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Intact protein profiling in breast cancer biomarker discovery: Protein identification issue and the solutions based on 3D protein separation, bottom-up and top-down mass spectrometry

机译:乳腺癌生物标志物发现中完整的蛋白质谱分析:蛋白质鉴定问题以及基于3D蛋白质分离,自下而上和自上而下的质谱法的解决方案

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摘要

Proteomics profiling of intact proteins based on MALDI-TOF MS and derived platforms has been used in cancer biomarker discovery studies. This approach suffers from a number of limitations such as low resolution, low sensitivity, and that no knowledge is available on the identity of the respective proteins in the discovery mode. Nevertheless, it remains the most high-throughput, untargeted mode of clinical proteomics studies to date. Here we compare key protein separation and MS techniques available for protein biomarker identification in this type of studies and define reasons of uncertainty in protein peak identity. As a result of critical data analysis, we consider 3D protein separation and identification workflows as optimal procedures. Subsequently, we present a new protocol based on 3D LC-MS/MS with top-down at high resolution that enabled the identification of HNRNP A2/B1 intact peptide as correlating with the estrogen receptor expression in breast cancer tissues. Additional development of this general concept toward next generation, top-down based protein profiling at high resolution is discussed.
机译:基于完整蛋白质的蛋白质组学分析(基于MALDI-TOF MS和衍生平台)已用于癌症生物标志物发现研究。该方法遭受许多局限性,例如低分辨率,低灵敏度,并且在发现模式下尚不了解各个蛋白质的身份。尽管如此,它仍然是迄今为止蛋白质组学研究中最高通量,非靶向的模式。在这里,我们比较了这类研究中用于蛋白质生物标志物鉴定的关键蛋白质分离和MS技术,并定义了蛋白质峰同一性不确定性的原因。作为关键数据分析的结果,我们将3D蛋白质分离和鉴定工作流程视为最佳程序。随后,我们提出了一种基于3D LC-MS / MS的新方案,该方案具有高分辨率的自上而下的功能,能够鉴定HNRNP A2 / B1完整肽与乳腺癌组织中的雌激素受体表达相关。讨论了此一般概念对高分辨率,下一代自上而下的蛋白质谱分析的进一步发展。

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