Identification of biomarkers associated with the recurrence of osteosarcoma using ceRNA regulatory network analysis

International Journal of Molecular Medicine
Shanyong ZhangHongwu Fan

Abstract

The aim of the present study was to identify the important mRNAs, micro (mi)RNAs and long non‑coding (lnc)RNAs that are associated with osteosarcoma recurrence. The GSE3905 dataset, which contains two sub‑datasets (GSE39040 and GSE39055), was downloaded from the Gene Expression Omnibus (GEO). Prognosis‑associated RNAs were identified by performing Cox regression univariate analysis and were subsequently used to construct a competing endogenous (ce)RNA regulatory network for Gene Set Enrichment Analysis (GSEA). Kaplan‑Meier survival analysis was used to determine the associations between expression levels and survival prognosis. In addition, another independent miRNA profile, GSE79181, was downloaded from GEO for validation. Among the differentially expressed RNAs, 417 RNAs (5 lncRNAs, 19 miRNAs, and 393 mRNAs) were observed to be associated with prognosis. The GSEA for the ceRNA regulatory network revealed that 'Mitogen‑activated protein kinase (MAPK) signaling pathway', 'Chemokine signaling pathway' and 'Spliceosome' were markedly associated with osteosarcoma. In addition, three lncRNAs [long intergenic non‑protein coding RNA 28 (LINC00028), LINC00323, and small nucleolar RNA host gene 1 (SNHG1)] and two miRNAs (hsa‑miR‑124 an...Continue Reading

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Datasets Mentioned

BETA
GSE3905
GSE39058
GSE39055
GPL15762
GPL14951
GSE30955
GSE39040
GSE79181

Methods Mentioned

BETA
biopsy

Software Mentioned

Linear Models for Microarray Analysis ( Limma )
GSEA
R
Limma
Gene Set Enrichment Analysis ( GSEA )
survival
miRanda
pheatmap
TargetScan
Cytoscape

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