Bioinformatics analysis of key biomarkers for retinoblastoma

J Int Med Res. 2021 Jun;49(6):3000605211022210. doi: 10.1177/03000605211022210.

Abstract

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.

Keywords: bilateral retinoblastoma; bioinformatics; differentially expressed genes; unilateral retinoblastoma.

MeSH terms

  • Biomarkers, Tumor / genetics
  • Computational Biology
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic
  • Humans
  • Retinal Neoplasms* / diagnosis
  • Retinal Neoplasms* / genetics
  • Retinoblastoma* / diagnosis
  • Retinoblastoma* / genetics

Substances

  • Biomarkers, Tumor