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构建抑瘤网络对有丝分裂原和致癌信号响应的模型。

Modeling the response of a tumor-suppressive network to mitogenic and oncogenic signals.

机构信息

National Laboratory of Solid State Microstructures, Nanjing University, Nanjing 210093, China.

Department of Physics, Nanjing University, Nanjing 210093, China.

出版信息

Proc Natl Acad Sci U S A. 2017 May 23;114(21):5337-5342. doi: 10.1073/pnas.1702412114. Epub 2017 May 8.

Abstract

Intrinsic tumor-suppressive mechanisms protect normal cells against aberrant proliferation. Although cellular signaling pathways engaged in tumor repression have been largely identified, how they are orchestrated to fulfill their function still remains elusive. Here, we built a tumor-suppressive network model composed of three modules responsible for the regulation of cell proliferation, activation of p53, and induction of apoptosis. Numerical simulations show a rich repertoire of network dynamics when normal cells are subject to serum stimulation and adenovirus E1A overexpression. We showed that oncogenic signaling induces ARF and that ARF further promotes p53 activation to inhibit proliferation. Mitogenic signaling activates E2F activators and promotes Akt activation. p53 and E2F1 cooperate to induce apoptosis, whereas Akt phosphorylates p21 to repress caspase activation. These prosurvival and proapoptotic signals compete to dictate the cell fate of proliferation, cell-cycle arrest, or apoptosis. The cellular outcome is also impacted by the kinetic mode (ultrasensitivity or bistability) of p53. When cells are exposed to serum deprivation and recovery under fixed E1A, the shortest starvation time required for apoptosis induction depends on the terminal serum concentration, which was interpreted in terms of the dynamics of caspase-3 activation and cytochrome release. We discovered that caspase-3 can be maintained active at high serum concentrations and that E1A overexpression sensitizes serum-starved cells to apoptosis. This work elucidates the roles of tumor repressors and prosurvival factors in tumor repression based on a dynamic network analysis and provides a framework for quantitatively exploring tumor-suppressive mechanisms.

摘要

内在的肿瘤抑制机制保护正常细胞免受异常增殖。虽然参与肿瘤抑制的细胞信号通路已被广泛鉴定,但它们如何协调发挥作用仍不清楚。在这里,我们构建了一个由三个模块组成的肿瘤抑制网络模型,负责调节细胞增殖、激活 p53 和诱导细胞凋亡。数值模拟表明,当正常细胞受到血清刺激和腺病毒 E1A 过表达时,网络会呈现出丰富的动力学变化。我们表明,致癌信号诱导 ARF,而 ARF 进一步促进 p53 激活以抑制增殖。有丝分裂信号激活 E2F 激活剂并促进 Akt 激活。p53 和 E2F1 协同诱导细胞凋亡,而 Akt 磷酸化 p21 以抑制半胱氨酸蛋白酶激活。这些促进生存和促凋亡信号相互竞争,决定细胞增殖、细胞周期停滞或凋亡的命运。细胞的结果也受到 p53 的动力学模式(超敏性或双稳性)的影响。当细胞在固定 E1A 下经历血清剥夺和恢复时,诱导细胞凋亡所需的最短饥饿时间取决于终末血清浓度,这可以从 caspase-3 激活和细胞色素 c 释放的动力学来解释。我们发现 caspase-3 可以在高血清浓度下保持活性,并且 E1A 过表达使血清饥饿的细胞对细胞凋亡敏感。这项工作基于动态网络分析阐明了肿瘤抑制因子和促进生存因子在肿瘤抑制中的作用,并为定量探索肿瘤抑制机制提供了框架。

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