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神经胶质瘤肿瘤蛋白质组学:具有临床应用价值的蛋白质生物标志物及未来展望。

Glioma tumor proteomics: clinically useful protein biomarkers and future perspectives.

机构信息

Centre for Research in Nanotechnology and Science, Indian Institute of Technology Bombay, Mumbai, India.

Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India.

出版信息

Expert Rev Proteomics. 2020 Mar;17(3):221-232. doi: 10.1080/14789450.2020.1731310. Epub 2020 Feb 19.

Abstract

: Despite being rare cancers, gliomas account for a significant number of cancer-related deaths. Identification and treatment of these tumors at an early stage would greatly improve the therapeutic outcomes. There is an urgent need for diagnostic and prognostic markers, which can identify disease early and discriminate the subtypes of these tumors thereby improving the existing treatment modalities.: In this article, we have reviewed published literature on proteomics biomarkers for gliomas and their importance in diagnosis or prognosis. Proteomic studies for the discovery of protein, autoantibody biomarkers, and biological pathway alterations in serum, CSF and tumor biopsies have been discussed in this review.: The rapid development in the field of mass spectrometry and increased sensitivity and reproducibility in assays has led to the identification and quantification of large number of proteins very precisely. Though genomic markers are the prime focus in the classification of gliomas, incorporating protein markers would further improve the existing classification. In this regard, data mining and studies on large cohorts of glioma patients would help in the identification of diagnostic and prognostic markers ultimately translating to the clinics.

摘要

: 尽管神经胶质瘤是罕见的癌症,但它们在癌症相关死亡中占了相当大的比例。如果能在早期识别和治疗这些肿瘤,将会大大改善治疗效果。目前迫切需要诊断和预后标志物,以便早期发现疾病并区分这些肿瘤的亚型,从而改进现有的治疗方式。: 在本文中,我们回顾了已发表的关于神经胶质瘤的蛋白质组学生物标志物的文献,以及它们在诊断或预后中的重要性。本文讨论了在血清、CSF 和肿瘤活检中发现蛋白质、自身抗体生物标志物和生物途径改变的蛋白质组学研究。: 质谱技术的快速发展以及检测方法的灵敏度和重现性的提高,使得大量蛋白质能够被非常精确地识别和定量。尽管基因组标志物是神经胶质瘤分类的主要关注点,但纳入蛋白质标志物将进一步改善现有的分类。在这方面,对大量神经胶质瘤患者进行数据挖掘和研究将有助于确定诊断和预后标志物,最终转化为临床应用。

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