小RNA
基因组
机制(生物学)
计算生物学
骨肉瘤
生物
基因
数据库
遗传学
生物信息学
癌症研究
基因表达
小桶
基因本体论
计算机科学
哲学
认识论
作者
Zhongqiu Li,Peng Zhang,Feifei Feng,Qiao Zhang
出处
期刊:Combinatorial Chemistry & High Throughput Screening
[Bentham Science]
日期:2020-04-01
卷期号:23 (5): 411-418
标识
DOI:10.2174/1386207323666200401103353
摘要
Background: Osteosarcoma is one of the most serious primary malignant bone tumors that threaten the lives of children and adolescents. However, the mechanism underlying and how to prevent or treat the disease have not been well understood. Aims & Objective: This aim of the present study was to identify the key genes and explore novel insights into the molecular mechanism of miR-542-3p over-expressed Osteosarcoma. Materials & Methods: Gene expression profile data GDS5367 was downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were screened using GEO2R, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the DAVID database. And protein-protein interaction (PPI) network was constructed by the STRING database. In addition, the most highly connected module was screened by plugin MCODE and hub genes by plugin CytoHubba. Furthermore, UALCAN and The Cancer Genome Atlas were performed for survival analysis. Result: In total, 1421 DEGs were identified, including 598 genes were up-regulated and 823 genes were down-regulated. GO analysis showed that DEGs were classified into three groups and DEGs mainly enriched in Steroid biosynthesis, Ubiquitin mediated proteolysis and p53 signaling pathway. Six hub genes (UBA52, RNF114, UBE2H, TRIP12, HNRNPC, and PTBP1) may be key genes with the progression of osteosarcoma. Conclusion: The results could better understand the mechanism of osteosarcoma, which may facilitate a novel insight into treatment targets.
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