应用SELDI-TOF-MS技术建立鼻咽癌诊断中的血清蛋白质
指纹图谱模型
张宝新;吴平;陈剑光;郭爱林;何惠娟;王旭光;吴英健;杨展
【期刊名称】《第四军医大学学报》 【年(卷),期】2009(030)014
【摘要】AIM: To find new biomarkers and to establish classification tree model for the detection and diagnosis of naso-pharyngeal carcinoma by surface enhanced laser desorption/ionization time-of-flight-mass spectrometry (SELDI-TOF-MS) and bioinformatics tools. METHODS: Serum samples from 30 naso-pharyngeal carcinoma patients and 24 non-cancer controls were analyzed using CM10 protein chip system by SELDI-TOF-MS technology. Protein peak identification and clustering were performed using the Biomarker Wizard software. The classification tree model was then constructed using Biomarker Patterns System. Double blind confirmation was applied to the classification tree model. The results from the models were compared with those from the EBVCA-IgA serology test in order to verify its application value. RESULTS: Five protein markers were identified with the relative molecular weights of 8559, 15 115, 15 836, 15 937 and16 089. The differences of these protein markers between nasepharyngeal carcinoma patients and non-cancer controls were statistically significant (P<0.05). The detective model could differentiate nasopharyngeal carcinoma from non-cancer
controls with the accuracy rate of 98.1% (53/54), sensitivity of 96.7% (29/30) and specificity of 100% (24/24). The accuracy rate, sensitivity and specificity of double blind confirmation procedure were 86.4% (19/22), 80.0% (8/10) and 91.7% (11/12), respectively. The sensitivity was better compared with that from the EBVCA-IgA serology test. CONCLUSION: SELDI-TOF-MS technology can be used to find protein markers of nasopharyngeal carcinoma and construct detective models with high sensitivity and specificity.%目的:检测鼻咽癌、耳鼻部良性疾病和正常人血清中蛋白质指纹图谱,筛选特异的蛋白质标志物,构建用于鼻咽癌诊断的分类树模型.方法:采用CMIO芯片及SELDI-TOF-MS技术对30例鼻咽癌患者及24例对照组血清样本进行蛋白质指纹图谱检测分析,所得到的结果采用Biomarker Wizard和Biomarker Patterns System软件分析并建立用于鼻咽痛诊断的分类树模型,并用其余10例鼻咽癌患者和12例对照组标本进行双盲验证.同时用酶联免疫法(ELISA)检测两组的血清EB病毒VCA-IgA抗体,将诊断模型的判定结果通过与血清EB病毒VCA-IgA抗体检测结果相对比验证其对于临床的应用价值.结果:从两组血清中筛选出Mr为8559,15 115,15 836,15 937,16089的5个差别有统计学意义(P<0.05)的标志蛋白,所建立的诊断模型对鼻咽癌诊断的准确率、灵敏度和特异度分别为98.1%(53/54),96.7%(29/30)和100%(24/24).双肓验证后的准确率、灵敏度和特异度分别86.4%(19/22),80.0%(8/10),和91.7%(11/12).灵敏度优于血清EB病毒VCA-IgA抗体检测对鼻咽癌的判定结果.结论:运用SELDI-TOF-MS技术可以筛选出鼻咽癌的相关标志蛋白,建立了高灵敏度和特异度的诊断模型,对鼻咽癌临床早期
诊断方法的建立具有潜在意义. 【总页数】4页(1317-1320)
【关键词】鼻咽癌;诊断;表面增强激光解吸电离飞行时间质谱;蛋白质指纹图谱 【作者】张宝新;吴平;陈剑光;郭爱林;何惠娟;王旭光;吴英健;杨展
【作者单位】广东医学院附属医院中心实验室,广东,湛江,524001;广东医学院附属医院中心实验室,广东,湛江,524001;广东省人民医院医学研究中心,广东,广州,510080;广东省人民医院医学研究中心,广东,广州,510080;广东医学院附属医院中心实验室,广东,湛江,524001;广东医学院附属医院中心实验室,广东,湛江,524001;广东医学院附属医院中心实验室,广东,湛江,524001;广东医学院附属医院中心实验室,广东,湛江,524001 【正文语种】中文 【中图分类】R739.6 【文献来源】
https://www.zhangqiaokeyan.com/academic-journal-cn_journal-fourth-military-medical-university_thesis/0201246943368.html 【相关文献】
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应用SELDI-TOF-MS技术建立鼻咽癌诊断中的血清蛋白质指纹图谱模型
