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目的:研究食管癌癌变过程中血清低相对分子质量蛋白的细微变化,探索食管癌发生的机制,寻找食管癌早期诊断的生物标志物和方法.方法:应用表面激光解析电离飞行时间质谱技术对食管癌患者血清和健康对照血清进行蛋白质谱指纹图谱检测,通过Biomarker Wizard软件筛选差异蛋白,使用人工神经网络软件建立食管癌早期诊断模型并用盲法验证其诊断效果;将食管癌早期和中晚期食管癌患者血清质谱图进行比对分析,寻找各期差异蛋白,并建立分期诊断模型.结果:发现食管癌和正常人差异蛋白5种,早期食管癌和中晚期食管癌差异蛋白3种.通过早期食管癌组和健康对照组建立早期诊断模型的灵敏度87.88%,特异度91.43%,准确度89.71%,经过盲法验证结果为灵敏度95.83%,特异度89.13%,准确度91.43%.早期食管癌和中晚期筛选的差异蛋白建立的分期诊断模型灵敏度75.76%,特异度79.17%,准确度77.19%.结论:表面增强激光解析离子化飞行时间质谱联合人工神经网络技术操作较为简便,在食管癌的诊断和分期上具有可行性.
OBJECTIVE: To study the subtle changes of low molecular weight protein in esophageal carcinogenesis, to explore the mechanism of esophageal carcinogenesis and to search biomarkers and methods for early diagnosis of esophageal cancer.Methods: The surface plasmon polarimetry time of flight mass spectrometry Cancer patients serum and healthy control serum protein fingerprinting detection, screening of differential proteins by Biomarker Wizard software, the use of artificial neural network software to establish early diagnosis of esophageal cancer model and blind diagnosis of its diagnostic effect; esophageal cancer early and advanced esophageal cancer The results showed that there were 5 differential proteins in esophageal cancer and normal human, 3 esophageal cancer in early esophageal cancer and 3 esophageal cancer in early and late esophageal cancer.According to the results of early esophageal The sensitivity and specificity of the early diagnosis model in cancer group and healthy control group were 87.88%, 91.43% and 89.71%, respectively, and the results of the sensitivity test were 95.83%, 89.13% and 91.43% The differential diagnosis of late screening established staging diagnostic model sensitivity of 75.76%, specificity of 79.17%, accurate Degree of 77.19% .Conclusion: Surface-enhanced laser desorption ionization time of flight mass spectrometry combined with artificial neural network technology is relatively simple and feasible in the diagnosis and staging of esophageal cancer.