基础医学与临床 ›› 2009, Vol. 29 ›› Issue (11): 1174-1179.

• 研究论文 • 上一篇    下一篇

SELDI-TOF-MS技术筛选NSCLC血清肿瘤标志物

叶韵斌 陈玲 佘志廉 陈慧菁 蔡丹 柳硕岩 陈强   

  1. 福建省肿瘤医院 福建省肿瘤医院 福建省肿瘤医院肿瘤免疫研究室
  • 收稿日期:2009-05-19 修回日期:2009-06-22 出版日期:2009-11-20 发布日期:2009-11-20
  • 通讯作者: 叶韵斌

Detection of serum protein biomarkers by surface enhancedlaser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS) in patients of non-small cell lung cancer

Yun-bin YE, Ling CHEN, Zhi-lian SHE, Hui-jing CHEN, Dan CAI, Shuo-yan LIU, Qiang CHEN   

  1. Fujian Provincial Tumor Hospital Fujian Provincial Tumor Hspital,Fujian Medical University
  • Received:2009-05-19 Revised:2009-06-22 Online:2009-11-20 Published:2009-11-20
  • Contact: Yun-bin YE,

摘要: 目的 分析非小细胞肺癌(NSCLC)血清蛋白表达谱的改变,筛选并建立NSCLC血清蛋白的差异表达谱。方法 应用表面增强激光解析电离化飞行时间质谱(SELDI-TOF-MS,简称SELDI-TOF或SELDI)技术,分析100例NSCLC患者和100例正常对照血清,获得蛋白表达图谱。用Biomarker Pattern(BPS)软件分析NSCLC差异蛋白并初步建立诊断模型。通过盲筛进一步验证诊断模型。结 果 发现NSCLC患者血清与正常人有16个显著差异的蛋白波峰,显著高表达8个(P<0.001)。显著低表达8个(P<0.001)。经BPS软件分析,建立分类树模型,其诊断的灵敏度为100%,特异度为100%。100例样本盲筛验证结果显示,其灵敏度为96.15%,特异度为95.83%。无吸烟史患者较有吸烟史患者血清中显著高表达蛋白质波峰有3个(P<0.05)。鳞癌患者较腺癌患者血清中显著高表达蛋白质波峰有2个(P<0.01)。不同病理分期患者之间未发现差异蛋白峰。结 论 SELDI-TOF-MS 技术可筛选出NSCLC差异性蛋白并建立NSCLC诊断的分类树模型,有望成为NSCLC早期诊断的辅助指标。

关键词: SELDI, 肿瘤, 非小细胞肺癌, 蛋白质组学

Abstract: Objective To analyze the characteristic of serum proteins in non-small cell lung cancer ( NSCLC) patients, establish serum markers pattern for the diagnosis of NSCLC. Methods Surface enhanced laser desorption ionization time of flight mass spectormetry( SELDI-TOF-MS ) technology was used to analyze serum samples including 100 cases of NSCLC patients and100 cases of healthy controls. Biomarker Pattern Software (BPS) was used to detect the protein peaks significantly different between NSCLC patients and healthy controls. And then established a diagnostic pattern.This pattern was further valuated by a blind test. Results Sixteen significantly different protein peaks were found in serum samples between NSCLC patients and healthy controls. Eight up-regulated protein peaks and eight down-regulated protein peaks (P<0.001)were identified in serum samples of patients of NSCLC comparing with healthy controls.Using BPS, a diagnostic pattern was established with 100% sensitivity and 100% specificity . A blind test generated a sensitivity of 96.15% and specificity of 95.83% respectively. Three up-regulated protein peaks(P<0.05)were identified in serum samples of patients of NSCLC with smoking history comparing with no smoking history. Two up-regulated protein peaks(P<0.01)were identified in serum samples of patients of squamous carcinoma comparing with adenocarcinoma .No significantly different protein peak was found in serum samples of NSCLC patients with different clinical stages. Conclusion SELDI-TOF-MS technology can identify the significantly different protein peaks and establish a diagnostic pattern with high sensitivity and specificity.It will provide a highly accurate approach for the diagnosis of NSCLC.

Key words: SELDI, carcinoma, non-small cell lung cancer, proteomics