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用于复杂分数阶杀伤的动力学框架。

A dynamical framework for complex fractional killing.

机构信息

Department of Molecular and Cellular Physiology, College of Medicine, University of Cincinnati, Cincinnati, OH, USA.

Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ, USA.

出版信息

Sci Rep. 2017 Aug 14;7(1):8002. doi: 10.1038/s41598-017-07422-2.

Abstract

When chemotherapy drugs are applied to tumor cells with the same or similar genotypes, some cells are killed, while others survive. This fractional killing contributes to drug resistance in cancer. Through an incoherent feedforward loop, chemotherapy drugs not only activate p53 to induce cell death, but also promote the expression of apoptosis inhibitors which inhibit cell death. Consequently, cells in which p53 is activated early undergo apoptosis while cells in which p53 is activated late survive. The incoherent feedforward loop and the essential role of p53 activation timing makes fractional killing a complex dynamical challenge, which is hard to understand with intuition alone. To better understand this process, we have constructed a representative model by integrating the control of apoptosis with the relevant signaling pathways. After the model was trained to recapture the observed properties of fractional killing, it was analyzed with nonlinear dynamical tools. The analysis suggested a simple dynamical framework for fractional killing, which predicts that cell fate can be altered in three possible ways: alteration of bifurcation geometry, alteration of cell trajectories, or both. These predicted categories can explain existing strategies known to combat fractional killing and facilitate the design of novel strategies.

摘要

当化疗药物应用于具有相同或相似基因型的肿瘤细胞时,一些细胞被杀死,而另一些细胞存活。这种分数杀伤导致了癌症的耐药性。通过一个不连贯的前馈回路,化疗药物不仅激活 p53 诱导细胞死亡,还促进凋亡抑制剂的表达,抑制细胞死亡。因此,p53 早期激活的细胞发生凋亡,而 p53 晚期激活的细胞存活。不连贯的前馈回路和 p53 激活时间的重要作用使得分数杀伤成为一个复杂的动态挑战,仅凭直觉很难理解。为了更好地理解这个过程,我们通过整合凋亡的控制和相关的信号通路,构建了一个有代表性的模型。在模型被训练以捕捉分数杀伤的观察特性后,我们用非线性动力学工具对其进行了分析。该分析提出了一个简单的分数杀伤动力学框架,该框架预测细胞命运可以通过三种可能的方式改变:分岔几何的改变、细胞轨迹的改变或两者兼有。这些预测的类别可以解释现有的对抗分数杀伤的策略,并有助于设计新的策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/12da/5556027/6f6f5f4cd2c7/41598_2017_7422_Fig1_HTML.jpg

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