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利用基本反应规则增强对 TRAIL 耐药的癌细胞中的细胞凋亡。

Enhancing apoptosis in TRAIL-resistant cancer cells using fundamental response rules.

机构信息

Institute for Advanced Biosciences, Keio University, Tsuruoka, 997-0035, Japan; Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, 252-8520, Japan.

出版信息

Sci Rep. 2011;1:144. doi: 10.1038/srep00144. Epub 2011 Nov 7.

DOI:10.1038/srep00144
PMID:22355661
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3216625/
Abstract

The tumor necrosis factor related apoptosis-inducing ligand (TRAIL) induces apoptosis in malignant cells, while leaving other cells mostly unharmed. However, several carcinomas remain resistant to TRAIL. To investigate the resistance mechanisms in TRAIL-stimulated human fibrosarcoma (HT1080) cells, we developed a computational model to analyze the temporal activation profiles of cell survival (IκB, JNK, p38) and apoptotic (caspase-8 and -3) molecules in wildtype and several (FADD, RIP1, TRAF2 and caspase-8) knock-down conditions. Based on perturbation-response approach utilizing the law of information (signaling flux) conservation, we derived response rules for population-level average cell response. From this approach, i) a FADD-independent pathway to activate p38 and JNK, ii) a crosstalk between RIP1 and p38, and iii) a crosstalk between p62 and JNK are predicted. Notably, subsequent simulations suggest that targeting a novel molecule at p62/sequestosome-1 junction will optimize apoptosis through signaling flux redistribution. This study offers a valuable prospective to sensitive TRAIL-based therapy.

摘要

肿瘤坏死因子相关凋亡诱导配体(TRAIL)可诱导恶性细胞凋亡,而使其他细胞基本不受伤害。然而,一些癌仍然对 TRAIL 具有抗性。为了研究 TRAIL 刺激的人纤维肉瘤(HT1080)细胞中的抗性机制,我们开发了一种计算模型来分析细胞存活(IκB、JNK、p38)和凋亡(caspase-8 和 -3)分子在野生型和几种(FADD、RIP1、TRAF2 和 caspase-8)敲低条件下的时间激活谱。基于利用信息(信号流)守恒定律的扰动向量响应方法,我们推导出了群体平均细胞响应的响应规则。从该方法中,i)预测了一种不依赖于 FADD 的途径来激活 p38 和 JNK,ii)RIP1 和 p38 之间的串扰,以及 iii)p62 和 JNK 之间的串扰。值得注意的是,随后的模拟表明,靶向 p62/自噬体-1 结合处的新型分子将通过信号流再分配优化细胞凋亡。本研究为敏感的 TRAIL 为基础的治疗提供了有价值的前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5059/3216625/a539d9dd9ff9/srep00144-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5059/3216625/eb9a08acb5ee/srep00144-f1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5059/3216625/dc5f28767e68/srep00144-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5059/3216625/f882f4f0ac90/srep00144-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5059/3216625/ad728b98f196/srep00144-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5059/3216625/a539d9dd9ff9/srep00144-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5059/3216625/eb9a08acb5ee/srep00144-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5059/3216625/1e137c36cab2/srep00144-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5059/3216625/0b027e132ad9/srep00144-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5059/3216625/dc5f28767e68/srep00144-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5059/3216625/f882f4f0ac90/srep00144-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5059/3216625/ad728b98f196/srep00144-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5059/3216625/a539d9dd9ff9/srep00144-f7.jpg

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