Department of Surgery, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333 ZA, Leiden, The Netherlands.
J Cancer Res Clin Oncol. 2012 Dec;138(12):1983-92. doi: 10.1007/s00432-012-1273-4. Epub 2012 Jul 5.
Detection of breast cancer at early stage increases patient's survival. Mass spectrometry-based protein analysis of serum samples is a promising approach to obtain biomarker profiles for early detection. A combination of commonly applied solid-phase extraction procedures for clean-up may increase the number of detectable peptides and proteins. In this study, we have evaluated whether the classification performance of breast cancer profiles improves by using two serum workup procedures.
Serum samples from 105 breast cancer patients and 202 healthy volunteers were processed according to a standardized protocol implemented on a high-end liquid-handling robot. Peptide and protein enrichments were carried out using weak-cation exchange (WCX) and reversed-phase (RP) C18 magnetic beads. Profiles were acquired on a matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometer. In this way, two different biomarker profiles were obtained for each serum sample, yielding a WCX- and RPC18-dataset.
The profiles were statistically evaluated with double cross-validation. Classification results of WCX- and RPC18-datasets were determined for each set separately and for the combination of both sets. Sensitivity and specificity were 82 and 87 % (WCX) and 73 and 93 % (RPC18) for the individual workup procedures. These values increased up to 84 and 95 %, respectively, upon combining the data.
It was found that MALDI-TOF peptide and protein profiles can be used for classification of breast cancer with high sensitivity and specificity. The classification performance even improved when two workup procedures were applied, since these provide a greater number of features (proteins).
早期发现乳腺癌可提高患者的生存率。基于质谱的血清样本蛋白质分析是获得早期检测生物标志物图谱的有前途的方法。通常应用的固相萃取程序的组合进行净化可能会增加可检测肽和蛋白质的数量。在这项研究中,我们评估了使用两种血清处理程序是否可以提高乳腺癌图谱的分类性能。
根据在高端液体处理机器人上实施的标准化方案,处理来自 105 名乳腺癌患者和 202 名健康志愿者的血清样本。使用弱阳离子交换(WCX)和反相(RP)C18 磁珠进行肽和蛋白质富集。在基质辅助激光解吸/电离飞行时间(MALDI-TOF)质谱仪上获取图谱。通过这种方式,为每个血清样本获得了两种不同的生物标志物图谱,产生了 WCX 和 RPC18 数据集。
使用双交叉验证对图谱进行了统计评估。分别对 WCX 和 RPC18 数据集的分类结果进行了确定,并对两个数据集的组合进行了确定。单独处理程序的敏感性和特异性分别为 82%和 87%(WCX)和 73%和 93%(RPC18)。当组合数据时,这些值分别增加到 84%和 95%。
发现 MALDI-TOF 肽和蛋白质图谱可用于乳腺癌的分类,具有高灵敏度和特异性。当应用两种处理程序时,分类性能甚至得到了提高,因为这两种方法提供了更多的特征(蛋白质)。