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目的通过对非小细胞肺癌患者放化疗前后及正常对照组血清蛋白质谱的测定,筛选差异蛋白,观察治疗前后血清蛋白质组谱变化。方法应用SELDI-TOF-MS及CM-10芯片对35例正常对照组、35例治疗前非小细胞肺癌患者及26例放化疗后非小细胞肺癌患者采集的血清样品进行蛋白质指纹图谱测定,并应用BioMarker Wizard 3.01及BioMarker Pattern System 5.01分析软件对测得数据进行处理及建立诊断模型。结果非小细胞肺癌组与正常对照组共检测到251个蛋白质峰,筛选出差异蛋白质峰16个,其中肺癌组8个蛋白质峰表达升高,8个蛋白质峰表达降低。以质荷比(M/Z)为2572.1、2885.8、3870.4、4161.4、5739.7和8164.3的6个蛋白质峰为依据组合构建分类决策树模型,原始判别总准确率为87%,敏感性为91%,特异性为83%;交叉验证总准确率为76%,敏感性为80%,特异性为71%。观察16个差异蛋白质峰的表达在放化疗前后的变化,显示均发生了不同程度的变化,趋向健康对照组,其中质荷比为2572.1、2885.8、4664.8、9228.4和9396.4的5个蛋白质峰在治疗前后发生显著变化。结论SELDI-TOF-MS技术对差异蛋白的筛选及治疗疗效的判定可能有一定的意义,需要进一步研究证明。
Objective To screen serum protein profiles of non-small cell lung cancer patients before and after radiotherapy and chemotherapy and normal control group, screen the differential proteins and observe the changes of serum proteome profile before and after treatment. Methods Serum samples collected from 35 patients with normal control, 35 patients with non-small cell lung cancer before treatment and 26 patients with non-small cell lung cancer after radiotherapy and chemotherapy were analyzed by protein fingerprinting using SELDI-TOF-MS and CM-10. BioMarker Wizard 3.01 and BioMarker Pattern System 5.01 software were used to process the measured data and establish a diagnostic model. Results A total of 251 protein peaks were detected in non-small cell lung cancer group and 16 normal control cells. Sixteen protein peaks were screened, including 8 protein peaks and 8 protein peaks in lung cancer group. The classification decision tree model was constructed based on six protein peaks with mass / charge ratio (M / Z) of 2572.1,2885.8,3870.4,4161.4,5739.7 and 8164.3. The original discriminant accuracy was 87% and the sensitivity was 91% The specificity was 83%. The overall accuracy of cross validation was 76%, the sensitivity was 80% and the specificity was 71%. The changes of 16 differential protein peaks before and after radiotherapy and chemotherapy showed that they all changed in different degrees and tended to the healthy control group. The five protein peaks with mass-to-charge ratios of 2572.1, 2885.8, 4664.8, 9228.4 and 9396.4 were treated in the treatment Before and after significant changes. Conclusion SELDI-TOF-MS technology may have some significance for the screening of differential proteins and the determination of curative effect, which needs further study to prove.