Abstract
Background: Circular RNAs (circRNAs) are a newly discovered type of non-coding RNA, which have been demonstrated to act as microRNA (miRNA) “sponges” to modulate gene expression. Emerging evidence has confirmed that circRNAs take part in many biological processes in a variety of malignant tumors, including gliomas, suggesting that they could serve as biomarkers or therapeutic targets for tumors. The purpose of this study was to explore the roles of circRNAs in gliomas and to provide valuable clues for clinical diagnosis and treatment.
Methods: RNA-seq data with poly(A)-/RNase R treatment was employed to investigate the expression profiles of circRNAs in tumor and paracancerous tissues derived from glioma patients. CircAST was used for full-length circRNA reconstruction and quantification. Bioinformatics analyses, including GO enrichment and KEGG pathway analyses, were performed to reveal the potential biological process and pathways of their host genes. A circRNA-miRNA interaction network was constructed to depict the interactions of the dysregulated circRNA transcripts with miRNAs.
Results: A total of 20,474 circular transcripts that originated from 16,022 circRNAs were successfully reconstructed in the samples. We detected 646 upregulated and 112 downregulated circular transcripts in tumor tissues compared with paracancerous tissues. GO analysis revealed that their host genes might be related to positive regulation of GTPase activity, regulation of synaptic transmission, and glutamatergic and dendrite morphogenesis in the cytoplasm and cytosol. KEGG pathway analysis showed that the glutamatergic synapse, neurotrophin signaling pathway, and ErbB signaling pathway might be linked to the occurrence and development of gliomas.
Conclusion: Our study revealed a comprehensive profile of differentially expressed circRNA transcripts in gliomas, indicating that aberrantly expressed circRNAs might play important roles in the occurrence and development of human gliomas.
Keywords: circRNA, isoforms, gliomas, differential analysis, tumors, KEGG.
Graphical Abstract