22 July 2019 : Clinical Research
Potential Five-MicroRNA Signature Model for the Prediction of Prognosis in Patients with Wilms TumorYihang Gong1ABCDE, Baojia Zou1ABCE, Jianxu Chen1DEF, Lei Ding1DEF, Peiping Li1CDF, Jiafan Chen1DF, Jiandi Chen2CE, Baimeng Zhang1BF, Jian Li1AEG*
Med Sci Monit 2019; 25:5435-5444
BACKGROUND: Wilms tumor (WT) is the most common type of pediatric renal malignancy, and is associated with poor prognosis. The aim of the present study was to identify microRNA (miRNA) signatures which might predict prognosis and categorize WTs into high- and low-risk subgroups.
MATERIAL AND METHODS: The miRNA expression profiles of WT patients and normal samples were obtained from the Therapeutically Applicable Research to Generate Effective Treatment database. Differentially expressed miRNAs between WT patients and normal samples were identified using the EdgeR package. Subsequently, correlations between differentially expressed miRNAs and the prognosis of overall survival were analyzed. Enrichment analyses for the targeted mRNAs were conducted via the Database for Annotation, Visualization, and Integration Discovery.
RESULTS: A total of 154 miRNAs were identified as differentially expressed in WT. Of those, 18 miRNAs were associated with overall survival (P<0.05). A prognostic signature of 5 differentially expressed miRNAs (i.e., has-mir-149, has-mir-7112, has-mir-940, has-mir-1248, and has-mir-490) was constructed to classify the patients into high- and low-risk subgroups. The targeted mRNAs of these prognostic miRNAs were primarily enriched in Gene Ontology terms (i.e., protein autophosphorylation, protein dephosphorylation, and stress-activated MAPK cascade) and the Kyoto Encyclopedia of Genes and Genomes signaling pathways (i.e., MAPK, AMPK, and PI3K-Akt).
CONCLUSIONS: The 5-miRNA signature model might be useful in determining the prognosis of WT patients. As a promising prediction tool, this prognosis signature might serve as a potential biomarker for WT patients.
Keywords: MicroRNAs, Prognosis, Wilms Tumor, Biomarkers, Tumor, China, Down-Regulation, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, gene ontology, Genetic Predisposition to Disease, Kaplan-Meier Estimate, Patients, RNA, Messenger, transcriptome, Up-Regulation
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