应用SELDI技术筛选肺癌血清标志物的研究

Identification of Serum Biomarkers for Lung Cancer Using SELDI-TOF-MS and Protein Chip Data

目的:采用SELDI技术筛选肺癌患者的血清标志物。方法:用WCX2芯片SELDI技术分别检测31例肺癌患者、32例健康人血清、29例肺部良性病变。应用Proteinchipsoft ware 3.2软件采集蛋白峰,找出差异蛋白;应用Biomarker Pattern软件建立诊断模型。结果:肺癌患者和健康人血液标本比较,两组间有23个差异蛋白(P<0.05),用这些差异蛋白构建的诊断模型诊断肺癌敏感度为100%,特异度为96.9%,ROC曲线下面积为100%。肺癌和肺部良性病变患者的血清进行差异蛋白质组学研究发现,两组间有8个差异蛋白(P<0.05),用这些差异蛋白构建的诊断模型诊断肺癌敏感度为71.0%,特异度为62.1%,ROC曲线下面积为92.68%。结论:SELDI技术可以将肺癌患者、肺部良性病变患者和健康人正确区分,这对肺癌的筛查和早期诊断有重要意义。

Objective： To screen for biomarkers in the serum of lung cancer patients using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry （SELDI-TOF-MS） and protein chip technology. Methods： Serum samples from 31 lung cancer patients, 32 healthy volunteers and 29 patients with other pulmonary diseases were analyzed using cation exchange protein chip WCX2. Proteomic spectra were generated by mass spectrometry. The peaks were detected by Ciphergen proteinchip software 3. 20. Using Biomarker Pattern 5.0 software a diagnostic system was developed for differentiation of lung cancer from the control group. Results： Twenty-three protein peaks were significantly different between lung cancer patients and the healthy controls （P〈0.05）. This particular marker pattern differentiated the patients with lung cancer from the healthy patients with a sensitivity of 100% and a specificity of 96.9%. The area under the receiver operator characteristic curve was 100%. Eight protein peaks were significantly different between lung cancer patients and the other pulmonary diseases （P〈0.05）. This second marker pattern differentiated the patients with lung cancer from the other pulmonary diseases with a sensitivity of 71% and a specificity of 62.1%. The area under the receiver operator characteristic curve was 92.68%. Conclusion： Protein chip and SELDI-TOF-MS are useful tools for the detection and identification of new biomarkers in the serum of lung cancer patients.