Mathematical modeling of the Phoenix Rising pathway.
Mathematical modeling of the Phoenix Rising pathway.
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DOI：
10.1371/journal.pcbi.1003461
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发表时间：
2014-02
影响因子：
4.3
通讯作者：
Yuan F
中科院分区：
文献类型：
--
作者：
Liu C;Li CY;Yuan F
在哺乳动物细胞中，细胞凋亡是一个受到严格控制的过程。它对胚胎发育、组织动态平衡和癌症治疗都很重要。细胞凋亡不仅诱导细胞死亡，还通过凤凰上升(Phoenix Rise，PR)途径释放促进周围细胞快速增殖的信号。为了定量了解这一途径中不同分子相互作用的动力学，我们建立了一个数学模型来模拟PR途径的各种变化对前列腺素E2(PGE2)分泌的影响，前列腺素E2是促进细胞增殖的关键因素。这些变化包括Caspase3(C3)、Caspase7(C7)和核因子κB(NFκB)的激活。此外，我们还模拟了环氧合酶-2(COX2)抑制和C3基因敲除对PGE2分泌水平的影响。10-Gray照射后48小时PGE2在MEF和4T1细胞中的模型预测与文献中的实验数据定量一致。与C7相比，该模型预测C3的激活对PGE2的产生更为关键。该模型还预测，当COX2的表达通过核因子κB失活或用外源COX2抑制剂处理细胞时，前列腺素E_2的产量会显著减少，从而导致PR途径中花生四烯酸转化为前列腺素H2的速率降低。总而言之，这项研究中开发的数学模型为研究细胞凋亡信号刺激组织再生的过程提供了新的见解。在未来的研究中，该模型可以用于实验数据分析，并帮助开发新的策略/药物来改善癌症治疗或正常组织再生。众所周知，细胞凋亡或程序性细胞死亡对胚胎发育、组织稳态和癌症治疗都很重要。此外，研究人员最近观察到，细胞凋亡可能会促进伤口愈合和组织再生，并加速化疗/放射治疗后不受欢迎的实体肿瘤的再生长。细胞凋亡诱导组织再生的机制与我们实验室最近发现的一个分子网络有关。为了定量地理解这个网络中不同分子之间相互作用的动力学，我们建立了一个数学模型，并通过将模拟结果与以前研究中报道的实验数据进行比较来验证它。为了获得诱导细胞凋亡后组织再生过程的新见解，我们使用该模型来模拟辐射对凋亡细胞中关键的生长刺激因子PGE2产生的影响。此外，我们还模拟了当细胞被不同的抑制剂处理时，前列腺素E_2的产生如何改变。我们期望新的数学模型可以在未来的研究中使用，以促进设计更好的癌症治疗或正常组织再生的方法。
Apoptosis is a tightly controlled process in mammalian cells. It is important for embryogenesis, tissue homoeostasis, and cancer treatment. Apoptosis not only induces cell death, but also leads to the release of signals that promote rapid proliferation of surrounding cells through the Phoenix Rising (PR) pathway. To quantitatively understand the kinetics of interactions of different molecules in this pathway, we developed a mathematical model to simulate the effects of various changes in the PR pathway on the secretion of prostaglandin E2 (PGE2), a key factor for promoting cell proliferation. These changes include activation of caspase 3 (C3), caspase 7 (C7), and nuclear factor κB (NFκB). In addition, we simulated the effects of cyclooxygenase-2 (COX2) inhibition and C3 knockout on the level of secreted PGE2. The model predictions on PGE2 in MEF and 4T1 cells at 48 hours after 10-Gray radiation were quantitatively consistent with the experimental data in the literature. Compared to C7, the model predicted that C3 activation was more critical for PGE2 production. The model also predicted that PGE2 production could be significantly reduced when COX2 expression was blocked via either NFκB inactivation or treatment of cells with exogenous COX2 inhibitors, which led to a decrease in the rate of conversion from arachidonic acid to prostaglandin H2 in the PR pathway. In conclusion, the mathematical model developed in this study yielded new insights into the process of tissue regrowth stimulated by signals from apoptotic cells. In future studies, the model can be used for experimental data analysis and assisting development of novel strategies/drugs for improving cancer treatment or normal tissue regeneration. Apoptosis, or programmed cell death, is known to be important for embryogenesis, tissue homoeostasis, and cancer treatment. Furthermore, researchers have recently observed that apoptosis may promote wound healing and tissue regeneration, and accelerate undesired solid tumor regrowth after chemotherapy/radiation therapy. Mechanisms of apoptosis-induced tissue regrowth are related to a molecular network discovered recently in our lab. To quantitatively understand the kinetics of interactions of different molecules in this network, we developed a mathematical model and validated it by comparing the simulation results to experimental data reported in previous studies. To gain new insights into the process of tissue regrowth after inducing apoptosis, we used the model to simulate the effects of radiation on the production of a key growth stimulating factor, PGE2, in apoptotic cells. Additionally, we simulated how PGE2 production could be altered when cells were treated with different inhibitors. We expect that the new mathematical model can be used in future studies to facilitate design of better approaches to cancer treatment or normal tissue regeneration.
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影响因子：
7.3
作者：
Li F;Huang Q;Chen J;Peng Y;Roop DR;Bedford JS;Li CY
通讯作者：
Li CY
影响因子：
3.7
作者：
Schlatter R;Schmich K;Lutz A;Trefzger J;Sawodny O;Ederer M;Merfort I
通讯作者：
Merfort I
影响因子：
2
作者：
Sturrock, Marc;Terry, Alan J.;Chaplain, Mark A. J.
通讯作者：
Chaplain, Mark A. J.
影响因子：
2.6
作者：
MEYN, RE;STEPHENS, LC;PETERS, LJ
通讯作者：
PETERS, LJ
影响因子：
3.3
作者：
Cherian, PP;Siller-Jackson, AJ;Jiang, JX
通讯作者：
Jiang, JX