Abstract
BACKGROUND/AIM: Canine mammary gland tumors (MGTs), as a potential model of human breast cancer, have a well-defined histological classification system. MicroRNA (miRNA) expression is a key part of the molecular signatures of both MGTs and human breast cancer, although the signatures alone do not yet provide a sufficient basis for definitive diagnosis. In this study, we investigated the association between miRNA expression patterns and histological classification. MATERIALS AND METHODS: Mammary gland tissue was collected from healthy dogs (n=7) and dog patients (n=80). Further samples (n=5) were obtained from established MGT cell lines. We targeted miRNAs differentially expressed in metastatic tumor tissue versus non-metastatic and normal tissue. A subset of samples was analyzed using small RNA next generation sequencing (NGS) with subsequent qPCR. RESULTS: Six differentially expressed miRNAs were selected from the NGS analysis and submitted for large-scale qPCR. The large-scale qPCR analysis revealed greater alternations in miRNA expression. Large-scale analysis, based on 79 samples, revealed a hierarchical clustering based on selected miRNAs that did not strikingly match the histopathological subtype classification. CONCLUSION: We successfully investigated the large-scale miRNA expression pattern in canine MGT and provided the whole miRNA expression. The selected miRNA demonstrated that there is no straightforward mapping between molecular signatures and histological classification of canine MGTs at the miRNA level.