[No authors listed]
OBJECTIVE:Increasing evidence suggested that dysregulated miR-154 in several tumor tissues is involved in the clinical progress of cancers patients. The objective of this study was to explore the expression pattern of miR-154 and its potential effects in human melanoma. PATIENTS AND METHODS:Microarray data from GEO datasets were analyzed to identify differentially expressed miRNAs. Real (RT-PCR) was performed to determine the expressions of miR-154 in melanoma cell lines and tumor tissues. The associations between miR-154 levels and clinical progress were studied using a series of statistical methods. Cell viability, invasion, migration, and apoptosis were detected by Cell Counting Kit-8 (CCK-8) assays, transwell assay, wound healing assays, and flow cytometry, respectively. TargetScan system was used to identify the target genes of miR-154 and Luciferase activity analysis was carried out to demonstrate the possible target. RESULTS:The expression levels of miR-154 were distinctly lower in tumor samples and melanoma cell lines than in normal controls (p < 0.01). The up-regulation of miR-154 in melanoma tissues was associated with advanced tumor stage (p = 0.028), ulceration (p = 0.046), and shorter overall survival (p = 0.0035). Moreover, the multivariate analysis suggested a decreased expression of miR-154 is an independent predictor of overall survival rates in melanoma patients. Functional observation showed that up-regulation of miR-154 suppressed the capability of proliferation, invasion, and migration, promoting apoptosis in melanoma cell lines. Bioinformatics analysis predicted AURKA (aurora kinase A) as a target of miR-154, which was confirmed using the luciferase activity assays. Besides, miR-154 overexpression rescued the suppressive effect of AURKA-mediated melanoma on cell proliferation, colony formation, and metastasis. CONCLUSIONS:These results revealed that miR-154 has clinical implications for targeted therapy of melanoma patients and indicated that miR-154 could represent a novel biomarker in predicting the clinical outcome for melanoma.
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