Ludvigsen Maja, Hamilton-Dutoit Stephen Jacques, d'Amore Francesco, Honoré Bent
Department of Biomedicine, Aarhus University, Aarhus, Denmark.
Proteomics Clin Appl. 2015 Feb;9(1-2):72-85. doi: 10.1002/prca.201400145. Epub 2015 Jan 22.
We describe the application of proteomic techniques for protein profiling and biomarker discovery in malignant lymphoma. Hematologic malignancies are primarily characterized by their clinical, morphological, immunophenotypical, and molecular-genetic features. However, when based on these parameters, apparently identical lymphomas may show distinct clinical courses, suggesting underlying biological heterogeneity. Recent proteomic analyses have identified differences in protein expression both with regard to subclassification of the malignant lymphoma entities, as well as in correlation with clinical outcome. In this review, studies on quantification of differential protein expression in and between malignant lymphoma entities are included. Studies are included that are based on patient samples, that is, serum/plasma or cytological specimens, as well as intact tumor tissues, together with studies that focus on tumor cells alone, or in conjunction with the tumor microenvironment. For biomarker discovery in malignant lymphoma, these approaches are used to uncover the underlying biological mechanisms and identify proteins with potential diagnostic and prognostic utility, either as predictive biomarkers or as novel future treatment targets.
我们描述了蛋白质组学技术在恶性淋巴瘤蛋白质谱分析和生物标志物发现中的应用。血液系统恶性肿瘤主要以其临床、形态学、免疫表型和分子遗传学特征为特点。然而，基于这些参数，看似相同的淋巴瘤可能表现出不同的临床病程，提示存在潜在的生物学异质性。最近的蛋白质组学分析已经确定了恶性淋巴瘤实体亚分类方面以及与临床结果相关性方面的蛋白质表达差异。在本综述中，纳入了关于恶性淋巴瘤实体内部和之间差异蛋白质表达定量的研究。纳入的研究基于患者样本，即血清/血浆或细胞学标本以及完整的肿瘤组织，同时也包括仅关注肿瘤细胞或结合肿瘤微环境的研究。对于恶性淋巴瘤生物标志物的发现，这些方法用于揭示潜在的生物学机制，并鉴定具有潜在诊断和预后价值的蛋白质，作为预测性生物标志物或未来新的治疗靶点。
