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翻译后修饰的新趋势:揭示多形性胶质母细胞瘤

Emerging trends in post-translational modification: Shedding light on Glioblastoma multiforme.

作者信息

Kumari Smita, Gupta Rohan, Ambasta Rashmi K, Kumar Pravir

机构信息

Molecular Neuroscience and Functional Genomics Laboratory, Department of Biotechnology, Delhi Technological, University, India.

Molecular Neuroscience and Functional Genomics Laboratory, Department of Biotechnology, Delhi Technological, University, India; School of Medicine, University of South Carolina, Columbia, SC, United States of America.

出版信息

Biochim Biophys Acta Rev Cancer. 2023 Nov;1878(6):188999. doi: 10.1016/j.bbcan.2023.188999. Epub 2023 Oct 18.

Abstract

Recent multi-omics studies, including proteomics, transcriptomics, genomics, and metabolomics have revealed the critical role of post-translational modifications (PTMs) in the progression and pathogenesis of Glioblastoma multiforme (GBM). Further, PTMs alter the oncogenic signaling events and offer a novel avenue in GBM therapeutics research through PTM enzymes as potential biomarkers for drug targeting. In addition, PTMs are critical regulators of chromatin architecture, gene expression, and tumor microenvironment (TME), that play a crucial function in tumorigenesis. Moreover, the implementation of artificial intelligence and machine learning algorithms enhances GBM therapeutics research through the identification of novel PTM enzymes and residues. Herein, we briefly explain the mechanism of protein modifications in GBM etiology, and in altering the biologics of GBM cells through chromatin remodeling, modulation of the TME, and signaling pathways. In addition, we highlighted the importance of PTM enzymes as therapeutic biomarkers and the role of artificial intelligence and machine learning in protein PTM prediction.

摘要

最近的多组学研究,包括蛋白质组学、转录组学、基因组学和代谢组学,揭示了翻译后修饰(PTM)在多形性胶质母细胞瘤(GBM)进展和发病机制中的关键作用。此外,PTM改变致癌信号事件,并通过作为药物靶向潜在生物标志物的PTM酶,为GBM治疗研究提供了一条新途径。此外,PTM是染色质结构、基因表达和肿瘤微环境(TME)的关键调节因子,在肿瘤发生中起关键作用。此外,人工智能和机器学习算法的应用通过识别新型PTM酶和残基,增强了GBM治疗研究。在此,我们简要解释GBM病因中蛋白质修饰的机制,以及通过染色质重塑、TME调节和信号通路改变GBM细胞生物学特性的机制。此外,我们强调了PTM酶作为治疗生物标志物的重要性,以及人工智能和机器学习在蛋白质PTM预测中的作用。

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