Abstract
Simple SummaryThe diagnosis of retinoblastoma (RB) is usually made by clinical examination and imaging modalities. Routine tissue biopsy is not done due to the risk of extraocular spread. Blood-based RNA cargoes could be promising surrogate markers for RB diagnosis and prognostication. Our data indicated that the size, morphology, and zeta potential (ZP) of RB and non-RB serum extracellular vesicles (EVs) met standard exosome properties with similar concentrations. MALTA1, AFAP1-AS1, miR-145, and miR-101 were identified as hub non-coding RNAs that promote RB progression by targeting cyclins, cyclin-dependent kinases, c-MYC, EZH2, ZEB1, TP53, and BCL2. Along with these, the aberrantly expressed miRNAs, lncRNAs, and their target mRNAs of RB EVs were implicated in cell cycle, metabolism, and tumor-associated signaling pathways. The differential expression of EV RNAs in RB compared to controls may aid in the identification of possible serum prognostic biomarkers for RB.The present study employed nanoparticle tracking analysis, transmission electron microscopy, immunoblotting, RNA sequencing, and quantitative real-time PCR validation to characterize serum-derived small extracellular vesicles (sEVs) from RB patients and age-matched controls. Bioinformatics methods were used to analyze functions, and regulatory interactions between coding and non-coding (nc) sEVs RNAs. The results revealed that the isolated sEVs are round-shaped with a size < 150 nm, 5.3 × 1011 ± 8.1 particles/mL, and zeta potential of 11.1 to −15.8 mV, and expressed exosome markers CD9, CD81, and TSG101. A total of 6514 differentially expressed (DE) mRNAs, 123 DE miRNAs, and 3634 DE lncRNAs were detected. Both miRNA-mRNA and lncRNA-miRNA-mRNA network analysis revealed that the cell cycle-specific genes including CDKNI1A, CCND1, c-MYC, and HIF1A are regulated by hub ncRNAs MALAT1, AFAP1-AS1, miR145, 101, and 16-5p. Protein-protein interaction network analysis showed that eye-related DE mRNAs are involved in rod cell differentiation, cone cell development, and retinol metabolism. In conclusion, our study provides a comprehensive overview of the RB sEV RNAs and regulatory interactions between them.
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