Digital Image Analysis of BAP-1 Accurately Predicts Uveal Melanoma Metastasis

BAP-1的数字图像分析可准确预测葡萄膜黑色素瘤转移

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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 κ 0.52) with manual BAP-1 scoring and 88% to 94% with DIA (Cohen's κ 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.

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