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提高基质辅助激光解吸电离飞行时间质谱血清聚糖分析的可重复性,增强卵巢肿瘤分类。

Enhancement of ovarian tumor classification by improved reproducibility in matrix-assisted laser desorption/ionization time-of-flight mass spectrometry of serum glycans.

机构信息

ASTA, Inc., Gyeonggi Biocenter, Eui-dong, Youngtong-gu, Suwon 443-270, South Korea.

出版信息

Anal Biochem. 2013 Dec 1;443(1):58-65. doi: 10.1016/j.ab.2013.07.048. Epub 2013 Aug 19.

Abstract

The serum N-glycome is a promising source of biomarker discovery. Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) profiling of serum N-glycans was attempted for differentiating borderline ovarian tumor from benign cases, for which a low data spread is essential. An experimental protocol using matrix-prespotted MALDI plates and fast vacuum drying of the loaded N-glycan samples was developed, thereby minimizing the intensity variations in the replicates to an average relative standard deviation (RSD) of 3.96% for the highest N-glycan peak (m/z 1485.53) of the Sigma-Aldrich serum standard. When applied to sera of ovarian tumors, this procedure exhibited an average RSD of 5.74% for m/z 1485.53 and of 7.28% for all MS peaks. This improved reproducibility combined with the OVA-Beyond(®) screening software resulted in 75.1% and 79.4% correct classification for benign and borderline tumor samples, respectively, while the classification rates by the conventional ovarian tumor marker CA-125 were 54.4% and 53.1%, respectively. Both true positive rate and true negative rate fluctuated with small numbers of markers and converged as the number of markers increased. Cross-validations were performed in comparison with CA-125. These results suggest that our optimized process for MALDI-TOF MS of the serum glycome has a great potential for the screening of early stage ovarian cancer.

摘要

血清 N-糖组是发现生物标志物的有前途的来源。尝试使用基质辅助激光解吸/电离飞行时间(MALDI-TOF)质谱(MS)对血清 N-糖进行分析,以区分交界性卵巢肿瘤与良性病例,这需要低数据分散。开发了一种使用基质预斑点 MALDI 板和加载 N-糖样本的快速真空干燥的实验方案,从而将重复的强度变化最小化到西格玛 - 奥尔德里奇血清标准的最高 N-糖峰(m/z 1485.53)的平均相对标准偏差(RSD)为 3.96%。当应用于卵巢肿瘤的血清时,该程序在 m/z 1485.53 处的平均 RSD 为 5.74%,在所有 MS 峰处的平均 RSD 为 7.28%。这种改进的重现性与 OVA-Beyond(®)筛选软件相结合,可分别正确分类良性和交界性肿瘤样本的 75.1%和 79.4%,而传统卵巢肿瘤标志物 CA-125 的分类率分别为 54.4%和 53.1%。真阳性率和真阴性率随标记物数量的减少而波动,并随着标记物数量的增加而收敛。与 CA-125 进行交叉验证。这些结果表明,我们优化的 MALDI-TOF MS 血清糖组分析过程对于早期卵巢癌的筛查具有很大的潜力。

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