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. 2020 Dec 15:762:145035.
doi: 10.1016/j.gene.2020.145035. Epub 2020 Aug 8.

Prediction of the differentially expressed circRNAs to decipher their roles in the onset of human colorectal cancers

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Prediction of the differentially expressed circRNAs to decipher their roles in the onset of human colorectal cancers

Rajabrata Bhuyan et al. Gene. .

Abstract

Circular RNAs belong to the class of endogenous long non-coding RNAs that play important roles in many physiological processes including tumorigenesis. One such process is the onset of colorectal cancers (CRC) which is one of the most prevalent cancers in the world. However, the involvement of the circRNAs in CRC progression is still obscure. In this study, we screened the differentially expressed circRNAs in CRC by taking 10 pairs of tumor and non-tumor transcriptomic data. Datasets were downloaded from EBI ENA database and differential expression analysis was performed. For functional characterization and pathway enrichment of differentially expressed circRNAs, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were employed. Interactions with miRNAs and RNA binding proteins (RBPs) were predicted using miRanda, miRTarBase and starBase tools respectively. Our results identified total of 122 differentially expressed circRNAs in CRC onset, including 85 upregulated and 37 downregulated. GO and KEGG analyses revealed these circRNAs to be involved in many tumorigenic pathways. In addition, we predicted many miRNA and RBP targets of significantly expressed circRNAs that could exhibit the functional role in CRC progression. Combined analyses of miRanda, miRTarBase and KEGG pathway suggested that the possibly affected genes by circRNA-miRNA sponge to be associated with many cancer related pathways. From our findings we concluded 16 novel differentially expressed circRNAs that could play important roles in carcinogenesis of CRC. Our findings provide new insights in circRNA research and could therefore be useful in the development of potential biomarker and therapeutic approaches for CRC.

Keywords: Bioinformatics; Biomarker; CRC; CircRNAs; Differential expression; Network analysis; Pathway enrichment; mi-RNA target.

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