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肿瘤标志物蛋白芯片中肺癌相关指标的筛选优化 被引量:4

Screening and optimizing the lung cancer related tumor markers from multi-tumor marker protein chip
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摘要 目的:分析多种肿瘤标志物(Tumor marker,TM)与肺癌的相关性,筛选相关指标,为建立检测肺癌的小型蛋白芯片提供依据。方法:使用TM蛋白芯片系统,检测311例肺癌患者血清中多种TM:癌抗原125(Cancer antigen 125,CA125)、癌抗原153(Cancer antigen 153,CA153)、糖链抗原199(Carbohydrate antigen,CA199)、癌胚抗原(Carcinoembryonic antigen,CEA)、甲胎蛋白(Alpha fetoprotein,AFP)、铁蛋白(Ferritin,FER)、游离型前列腺特异性抗原(Free prostate specific antigen,free-PSA)及前列腺特异性抗原(Prostate specific antigen,PSA)的水平。筛选出肺癌中阳性率高的的指标,采用Kappa检验比较其与TM蛋白芯片系统检测结果的一致性,寻找最佳联检组合。结果:311例肺癌患者中TM升高主要集中在4项指标:CEA(41.5%)、CA153(15.2%)、CA199(20.9%)、CA125(37.0%);Kappa检验得出,一致性极强的小型组合有5种,使用成本-效果分析法得出最佳组合为CA125+CEA。结论:血清CEA和CA125水平升高对肺癌的诊断有较高的临床价值,选择CA125+CEA联合检测,可以在不降低检出率的情况下降低检测成本。 Objective:To screen and optimize the lung cancer related tumor markers from multi-tumor marker protein chip.Methods:With the multi-tumor marker protein chip,the sera of 311 patients with lung cancer were detected for multi-tumor markers including carcinoembryonic antigen(CEA),alpha fetoprotein(AFP),carbohydrate antigen 199(CA199),cancer antigen 153(CA153),cancer antigen 125(CA125),prostate specific antigen(PSA),free-PSA,and ferritin.Lung cancer related parameters were analyzed by Kappa test and cost-effectiveness analysis.Results:There were four kinds of tumor markers which were apparently increased in the serum among the 311 lung cancer patients:CEA(41.5%),CA153(15.2%),CA199(20.9%),and CA125(37.0%).Five tumor marker combinations were found to be strongly consistent with the results of multi-tumor marker protein chip by Kappa test,and the combination of CEA with CA125 was proved to be the best by cost-effectiveness analysis.Conclusion:The combined detection of sera CEA and CA125 is helpful to diagnose lung cancer,which is consistent with the positive rate of diagnosis by using multi-tumor marker protein chip and the two combination test can cut down the cost of diagnosis of lung cancer.
出处 《重庆医科大学学报》 CAS CSCD 北大核心 2011年第11期1353-1356,共4页 Journal of Chongqing Medical University
基金 湖北省自然科学基金资助项目(编号:2010CDB05502) 肿瘤生物学行为湖北省重点实验室科研启动基金资助项目
关键词 肿瘤标志物 肺癌 诊断 tumor markers lung cancer diagnosis
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