应用锚定芯片飞行时间质谱技术筛选小细胞肺癌患者血清中的肿瘤标志物蛋白。
Use of anchorchip-time-of-flight spectrometry technology to screen tumor biomarker proteins in serum for small cell lung cancer.
机构信息
Department of Respiratory Medicine, Second Affiliated Hospital of Medical School, Xi'an Jiaotong University, N-710000 Xi'an, China.
出版信息
Diagn Pathol. 2010 Sep 20;5:60. doi: 10.1186/1746-1596-5-60.
BACKGROUND
The purpose of this study is to discover potential biomarkers in serum for the detection of small cell lung cancer (SCLC).
METHODS
74 serum samples including 30 from SCLC patients and 44 from healthy controls were analyzed using ClinProt system combined with matrix-assisted laser desorption/ionization time-of-flight masss spectrometry (MALDI-TOF-MS). ClinProt software and genetic algorithm analysis selected a panel of serum markers that most efficiently predicted which patients had SCLC.
RESULTS
The diagnostic pattern combined with 5 potential biomarkers could differentiate SCLC patients from healthy persons, with a sensitivity of 90%, specificity of 97.73%. Remarkably, 88.89% of stage I/II patients were accurately assigned to SCLC.
CONCLUSIONS
Anchorchip-time-of-flight spectrometry technology will provide a highly accurate approach for discovering new biomarkers for the detection of SCLC.
背景
本研究旨在发现用于检测小细胞肺癌（SCLC）的血清潜在生物标志物。
方法
使用 ClinProt 系统结合基质辅助激光解吸/电离飞行时间质谱（MALDI-TOF-MS）分析了 74 份血清样本，其中包括 30 份 SCLC 患者样本和 44 份健康对照样本。ClinProt 软件和遗传算法分析选择了一组血清标志物，这些标志物能够最有效地预测哪些患者患有 SCLC。
结果
诊断模式结合 5 个潜在的生物标志物能够区分 SCLC 患者和健康人，其灵敏度为 90%，特异性为 97.73%。值得注意的是，88.89%的 I/II 期患者被准确地归类为 SCLC。
结论
Anchorchip-time-of-flight 光谱技术将为发现用于检测 SCLC 的新生物标志物提供一种高度准确的方法。
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