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使用计算机支持的图像分析系统在免疫组化切片上定量细胞和细胞亚区室中的蛋白质表达。

Quantification of protein expression in cells and cellular subcompartments on immunohistochemical sections using a computer supported image analysis system.

机构信息

Institute of Pathology, and Department of Prostate Cancer Research, University Hospital of Bonn, Bonn, Germany.

出版信息

Histol Histopathol. 2013 May;28(5):605-10. doi: 10.14670/HH-28.605. Epub 2013 Jan 30.

Abstract

Quantification of protein expression based on immunohistochemistry (IHC) is an important step for translational research and clinical routine. Several manual ('eyeballing') scoring systems are used in order to semi-quantify protein expression based on chromogenic intensities and distribution patterns. However, manual scoring systems are time-consuming and subject to significant intra- and interobserver variability. The aim of our study was to explore, whether new image analysis software proves to be sufficient as an alternative tool to quantify protein expression. For IHC experiments, one nucleus specific marker (i.e., ERG antibody), one cytoplasmic specific marker (i.e., SLC45A3 antibody), and one marker expressed in both compartments (i.e., TMPRSS2 antibody) were chosen. Stainings were applied on TMAs, containing tumor material of 630 prostate cancer patients. A pathologist visually quantified all IHC stainings in a blinded manner, applying a four-step scoring system. For digital quantification, image analysis software (Tissue Studio v.2.1, Definiens AG, Munich, Germany) was applied to obtain a continuous spectrum of average staining intensity. For each of the three antibodies we found a strong correlation of the manual protein expression score and the score of the image analysis software. Spearman's rank correlation coefficient was 0.94, 0.92, and 0.90 for ERG, SLC45A3, and TMPRSS2, respectively (p⟨0.01). Our data suggest that the image analysis software Tissue Studio is a powerful tool for quantification of protein expression in IHC stainings. Further, since the digital analysis is precise and reproducible, computer supported protein quantification might help to overcome intra- and interobserver variability and increase objectivity of IHC based protein assessment.

摘要

基于免疫组织化学(IHC)的蛋白质表达定量是转化研究和临床常规的重要步骤。为了基于显色强度和分布模式对蛋白质表达进行半定量,使用了几种手动(“目测”)评分系统。然而,手动评分系统既耗时又容易受到观察者内和观察者间变异性的影响。我们的研究目的是探索新的图像分析软件是否足以替代定量蛋白质表达。对于 IHC 实验,选择了一个核特异性标志物(即 ERG 抗体)、一个细胞质特异性标志物(即 SLC45A3 抗体)和一个在两个隔室中表达的标志物(即 TMPRSS2 抗体)。染色应用于包含 630 例前列腺癌患者肿瘤组织的 TMAs 上。病理学家以盲法方式对所有 IHC 染色进行视觉定量,应用四级评分系统。对于数字定量,应用图像分析软件(Tissue Studio v.2.1,Definiens AG,慕尼黑,德国)获取平均染色强度的连续谱。对于三种抗体中的每一种,我们都发现手动蛋白质表达评分与图像分析软件评分之间存在很强的相关性。ERG、SLC45A3 和 TMPRSS2 的 Spearman 秩相关系数分别为 0.94、0.92 和 0.90(p ⟨0.01)。我们的数据表明,图像分析软件 Tissue Studio 是 IHC 染色中定量蛋白质表达的有力工具。此外,由于数字分析精确且可重复,计算机支持的蛋白质定量可能有助于克服观察者内和观察者间变异性,并提高基于 IHC 的蛋白质评估的客观性。

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