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从核心回路量化上皮-间质转化的格局和动力学路径。

Quantifying the landscape and kinetic paths for epithelial-mesenchymal transition from a core circuit.

作者信息

Li Chunhe, Hong Tian, Nie Qing

机构信息

Department of Mathematics, University of California, Irvine, Irvine, CA, USA.

出版信息

Phys Chem Chem Phys. 2016 Jul 21;18(27):17949-56. doi: 10.1039/c6cp03174a. Epub 2016 Jun 21.

Abstract

Epithelial-mesenchymal transition (EMT), as a crucial process in embryonic development and cancer metastasis, has been investigated extensively. However, how to quantify the global stability and transition dynamics for EMT under fluctuations remains to be elucidated. Starting from a core EMT genetic circuit composed of three key proteins or microRNAs (microRNA-200, ZEB and SNAIL), we uncovered the potential landscape for the EMT process. Three attractors emerge from the landscape, which correspond to epithelial, mesenchymal and partial EMT states respectively. Based on the landscape, we analyzed two important quantities of the EMT system: the barrier heights between different basins of attraction that describe the degree of difficulty for EMT or backward transition, and the mean first passage time (MFPT) that characterizes the kinetic transition rate. These quantities can be harnessed as measurements for the stability of cell types and the degree of difficulty of transitions between different cell types. We also calculated the minimum action paths (MAPs) by path integral approaches. The MAP delineates the transition processes between different cell types quantitatively. We propose two different EMT processes: a direct EMT from E to P, and a step-wise EMT going through an intermediate state, depending on different extracellular environments. The landscape and kinetic paths we acquired offer a new physical and quantitative way for understanding the mechanisms of EMT processes, and indicate the possible roles for the intermediate states.

摘要

上皮-间质转化(EMT)作为胚胎发育和癌症转移中的一个关键过程,已得到广泛研究。然而,如何在波动情况下量化EMT的全局稳定性和转变动力学仍有待阐明。从由三种关键蛋白质或微小RNA(微小RNA-200、ZEB和SNAIL)组成的核心EMT基因回路出发,我们揭示了EMT过程的潜在态势。该态势中出现了三个吸引子,分别对应上皮、间质和部分EMT状态。基于此态势,我们分析了EMT系统的两个重要量:不同吸引子盆地之间的势垒高度,它描述了EMT或逆向转变的难度程度;以及平均首次通过时间(MFPT),它表征了动力学转变速率。这些量可作为细胞类型稳定性和不同细胞类型之间转变难度程度的度量。我们还通过路径积分方法计算了最小作用路径(MAPs)。MAP定量地描绘了不同细胞类型之间的转变过程。我们提出了两种不同的EMT过程:一种是从E到P的直接EMT,另一种是根据不同的细胞外环境经历中间状态的逐步EMT。我们获得的态势和动力学路径为理解EMT过程的机制提供了一种新的物理和定量方法,并指出了中间状态的可能作用。

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本文引用的文献

1
An Ovol2-Zeb1 Mutual Inhibitory Circuit Governs Bidirectional and Multi-step Transition between Epithelial and Mesenchymal States.
PLoS Comput Biol. 2015 Nov 10;11(11):e1004569. doi: 10.1371/journal.pcbi.1004569. eCollection 2015 Nov.
2
DNA-Binding Kinetics Determines the Mechanism of Noise-Induced Switching in Gene Networks.
Biophys J. 2015 Oct 20;109(8):1746-57. doi: 10.1016/j.bpj.2015.08.035.
3
Coupling the modules of EMT and stemness: A tunable 'stemness window' model.
Oncotarget. 2015 Sep 22;6(28):25161-74. doi: 10.18632/oncotarget.4629.
4
Stemness of the hybrid Epithelial/Mesenchymal State in Breast Cancer and Its Association with Poor Survival.
PLoS One. 2015 May 28;10(5):e0126522. doi: 10.1371/journal.pone.0126522. eCollection 2015.
5
Semi-adaptive response and noise attenuation in bone morphogenetic protein signalling.
J R Soc Interface. 2015 Jun 6;12(107). doi: 10.1098/rsif.2015.0258.
6
Quantifying the Landscape for Development and Cancer from a Core Cancer Stem Cell Circuit.
Cancer Res. 2015 Jul 1;75(13):2607-18. doi: 10.1158/0008-5472.CAN-15-0079. Epub 2015 May 13.
8
Quantifying the underlying landscape and paths of cancer.
J R Soc Interface. 2014 Nov 6;11(100):20140774. doi: 10.1098/rsif.2014.0774.
9
Landscape and flux reveal a new global view and physical quantification of mammalian cell cycle.
Proc Natl Acad Sci U S A. 2014 Sep 30;111(39):14130-5. doi: 10.1073/pnas.1408628111. Epub 2014 Sep 16.
10
Mathematical models of the transitions between endocrine therapy responsive and resistant states in breast cancer.
J R Soc Interface. 2014 May 7;11(96):20140206. doi: 10.1098/rsif.2014.0206. Print 2014 Jul 6.

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