Flagship Biosciences, 10955 Westmoor Dr., Westminster, CO 80021, USA.
Lab Invest. 2012 Sep;92(9):1342-57. doi: 10.1038/labinvest.2012.91. Epub 2012 Jul 16.
Quantitative clinical measurement of heterogeneity in immunohistochemistry staining would be useful in evaluating patient therapeutic response and in identifying underlying issues in histopathology laboratory quality control. A heterogeneity scoring approach (HetMap) was designed to visualize a individual patient's immunohistochemistry heterogeneity in the context of a patient population. HER2 semiquantitative analysis was combined with ecology diversity statistics to evaluate cell-level heterogeneity (consistency of protein expression within neighboring cells in a tumor nest) and tumor-level heterogeneity (differences of protein expression across a tumor as represented by a tissue section). This approach was evaluated on HER2 immunohistochemistry-stained breast cancer samples using 200 specimens across two different laboratories with three pathologists per laboratory, each outlining regions of tumor for scoring by automatic cell-based image analysis. HetMap was evaluated using three different scoring schemes: HER2 scoring according to American Society of Clinical Oncology and College of American Pathologists (ASCO/CAP) guidelines, H-score, and a new continuous HER2 score (HER2(cont)). Two definitions of heterogeneity, cell-level and tumor-level, provided useful independent measures of heterogeneity. Cases where pathologists had disagreement over reads in the area of clinical importance (+1 and +2) had statistically significantly higher levels of tumor-level heterogeneity. Cell-level heterogeneity, reported either as an average or the maximum area of heterogeneity across a slide, had low levels of dependency on the pathologist choice of region, while tumor-level heterogeneity measurements had more dependence on the pathologist choice of regions. HetMap is a measure of heterogeneity, by which pathologists, oncologists, and drug development organizations can view cell-level and tumor-level heterogeneity for a patient for a given marker in the context of an entire patient cohort. Heterogeneity analysis can be used to identify tumors with differing degrees of heterogeneity, or to highlight slides that should be rechecked for QC issues. Tumor heterogeneity plays a significant role in disconcordant reads between pathologists.
定量评估免疫组化染色异质性在评估患者治疗反应和识别组织病理学实验室质量控制中的潜在问题方面具有重要作用。设计了一种异质性评分方法（HetMap），用于在患者人群中可视化个体患者的免疫组化异质性。HER2 半定量分析与生态学多样性统计相结合，评估细胞水平异质性（肿瘤巢内相邻细胞中蛋白表达的一致性）和肿瘤水平异质性（肿瘤内蛋白表达的差异，由组织切片代表）。该方法使用 200 个来自两个不同实验室的 HER2 免疫组化染色乳腺癌样本进行评估，每个实验室有 3 名病理学家，每个病理学家都为自动基于细胞的图像分析评分勾画肿瘤区域。HetMap 使用三种不同的评分方案进行评估：根据美国临床肿瘤学会和美国病理学家协会（ASCO/CAP）指南的 HER2 评分、H 评分和新的连续 HER2 评分（HER2(cont)）。细胞水平和肿瘤水平的两种异质性定义提供了有用的异质性独立度量。在临床重要区域（+1 和+2）的病理学家之间存在阅读分歧的病例，肿瘤水平的异质性具有统计学意义上的更高水平。细胞水平异质性，无论是作为平均水平还是整个幻灯片上的最大异质性面积报告，对病理学家选择区域的依赖性较低，而肿瘤水平异质性测量对病理学家选择区域的依赖性较高。HetMap 是一种异质性测量方法，病理学家、肿瘤学家和药物开发组织可以根据整个患者队列中给定标志物查看患者的细胞水平和肿瘤水平异质性。异质性分析可用于识别具有不同程度异质性的肿瘤，或突出需要重新检查 QC 问题的幻灯片。肿瘤异质性在病理学家之间的不一致阅读中起着重要作用。
