School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, 110067, India.
Department of Chemistry, Indian Institute of Technology Delhi, New Delhi, 110016, India.
Sci Rep. 2021 Jan 27;11(1):2349. doi: 10.1038/s41598-021-82054-1.
We study a minimal model of the stress-driven p53 regulatory network that includes competition between active and mutant forms of the tumor-suppressor gene p53. Depending on the nature and level of the external stress signal, four distinct dynamical states of p53 are observed. These states can be distinguished by different dynamical properties which associate to active, apoptotic, pre-malignant and cancer states. Transitions between any two states, active, apoptotic, and cancer, are found to be unidirectional and irreversible if the stress signal is either oscillatory or constant. When the signal decays exponentially, the apoptotic state vanishes, and for low stress the pre-malignant state is bounded by two critical points, allowing the system to transition reversibly from the active to the pre-malignant state. For significantly large stress, the range of the pre-malignant state expands, and the system moves to irreversible cancerous state, which is a stable attractor. This suggests that identification of the pre-malignant state may be important both for therapeutic intervention as well as for drug delivery.
我们研究了一个应激驱动的 p53 调控网络的最小模型，该模型包括肿瘤抑制基因 p53 的活性形式和突变形式之间的竞争。根据外部应激信号的性质和水平，观察到 p53 的四种不同的动力学状态。这些状态可以通过与活性、凋亡、前恶性和癌症状态相关的不同动力学特性来区分。如果应激信号是振荡的或恒定的，那么在任何两个状态之间的转换，即活性、凋亡和癌症，都是单向的和不可逆的。当信号指数衰减时，凋亡状态消失，对于低应激，前恶性状态由两个临界点限制，允许系统从活性状态可逆地过渡到前恶性状态。对于显著大的应激，前恶性状态的范围扩大，系统进入不可逆的癌变状态，这是一个稳定的吸引子。这表明，前恶性状态的识别对于治疗干预和药物输送都可能很重要。
