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血清蛋白质指纹图谱模型在肾癌诊断中的应用

Application of serum protein fingerprinting model for the diagnosis of renal cell carcinoma

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【作者】 张锐强谢静刘振元张玉石李汉忠邓碧萍李宁王彭

【Author】 ZNANG Rui-qiang,X1E Jing,LIU Zhen-yuan,ZHANG Yu-shi,LI Han-zhong,DENG Bi-ping,LI Ning,WANG Peng, Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing 100730, China

【机构】 中国医学科学院中国协和医科大学北京协和医院泌尿外科中国医学科学院中国协和医科大学北京协和医院中心实验室中国医学科学院中国协和医科大学北京协和医院泌尿外科

【摘要】 目的探讨肾癌早期诊断的新方法。方法血清标本66份,其中肾癌患者34份,健康对照组32份,应用表面增强激光解吸离子化飞行时间质谱(SELDI-TOF-MS)技术获得WCX2蛋白芯片表达图谱,采用Biomarker PatternsTM软件分析差异蛋白并初步建立肾癌血清标志物诊断模型。结果在相对分子质量1000—50 000范围内共检测到101个蛋白峰,其中7个有统计学意义(P< 0.01)。所建立肾癌诊断模型敏感性为88%(30/34),特异性为91%(29/32)。采用此模型盲法分析42份未知血清标本,敏感性为80%(16/20),特异性为82%(18/22)。结论用SELDI—TOF—MS技术平台和生物信息学技术建立的诊断模型为肾癌早期诊断提供了新途径。

【Abstract】 Objective To investigate a biomarker pattern for the early diagnosis of renal cell carcinoma (RCC). Methods Serum samples from 34 RCC patients and 32 healthy controls were analyzed using WCX2 Protein Chip by surface-enhanced laser desorption and ionization time of flight mass spectrometry (SELDI-TOF-MS) technology. Proteomic spectra were generated by mass spectrometry. The data was analyzed with Biomarker Patterns Software (BPS) software. Results Overall, 101 protein peaks were detected within relative molecular weight range 1000 -50 000 Da. Of these,7 differentially expressing potential bi-omarkers were identified (P <0. 01) ;and a primary diagnosis model was set up using 2 peaks. The sensitivity for diagnosing RCC was 88% (30/34) ,and the specificity was 91% (29/32). Using the pattern, blind test of extra 42 pieces of serum samples resulted in a sensitivity of 80% ( 16/20) and specificity of 82% ( 18/ 22). Conclusions The SELDI-TOF-MS Protein Chip and bioinformatics technology based analytical method using the peripheral blood sample is a new approach for the clinical diagnosis of patients with early RCC.

【关键词】 肾肿瘤肿瘤标记,生物学
【Key words】 Kidney neoplasmsCarcinomaTumor markers, biological
  • 【文献出处】 中华泌尿外科杂志 ,Chinese Journal of Urology , 编辑部邮箱 ,2006年08期
  • 【分类号】R737.11
  • 【被引频次】19
  • 【下载频次】164
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