血清蛋白质指纹图谱诊断模型在肾癌中的应用

目的 检测肾癌患者血清蛋白质,筛选特异的蛋白质标记物,构建用于肾癌早期诊断的血清蛋白质指纹图谱模型.方法 应用蛋白质芯片CM10及表面增强激光解吸/离子化飞行时间质谱(SELDI-TOF-MS)技术测定168例血清标本(其中肾癌53例,肾良性占位性病变47例,健康志愿者68例)的蛋白质质谱,用随机抽取的118例标本(肾癌38例,肾良性占位病变30例,健康志愿者50例)作为训练组,应用支持向量机进行训练和交叉验证,建立肾癌诊断模型;其余50例标本进行盲法验证.结果 利用质荷比分别为5350、4100、3446、5027和6115的5个蛋白峰建立区分肾癌和正常人的诊断模型,其敏感性为94.74%,特异性为92%.盲法验证显示敏感性为93.33%,特异性为88.89%.区分肾癌和肾良性占位病变的诊断模型,敏感性为92.11%,特异性为90%.区分透明细胞癌和其他病理类型的肾癌的诊断模型对透明细胞癌的判别率为92.84%,对其他病理类型的肾癌的判别率为81.82%.结论 表面增强激光解吸电离/飞行时间质谱技术结合支持向量机建立肾癌血清蛋白质指纹图谱模型对诊断肾癌具有较高的敏感性与特异性.

Application of serum protein fingerprint model in diagnosis of renal cell carcinoma

Objective To detect new biomarkers and to establish a serum protein fingerprint model for early detection and diagnosis of renal cell carcinoma.Methods The serum samples of 53 renal cell carcinoma patients,47 benign renal masses patients,and 68 healthy volunteers were randomly divided into 2 sets:training set(n=118,including 38 renal cell carcinoma patients,30 benign renal masses patients,and 50 healthy volunteers) and test set(n=50).The fingerprint expressions of protein chips were obtained by using surfac...