Momtahen, Shabnam

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.

AbstractBackgroundPoromas, and their malignant counterparts, porocarcinomas, harbor recurrent translocations involving YAP1‐MAML2, YAP1‐NUTM1, and infrequently WWTR1‐NUTM1; YAP1‐NUTM1 being the most common in porocarcinomas. NUT immunohistochemistry (IHC) can be used to identify NUTM1‐translocated tumors. This study sought to investigate potential novel NUTM1‐fusion partners among NUT IHC‐positive poromas and porocarcinomas.MethodsThirteen NUT IHC‐positive poroid tumors (four poromas and nine porocarcinomas) were identified within a multi‐institutional international cohort. Next‐generation sequencing (NGS) assessed for NUTM1 fusion partners.ResultsNGS detected a NUTM1 fusion in 12 of 13 cases: YAP1‐NUTM1 (11/12 cases) and WWTR1‐NUTM1 (1/12 cases). Two of the cases (2/12) with NUTM1 fusion were not called by the NGS algorithm but had at least one read‐spanning YAP1‐NUTM1 break point upon manual review. A NUTM1 fusion was not identified in one case; however, the sample had low RNA quality. The following fusion events were identified: YAP1 exon 4::NUTM1 exon 3 in six cases, YAP1 exon 6::NUTM1 exon 2 in one case, YAP1 exon 3::NUTM1 exon 3 in three cases, WWTR1 exon 3::NUTM1 exon 3 in one case, and YAP1 exon 8::NUTM1 exon 3 fusion in one case.ConclusionWhile no novel NUTM1 fusion partners were identified within our cohort, 12 of 13 cases had discoverable NUTM1 fusions; YAP1‐NUTM1 fusion was detected in 11 cases (92%) and WWTR1‐NUTM1 in 1 case (8%). These data corroborate findings from other recent investigations and further substantiate the utility of NUT IHC in diagnosing a subset of poroid neoplasms. In addition, two of our cases harbored fusions of YAP1 exon 6 to NUTM1 exon 3 and YAP1 exon 8 to NUTM1 exon 2, which have not been reported before in poroid neoplasms and indicate novel break points of YAP1.