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SELDI-TOF-MS技术诊断贲门癌高发区慢性萎缩性贲门炎及贲门黏膜不典型增生
作者姓名:Wang DC  Wang LD  Zheng S  Fan ZM  Li JL  Feng CW  Zhang YR  Liu B  Gao SS  He X
作者单位:1. 450052,郑州大学医学院癌症研究室,河南省食管癌重点开放实验室
2. 浙江大学肿瘤研究所
3. 河南省林州市姚村食管癌医院病理科
4. 郑州大学医学院第二附属医院消化内科
5. 河南省人民医院消化内科
6. 首都医科大学附属北京同仁医院消化内科
基金项目:国家杰出青年科学基金资助项目(30025016),河南省高校创新人才工程项目(1999125),河南省医药卫生创新人才工程项目(200084),郑州大学211工程项目
摘    要:目的探讨贲门癌高发区人群贲门黏膜不典型增生(DYS)、慢性萎缩性贲门炎(CAG)的血清学诊断方法,为贲门癌高危人群的筛查提供新手段。方法采用弱阳离子结合芯片(WCX2)及表面增强激光解吸/电离飞行时间质谱仪(SELDI-TOF-MS)检测食管癌高发区无症状普查人群143人(其中活检组织诊断为正常63人,CAG57人,DYS23人)的血清蛋白质质谱,对原始信号的总离子强度及相对分子质量做均一化校正及噪声滤过,并对同一质荷比蛋白质质谱峰平均强度值做组间t检验。应用BiomarkerPattern软件建立决策树分类模型,经10倍交叉验证得到该分类模型对测试组病变人群的诊断率和排除率。结果采用DYS和正常组质荷比为M3894·0的一种蛋白质建立的决策树分类模型,其对测试组DYS诊断率为87%,排除率为86%;CAG和正常组则有质荷比为M2942·15和M33316·6的2种蛋白质建立决策树分类模型,对测试组CAG诊断率为93%,排除率为92%。结论SELDI-TOF-MS蛋白质芯片技术检测血清蛋白质质谱法诊断贲门癌高发区DYS和CAG有较高的敏感性和特异性,为贲门癌高危人群筛查提供了新的血清学手段。

关 键 词:胃肿瘤  胃炎  表面增强激光解吸/电离飞行时间质谱仪
收稿时间:12 31 2004 12:00AM
修稿时间:2004-12-31

The application of surface-enhanced laser desorption/ionization-time of flight-mass spectrometry in diagnosing dysplasia and chronic atrophic gastric-carditis in population with high risk of gastric-cardia adenocarcinoma
Wang DC,Wang LD,Zheng S,Fan ZM,Li JL,Feng CW,Zhang YR,Liu B,Gao SS,He X.The application of surface-enhanced laser desorption/ionization-time of flight-mass spectrometry in diagnosing dysplasia and chronic atrophic gastric-carditis in population with high risk of gastric-cardia adenocarcinoma[J].Chinese Journal of Internal Medicine,2005,44(8):573-576.
Authors:Wang Dao-cun  Wang Li-dong  Zheng Shu  Fan Zong-min  Li Ji-lin  Feng Chang-wei  Zhang Yan-rui  Liu Bin  Gao Shan-shan  He Xin
Affiliation:Laboratory for Cancer Research, College of Medicine, Zhengzhou University, Henan Key Laboratory for Esophageal Cancer, Zhengzhou 450052, China.
Abstract:Objectives To evaluate the serum biomarkers for diagnosis of gastric cardia dysplasia (DYS) and chronic atrophic gastric-carditis (CAG) and to provide a novel screening method for high risk population of gastric-cardia adenocarcinoma (GCA). Methods Proteomic spectra were generated by surface-enhanced laser desorption/inionation-time of flight-mass spectra (SELDI-TOF-MS) and weak cation exchange protein chip system. A set of spectra derived from analysis of serum from 143 symptom-free subjects at high-risk area for GCA, including 63 cases with histologically normal gastric cardia epithelia, 57 of CAG and 23 of DYS, were analyzed by bioinformatics like decision tree classification algorithm. The sensitivity and the specificity for test group were performed by using 10-fold cross validation classification with the decision tree classification model. Results One protein spot with a ratio of mass to charge (M/Z) of M3894.0 was selected to build a decision tree classification model to identify the case with DYS or normal. With this classification model, the sensitive rate for DYS identification was 87%(20/23). Two proteins with M/Z of M2942.15 and M33316.6 were used to build a decision tree classification model. With this model, the sensitivity for discriminating CAG from normal was 93% (53/57) and the specificity was 92 (58/63). Conclusions The gastric cardia lesions of DYS and CAG could be identified by SELDI-TOF-MS technique specifically in symptom-free subjects at high incidence area for GCA. The present findings provide a new screening way for high-risk subjects with CGA.
Keywords:Stomach neoplasms  Gastritis  SELDI-TOF-MS
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