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3
The prolyl-isomerase Pin1 activates the mitochondrial death program of p53.脯氨酰异构酶 Pin1 激活 p53 的线粒体死亡程序。
Cell Death Differ. 2013 Feb;20(2):198-208. doi: 10.1038/cdd.2012.112. Epub 2012 Aug 31.
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Molecular definitions of cell death subroutines: recommendations of the Nomenclature Committee on Cell Death 2012.细胞死亡程序的分子定义:细胞死亡命名委员会 2012 年的建议。
Cell Death Differ. 2012 Jan;19(1):107-20. doi: 10.1038/cdd.2011.96. Epub 2011 Jul 15.
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Theoretical and experimental analysis links isoform-specific ERK signalling to cell fate decisions.理论和实验分析将 ERK 信号通路与细胞命运决定联系起来。
Mol Syst Biol. 2009;5:334. doi: 10.1038/msb.2009.91. Epub 2009 Dec 22.
6
Activated cAMP response element binding protein is overexpressed in human mesotheliomas and inhibits apoptosis.激活的 cAMP 反应元件结合蛋白在人类间皮瘤中过表达并抑制细胞凋亡。
Am J Pathol. 2009 Nov;175(5):2197-206. doi: 10.2353/ajpath.2009.090400. Epub 2009 Oct 8.
7
Visualization of ATP levels inside single living cells with fluorescence resonance energy transfer-based genetically encoded indicators.利用基于荧光共振能量转移的基因编码指示剂对单个活细胞内的ATP水平进行可视化。
Proc Natl Acad Sci U S A. 2009 Sep 15;106(37):15651-6. doi: 10.1073/pnas.0904764106. Epub 2009 Aug 31.
8
Understanding the Warburg effect: the metabolic requirements of cell proliferation.理解瓦伯格效应:细胞增殖的代谢需求。
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9
Hepatocellular carcinoma incidence, mortality, and survival trends in the United States from 1975 to 2005.1975年至2005年美国肝细胞癌的发病率、死亡率及生存趋势
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10
Dynamics of outer mitochondrial membrane permeabilization during apoptosis.细胞凋亡过程中线粒体外膜通透性改变的动力学
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根据体外早期信号转导反应预测细胞死亡剂量反应。

Forecasting cell death dose-response from early signal transduction responses in vitro.

作者信息

Vrana Julie A, Currie Holly N, Han Alice A, Boyd Jonathan

机构信息

C. Eugene Bennett Department of Chemistry, West Virginia University, 217 Clark Hall, Prospect Street, Morgantown, West Virginia 26506.

C. Eugene Bennett Department of Chemistry, West Virginia University, 217 Clark Hall, Prospect Street, Morgantown, West Virginia 26506

出版信息

Toxicol Sci. 2014 Aug 1;140(2):338-51. doi: 10.1093/toxsci/kfu089. Epub 2014 May 13.

DOI:10.1093/toxsci/kfu089
PMID:24824809
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4176052/
Abstract

The rapid pharmacodynamic response of cells to toxic xenobiotics is primarily coordinated by signal transduction networks, which follow a simple framework: the phosphorylation/dephosphorylation cycle mediated by kinases and phosphatases. However, the time course from initial pharmacodynamic response(s) to cell death following exposure can have a vast range. Viewing this time lag between early signaling events and the ultimate cellular response as an opportunity, we hypothesize that monitoring the phosphorylation of proteins related to cell death and survival pathways at key, early time points may be used to forecast a cell's eventual fate, provided that we can measure and accurately interpret the protein responses. In this paper, we focused on a three-phased approach to forecast cell death after exposure: (1) determine time points relevant to important signaling events (protein phosphorylation) by using estimations of adenosine triphosphate production to reflect the relationship between mitochondrial-driven energy metabolism and kinase response, (2) experimentally determine phosphorylation values for proteins related to cell death and/or survival pathways at these significant time points, and (3) use cluster analysis to predict the dose-response relationship between cellular exposure to a xenobiotic and plasma membrane degradation at 24 h post-exposure. To test this approach, we exposed HepG2 cells to two disparate treatments: a GSK-3β inhibitor and a MEK inhibitor. After using our three-phased approach, we were able to accurately forecast the 24 h HepG2 plasma membrane degradation dose-response from protein phosphorylation values as early as 20 min post-MEK inhibitor exposure and 40 min post-GSK-3β exposure.

摘要

细胞对有毒异生物素的快速药效学反应主要由信号转导网络协调,该网络遵循一个简单的框架:由激酶和磷酸酶介导的磷酸化/去磷酸化循环。然而,从初始药效学反应到暴露后细胞死亡的时间进程可能有很大差异。将早期信号事件与最终细胞反应之间的这段时间间隔视为一个机会,我们假设,只要我们能够测量并准确解读蛋白质反应,在关键的早期时间点监测与细胞死亡和存活途径相关的蛋白质磷酸化情况,就可用于预测细胞的最终命运。在本文中,我们重点关注一种分三个阶段预测暴露后细胞死亡的方法:(1)通过利用三磷酸腺苷生成的估计值来反映线粒体驱动的能量代谢与激酶反应之间的关系,确定与重要信号事件(蛋白质磷酸化)相关的时间点;(2)通过实验确定在这些重要时间点与细胞死亡和/或存活途径相关的蛋白质的磷酸化值;(3)使用聚类分析预测细胞暴露于异生物素后24小时细胞膜降解与剂量反应之间的关系。为了验证这种方法,我们将HepG2细胞暴露于两种不同的处理:一种GSK - 3β抑制剂和一种MEK抑制剂。在使用我们的三阶段方法后,我们能够早在MEK抑制剂暴露后20分钟和GSK - 3β暴露后40分钟,就根据蛋白质磷酸化值准确预测24小时HepG2细胞膜降解的剂量反应。