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目的:分析喉癌患者与正常人血清蛋白指纹图谱的变化,建立能鉴别喉癌和正常人血清标志物的诊断模型。方法:利用固定金属亲和表面蛋白质芯片和表面增强激光解吸离子化飞行时间质谱对32例喉癌(18例声门型癌,14例声门上型癌)和38例正常人血清蛋白质谱进行分析。获得的结果采用Ciphergen公司的Biomar-ker Wizard和Biomarker Pattern软件分析。结果:通过对喉癌患者术前血清与正常人血清蛋白质谱分析发现共有15个蛋白质表达量有明显差异。并获得相对分子质量为3795.04、5068.18、5339.78、5909.28、6629.74、9266.32、13879.60、14037.10这8个蛋白质组成的模型,可将喉癌与正常人正确分组,其正确分组率分别为87.50%(28/32)和86.84%(33/38)。结论:用SELDI-TOF-MS技术初步建立的蛋白质模型为早期诊断喉癌提供了新的技术平台。
OBJECTIVE: To analyze the changes of serum protein fingerprints in patients with laryngeal cancer and normal subjects, and establish a diagnostic model to identify serum markers of laryngeal cancer and normal individuals. Methods: Serum protein profiles of 32 laryngeal carcinomas (18 cases of glottic carcinoma, 14 cases of supraglottic carcinoma) and 38 normal controls were studied by immobilized metal affinity surface protein chip and surface enhanced laser desorption ionization time of flight mass spectrometry analysis. The results obtained were analyzed using Ciphergen Biomar-ker Wizard and Biomarker Pattern software. Results: Serum protein profiles of preoperative serum and normal human in patients with laryngeal cancer were found to have significant differences in 15 protein expression levels. And get the molecular weight of 3795.04,5068.18,5339.78,5909.28,6629.74,9266.32,13879.60,14037.10 the eight protein model can be correctly grouped laryngeal cancer and normal people, the correct grouping rates were 87.50% (28 / 32) and 86.84% (33/38). Conclusion: The protein model preliminarily established by SELDI-TOF-MS technology provides a new technology platform for the early diagnosis of laryngeal cancer.