Institute of Biophysics and Department of Physics, Central China Normal University, Wuhan, 430079, China.
Department of Mathematics and Physics, Xuzhou Medical University, Xuzhou, 221004, China.
Sci Rep. 2017 Aug 29;7(1):9890. doi: 10.1038/s41598-017-10321-1.
Quantitative modeling of microscopic genes regulatory mechanisms in an individual cell is a crucial step towards understanding various macroscopic physiological phenomena of cell populations. Based on the regulatory mechanisms of genes zeb1 and cdh1 in the growth and development of breast cancer cells, we propose a kinetic model at the level of single cell. By constructing the effective landscape of underlying stationary probability for the genes expressions, it is found that (i) each breast cancer cell has three phenotypic states (i.e., the stem-like, basal, and luminal states) which correspond to three attractions of the probability landscape. (ii) The interconversions between phenotypic states can be induced by the noise intensity and the property of phenotypic switching is quantified by the mean first-passage time. (iii) Under certain conditions, the probabilities of each cancer cell appearing in the three states are consistent with the macroscopic phenotypic equilibrium proportions in the breast cancer SUM159 cell line. (iv) Our kinetic model involving the TGF-β signal can also qualitatively explain several macroscopic physiological phenomena of breast cancer cells, such as the "TGF-β paradox" in tumor therapy, the five clinical subtypes of breast cancer cells, and the effects of transient TGF-β on breast cancer metastasis.
在单个细胞中对微观基因调控机制进行定量建模是理解细胞群体各种宏观生理现象的关键步骤。基于基因 zeb1 和 cdh1 在乳腺癌细胞生长和发育中的调控机制，我们提出了一个单细胞水平的动力学模型。通过构建基因表达的潜在静止概率有效景观，发现：(i) 每个乳腺癌细胞具有三种表型状态（即干细胞样、基底样和腔细胞样状态），它们对应于概率景观的三个吸引力。(ii) 表型状态之间的转换可以由噪声强度诱导，并且表型转换的性质可以通过平均首次通过时间来量化。(iii) 在某些条件下，三种状态中每个癌细胞出现的概率与乳腺癌 SUM159 细胞系中的宏观表型平衡比例一致。(iv) 我们涉及 TGF-β 信号的动力学模型还可以定性地解释乳腺癌细胞的几种宏观生理现象，例如肿瘤治疗中的“TGF-β 悖论”、乳腺癌细胞的五个临床亚型以及瞬态 TGF-β 对乳腺癌转移的影响。
