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概念验证:网络和系统生物学方法有助于发现有效的抗癌药物组合。

Proof of concept: network and systems biology approaches aid in the discovery of potent anticancer drug combinations.

机构信息

Department of Pathology, Barbara Ann Karmanos Cancer Institute, Wayne State University School of Medicine, 740 Hudson Webber Cancer Research Center, 4100 John R St, Detroit, Michigan 48201, USA.

出版信息

Mol Cancer Ther. 2010 Dec;9(12):3137-44. doi: 10.1158/1535-7163.MCT-10-0642. Epub 2010 Nov 1.

DOI:10.1158/1535-7163.MCT-10-0642
PMID:21041384
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3058926/
Abstract

Cancer therapies that target key molecules have not fulfilled expected promises for most common malignancies. Major challenges include the incomplete understanding and validation of these targets in patients, the multiplicity and complexity of genetic and epigenetic changes in the majority of cancers, and the redundancies and cross-talk found in key signaling pathways. Collectively, the uses of single-pathway targeted approaches are not effective therapies for human malignancies. To overcome these barriers, it is important to understand the molecular cross-talk among key signaling pathways and how they may be altered by targeted agents. Innovative approaches are needed, such as understanding the global physiologic environment of target proteins and the effects of modifying them without losing key molecular details. Such strategies will aid the design of novel therapeutics and their combinations against multifaceted diseases, in which efficacious combination therapies will focus on altering multiple pathways rather than single proteins. Integrated network modeling and systems biology have emerged as powerful tools benefiting our understanding of drug mechanisms of action in real time. This review highlights the significance of the network and systems biology-based strategy and presents a proof of concept recently validated in our laboratory using the example of a combination treatment of oxaliplatin and the MDM2 inhibitor MI-219 in genetically complex and incurable pancreatic adenocarcinoma.

摘要

针对关键分子的癌症疗法并未如预期那样对大多数常见恶性肿瘤有效。主要挑战包括对这些靶点在患者中的不完全理解和验证、大多数癌症中遗传和表观遗传变化的多样性和复杂性,以及关键信号通路中的冗余和串扰。总之,单一途径靶向方法的应用并不是治疗人类恶性肿瘤的有效方法。为了克服这些障碍,了解关键信号通路之间的分子串扰以及靶向药物如何改变它们非常重要。需要创新的方法,例如了解目标蛋白的全局生理环境以及在不丢失关键分子细节的情况下修饰它们的效果。这些策略将有助于设计针对多方面疾病的新型治疗方法及其组合,其中有效的联合治疗将侧重于改变多个途径,而不是单一蛋白质。基于网络的综合建模和系统生物学已经成为实时了解药物作用机制的有力工具。本文强调了基于网络和系统生物学的策略的重要性,并以我们实验室最近使用奥沙利铂和 MDM2 抑制剂 MI-219 联合治疗遗传复杂且无法治愈的胰腺腺癌为例,提出了一个概念验证。

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本文引用的文献

1
MI-219-zinc combination: a new paradigm in MDM2 inhibitor-based therapy.MI-219-锌复合物:基于 MDM2 抑制剂的治疗的新范例。
Oncogene. 2011 Jan 6;30(1):117-26. doi: 10.1038/onc.2010.403. Epub 2010 Sep 6.
2
Genetic analysis of complex disease--a roadmap to understanding or a colossal waste of money.
Pediatr Endocrinol Rev. 2010 Mar-Apr;7(3):258-65.
3
MDM2 inhibitor MI-319 in combination with cisplatin is an effective treatment for pancreatic cancer independent of p53 function.MDM2 抑制剂 MI-319 联合顺铂治疗胰腺癌有效,与 p53 功能无关。
Eur J Cancer. 2010 Apr;46(6):1122-31. doi: 10.1016/j.ejca.2010.01.015. Epub 2010 Feb 13.
4
Choice of starting dose for molecularly targeted agents evaluated in first-in-human phase I cancer clinical trials.在首次人体 I 期癌症临床试验中评估的分子靶向药物的起始剂量选择。
J Clin Oncol. 2010 Mar 10;28(8):1401-7. doi: 10.1200/JCO.2009.25.9606. Epub 2010 Feb 1.
5
Unveiling the role of network and systems biology in drug discovery.揭示网络和系统生物学在药物发现中的作用。
Trends Pharmacol Sci. 2010 Mar;31(3):115-23. doi: 10.1016/j.tips.2009.11.006. Epub 2010 Feb 1.
6
Awakening guardian angels: drugging the p53 pathway.唤醒守护天使:抑制 p53 通路。
Nat Rev Cancer. 2009 Dec;9(12):862-73. doi: 10.1038/nrc2763.
7
Dynamic interactions of proteins in complex networks: a more structured view.复杂网络中蛋白质的动态相互作用:一种更具结构化的观点。
FEBS J. 2009 Oct;276(19):5390-405. doi: 10.1111/j.1742-4658.2009.07251.x. Epub 2009 Aug 27.
8
Network analyses in systems pharmacology.系统药理学中的网络分析。
Bioinformatics. 2009 Oct 1;25(19):2466-72. doi: 10.1093/bioinformatics/btp465. Epub 2009 Jul 30.
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Systems pathology--taking molecular pathology into a new dimension.系统病理学——将分子病理学带入一个新维度。
Nat Rev Clin Oncol. 2009 Aug;6(8):455-64. doi: 10.1038/nrclinonc.2009.102. Epub 2009 Jul 7.
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