Identification of potential crucial genes and construction of microRNA-mRNA negative regulatory networks in osteosarcoma

Yue Pan,Junquan Chen,Zhehao Dai,Lingyun Lu,Yong Zhong

doi:10.1186/s41065-018-0061-9

Abstract

BackgroundThis study aimed to identify potential crucial genes and construction of microRNA-mRNA negative regulatory networks in osteosarcoma by comprehensive bioinformatics analysis.MethodsData of gene expression profiles (GSE28424) and miRNA expression profiles (GSE28423) were downloaded from GEO database. The differentially expressed genes (DEGs) and miRNAs (DEMIs) were obtained by R Bioconductor packages. Functional and enrichment analyses of selected genes were performed using DAVID database. Protein–protein interaction (PPI) network was constructed by STRING and visualized in Cytoscape. The relationships among the DEGs and module in PPI network were analyzed by plug-in NetworkAnalyzer and MCODE seperately. Through the TargetScan and comparing target genes with DEGs, the miRNA-mRNA regulation network was established.ResultsTotally 346 DEGs and 90 DEMIs were found to be differentially expressed. These DEGs were enriched in biological processes and KEGG pathway of inflammatory immune response. 25 genes in the PPI network were selected as hub genes. Top 10 hub genes were TYROBP, HLA-DRA, VWF, PPBP, SERPING1, HLA-DPA1, SERPINA1, KIF20A, FERMT3, HLA-E. PPI network of DEGs followed a pattern of power law network and met the characteristics of small-world network. MCODE analysis identified 4 clusters and the most significant cluster consisted of 11 nodes and 55 edges. SEPP1, CKS2, TCAP, BPI were identified as the seed genes in their own clusters, respectively. The miRNA-mRNA regulation network which was composed of 89 pairs was established. MiR-210 had the highest connectivity with 12 target genes. Among the predicted target of MiR-96, HLA-DPA1 and TYROBP were the hub genes.ConclusionOur study indicated possible differentially expressed genes and miRNA, and microRNA-mRNA negative regulatory networks in osteosarcoma by bioinformatics analysis, which may provide novel insights for unraveling pathogenesis of osteosarcoma.

Highlights

This study aimed to identify potential crucial genes and construction of microRNA-mRNA negative regulatory networks in osteosarcoma by comprehensive bioinformatics analysis
Identification of differentially expressed genes and miRNAs from public microarray data To explore the Differentially expressed gene (DEG) and Differentially expressed miRNAs (DEMI) in osteosarcoma compared to normal bone, the public gene expression (GSE28424) and miRNA expression (GSE28423) profiles were downloaded from the Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo)
Identification of DEGs and DEMIs Compared with normal bone samples, a total of 346 DEGs were identified in the osteosarcoma cells, which contained 43 up-regulated and 303 down-regulated genes

Summary

Introduction

This study aimed to identify potential crucial genes and construction of microRNA-mRNA negative regulatory networks in osteosarcoma by comprehensive bioinformatics analysis. With the development of surgery and chemotherapy, the survival rate in osteosarcoma patients. Pan et al Hereditas (2018) 155:21 in osteosarcoma by epigenetic methylation of promoter DNA and activating the expression of SPARCL1 could inhibit the osteosarcoma metastasis in vitro and in vivo [5]. Numerous studies shows that microRNAs (miRNAs) may play essential roles in osteosarcoma tumorigenesis by negatively regulating expression level of target gene. MiR-497, for instance, can activate P21 expression by inhibiting the expression of MAPK/Erk signaling pathway, and promote the apoptosis of osteosarcoma cells [7]. The miRNA-mRNA negative regulation network in osteosarcoma had been not fully delineated

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