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Anti-Cancer Agents in Medicinal Chemistry

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ISSN (Print): 1871-5206
ISSN (Online): 1875-5992

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Research Article

Bioinformatics Analysis Predicts hsa_circ_0026337/miR-197-3p as a Potential Oncogenic ceRNA Network for Non-Small Cell Lung Cancers

Author(s): Qian Zhang*, Lingkai Kang, Xiaoyue Li*, Zhirui Li, Shimin Wen and Xi Fu

Volume 22, Issue 5, 2022

Published on: 12 July, 2021

Page: [874 - 886] Pages: 13

DOI: 10.2174/1871520621666210712090721

Price: $65

Abstract

Background: Circular RNAs (circRNAs) play an essential role in developing tumors, but their role in Non- Small Cell Lung Cancer (NSCLC) is unclear. Thus, the present study explored the possible molecular mechanism of circRNAs in NSCLC.

Methods: Three circular RNA (circRNA) microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differential expressions of circRNAs (DECs) were identified in NSCLC tissue and compared to adjacent healthy tissue. The online cancer-specific circRNA database (CSCD) was used for the analysis of the DECs function. Protein-Protein Interaction (PPI) network, Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), Cytoscape and UALCAN were used to predict the critical nodes and perform patient survival analysis, respectively. The interaction between the DECs, the predicted miRNAs, and hub genes was also determined. Finally, the circRNA-miRNA-mRNA network was established.

Results: The expression of hsa_circ_0049271, hsa_circ_0026337, hsa_circ_0043256, and hsa_circ_0008234 was decreased in NSCLC tissues. The Encyclopedia of RNA Interactomes (ENCORI) and CSCD database results showed that hsa_circ_0026337 was found to sponge with miR-1193, miR-197-3p, miR-3605-5p, miR-433-3p and miR-652-3p, and hsa_circ_0043256 to sponge with miR-1252-5p, miR-494-3p and miR-558, respectively. Subsequently, 100 mRNAs were predicted to bind with these seven miRNA response elements (MREs). The GO analysis and KEGG pathway revealed that these 100 MREs might be involved in “histone deacetylase binding” and “cellular senescence.” PPI network and Cytoscape identified the top ten hub genes. Survival analysis data showed that the low expression of hsa_circ_0026337 was significantly associated with shortened survival time in NSCLC (P = 0.037), which increased the expression level of hsa-miR-197-3p, thereby inhibiting the translation of specific proteins.

Conclusion: This study examined the circRNA-miRNA-mRNA regulatory network associated with NSCLC and explored the potential functions of DECs in the network to elucidate the mechanisms underlying disease progression in NSCLC.

Keywords: Bioinformatics analysis, GEO, NSCLC, circRNAs, miRNAs, ceRNA network.

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