| Popis: |
Background The aim of this study was to develop a robust miRNA signature and construct a nomogram model associated with uveal melanoma (UM) to improve prognosis prediction.Methods MiRNA and mRNA sequencing data of 80 uveal melanoma samples were downloaded from The Cancer Genome Atlas (TCGA) database. The patients were further randomly assigned to a training set (n = 40, used to identify key miRNAs) and a testing set (n = 40, used to internal verify the signature). Then miRNAs data of GSE84976 and GSE68828 were downloaded from Gene Expression Omniniub (GEO) database for outside verification. Combining univariate analysis and LASSO methods for identifying a robust miRNA biomarker in training set and the signature was validated in testing set and outside dataset. A prognostic nomogram was constructed and decision curve analyses and reduction curve analyses were performed to evaluate the clinical usefulness of the nomogram. A miRNA-mRNA network in UM was constructed and pathway enrichment of these miRNAs was conducted based on the genes in network.Results In total, a 3-miRNA was identified and validated which can robustly predict UM patient’s survival. According to univariate and multivariate analyses, age at diagnosis, tumor node metastasis (TNM) classification, stage and 3-miRNA signature significantly correlated with the survival outcomes. These characteristics were used to establish nomogram. The nomogram showed good accuracies in predicting 1 and 3 years overall survival and the decision curve revealed the clinical usefulness of our nomogram. What’s more, a miRNA-mRNA network was constructed. Pathway enrichment showed that this network was largely take part in mRNA processing, mRNA surveillance pathway, spliceosome and so no.Conclusions We developed a 3-miRNA biomarker and constructed a prognostic nomogram, which afforded a quantitative tool for predicting the survival of UM. Our finding also provided some new potential targets for the treatment of UM. |
