Digital morphometry of tumor nuclei correlates to BAP-1 status, monosomy 3, gene expression class and survival in uveal melanoma.

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.