上行型与下行型鼻咽癌患者血清蛋白指纹图谱的检测及意义

Detection and Clinical Significance of Serum Proteomic Patterns for Ascending and Descending Types of Nasopharyngeal Carcinoma by Protein Chip Technology

目的:通过分析上行型与下行型鼻咽癌的血清蛋白质谱,筛选鼻咽癌蛋白质标志物,为预测鼻咽癌临床分型提供可能的简易方法。方法:应用CM10弱阳离子交换芯片和表面增强激光解吸离子化飞行时间质谱技术(SELDI-TOF-MS)分析22例上行型鼻咽癌和26例下行型鼻咽癌患者的血清标本,采用Biomarker Wizard 3.01及Biomaker Pattern 5.01分析软件对测得的数据进行处理并建立相应的检测模型。结果:通过对上行型、下行型鼻咽癌患者血清蛋白指纹图谱数据的比较,筛选出差异蛋白质峰9个(P<0.05),相对分子量分别为2 776.27 Da,3 940.04 Da,6 440.51 Da和9 138.54 Da的4个蛋白质峰被选择用于构建分类决策树模型,该模型交叉验证总准确率为81.3%,上行型鼻咽癌患者检出率为77.3%,下行型鼻咽癌患者检出率为84.6%。分别对这4个蛋白质峰进行数据库搜索,得到4种与分子量最为接近的蛋白质。结论:应用SELDI-TOF-MS技术构建的分类决策树模型能达到区分上下型鼻咽癌患者的效果,这可能对鼻咽癌的分子分型、制定个体化治疗方案及预后预测方面有一定的临床意义,可进一步深入研究。

Objective： To screen serum protein biomarkers by SELDI-TOF-MS to establish a subset to be used in the predic- tion of ascending and descending types of loco-regionally advanced nasopharyngeal carcinoma（NPC） . Methods： Proteomic spectra from serum of 22 ascending types of loco-regionally advanced NPC patients and 26 descending types of NPC subjects were analyzed by CM-10 protein chip and surface enhanced laser desorption ionization-time of flight-mass spectrometry（SELDI-TOF-MS）. Biomarker Wizard 3.01 and Biomarker Pattern 5.01 were used in combination to analyze the data and to develop decision tree model. Results： The data of ascending NPC types and descending types of NPC subjects were compared and 9 discrepant protein peaks were found （P 〈0.05）. Of the 9 protein peaks, 4 protein biomarkers（2 776.27 Da,3 940.04 Da,6 440.51 Da,9 138.54 Da） were chosen using the decision tree model. The diagnostic accuracy was 81.3%. Four proteins with similar molecule weights to them were obtained through searching in the database. Conclusion： The established serum proteomic pattern can best divide NPC patients into those with ascending or descending types. It may be helpful in assessing clinical type, making individualized therapeutic plan and predicting prognosis, which needs to be demonstrated by further study.