Department of Pathology, Yale School of Medicine, New Haven, CT, USA.
Expert Rev Mol Diagn. 2020 May;20(5):509-522. doi: 10.1080/14737159.2020.1743178. Epub 2020 Mar 30.
: Automated image analysis provides an objective, quantitative, and reproducible method of measurement of biomarkers. Image quantification is particularly well suited for the analysis of tissue microarrays which has played a major pivotal role in the rapid assessment of molecular biomarkers. Data acquired from grinding up bulk tissue samples miss spatial information regarding cellular localization; therefore, methods that allow for spatial cell phenotyping at high resolution have proven to be valuable in many biomarker discovery assays. Here, we focus our attention on breast cancer as an example of a tumor type that has benefited from quantitative biomarker studies using tissue microarray format.: The history of immunofluorescence and immunohistochemistry and the current status of these techniques, including multiplexing technologies (spectral and non-spectral) and image analysis software will be addressed. Finally, we will turn our attention to studies that have provided proof-of-principle evidence that have been impacted from the use of these techniques.: Assessment of prognostic and predictive biomarkers on tissue sections and TMA using Quantitative immunohistochemistry is an important advancement in the investigation of biologic markers. The challenges in standardization of quantitative technologies for accurate assessment are required for adoption into routine clinical practice.
: 自动化图像分析为生物标志物的测量提供了一种客观、定量和可重复的方法。图像定量特别适合于组织微阵列的分析，它在快速评估分子生物标志物方面发挥了重要的关键作用。从研磨大块组织样本中获得的数据会丢失关于细胞定位的空间信息；因此，允许以高分辨率进行空间细胞表型分析的方法已被证明在许多生物标志物发现测定中非常有价值。在这里，我们以乳腺癌为例，关注受益于使用组织微阵列格式进行定量生物标志物研究的肿瘤类型。本文将重点介绍免疫荧光和免疫组织化学的历史以及这些技术的现状，包括多重技术（光谱和非光谱）和图像分析软件。最后，我们将关注那些已经提供了使用这些技术产生的原理验证证据的研究。: 在组织切片和 TMA 上使用定量免疫组织化学评估预后和预测生物标志物是生物标志物研究的重要进展。为了将这些技术纳入常规临床实践，需要对定量技术进行标准化以进行准确评估。
