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将癌细胞周期建模作为合理药物开发的工具:环疗法的系统药理学方法。

Modelling of the cancer cell cycle as a tool for rational drug development: A systems pharmacology approach to cyclotherapy.

作者信息

Jackson Robert C, Di Veroli Giovanni Y, Koh Siang-Boon, Goldlust Ian, Richards Frances M, Jodrell Duncan I

机构信息

Pharmacometrics Ltd, Cambridge, United Kingdom.

Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.

出版信息

PLoS Comput Biol. 2017 May 3;13(5):e1005529. doi: 10.1371/journal.pcbi.1005529. eCollection 2017 May.

DOI:10.1371/journal.pcbi.1005529
PMID:28467408
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5435348/
Abstract

The dynamic of cancer is intimately linked to a dysregulation of the cell cycle and signalling pathways. It has been argued that selectivity of treatments could exploit loss of checkpoint function in cancer cells, a concept termed "cyclotherapy". Quantitative approaches that describe these dysregulations can provide guidance in the design of novel or existing cancer therapies. We describe and illustrate this strategy via a mathematical model of the cell cycle that includes descriptions of the G1-S checkpoint and the spindle assembly checkpoint (SAC), the EGF signalling pathway and apoptosis. We incorporated sites of action of four drugs (palbociclib, gemcitabine, paclitaxel and actinomycin D) to illustrate potential applications of this approach. We show how drug effects on multiple cell populations can be simulated, facilitating simultaneous prediction of effects on normal and transformed cells. The consequences of aberrant signalling pathways or of altered expression of pro- or anti-apoptotic proteins can thus be compared. We suggest that this approach, particularly if used in conjunction with pharmacokinetic modelling, could be used to predict effects of specific oncogene expression patterns on drug response. The strategy could be used to search for synthetic lethality and optimise combination protocol designs.

摘要

癌症的动态变化与细胞周期和信号通路的失调密切相关。有人认为,治疗的选择性可以利用癌细胞中检查点功能的丧失,这一概念被称为“周期疗法”。描述这些失调的定量方法可以为新型或现有癌症治疗的设计提供指导。我们通过一个细胞周期数学模型来描述和阐释这一策略,该模型包括对G1-S检查点和纺锤体组装检查点(SAC)、表皮生长因子(EGF)信号通路以及细胞凋亡的描述。我们纳入了四种药物(帕博西尼、吉西他滨、紫杉醇和放线菌素D)的作用位点,以说明这种方法的潜在应用。我们展示了如何模拟药物对多个细胞群体的作用,从而便于同时预测对正常细胞和转化细胞的影响。由此可以比较异常信号通路或促凋亡蛋白或抗凋亡蛋白表达改变的后果。我们认为,这种方法,特别是与药代动力学模型结合使用时,可用于预测特定癌基因表达模式对药物反应的影响。该策略可用于寻找合成致死性并优化联合方案设计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9dc/5435348/ed6d80a19c4d/pcbi.1005529.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9dc/5435348/1af30ab2f892/pcbi.1005529.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9dc/5435348/3000e01d2fac/pcbi.1005529.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9dc/5435348/2b4a9ec2a7a5/pcbi.1005529.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9dc/5435348/0f1ff59dd7d1/pcbi.1005529.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9dc/5435348/c621fc3742e1/pcbi.1005529.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9dc/5435348/ed6d80a19c4d/pcbi.1005529.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9dc/5435348/1af30ab2f892/pcbi.1005529.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9dc/5435348/3000e01d2fac/pcbi.1005529.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9dc/5435348/2b4a9ec2a7a5/pcbi.1005529.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9dc/5435348/0f1ff59dd7d1/pcbi.1005529.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9dc/5435348/c621fc3742e1/pcbi.1005529.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9dc/5435348/ed6d80a19c4d/pcbi.1005529.g006.jpg

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