Digital image analysis of BAP-1 accurately predicts uveal melanoma metastasis

Abstract

Purpose: Reduced nuclear expression of BRCA1 associated protein 1 (BAP-1) is associated with a high risk for metastasis in uveal melanoma. Manual assessment of the expression level may face issues with interobserver reproducibility. This could be improved with digital image analysis (DIA). Methods: Thirty enucleated eyes with uveal melanoma from the Emory Eye Center (Atlanta, GA; years 2009–2017) were included and stained with BAP-1. Retrospective data on patient and tumor characteristics were retrieved. Patients were randomized to a training or validation cohort. Their tumor sections were digitally scanned and scored for percentage of BAP-1–positive cells with the QuPath Bioimage analysis software. Results: Interobserver concordance was 75% (Cohen’s k 0.52) with manual BAP-1 scoring and 88% to 94% with DIA (Cohen’s k 0.75–0.88). Positive and negative predictive values for metastasis were 90% and 100% with DIA, 80% and 86% with manual scoring, and 78% and 88% with gene expression class 2. In binary logistic regression, manual and DIA of BAP-1 and gene expression class 2 were associated with metastasis, but none retained significance in multiple regression. Metastasis-free survival was significantly shorter with low BAP-1 expression as defined by DIA (log-rank P = 0.02), but not with manual scoring (log-rank P = 0.36) or with gene expression class 2 (log-rank P = 0.17). Conclusions: DIA of BAP-1 is a competitive alternative to manual assessment as well as gene expression profiling in prognostication of enucleated specimens with uveal melanoma. Translational Relevance: The emerging scope for automatization of qualified diagnostic tasks is applied to uveal melanoma.