Publication Details

AFRICAN RESEARCH NEXUS

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A panel of circulating MicroRNAs detects uveal melanoma with high precision

Translational Vision Science and Technology, Volume 8, No. 6, Article 12, Year 2019

Purpose: To determine if a circulating microRNA (miRNA) panel could be used to distinguish between uveal melanoma and uveal nevi. Methods: We report on a multicenter, cross-sectional study conducted between June 2012 and September 2015. The follow-up time was approximately 3 to 5 years. Blood was drawn from participants presenting with a uveal nevus (n = 10), localized uveal melanoma (n = 50), or metastatic uveal melanoma (n = 5). Levels of 17 miRNAs were measured in blood samples of study participants using a sensitive real-time PCR system. Results: A panel of six miRNAs (miR-16, miR-145, miR-146a, miR-204, miR-211, and miR-363-3p) showed significant differences between participants with uveal nevi compared with patients with localized and metastatic uveal melanoma. Importantly, miR-211 was able to accurately distinguish metastatic disease from localized uveal melanoma (P < 0.0001; area under the curve = 0.96). When the six-miRNA panel was evaluated as a group it had the ability to identify uveal melanoma when four or more miRNAs (93% sensitivity and 100% specificity) reached or exceeded their cut-point. Conclusions: This miRNA panel, in tandem with clinical findings, may be suited to confirm benign lesions. In addition, due to the panel’s high precision in identifying malignancy, it has the potential to augment melanoma detection in subsequent clinical follow-up of lesions with atypical clinical features. Translational Relevance: Uveal nevi mimic the appearance of uveal melanoma and their transformation potential cannot be definitively determined without a biopsy. This panel is most relevant at the nevus stage and in lesions with uncertain malignant potential as a companion diagnostic tool to assist in clinical decision-making. © 2019, Association for Research in Vision and Ophthalmology Inc. All rights reserved.
Statistics
Citations: 26
Authors: 7
Affiliations: 8
Identifiers
Research Areas
Cancer
Health System And Policy
Study Design
Cross Sectional Study
Cohort Study
Study Approach
Quantitative