A Droplet Digital Polymerase Chain Reaction-Based Tool to Aid in Melanoma Diagnosis.

Abstract

Context.—: Detecting copy number variations (CNVs) at certain loci can aid in the diagnosis of histologically ambiguous melanocytic neoplasms. Droplet digital polymerase chain reaction (ddPCR) is a rapid, automated, and inexpensive method for CNV detection in other cancers, but not yet melanoma.

Objective.—: To evaluate the performance of a 4-gene ddPCR panel that simultaneously tests for ras responsive binding element protein 1 (RREB1) gain; cyclin-dependent kinase inhibitor 2A (CDKN2A) loss; MYC proto-oncogene, bHLH transcription factor (MYC) gain; and MYB proto-oncogene, transcription factor (MYB) loss in melanocytic neoplasms.

Design.—: One hundred sixty-four formalin-fixed, paraffin-embedded skin samples were used to develop the assay, of which 65 were used to evaluate its performance. Chromosomal microarray analysis (CMA) data were used as the gold standard.

Results.—: ddPCR demonstrated high concordance with CMA in detecting RREB1 gain (sensitivity, 86.7%; specificity, 88.9%), CDKN2A loss (sensitivity, 80%; specificity, 100%), MYC gain (sensitivity, 70%; specificity, 100%), and MYB loss (sensitivity, 71.4%; specificity, 100%). When one CNV was required to designate the test as positive, the 4-gene ddPCR panel distinguished nevi from melanomas with a sensitivity of 78.4% and a specificity of 71.4%. For reference, CMA had a sensitivity of 86.2% and a specificity of 78.6%. Our data also revealed interesting relationships with histology, namely (1) a positive correlation between RREB1 ddPCR copy number and degree of tumor progression; (2) a statistically significant correlation between MYC gain and nodular growth; and (3) a statistically significant correlation between MYB loss and a sheetlike pattern of growth.

Conclusions.—: With further validation, ddPCR may aid both in our understanding of melanomagenesis and in the diagnosis of challenging melanocytic neoplasms.