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目的:应用表面增强激光解析离子飞行时间质谱(Surface-enhanced laser desorption ionization time of flight mass spectrometry,SELDI-TOF-MS)技术筛选与恶性肿瘤化疗后血糖变化情况相关的血清蛋白质组指纹并建立模型。方法:应用CM10弱阳离子芯片结合SELDI-TOF-MS技术检测197例恶性肿瘤患者化疗后血清样本的蛋白质谱,2年后随访,按血糖标准分为血糖正常组(171例)、糖耐量异常组(16例)和糖尿病组(10例),利用Biomarker Wizard软件比较各组间的血清蛋白质指纹图谱,Biomarker Pattern软件建立模型。结果:M/Z为4276和4662的两个蛋白质组成的诊断模型可将糖尿病组与糖耐量异常组准确分组,灵敏度、特异度和准确度分别为70%、81.25%和76.92%;M/Z为2818、7535和2633的三个蛋白质组成的诊断模型可将糖尿病组与血糖正常组准确分组,灵敏度、特异度和准确度分别为80%、79.53%和82.32%;M/Z为2818、7744、3187、2564、4175、5165和3374的七个蛋白质组成的诊断模型可将糖耐量异常组与血糖正常组准确分组,灵敏度、特异度和准确度分别为87.5%、87.72%和88.77%。结论:SELDI-TOF-MS技术筛选出恶性肿瘤化疗后三组血糖情况的蛋白质指纹,M/Z为4175、4276、4086、3158、3374、3316、2044、3441、4662和4290可作为预测化疗后糖尿病的指标,M/Z为2818、3374、3352、4276、2932、8817、4070、3187、7535和15525可作为预测化疗后糖耐量异常的指标,M/Z为6021、3187、2818、2932、3273、4070、7916、8817、8057和4387可作为预测化疗后可能不会发生糖尿病的指标,这为化疗副反应的防治提供了科学依据。
Objective: To screen the fingerprints of serum proteome associated with the changes of blood glucose after chemotherapy and to establish the model by SELDI-TOF-MS. Methods: The protein profiles of serum samples from 197 patients with malignant tumor after chemotherapy were detected by CM10 weak cation chip combined with SELDI-TOF-MS. Two years after follow-up, the blood glucose level was divided into normal glucose group (171 cases), abnormal glucose tolerance group (16 cases) and diabetes mellitus group (10 cases). Biomarker Wizard software was used to compare the serum protein fingerprinting between groups. Biomarker Pattern software was used to establish the model. Results: The two proteins with M / Z 4276 and 4662 could be used to diagnose diabetic patients and patients with impaired glucose tolerance accurately. The sensitivity, specificity and accuracy were 70%, 81.25% and 76.92%, respectively. M / Z The diagnostic model consisting of three proteins, 2818, 7535 and 2633, accurately grouped diabetes mellitus and normal glucose groups with sensitivity, specificity and accuracy of 80%, 79.53% and 82.32%, respectively; M / Z was 2818 and 7744 , 3187, 2564, 4175, 5165 and 3374 can accurately group glucose tolerance group and normal glucose group with sensitivity, specificity and accuracy of 87.5%, 87.72% and 88.77%, respectively. Conclusion: SELDI-TOF-MS was used to screen out protein fingerprints of blood glucose in three groups after chemotherapy. M / Z was 4175,4276,4086,3158,3374,3316,2044,3441,4662 and 4290, which could be used as predictors of postoperative chemotherapy Diabetes mellitus, M / Z is 2818,3374,3352,4276,2932,8817,4070,3187,7535 and 15525 can be used as predictors of post-chemotherapy glucose tolerance abnormalities, M / Z is 6021,3187,2818,2932, 3273, 4070, 7916, 8817, 8057 and 4387 can be used as predictors for the possible absence of diabetes after chemotherapy, providing a scientific basis for the prevention and treatment of chemotherapy side effects.