Background: Long intergenic non-protein coding RNA 520 (LINC00520), a novel identified lncRNA, has been shown to modulate the malignant phenotype of tumor cells in some malignant tumors. However, the exact role and molecular mechanism of LINC00520 in malignant melanoma has not been studied. Methods: The expression of LINC00520 in melanoma tissues were detected by using RNA-seq analysis and qRT-PCR. Melanoma cases from the public databases (The Cancer Genome Atlas (TCGA), GEO#GSE15605, GEO#GSE34460 and GEO#GSE24996) were included in this study. CCK-8 assay, EdU assay, transwell and scratch wound assay were used to explore the role of LINC00520 in melanoma cells. Luciferase reporter assays, MS2-RIP, RNA pull-down and RNA-ChIP assay were used to demonstrate the molecular biological mechanism of LINC00520 in melanoma. Results: We found that LICN00520 was found to be overexpressed in melanoma tissue. High expression of LICN00520 is a risk factor for the prognosis of melanoma patients. LINC00520 promotes the proliferation, invasion and migration of melanoma cells. LICN00520 exerted its oncogenic role by competitive binding miR-125b-5p to promote Eukaryotic initiation factor 5A2 (EIF5A2) expression. We also showed that LICN00520 promotes the growth and metastasis of melanoma in vivo through regulating miR-125b-5p/EIF5A2 axis. Conclusions: All results elucidated the role and molecular mechanism of LINC00520 in the malignant development of melanoma. LINC00520, a new oncogene in melanoma, maybe serve as a survival biomarkers or therapeutic target for melanoma patients.

Background: A high recurrence rate has always been a serious problem for treatment of hepatocellular carcinoma (HCC). Exploring predictors of postoperative and posttransplantation recurrence in patients with HCC can guide treatment strategies for clinicians. Results: In this study, logistic regression and multivariate Cox regression models were constructed with microRNA expression profile data from The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO). The accuracy of predictions was assessed using receiver operating characteristic curve (ROC) and Kaplan‒Meier survival curve analyses. The results showed that the combination of 10 miRNAs (including hsa-miR-509-3p, hsa-miR-769-3p, hsa-miR-671-3p, hsa-miR-296-5p, hsa-miR-767-5p, hsa-miR-421, hsa-miR-193a-3p, hsa-miR-139-3p, hsa-miR-342-3p, and hsa-miR-193a-5p) accurately predicted postoperative and posttransplantation malignancy recurrence in HCC patients and was also valuable for prognostic evaluation of HCC patients. The 10-miRNA prediction model might assist doctors in making prognoses for HCC patients who have a high probability of relapse following surgery and in offering additional, individualized treatment to lessen that risk.