一种联合生物标志物模式可提高肺癌的鉴别能力。

A combined biomarker pattern improves the discrimination of lung cancer.

机构信息

Key Laboratory for Cell Proliferation and Regulation Biology Ministry of Education, Beijing Normal University, China.

出版信息

Biomarkers. 2011 Feb;16(1):20-30. doi: 10.3109/1354750X.2010.521257. Epub 2010 Oct 22.

DOI:10.3109/1354750X.2010.521257

PMID:20964562

Abstract

A total of 227 sera were analysed using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) to find novel serum biomarkers for lung cancer. The results showed that the 11.53, 11.70, 13.78, 13.90 and 14.07 k m/z peaks identified as native serum amyloid A (SAA), SAA with N-terminal Arg cleaved, native transthyretin (TTR) and its two variants significantly differentiated lung cancer sera from normal control sera (p <0.01). A 'biomarker pattern' combining SAA and TTR was tested to distinguish lung cancer patients from normal control individuals, and the diagnostic positive rate of lung cancer was improved to 91.6%.

摘要

采用表面增强激光解吸/电离飞行时间质谱（SELDI-TOF MS）分析了 227 份血清，以寻找用于诊断肺癌的新型血清生物标志物。结果显示，11.53、11.70、13.78、13.90 和 14.07 m/z 峰被鉴定为天然血清淀粉样蛋白 A（SAA）、N 端精氨酸裂解的 SAA、天然转甲状腺素蛋白（TTR）及其两种变体，这些峰可显著区分肺癌血清与正常对照血清（p<0.01）。将 SAA 和 TTR 结合的“生物标志物模式”用于区分肺癌患者和正常对照个体，可将肺癌的诊断阳性率提高至 91.6%。