蛋白质质谱在肺鳞癌早期诊断中的研究

目的 探讨应用血清蛋白质谱建立肺鳞癌患者的诊断模型,提高肺鳞癌早期诊断率.方法 应用表面加强激光解吸电离飞行时间质谱（Surface-enhanced desorption ionization time-of-flight mass spectrometry,SELDI-TOF-MS）技术及其配套的蛋白质芯片对50例肺鳞癌患者和50例健康人血清中的蛋白质组图谱进行检测,结合相关软件建立决策分类树诊断模型,并评估该模型的诊断价值.结果 两组间有9个差异性表达蛋白峰,其中3个在肺鳞癌患者血清中高表达,m/z（质荷比）分别是9 194.06 Da,11 681.15 Da和51 370.19 Da,应用数据建立分类树模型,获得了一个由7个蛋白9 194.06 Da,51 370.1 Da,15 879.1 Da,6 624.57 Da,8 929.80 Da,11 681.1 Da,1 013.77 Da组成的标志蛋白组合模式.在训练组中,该模型的敏感性和特异性分别为92%和96%.结论 该模型对诊断肺鳞癌具有较高的灵敏度和特异度,值得临床应用.

The use of plasma SELDI-TOF-MS proteomic patterns in the early detection of lung squamous cell cancers

Objective To improve the early diagnostic rate of lung squamous cell carcinoma by using surface-enhanced desorption ionization time-of-fight mass spectrometry (SELDITOF-MS) to develop proteomic diagnosis. Methods 50 patients with lung cancer and 50 healthy individuals were detected using SELDI-TOF-MS and protein chips.The diagnostic model was established with the assistance of software and its diagnostic value was evaluated. Results There were nine peaks for the differently expressed proteins in the two groups. Three of which were highly expressed in patients with lung cancer (m/z: 9194.06, 11681.15, and 51370.19). Using tree analysis pattern, the combination of seven biomarkers (9194.06, 51370.1, 15879.1, 6624.57, 8929.80, 11681.1, and 1013.77) may identify lung cancer from normal controls with a sensitivity of 92% and a specificity of 96%.Conclusions The profiling has a high sensitivity and specificity to identify lung cancer.