Keresztes Dávid, Kerestély Márk, Szarka Levente, Kovács Borbála M, Schulc Klára, Veres Dániel V, Csermely Peter
Department of Molecular Biology, Semmelweis University, Budapest, Hungary.
Department of Molecular Biology, Semmelweis University, Budapest, Hungary; Division of Oncology, Department of Internal Medicine and Oncology, Semmelweis University, Budapest, Hungary.
Biomed Pharmacother. 2025 Feb;183:117880. doi: 10.1016/j.biopha.2025.117880. Epub 2025 Jan 29.
Drug resistance is a major cause of tumor mortality. Signaling networks became useful tools for driving pharmacological interventions against cancer drug resistance. Signaling datasets now cover the entire human cell. Recently, network adaptation became understood as a learning process. We review rapidly increasing evidence showing that the development of cancer drug resistance can be described as learning of signaling networks. During drug adaptation, the network forgets drug-affected pathways by desensitization and relearns by strengthening alternative pathways. Thus, resistant cancer cells develop a drug resistance memory. We show that all key players of cellular learning (i.e., IDPs, protein translocation, microRNAs/lncRNAs, scaffolding proteins and epigenetic/chromatin memory) have important roles in the development of cancer drug resistance. Moreover, all of them are central components of the epithelial-mesenchymal transition leading to metastases and resistance. Phenotypic plasticity was recently listed as a hallmark of cancer. We review how network plasticity induces rare, pre-existent drug-resistant cells in the absence of drug treatment. Key network methods assessing the development of drug resistance and network pharmacological interventions against drug resistance are summarized. Finally, we highlight the class of cellular memory drugs affecting cellular learning and forgetting, and we summarize current challenges to prevent or break drug resistance using network models.
耐药性是肿瘤死亡的主要原因。信号网络成为推动针对癌症耐药性进行药物干预的有用工具。信号数据集现在覆盖了整个人类细胞。最近,网络适应性被理解为一个学习过程。我们综述了迅速增加的证据,表明癌症耐药性的发展可以被描述为信号网络的学习。在药物适应过程中,网络通过脱敏忘记受药物影响的途径,并通过强化替代途径重新学习。因此,耐药癌细胞形成了耐药记忆。我们表明,细胞学习的所有关键参与者(即内在无序蛋白、蛋白质易位、微小RNA/长链非编码RNA、支架蛋白和表观遗传/染色质记忆)在癌症耐药性的发展中都发挥着重要作用。此外,它们都是导致转移和耐药的上皮-间质转化的核心组成部分。表型可塑性最近被列为癌症的一个标志。我们综述了网络可塑性如何在无药物治疗的情况下诱导罕见的、预先存在的耐药细胞。总结了评估耐药性发展的关键网络方法和针对耐药性的网络药理学干预措施。最后,我们强调了影响细胞学习和遗忘的细胞记忆药物类别,并总结了使用网络模型预防或打破耐药性的当前挑战。
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