Construction of the miRNA-mRNA regulatory network and analysis of hub genes in oral squamous cell carcinoma
Jazyk angličtina Země Česko Médium print-electronic
Typ dokumentu časopisecké články
PubMed
35132271
DOI
10.5507/bp.2022.001
Knihovny.cz E-zdroje
- Klíčová slova
- bioinformatics, oral squamous cell carcinoma (OSCC), regulatory network,
- MeSH
- adrenalin MeSH
- Aurora kinasa A genetika metabolismus MeSH
- dlaždicobuněčné karcinomy hlavy a krku * genetika MeSH
- genové regulační sítě MeSH
- kvalita života MeSH
- lidé MeSH
- messenger RNA genetika metabolismus MeSH
- mikro RNA * genetika MeSH
- nádory úst * genetika MeSH
- PPAR gama genetika metabolismus MeSH
- regulace genové exprese u nádorů MeSH
- stanovení celkové genové exprese MeSH
- transkripční faktory genetika MeSH
- výpočetní biologie metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- adrenalin MeSH
- Aurora kinasa A MeSH
- messenger RNA MeSH
- mikro RNA * MeSH
- PPAR gama MeSH
- transkripční faktory MeSH
BACKGROUND: Oral squamous cell carcinoma (OSCC) severely affects the quality of life and the 5-year survival rate is low. Exploring the potential miRNA-mRNA regulatory network and analyzing hub genes and clinical data can provide a theoretical basis for further elucidating the pathogenesis of OSCC. METHODS: The miRNA expression datasets of GSE113956 and GSE124566 and mRNA expression datasets of GSE31056, GSE37991 and GSE13601 were obtained from the Gene Expression Omnibus databases. The differentially expressed miRNAs (DEMs) and mRNAs (DEGs) were screened using GEO2R. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by DAVID database. The PPI network was established through STRING database and the hub genes were preliminarily screened out by Cytoscape software. After identifying the hub genes in the TCGA database, we predicted the potential DEM transcription factors, constructed a miRNA-mRNA regulatory network, and analyzed the relationship between the hub genes and clinical data. RESULTS: A total of 28 DEMs and 764 DEGs were screened out, which were composed of 285 up-regulated genes and 479 down-regulated genes. Enrichment analysis showed that up-regulation of DEGs were mainly enriched in extracellular matrix organization and cancer-related pathway, while down-regulation of DEGs were mainly enriched in muscular system process and adrenaline signal transduction. After preliminary screening by PPI network and identification in TCGA, the up-regulated FN1, COL1A1, COL1A2, AURKA, CCNB1, CCNA2, SPP1, CDC6, and down-regulated ACTN2, TTN, IGF1, CAV3, MYL2, DMD, LDB3, CSRP3, ACTA1, PPARG were identified as hub genes. The miRNA-mRNA regulation network showed that hsa-miR-513b was the DEM with the most regulation, and COL1A1 was the DEG with the most regulation. In addition, CDC6, AURKA, CCNB1 and CCNA2 were related to overall survival and tumor differentiation. CONCLUSIONS: The regulatory relationship of hsa-miR-513b/ CDC6, CCNB1, CCNA2 and the regulatory relationship of hsa-miR-342-5p /AURKA were not only verified in the miRNA-mRNA regulatory network but also related to overall survival and tumor differentiation. These results indicated that they participated in the cellular regulatory process, and provided a molecular mechanism model for the study of pathogenesis.
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