Integrated analysis of multiple bioinformatics studies to identify microRNA-target gene-transcription factor regulatory networks in retinoblastoma.

ABSTRACT:

Background

In children, retinoblastoma (RB) is one of the most common primary malignant ocular tumors and has a poor prognosis and high mortality. To understand the molecular mechanisms of RB, we identified microRNAs (miRNAs), key genes and transcription factors (TFs) using bioinformatics analysis to build potential miRNA-gene-TF networks.

Methods

We collected three gene expression profiles and one miRNA expression profile from the Gene Expression Omnibus (GEO) database. We used the limma R package to identify overlapping differentially expressed genes (DEGs) and differentially expressed miRNAs in RB tissues compared to noncancer tissues. The robust rank aggregation (RRA) method was implemented to identify key genes among the DEGs. Then, miRNA-key gene-TF networks were built

SUBMITTER: Wen Y 

PROVIDER: S-EPMC9372260 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature