| 张霞 李琦 吴小意 陈文妃 张宗德 张杰.SELDI-TOF-MS筛选慢性阻塞性肺疾病血清标志蛋白的初步研究[J].现代生物医学进展英文版,2014,14(34):6618-6621. |
| SELDI-TOF-MS筛选慢性阻塞性肺疾病血清标志蛋白的初步研究 |
| Application of SELDI-TOF-MS Technology Analyzing SerumProteinProfiling in Diagnosis of Chronic Obstructive Pulmonary Disease |
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| DOI： |
| 中文关键词: 慢性阻塞性肺疾病 表面增强激光解析电离飞行时间质谱 蛋白质组学 |
| 英文关键词: Chronic obstructive pulmonary disease Surface-enhanced laser desorption ionization time-of-flight mass spectrometry Proteomics |
| 基金项目:国家科技重大专项课题（2013ZX10003002） |
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| 中文摘要: |
| 目的：利用表面增强激光解吸电离飞行时间质谱技术（SELDI-TOF-MS)筛选慢性阻塞性肺疾病（COPD）血清特异标志物。方
法：应用SELDI-TOF-MS技术检测30 例COPD 稳定期患者和30 例健康对照者血清蛋白指纹图谱，采用Biomarker pattern 软件
进行分析，建立COPD 的诊断模型。结果：COPD 患者血清蛋白图谱与对照组相比，在相对分子质量2 000-15 000 范围内共检测到
75 个蛋白峰，发现19 个有统计学差异的蛋白峰(P<0.05)。通过对COPD 组与对照组间的数据作进一步分析，经BPS 软件分析，建
立质荷比（M/Z）3 167、4 645 的差异蛋白组成的诊断模型，其诊断敏感度为96.67 %，特异度为96.67 %。结论：SELDI-TOF-MS 技
术是一种快速、简单易行、用量少和高通量的分析方法。能直接筛选出COPD 血清中特异表达标志物，用特异表达标志物建立的
诊断模型能有效区分COPD 患者与健康对照者，有望成为COPD 诊断的辅助指标。 |
| 英文摘要: |
| Objective:To screen the serum protein biomarkers of chronic obstructive pulmonary disease (COPD) by using
surface-enhanced laser adsorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology.Methods:SELDI-TOF-MS
was used to analyze serum samples including 30 cases of stable COPD patients and 30 cases of healthy controls. Biomarker Pattern
Software was used to establish a diagnostic pattern.Results:Compared with normal controls, 75 protein peaks were detected at the
molecular range of 2 000-15000Da and nineteen protein biomarkers were identified. Analyzed by BPS, two protein peaks (M/Z 3 167,4
645) were chosen to build the model for COPD detection. The diagnostic model separated the COPD from the control samples with
sensitivity of 96.67 % and specificity of 96.67 %.Conclusion:SELDI-TOF-MS is a quick, easy and practical, high throughput analytic
method. It can detect biological markers of COPD, and it shows the diagnostic model established by distinguished proteomic peaks can
discriminate COPD patients fromhealthy controls. It will provide a highly accurate approach for the diagnosis of COPD. |
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