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Prospective pathway signaling and prognostic values of MicroRNA-9 in ovarian cancer based on gene expression omnibus (GEO): a bioinformatics analysis

Authors :
Li Zuo
Xiaoli Li
Yue Tan
Hailong Zhu
Mi Xiao
Source :
Journal of Ovarian Research, Vol 14, Iss 1, Pp 1-14 (2021)
Publication Year :
2021
Publisher :
BMC, 2021.

Abstract

Abstract Objective MicroRNAs (miRNAs) play a vital role in the development of ovarian cancer (OC). The aim of this study to investigate the prognostic value and potential signaling pathways of hsa-miR-9-5p (miR-9) in OC through literature review and bioinformatics methods. Methods The expression of miR-9 in OC was assessed using the public datasets from the Gene Expression Omnibus (GEO) database. And a literature review was also performed to investigate the correlation between miR-9 expression and the OC prognosis. Two mRNA datasets (GSE18520 and GSE36668) of OC tissues and normal ovarian tissues (NOTs) were downloaded from GEO to identify the differentially expressed genes (DEGs). The target genes of hsa-miR-9-5p (TG-miR-9-5p) were predicted using miRWALK3.0 and TargetScan. Then the gene overlaps between DEGs in OC and the predicted TG-miR-9-5p were confirmed using a Venn diagram. After that, overlapping genes were subjected to Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Finally, a protein-protein interaction (PPI) network was constructed using STRING and Cytoscape, and the impact of hub genes on OC prognosis was analyzed. Results It was found that OC patients with miR-9 low expression had poor prognosis. A total of 107 DEGs related to both OC and miR-9 were identified. Dozens of DEGs were enriched in developmental process, extracellular matrix structural constituent, cell junction, axon guidance. In the PPI network analysis, 5 of the top 10 hub genes was significantly associated with decreased overall survival of OC patients, namely FBN1 (HR = 1.64, P

Details

Language :
English
ISSN :
17572215
Volume :
14
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Journal of Ovarian Research
Publication Type :
Academic Journal
Accession number :
edsdoj.41d2f350d4cc473d9ca8e35faa4d39db
Document Type :
article
Full Text :
https://doi.org/10.1186/s13048-021-00779-z