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Digital Image Analysis of BAP-1 Accurately Predicts Uveal Melanoma Metastasis
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:...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Association for Research in Vision and Ophthalmology
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6504204/ https://www.ncbi.nlm.nih.gov/pubmed/31110912 http://dx.doi.org/10.1167/tvst.8.3.11 |
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author | Stålhammar, Gustav See, Thonnie Rose O. Phillips, Stephen Seregard, Stefan Grossniklaus, Hans E. |
author_facet | Stålhammar, Gustav See, Thonnie Rose O. Phillips, Stephen Seregard, Stefan Grossniklaus, Hans E. |
author_sort | Stålhammar, Gustav |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6504204 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | The Association for Research in Vision and Ophthalmology |
record_format | MEDLINE/PubMed |
spelling | pubmed-65042042019-05-20 Digital Image Analysis of BAP-1 Accurately Predicts Uveal Melanoma Metastasis Stålhammar, Gustav See, Thonnie Rose O. Phillips, Stephen Seregard, Stefan Grossniklaus, Hans E. Transl Vis Sci Technol Articles 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. The Association for Research in Vision and Ophthalmology 2019-05-06 /pmc/articles/PMC6504204/ /pubmed/31110912 http://dx.doi.org/10.1167/tvst.8.3.11 Text en Copyright 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |
spellingShingle | Articles Stålhammar, Gustav See, Thonnie Rose O. Phillips, Stephen Seregard, Stefan Grossniklaus, Hans E. Digital Image Analysis of BAP-1 Accurately Predicts Uveal Melanoma Metastasis |
title | Digital Image Analysis of BAP-1 Accurately Predicts Uveal Melanoma Metastasis |
title_full | Digital Image Analysis of BAP-1 Accurately Predicts Uveal Melanoma Metastasis |
title_fullStr | Digital Image Analysis of BAP-1 Accurately Predicts Uveal Melanoma Metastasis |
title_full_unstemmed | Digital Image Analysis of BAP-1 Accurately Predicts Uveal Melanoma Metastasis |
title_short | Digital Image Analysis of BAP-1 Accurately Predicts Uveal Melanoma Metastasis |
title_sort | digital image analysis of bap-1 accurately predicts uveal melanoma metastasis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6504204/ https://www.ncbi.nlm.nih.gov/pubmed/31110912 http://dx.doi.org/10.1167/tvst.8.3.11 |
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