Abstract
Purpose :
Our research focuses on examining the global patterns of miRNA expression using antecedent microarrays in tumor samples from retinoblastomas. The NCBI Gene Expression Repository now houses these datasets. They were then evaluated using bioinformatics software and tools to identify a panel of dysregulated informative miRNAs.
Methods :
Using the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/), we conducted a thorough search to locate appropriate miRNA expression profiles in microarray datasets. The online resource GEO2R in the GEO database was utilized to acquire the differentially expressed miRNAs (DEMs). This tool compares two or more sample groups in a GEO dataset using the Bioconductor project's GEOquery and limma R packages. We have used the RMA algorithm to perform normalization.
Results :
It was discovered that eight miRNAs were downregulated, and six miRNAs were overexpressed in patient tumor samples. When these dysregulated miRNAs were subjected to a signaling pathway analysis, the TNF signaling pathway, the p53 signaling pathway, and miRNAs in cancer were found to be the primary pathways.
Conclusions :
Non-coding RNAs (ncRNAs) were initially believed to be undefined products of random transcription. Nonetheless, recent studies have highlighted the functional significance of ncRNAs in cellular physiology and pathological processes. There has been much attention and proof that miRNAs and tumor growth are closely related. MiRNA analyses can offer fresh viewpoints and methods for creating individualized treatments for retinoblastoma.
This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.