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目的:探讨蛋白指纹图谱技术筛选肝细胞癌(HCC)患者血清中可用于诊断的特异性标志物。方法:采用弱阳离子纳米磁性微球捕获血清中的蛋白,ProteinChip PBS II-C型蛋白质芯片阅读仪检测绘制成蛋白指纹图谱。所有蛋白指纹图谱采用Biomarker Wizard 3.1分析之后用Biomarker Patterns Software识别最终用于诊断的蛋白标志物并优化组合建立诊断模型。结果:在肝细胞癌患者和对照组之间找到72个差异蛋白峰(P<0.01)。其中质荷比(m/z)为4471、8936、11670和13752的蛋白峰建立肝细胞癌的诊断模型。该诊断模型能很好地把肝细胞癌患者从正常人群中区分出来,其敏感性为93.3%(56/60),特异性为95.1%(78/82)。经双盲实验验证,该模型对肝细胞癌诊断的敏感性为88.9%(32/36),特异性为90.6%(58/64)。结论:采用纳米磁性微球与蛋白质芯片阅读仪联用的蛋白指纹图谱技术可以检测肝细胞癌患者血清中的特异性蛋白标志物,并建立敏感性和特异性均较高的肝细胞癌诊断模型。
Objective: To explore the protein fingerprinting technique for screening specific markers in serum of patients with hepatocellular carcinoma (HCC) for diagnosis. Methods: The protein in serum was captured by a weak cation nanometer magnetic microsphere. ProteinChip PBS II-C protein chip reader was used to detect the protein fingerprinting. All protein fingerprints were analyzed by Biomarker Wizard 3.1 and Biomarker Patterns Software was used to identify protein markers that were finally used for diagnosis and to optimize the combination to establish a diagnostic model. Results: 72 differential protein peaks were found between hepatocellular carcinoma patients and controls (P <0.01). Protein peaks with mass-to-charge ratios (m / z) of 4471, 8936, 11670 and 13752 establish a diagnostic model of hepatocellular carcinoma. The diagnostic model can well distinguish patients with hepatocellular carcinoma from the normal population, with a sensitivity of 93.3% (56/60) and a specificity of 95.1% (78/82). The double-blind experiments showed that the sensitivity of the model to the diagnosis of hepatocellular carcinoma was 88.9% (32/36) and the specificity was 90.6% (58/64). Conclusion: The protein fingerprinting technique using magnetic nanospheres and protein chip reader can detect specific protein markers in serum of patients with hepatocellular carcinoma and establish a diagnostic model of hepatocellular carcinoma with high sensitivity and specificity .