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用于检测子宫内膜癌的血清蛋白质组学特征。

Serum proteomic features for detection of endometrial cancer.

作者信息

Zhu L-R, Zhang W-Y, Yu L, Zheng Y-H, Zhang J-Z, Liao Q-P

机构信息

Department of Obstetrics and Gynecology, First Hospital of Peking University, Beijing, China.

出版信息

Int J Gynecol Cancer. 2006 May-Jun;16(3):1374-8. doi: 10.1111/j.1525-1438.2006.00561.x.

Abstract

To find new potential biomarkers for detection of endometrial cancer (EC), 70 serum samples including 40 from EC patients and 30 from normal healthy females were detected by surface-enhanced laser desorption-ionization time-of-flight mass spectrometry (SELDI-TOF-MS) using WCX2 (weak cation exchange) protein chip. Mass spectra were then assessed with three powerful data-mining tools: a tree classifier, Biomarker Wizard software, and Biomarker Patterns System. The diagnostic pattern combined with 13 potential biomarkers could differentiate EC patients from healthy persons, with a specificity of 100%, sensitivity of 92.5%, and total coincidence of 95.7%. The combination of surface-enhanced laser desorption-ionization with bioinformatics tools could help find new biomarkers and establish with high sensitivity and specificity for the detection of EC.

摘要

为寻找用于检测子宫内膜癌(EC)的新的潜在生物标志物,使用WCX2(弱阳离子交换)蛋白质芯片,通过表面增强激光解吸电离飞行时间质谱(SELDI-TOF-MS)对70份血清样本进行检测,其中包括40份来自EC患者的样本和30份来自正常健康女性的样本。然后使用三种强大的数据挖掘工具评估质谱图:树分类器、生物标志物向导软件和生物标志物模式系统。结合13种潜在生物标志物的诊断模式可将EC患者与健康人区分开来,特异性为100%,敏感性为92.5%,总符合率为95.7%。表面增强激光解吸电离与生物信息学工具的结合有助于发现新的生物标志物,并建立高灵敏度和特异性的EC检测方法。

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