[高发区食管癌筛查血清蛋白质指纹图谱诊断模型的建立及其临床价值]
[Establishment of a diagnostic model of serum protein fingerprint pattern for esophageal cancer screening in high incidence area and its clinical value].
作者信息
Wang Shi-Jie, Zhang Li-Wei, Yu Wei-Fang, Yu Jie-Kai, Zheng Shu, Li Ying-Sai, Er Li-Mian, Wen Deng-Gui, Gao Jin-Hong
机构信息
Department of Endoscopy, The Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, China.
出版信息
Zhonghua Zhong Liu Za Zhi. 2007 Jun;29(6):441-3.
OBJECTIVE
To analyze the alterations of serum proteomic pattern in esophageal squamous cell carcinoma (ESCC) by SELDI-TOF-MS, to establish a diagnostic model of ESCC screening in high incidence area and investigate its clinical value.
METHODS
SELDI-TOF-MS and CM10 proteinChip were used to detect the serum proteomic patterns of 36 cases of ESCC and 38 healthy control subjects in high incidence area. The data were analyzed and a diagnostic model was established by using support vector machine (SVM). The diagnostic model was evaluated by leave-one-out cross validation.
RESULTS
At the molecular weight range of 2000 to 20,000, 31 protein peaks were significantly different between ESCC and controls (P < 0.01). A diagnostic model consisting of 4 protein peaks could do the best in diagnosis of ESCC and controls. The accuracy was 85.1%, sensitivity was 86.1%, specificity was 84.2%, and positive value was 83.8%.
CONCLUSION
The diagnostic model formed by 4 protein peaks, established in this study, can well distinguish ESCC from healthy subjects. It provides a new approach for ESCC screening in high incidence area.
目的
采用表面增强激光解吸电离飞行时间质谱（SELDI-TOF-MS）分析食管鳞状细胞癌（ESCC）患者血清蛋白质组图谱的变化，建立高发区ESCC筛查的诊断模型并探讨其临床价值。
方法
应用SELDI-TOF-MS及CM10蛋白质芯片检测高发区36例ESCC患者和38例健康对照者的血清蛋白质组图谱，对数据进行分析并采用支持向量机（SVM）建立诊断模型，通过留一法交叉验证对诊断模型进行评估。
结果
在分子量范围为2000至20000时，ESCC组与对照组之间有31个蛋白质峰存在显著差异（P < 0.01）。由4个蛋白质峰组成的诊断模型对ESCC与对照组的诊断效果最佳，准确率为85.1%，灵敏度为86.1%，特异度为84.2%，阳性预测值为83.8%。
结论
本研究建立的由4个蛋白质峰组成的诊断模型能够很好地区分ESCC患者与健康人，为高发区ESCC筛查提供了一种新方法。
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