Differences in microRNA expression between melanoma and healthy adjacent skin.

Abstract

Background: The tumor microenvironment is composed of cancer-associated fibroblasts, tumor-associated macrophages, endothelial cells, immune cells, signaling molecules and extracellular matrix structures, which closelycommunicate with the tumor via multiple mechanisms. MicroRNAs are paracrine regulators that provide a direct interaction between the microenvironment and cancer cells. In the presentstudy, we aimed to identify the microRNA expression profile in melanoma compared with thatin healthy adjacent skin, with a further assessment of altered microRNA signaling pathways and target genes.

Methods: Formalin-fixed paraffin-embedded (FFPE) melanoma tissue samples were separated by dissection into tumor and surrounding health tissue fragments. MicroRNA expression profiles were obtained by microarray using Gene Atlas Microarray System (Affymetrix, California, USA). To confirm microarray results real-time PCR was carried out. Bioinformatic analysis was performed using the DIANA-miRPath v.3.0 database. Target genes for miR-146a-5p were determined using three algorithms: TargetScan 7.0, miRWalk 2.0 and miRTarBase v.4.5.

Results: A microarray profiling revealed 143 microRNAs asdifferent in tumor versus adjacent tissues. Expression level of hsa-miR-146a-5p showedto be higher in melanoma cells as compared to thehealthy adjacent skin. The bioinformatic study has determined several signaling cascades associated with miR-146a-5p:Toll-like receptor pathway, NF-κB pathway, ErB pathway, and measles signaling pathway. The 38 target genes have been shown for miR-146a-5p of which NRAS gene is known asone of the most frequent mutated in melanoma.

Conclusions: Elucidation of the role of miR-146-a-5p in complex interactions between the tumor and the cells of healthy adjacent skin is necessary for our understanding of the mechanisms oftumor progression. Significant differences found between cancer cells and adjacent tissues in microRNA expression profile corresponding to divergent mRNA/protein levels in these structures should be taken into account when tumor samples characterization estimatedby high-throughput methods.