Proteomic-based prognosis of brain tumor patients using direct-tissue matrix-assisted laser desorption ionization mass spectrometry
Proteomic-based prognosis of brain tumor patients using direct-tissue matrix-assisted laser desorption ionization mass spectrometry
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DOI：
10.1158/0008-5472.can-04-3016
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发表时间：
2005-09-01
期刊：
影响因子：
11.2
通讯作者：
Caprioli, RM
中科院分区：
文献类型：
--
作者：
Schwartz, SA;Weil, RJ;Caprioli, RM
原发性人类脑肿瘤（神经胶质瘤）的临床诊断和治疗决策几乎完全基于组织组织学。由于这些肿瘤的异质性和浸润性，神经胶质瘤的诊断方法可能具有高度主观性，并且取决于神经病理学家的技能。因此，迫切需要开发更精确、非主观和系统的方法来对人类神经胶质瘤进行分类。为此，质谱分析已应用于这些肿瘤以确定神经胶质瘤特异性蛋白质模式。通过使用基质辅助激光解吸电离质谱 (MS) 直接分析组织样本，从不同级别的人类神经胶质瘤中获得了蛋白质谱。将统计算法应用于组织切片的 MS 图谱，识别出与肿瘤组织学和患者生存相关的蛋白质模式。使用 108 名神经胶质瘤患者的数据集，根据组织蛋白谱确定了两个患者群体，即短期生存组和长期生存组。此外，对 57 名被诊断患有高级别、IV 级恶性神经胶质瘤的患者进行了分析，并开发了一种新的分类方案，根据蛋白质组谱将短期和长期存活患者分开。所描述的蛋白质模式作为患者生存的独立指标。这些结果表明，这种监测神经胶质瘤的新分子方法可以提供肿瘤恶性肿瘤的临床相关信息，适合高通量临床筛查。
Clinical diagnosis and treatment decisions for a subset of primary human brain tumors, gliomas, are based almost exclusively on tissue histology. Approaches for glioma diagnosis can be highly subjective due to the heterogeneity and infiltrative nature of these tumors and depend on the skill of the neuropathologist. There is therefore a critical need to develop more precise, nonsubjective, and systematic methods to classify human gliomas. To this end, mass spectrometric analysis has been applied to these tumors to determine glioma-specific protein patterns. Protein profiles have been obtained from human gliomas of various grades through direct analysis of tissue samples using matrix-assisted laser desorption ionization mass spectrometry (MS). Statistical algorithms applied to the MS profiles from tissue sections identified protein patterns that correlated with tumor histology and patient survival. Using a data set of 108 glioma patients, two patient populations, a short-term and a long-term survival group, were identified based on the tissue protein profiles. In addition, a subset of 57 patients diagnosed with high-grade, grade IV, malignant gliomas were analyzed and a novel classification scheme that segregated short-term and long-term survival patients based on the proteomic profiles was developed. The protein patterns described served as an independent indicator of patient survival. These results show that this new molecular approach to monitoring gliomas can provide clinically relevant information on tumor malignancy and is suitable for high-throughput clinical screening.