Abstract:

Genomic assessment is becoming the standard of care in the diagnosis of some melanocytic neoplasms. However, problems persist. Traditional methods to identify copy number variation (CNV), such as array comparative genomic hybridization (aCGH), are effective but expensive and time-consuming. Droplet digital PCR (ddPCR) is a novel, rapid, and inexpensive technique to obtain precise CNV data. But, it can fail in tissues that are heterogenous, small in size, previously fixed, or have a subtle degree of CNV. While promising, the potential of ddPCR in melanoma diagnosis has never been studied. Here, we assessed the concordance rate of ddPCR with aCGH in the quantification of the most common CNV in melanoma: RREB1 (ras responsive element binding protein-1). Thirty-two formalin fixed tissue samples were identified from twenty-five patients. Samples were tested via aCGH for identification of CNV in the RREB1 gene. In many cases, the neoplasms were borderline lesions that had aCGH testing performed to aid diagnosis. After screening multiple reference genes, and optimizing assay conditions for amplification of the gene of interest, ddPCR was performed. Concordance analysis of ddPCR with aCGH for the quantification of RREB1 CNV revealed a sensitivity and specificity of 91.7%, and 95.0%, respectively. These are the first results to demonstrate robust efficacy of ddPCR in quantitating RREB1 CNV status on FFPE clinical samples. We report the first use of a rapid and inexpensive method for obtaining highly precise data on the most common CNV in melanoma.

Financial Disclosure: No current or relevant financial relationships exist.

Marie Syku

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Rapid and Inexpensive Detection of the Commonest CNV in Melanoma: Sensitive and Specific Quantitation of RREB1 CNV Using Droplet Digital PCR in FFPE