摘要
目的:应用SELDI质谱仪建立大肠癌血清蛋白质指纹图谱的诊断模型。方法:测定182例血清标本(其中55例大肠癌、35例大肠腺瘤、92例健康人)的蛋白质指纹图谱,结合人工神经网络及支持向量机对这些数据进行处理,建立相应的指纹图谱诊断模型。结果:运用生物信息学方法从大肠癌与健康对照中筛选出了4个质荷比位于5 911 Da、8 922 Da、8 943 Da、8 817 Da(M/Z)峰,用它们建立的诊断模型的特异性为93.3%,敏感度为90.9%,Youden指数为0.84242。从大肠癌与大肠腺瘤中筛选出7个质荷比位于17 247 Da、18 420 Da、5 911 Da、9 294 Da、4 654 Da、21 694 Da、21 742 Da的峰值,建立模型的特异性为83.2%,敏感度为89.3%,Youden指数为0.72484。结论:该方法在大肠癌的诊断中较传统方法具有更高的敏感性和特异性。
Objective： To develop a bioinformatic tool and to use it to identify proteomic patterns in serum, distinguishing colorectal cancer from colorectal adenoma and healthy individuals. Methods： 182 serum samples including 55 colorectal cancer patients, 35 colorectal adenoma and 92 healthy individuals were subjected to analysis by surface-enhanced laser desorption/ionization （SELDI） mass spectrometry. Results： The diagnostic pattern combined of 4 candidate biomarkers （M/Z 5 911,8 922,8 944,and 8 817） could separate colorectal patients from healthy control with a specificity of 93, 3% ,sensitivity of 90.9% ,and Youden index value of 0. 84242. The diagnostic pattern combined of 7 candidate biomarkers （M/Z 17 247,18 420,5 911, 9 294,4 654,21 694,and 21 742） could separate colorectal cancer patients from colorectal adenoma patients with a specificity of 83.2% ,sensitivity of 89.3% ,and Youden index value of 0. 72484.Conclusions： Combination of SELDI with bioinformatics tool can identify some new biomarkers from the sera of colorectal cancer patients, which has a high sensitivity and specificity to distinguish colorectal cancer patients from healthy control.
出处
《浙江大学学报（医学版）》
CAS
CSCD
北大核心
2009年第5期470-477,共8页
Journal of Zhejiang University(Medical Sciences)
基金
教育部霍英东优选资助基金(114031)
浙江省科技发展计划项目(2006C23033)
