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利用新型组合搜索算法探索乳腺癌细胞的蛋白质翻译后修饰。

Exploring Protein Post-Translational Modifications of Breast Cancer Cells Using a Novel Combinatorial Search Algorithm.

机构信息

Research Institute, Medical University of Pleven, 5800 Pleven, Bulgaria.

Department of Breast Surgery, Shterev Hospital, 1000 Sofia, Bulgaria.

出版信息

Int J Mol Sci. 2024 Sep 13;25(18):9902. doi: 10.3390/ijms25189902.

Abstract

Post-translational modification of proteins plays an important role in cancer cell biology. Proteins encoded by oncogenes may be activated by phosphorylation, products of tumour suppressors might be inactivated by phosphorylation or ubiquitinylation, which marks them for degradation; chromatin-binding proteins are often methylated and/or acetylated. These are just a few of the many hundreds of post-translational modifications discovered by years of painstaking experimentation and the chemical analysis of purified proteins. In recent years, mass spectrometry-based proteomics emerged as the principal technique for identifying such modifications in samples from cultured cells and tumour tissue. Here, we used a recently developed combinatorial search algorithm implemented in the MGVB toolset to identify novel modifications in samples from breast cancer cell lines. Our results provide a rich resource of coupled protein abundance and post-translational modification data seen in the context of an important biological function-the response of cells to interferon gamma treatment-which can serve as a starting point for future investigations to validate promising modifications and explore the utility of the underlying molecular mechanisms as potential diagnostic or therapeutic targets.

摘要

蛋白质的翻译后修饰在癌细胞生物学中起着重要作用。癌基因编码的蛋白质可能通过磷酸化激活,肿瘤抑制因子的产物可能通过磷酸化或泛素化失活,从而被标记为降解;染色质结合蛋白通常被甲基化和/或乙酰化。这些只是通过多年艰苦的实验和对纯化蛋白质的化学分析发现的数百种翻译后修饰中的一小部分。近年来,基于质谱的蛋白质组学已成为鉴定培养细胞和肿瘤组织样本中此类修饰的主要技术。在这里,我们使用了最近开发的组合搜索算法,该算法在 MGVB 工具集中实现,用于鉴定乳腺癌细胞系样本中的新修饰。我们的研究结果为在一个重要的生物学功能——细胞对干扰素γ处理的反应——背景下观察到的耦合蛋白质丰度和翻译后修饰数据提供了丰富的资源,这可以作为未来研究的起点,以验证有前途的修饰,并探索潜在的诊断或治疗靶点的基础分子机制的实用性。

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