Bioinformatics analysis of key biomarkers for retinoblastoma

Objective To identify key genes involved in occurrence and development of retinoblastoma. Methods The microarray dataset, GSE5222, was downloaded from the gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) between unilateral and bilateral retinoblastoma were identified and...

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Bibliographic Details
Main Authors: Xin-mei Zhao, Yuan-Bin Li, Peng Sun, Ya-di Pu, Meng-jie shan, Yuan-meng Zhang
Format: Article
Language:English
Published: SAGE Publishing 2021-06-01
Series:Journal of International Medical Research
Online Access:https://doi.org/10.1177/03000605211022210
Description
Summary:Objective To identify key genes involved in occurrence and development of retinoblastoma. Methods The microarray dataset, GSE5222, was downloaded from the gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) between unilateral and bilateral retinoblastoma were identified and functional enrichment analysis performed. The protein–protein interaction (PPI) network was constructed and analysed by STRING and Cytoscape. Results DEGs were mainly associated with activation of cysteine-type endopeptidase activity involved in apoptotic process and small molecule catabolic process. Seven genes (WAS, GNB3, PTGER1, TACR1, GPR143, NPFF and CDKN2A) were identified as HUB genes. Conclusion Our research provides more understanding of the mechanisms of the disease at a molecular level and may help in the identification of novel biomarkers for retinoblastoma.
ISSN:1473-2300