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急性髓系白血病血清特征性标志物的初步筛选及临床意义

[Preliminarily screening of serum characteristic markers in acute myeloid leukemia and clinical significance].

作者信息

He Ai-Li, Bai Ju, Huang Chen, Zhang Wang-Gang, Yang Juan, Wang Jian-Li, Meng Xin, Tian Wei

机构信息

Department of Hematology, Second Affiliated Hospital, Xi'an Jiaotong University Medical College, Xi'an 710004, Shaanxi Province, China.

出版信息

Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2010 Oct;18(5):1132-7.

Abstract

This study was purposed to preliminarily screen characteristic tumor markers of acute myeloid leukemia (AML) and to investigate the serum proteomics characteristics of patients with AML and their significance in pathogenesis. 14 patients with AML and 28 healthy controls were enrolled in this study. The serum protein components were captured by weak cation exchange nanometer magnetic beads, the protein mass-spectra of all samples were detected by Autoflex II matrix-assisted laser desorption/ionization time of flight mass spectrometer, and the detection data were analyzed by means of CliprotoolsTM2.2 software, then the differential protein molecules were screened and the diagnostic model was established. Sera of 7 AML patients and 14 healthy controls were selected to verify the established model by using blind test. The results indicated that about 69 protein peaks could be detected within the range of 0.7-10 kD in protein spectra of serum samples from AML patients and controls. Compared with healthy controls, there were 44 statistically differential expression peaks in AML group (p<0.0001). Among them, 10 protein peaks were upregulated protein peaks and 34 protein peaks were downregulated. Diagnostic model was established on the basis of Quick Classifier Algorithm (QC), and the three mass peaks had the strongest power for software to automatically distinguish AML group from control group. Mass charge ratios (m/z) were 3216.57, 4089.7, and 7762.87 respectively. Sensitivity was expected as 86.4% while 82.8% in this established model group. Category validation showed that this diagnostic model correctly identified all 6 cases out of AML and 12 cases out of 14 healthy controls. In cross validation, the model sensitivity and specificity both were 85.7%. It is concluded that the AML QC model is composed of three protein peaks, which can effectively distinguish AML patients from healthy controls. Owing to higher sensitivity and specificity, they may act as serum tumor markers of AML. Among the three proteins, the one with m/z 7762.87 is the platelet-derived protein chemokine (PF4) protein. This finding will probably provide significant experimental evidence for understanding pathogenesis, molecular type, prognosis and treatment effect of AML.

摘要

本研究旨在初步筛选急性髓系白血病(AML)的特征性肿瘤标志物,探讨AML患者血清蛋白质组学特征及其在发病机制中的意义。本研究纳入了14例AML患者和28例健康对照者。采用弱阳离子交换纳米磁珠捕获血清蛋白成分,用Autoflex II基质辅助激光解吸/电离飞行时间质谱仪检测所有样本的蛋白质质谱,并用CliprotoolsTM2.2软件分析检测数据,然后筛选差异蛋白分子并建立诊断模型。选取7例AML患者和14例健康对照者的血清进行盲法验证所建立的模型。结果表明,AML患者和对照者血清样本蛋白质谱在0.7 - 10 kD范围内可检测到约69个蛋白峰。与健康对照相比,AML组有44个具有统计学差异的表达峰(p<0.0001)。其中,10个蛋白峰为上调蛋白峰,34个蛋白峰为下调蛋白峰。基于快速分类算法(QC)建立诊断模型,三个质谱峰对软件自动区分AML组和对照组的能力最强。质荷比(m/z)分别为3216.57、4089.7和7762.87。预期灵敏度为86.4%,而本模型组为82.8%。类别验证表明,该诊断模型正确识别出了14例AML患者中的6例和14例健康对照者中的12例。交叉验证中,模型的灵敏度和特异度均为85.7%。结论是,AML的QC模型由三个蛋白峰组成,可有效区分AML患者和健康对照者。由于具有较高的灵敏度和特异度,它们可能作为AML的血清肿瘤标志物。在这三种蛋白中,质荷比为7762.87的蛋白是血小板衍生蛋白趋化因子(PF4)蛋白。这一发现可能为理解AML的发病机制、分子类型、预后和治疗效果提供重要的实验证据。

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