利用SELDI-TOF-MS蛋白质指纹图谱技术建立肺腺癌诊断模型

Establishment of diagnostic model of lung adenocarcinoma using SELDI-TOF-MS protein fingerprinting technology

目的:寻找肺腺癌患者血浆(清)蛋白特异性生物标志物,用最佳的标志蛋白组合建立肺腺癌诊断模型,并探讨其用于肺腺癌筛查的可行性。方法:应用表面增强激光解吸电离飞行时间质谱(SELDI-TOF-MS)技术及CM10芯片,检测45例肺腺癌患者和40例正常人血清蛋白质指纹图谱,用Biomark Wizrd和Biomark Patterns Software软件对结果进行分析,建立肺腺癌诊断模型;双盲法分析另外19例肺腺癌和20例正常人血清的SELDI质谱数据,验证该模型诊断肺腺癌的准确度。结果:肺腺癌患者和正常人血清蛋白质指纹图谱间有31个差异蛋白(P<0.05),其中以分子量为11.66kD的蛋白在两组血清中的差异最为显著(P<10-7),该蛋白对诊断肺腺癌有很强的敏感性和特异性;软件自动筛选出分子量为11.66kD的标志蛋白为主根结点,联合3882.9、4673.2、3158.2和2047.2等4个标志蛋白建立了最佳的肺腺癌诊断模型,对肺腺癌诊断(盲法)的敏感性为84.2%(16/19),特异性为90.0%(18/20)。结论:SELDI-TOF-MS技术建立的肺腺癌血清检测法,快速、简单、特异和敏感,为肺腺癌诊断和筛查提供了一个可行的途径和方法。

Objective To establish the diagnostic model of lung adenocarcinoma using optimum combination pattern of marked proteins in patient serum, and explore the feasibility of screening for lung adenocarcinoma using SELDI- TOF-MS protein fingerprinting assay. Methods Protein spectra of 3,5 cases of patients with lung adenocarcinoma and 40 normal controls were generated using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry （SELDI-TOF-MS） on CM10 chips. The biomarker wizard and biomarker pattems system software were used to analyze the distinct proteins between two groups, and create a best decision classification tree model for diagnosing lung adenocarcinoma. Then the model established was blindly validated by the protein fingerprints of 19 cases of lung cancer and 40 cases of healthy cntrols. Results Thirty one distinguished proteomic peaks in total were detected, five of them were used to build a proteomic pattern. The proteomic pattern couLd differentiate the patients with lung adenocarcinoma from the healthy people with a sensitivity of 84.2% （16/19） and a specificity of 90.0% （18/20） in the blinded sample set. Conclusion SELDI-TOF-MS serum protein fingerprinting is a quick, easy,and convenient tool for lung adenocarcinoma detection and diagnosis ,which may be used in screening for lung adenocarcinoma.