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癌症中自噬的复杂调控——发现双刃剑网络的综合方法。

Complex regulation of autophagy in cancer - integrated approaches to discover the networks that hold a double-edged sword.

机构信息

Department of Genetics, Eötvös Loránd University, Pázmány P. s. 1C, H-1117 Budapest, Hungary.

出版信息

Semin Cancer Biol. 2013 Aug;23(4):252-61. doi: 10.1016/j.semcancer.2013.06.009. Epub 2013 Jun 28.

Abstract

Autophagy, a highly regulated self-degradation process of eukaryotic cells, is a context-dependent tumor-suppressing mechanism that can also promote tumor cell survival upon stress and treatment resistance. Because of this ambiguity, autophagy is considered as a double-edged sword in oncology, making anti-cancer therapeutic approaches highly challenging. In this review, we present how systems-level knowledge on autophagy regulation can help to develop new strategies and efficiently select novel anti-cancer drug targets. We focus on the protein interactors and transcriptional/post-transcriptional regulators of autophagy as the protein and regulatory networks significantly influence the activity of core autophagy proteins during tumor progression. We list several network resources to identify interactors and regulators of autophagy proteins. As in silico analysis of such networks often necessitates experimental validation, we briefly summarize tractable model organisms to examine the role of autophagy in cancer. We also discuss fluorescence techniques for high-throughput monitoring of autophagy in humans. Finally, the challenges of pharmacological modulation of autophagy are reviewed. We suggest network-based concepts to overcome these difficulties. We point out that a context-dependent modulation of autophagy would be favored in anti-cancer therapy, where autophagy is stimulated in normal cells, while inhibited only in stressed cancer cells. To achieve this goal, we introduce the concept of regulo-network drugs targeting specific transcription factors or miRNA families identified with network analysis. The effect of regulo-network drugs propagates indirectly through transcriptional or post-transcriptional regulation of autophagy proteins, and, as a multi-directional intervention tool, they can both activate and inhibit specific proteins in the same time. The future identification and validation of such regulo-network drug targets may serve as novel intervention points, where autophagy can be effectively modulated in cancer therapy.

摘要

自噬是真核细胞中一种高度调控的自我降解过程,是一种与上下文相关的肿瘤抑制机制,它也可以促进肿瘤细胞在应激和治疗耐药时的存活。由于这种模糊性,自噬被认为是肿瘤学中的双刃剑,使得抗癌治疗方法极具挑战性。在这篇综述中,我们介绍了自噬调控的系统水平知识如何帮助开发新的策略和有效地选择新的抗癌药物靶点。我们专注于自噬的蛋白质相互作用物和转录/转录后调节剂,因为蛋白质和调节网络在肿瘤进展过程中显著影响核心自噬蛋白的活性。我们列出了几种网络资源来识别自噬蛋白的相互作用物和调节剂。由于对这些网络的计算机分析通常需要实验验证,我们简要总结了几种可用于研究自噬在癌症中作用的可操作的模式生物。我们还讨论了用于人类高通量监测自噬的荧光技术。最后,我们综述了药理学调节自噬的挑战。我们建议基于网络的概念来克服这些困难。我们指出,在抗癌治疗中,应该优先考虑自噬的上下文依赖性调节,即在正常细胞中刺激自噬,而仅在应激癌细胞中抑制自噬。为了实现这一目标,我们引入了针对特定转录因子或 miRNA 家族的网络分析所识别的 regulo-network 药物的概念。regulo-network 药物的作用通过自噬蛋白的转录或转录后调节间接传播,作为一种多向干预工具,它们可以同时激活和抑制同一时间的特定蛋白质。未来对这些 regulo-network 药物靶点的鉴定和验证可能成为新的干预点,可以有效地调节癌症治疗中的自噬。

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