Centre for PanorOmic Sciences, The University of Hong Kong, Pokfulam, Hong Kong SAR.
School of Biomedical Sciences, The University of Hong Kong, Pokfulam, Hong Kong SAR.
Expert Rev Proteomics. 2021 Mar;18(3):221-232. doi: 10.1080/14789450.2021.1914594. Epub 2021 Apr 20.
: Cancer cell lines (CCLs) have been a major resource for cancer research. Over the past couple of decades, they have been instrumental in omic profiling method development and as model systems to generate new knowledge in cell and cancer biology. More recently, with the increasing amount of genomic, transcriptomic and proteomic data being generated in hundreds of CCLs, there is growing potential for integrative proteogenomic data analyses to be performed.: In this review, we first describe the most commonly used proteome profiling methods in CCLs. We then discuss how these proteomics data can be integrated with genomics data for proteogenomics analyses. Finally, we highlight some of the recent biological discoveries that have arisen from proteogenomics analyses of CCLs.: Protegeonomics analyses of CCLs have so far enabled the discovery of novel proteins and proteoforms. It has also improved our understanding of biological processes including post-transcriptional regulation of protein abundance and the presentation of antigens by major histocompatibility complex alleles. With proteomics data to be generated in hundreds to thousands of CCLs in coming years, there will be further potential for large-scale proteogenomics analyses and data integration with the phenotypically well-characterized CCLs.
: 癌细胞系 (CCLs) 一直是癌症研究的主要资源。在过去的几十年中，它们在开发组学 profiling 方法方面发挥了重要作用，并且作为模型系统，为细胞和癌症生物学领域的新知识生成提供了支持。最近，随着数百种 CCL 中产生的基因组、转录组和蛋白质组数据的不断增加，对整合蛋白质基因组数据进行分析的潜力也越来越大。: 在这篇综述中，我们首先描述了 CCL 中最常用的蛋白质组学分析方法。然后，我们讨论了如何将这些蛋白质组学数据与基因组学数据整合进行蛋白质基因组学分析。最后，我们强调了一些最近从 CCL 的蛋白质基因组学分析中产生的生物学发现。: 迄今为止，对 CCL 的蛋白质基因组学分析已经能够发现新的蛋白质和蛋白质形式。它还提高了我们对包括蛋白质丰度的转录后调控以及主要组织相容性复合体等位基因对抗原的呈递等生物学过程的理解。随着未来几年将在数百到数千个 CCL 中生成蛋白质组学数据，将会有进一步的潜力进行大规模的蛋白质基因组学分析和与表型特征良好的 CCL 进行数据整合。
