Detection of a MicroRNA molecular signature of ultraviolet radiation in the superficial regions of melanocytic nevi on sun-exposed skin

How melanocytes transform into melanoma cells remains largely unknown. However, prolonged ultraviolet radiation exposure is linked with melanoma, and the DNA of melanomas arising in chronically sun-exposed skin is characterized by an elevated number of pyrimidine transitions, mainly C>T (predominantly caused by ultraviolet B), and transversions of GC>TA or AT>CG (caused by ultraviolet A over indirect mechanisms). Since ultraviolet penetrates mostly only the superficial dermis, we sought to determine the extent to which superficial and deep melanocytes of nevi in sun-exposed skin differ in their miRNA expression and consider the changes as likely secondary to ultraviolet radiation-induced damage. The differentially expressed miRNAs were analyzed for known potential oncomiRs or linked to potential oncogenes or tumor suppressors. Superficial and deep melanocytes were microdissected from the nevi of 14 patients. The suspensions were processed for hybridization to a ribonucleotide protection system with 2280 total probes, including 2256 miRNA probes targeting 2083 human miRNAs. A comprehensive analysis of all human miRNAs registered in miRBase 11.0 was performed using the HTG Molecular Diagnostic database. Statistical analysis of these data yielded for 14 samples a statistically relevant profile of 39 miRNA species at FDR<0.1 that were differentially expressed between superficial and deep melanocytes. Ingenuity Pathway Analysis based on the expression data of these 39 miRNAs suggested the gene transcripts AR, MDM2, SMAD2/3, and YBX1 as the most probable miRNA targets, which were validated at the protein level. Our findings suggest that superficial ultraviolet radiation-damaged melanocytes can be differentiated from deep melanocytes on the basis of the expression of 39 miRNAs, the most probable gene transcript and protein targets of which are AR, MDM2, SMAD2/3, and YBX1, with YBX1 expression validating the best the molecular signature in immunohistochemical analysis.