St. Erik Eye Hospital, Stockholm, Sweden; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Departments of Ophthalmology and Pathology, Emory University School of Medicine, Atlanta, GA, USA.
Exp Eye Res. 2020 Apr;193:107987. doi: 10.1016/j.exer.2020.107987. Epub 2020 Feb 22.
Cytologic features such as the shape and size of tumor cells can predict metastatic death in uveal melanoma and other cancers but suffer from poor reproducibility. In this study, we investigate the interobserver concordance of digital morphometry, and correlate the results with BRCA associated protein-1 (BAP-1) expression and BAP-1 gene mutation status, monosomy 3, gene expression classifications and patient survival in uveal melanoma. The average number of cells analyzed in each of 107 tumors, was 1957 (SD 349). Mean time consumption was less than 2.5 min per tumor. Identical morphometric classification was obtained for ≥85% of tumors in all twelve evaluated morphometric variables (κ 0.70-0.93). The mean nucleus area, nucleus perimeter, nucleus max caliper and nucleus to cell area ratio were significantly greater in tumors with low BAP-1 expression and gene expression class 2. Patients had significantly shorter survival if their tumors had low BAP-1 (Log-Rank p = 0.002), gene expression class 2 (p = 0.004), long nucleus perimeters (p = 0.031), long nucleus max calipers (p = 0.029) and high mean nucleus to cell area ratios (p = 0.041) as defined in a training cohort and then tested in a validation cohort. Long nucleus perimeters and long nucleus max calipers correlated with monosomy 3 (Pearson Chi-Square p = 0.006 and p = 0.009, respectively). Long nucleus perimeters also correlated with BAP-1 mutation (p = 0.017). We conclude that digital morphometry can be fast and highly reproducible, that for the first time, morphometry parameters can be objectively quantitated in thousands of cells at a time in sub-μm resolutions, and that variables describing the shape and size tumor nuclei correlate to BAP-1 status, monosomy 3, gene expression class as well as patient survival.
细胞学特征，如肿瘤细胞的形状和大小，可预测葡萄膜黑色素瘤和其他癌症的转移死亡，但重复性差。在这项研究中，我们研究了数字形态计量学的观察者间一致性，并将结果与 BRCA 相关蛋白-1（BAP-1）表达和 BAP-1 基因突变状态、单体型 3、基因表达分类以及葡萄膜黑色素瘤患者的生存相关联。在 107 个肿瘤中，每个肿瘤分析的平均细胞数为 1957 个（标准差 349 个）。每个肿瘤的平均用时小于 2.5 分钟。在所有 12 个评估的形态计量学变量中，≥85%的肿瘤获得了相同的形态计量学分类（κ 值为 0.70-0.93）。BAP-1 表达水平低和基因表达分类 2 的肿瘤细胞核面积、细胞核周长、细胞核最大卡尺和细胞核与细胞面积比显著增大。如果肿瘤的 BAP-1 （对数秩检验，p=0.002）、基因表达分类 2（p=0.004）、细胞核周长较长（p=0.031）、细胞核最大卡尺较长（p=0.029）和核/细胞面积比较高（p=0.041），则患者的生存时间明显缩短，在训练队列中定义，并在验证队列中进行测试。长核周长与单体型 3 相关（Pearson Chi-Square p=0.006 和 p=0.009）。长核周长也与 BAP-1 突变相关（p=0.017）。我们的结论是，数字形态计量学可以快速且具有高度可重复性，这是首次能够以亚微米分辨率同时对数千个细胞的形态计量学参数进行客观量化，并且描述肿瘤细胞核形状和大小的变量与 BAP-1 状态、单体型 3、基因表达分类以及患者生存相关。
