动力学和功能的理解。
