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采用 MALDI 成像质谱法对乳腺癌组织中 HER2 受体状态进行分类。

Classification of HER2 receptor status in breast cancer tissues by MALDI imaging mass spectrometry.

机构信息

Institute of Pathology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, Neuherberg, Germany.

出版信息

J Proteome Res. 2010 Apr 5;9(4):1854-63. doi: 10.1021/pr901008d.

DOI:10.1021/pr901008d
PMID:20170166
Abstract

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.

摘要

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。

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