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目的用表面增强激光解吸离子化飞行时间质谱(SELD I-TOF-MS)分析食管癌高发区自然人群中贲门癌和正常对照血清蛋白表达谱的改变,筛选并建立高发区贲门癌血清蛋白指纹图诊断模型并探究其临床价值。方法采用CM10蛋白芯片及SELD I-TOF-MS技术对34例贲门癌和38例正常对照者血清蛋白指纹图谱进行检测,所得结果用ZUC I-蛋白芯片数据分析系统(ZUC I-Prote in Ch ip Data Analyze System)软件包分析,建立贲门癌蛋白指纹图诊断模型,并用留一法交叉验证作为评估模型、判别效果的方法。结果通过软件包运算,用3个质荷比峰(5 643.457 93、8 570.821 26、15 940.153 3 m/z)建立了贲门癌蛋白指纹图诊断模型,其准确度93.06%,敏感度85.29%,特异度100%,阳性预测值100%。结论本组建立的诊断模型可以有效区分贲门癌和健康人,为肿瘤高发区贲门癌的诊断与筛查提供了一条崭新途径。
Objective To detect the changes of serum protein profiles of cardia carcinoma and normal controls in patients with esophageal cancer in high incidence areas by using surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELD-TOF-MS), to screen and establish serum protein fingerprints Diagnose the model and explore its clinical value. Methods Serum protein fingerprints of 34 patients with cardia carcinoma and 38 normal controls were detected by CM10 protein chip and SELD I-TOF-MS. The results were analyzed by ZUC I-Prote in Ch ip Data Analyze System) software package to establish a diagnosis model of cardia cancer protein fingerprinting, and to use a method of cross-validation as a model to determine the effect of the method. Results According to the software package, a fingerprint model of cardia cancer protein fingerprinting was established with 3 peaks of mass-to-charge ratio (5 643.457 93,8 570.821 26,15 940.153 3 m / z) with the accuracy of 93.06% and the sensitivity of 85.29% Specificity 100%, positive predictive value 100%. Conclusion The diagnosis model established in this study can effectively distinguish cardia cancer and healthy people, providing a new way for the diagnosis and screening of cardia cancer in high incidence areas.