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MicroRNA expression in esophageal squamous cell carcinoma: Novel diagnostic and prognostic biomarkers



MicroRNA expression in esophageal squamous cell carcinoma: Novel diagnostic and prognostic biomarkers



Molecular Medicine Reports 15(6): 3833-3839



The aim of the present study was to identify more effective molecular diagnostic biomarkers for esophageal squamous cell carcinoma (ESCC). The non‑coding RNA profile GSE43732, generated from 238 paired frozen tissues from 119 patients, was analyzed. Raw data were preprocessed and the differentially expressed miRNAs were screened by limma package with log2 fold change >2. Prognosis‑associated miRNAs were identified using receiver operating characteristic (ROC) and Kaplan-Meier (KM) curve analysis. miRNAs with an area under the ROC curve of ≥0.7 were selected. miRNA target genes were identified from verification and predictive databases, and an miRNA regulatory network was constructed and visualized using Cytoscape software. Gene Ontology and pathway enrichment analyses of the target genes were performed using TargetMine. A total of 107 differentially expressed miRNAs, including 54 upregulated and 53 downregulated miRNAs, were obtained. The KM survival curves revealed that 44 miRNAs were significantly associated with prognosis. Furthermore, 9 upregulated and 3 downregulated miRNAs were obtained. Two upregulated miRNAs, hsa‑miR‑143‑3p and hsa‑miR‑145‑5p, and two downregulated miRNAs, hsa‑miR‑182‑5p and hsa‑miR‑455‑5p, were identified and demonstrated to be associated with prognosis in ESCC. In addition, 8 known and 245 predicted target genes of hsa‑miR‑455‑5p were screened and the regulatory networks were constructed. Furthermore, these genes were functionally associated with macromolecule metabolic process and melanoma. In conclusion, two novel tumor suppressive miRNAs including miR‑182‑5p and miR‑455‑5p were identified. miR‑455‑5p in particular may be involved in the regulation of ESCC. These miRNAs may be used to predict the prognosis of ESCC.

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Accession: 059969334

Download citation: RISBibTeXText

PMID: 28440443

DOI: 10.3892/mmr.2017.6479


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