Institute of Pathology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, Neuherberg, Germany.
J Proteome Res. 2010 Apr 5;9(4):1854-63. doi: 10.1021/pr901008d.
Clinical laboratory testing for HER2 status in breast cancer tissues is critically important for therapeutic decision making. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is a powerful tool for investigating proteins through the direct and morphology-driven analysis of tissue sections. We hypothesized that MALDI-IMS may determine HER2 status directly from breast cancer tissues. Breast cancer tissues (n = 48) predefined for HER2 status were subjected to MALDI-IMS, and protein profiles were obtained through direct analysis of tissue sections. Protein identification was performed by tissue microextraction and fractionation followed by top-down tandem mass spectrometry. A discovery and an independent validation set were used to predict HER2 status by applying proteomic classification algorithms. We found that specific protein/peptide expression changes strongly correlated with the HER2 overexpression. Among these, we identified m/z 8404 as cysteine-rich intestinal protein 1. The proteomic signature was able to accurately define HER2-positive from HER2-negative tissues, achieving high values for sensitivity of 83%, for specificity of 92%, and an overall accuracy of 89%. Our results underscore the potential of MALDI-IMS proteomic algorithms for morphology-driven tissue diagnostics such as HER2 testing and show that MALDI-IMS can reveal biologically significant molecular details from tissues which are not limited to traditional high-abundance proteins.
临床实验室检测乳腺癌组织中的 HER2 状态对于治疗决策至关重要。基质辅助激光解吸/电离(MALDI)成像质谱(IMS)是一种通过直接和形态驱动分析组织切片来研究蛋白质的强大工具。我们假设 MALDI-IMS 可以直接从乳腺癌组织中确定 HER2 状态。对 HER2 状态预先定义的乳腺癌组织(n = 48)进行 MALDI-IMS 分析,并通过直接分析组织切片获得蛋白质图谱。通过组织微提取和分级,然后进行自上而下的串联质谱分析进行蛋白质鉴定。使用蛋白质组学分类算法,利用发现和独立验证集来预测 HER2 状态。我们发现,特定蛋白质/肽的表达变化与 HER2 过表达强烈相关。在这些变化中,我们鉴定出 m/z 8404 为富含半胱氨酸的肠蛋白 1。蛋白质组学特征能够准确地区分 HER2 阳性和 HER2 阴性组织,具有 83%的高灵敏度、92%的高特异性和 89%的总体准确性。我们的研究结果强调了 MALDI-IMS 蛋白质组学算法在形态驱动组织诊断(如 HER2 检测)中的潜力,并表明 MALDI-IMS 可以从组织中揭示具有生物学意义的分子细节,而不仅仅局限于传统的高丰度蛋白质。