摘要目的 应用蛋白组学对肾透明细胞癌进行尿液差异蛋白研究,寻找显著性表达的差异蛋白,以提高肾透明细胞癌的检出率. 方法 2010年3-5月收治肾透明细胞癌患者11例,男10例,女1例.年龄46～ 78岁,平均63岁.所有患者手术或穿刺病理均确诊为肾透明细胞癌,临床分期:Ⅰa期3例,Ⅰb期6例,Ⅱ期1例,ⅣV期1例.正常对照组10例,均为男性,年龄25 ～ 32岁,平均29岁.应用磁珠联合基质辅助激光解吸附电离飞行时间质谱(MALDI-TOF MS)技术对两组的尿液进行差异蛋白研究,筛选出肾透明细胞癌的尿液差异蛋白,并应用遗传算法建立诊断模型. 结果 筛选出差异蛋白峰160个,具有显著性差异的蛋白峰1个,相对分子质量为2221.71(P=0.0304).利用ClinProTools 2.2软件通过遗传算法优化选择,筛选出符合条件的13个差异蛋白峰建立诊断模型,交叉验证的特异性和敏感性均为100％. 结论 应用磁珠联合MALDI-TOF MS技术和遗传算法建立的肾透明细胞癌尿液差异蛋白的诊断模型特异性和敏感性极高,有助于提高肾透明细胞癌的检出率.

abstractsObjective To study the application of proteomics in detecting differentially expressed proteins in renal clear cell carcinoma (RCCC) patient's urine in order to improve the diagnosis rate of RCCC.Methods From Mar.2010 to May.2010,the urine samples of 11 RCCC cases were collected,including 10 males and 1 female with average age of 63 (46-78) years.All patients were finally diagnosed as RCCC by post-operative or biopsy pathology.The normal control urine samples were collected from 10 males with average age of 29 (25-32) years.WCX beads combined with matrix assisted laser desorption ionization time of flighl mass spectrometry (MALDI-TOF MS) technique was applied in detecting differentially expressed proteins in RCCC patient's urine to find out differentially expressed proteins.And genetic algorithm was utilized to establish a diagnosis model.Results 160 differentially expressed proteins in RCCC patient 's urine were detected,and 1 was in significant difference,P=0.0304.ClinProTools 2.2 software was utilized with genetic algorithm to find out 13 differentially expressed proteins to establish a diagnosis model,and the sensitivity and specificity rate was 100％ after cross validation.Conclusions The diagnosis model established by genetic algorithms has high sensitivity and specificity rate,and can improve the diagnosis of RCCC.