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The prognostic value of circular RNA regulatory genes in competitive endogenous RNA network in gastric cancer

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Abstract

Accumulating evidence shows that circular RNA (circRNA) is an important regulator of many diseases, especially cancer. Gastric cancer (GC) is a malignant tumor of the digestive system. The regulatory role and potential mechanism of circRNAs in GC remain unknown. This study aims to explore the function and regulatory mechanism of circRNA-related competitive endogenous RNA (ceRNA) in GC. The circRNA expression profile was downloaded from the Gene Expression Omnibus (GEO) database. The RNA expression profile and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. Difference analysis was conducted after quality control. Based on CircInteractome, TargetScan, and miRDB databases, a circRNA-related ceRNA network was constructed. R package “clusterProfiler” was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Then, a univariate and multivariate Cox regression was used to construct a prognostic-related gene model to predict survival models. Finally, a gene set enrichment analysis (GSEA) analysis was performed to elucidate the function of genes related to prognosis. Altogether, 23 DEcircRNAs, 319 DEmiRNAs, and 14,541 DEmRNAs were identified. Based on ceRNA trends, the ceRNA network included 15 DEcircRNAs, 25 DEmiRNAs, and 1099 DEmRNAs in GC. Univariate and multivariate Cox proportional hazards regression analysis was used to establish a survival model with 11 prognosis-related genes and its AUC was 0.741, indicating good sensitivity and specificity in the prediction of GC prognosis. Finally, three prognostic-related genes were selected randomly to verify expression levels, which were consistent with the analysis result. The prognostic genes were significantly enriched in cancer-related biological processes, suggesting their roles in the onset and progression of GC. Our study constructs a prognostic model of GC, deepens our understanding of circRNA-related ceRNA networks in GC biology, and provided further implications for the diagnosis and treatment of GC.

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Fig. 1: Identification of significantly differently expressed circRNA in GC.
Fig. 2: Differential expression analysis of GC transcriptome sequencing data in TCGA database.
Fig. 3: ceRNA network of circRNA–miRNA–mRNA in GC.
Fig. 4: Top 10 enriched GO terms of circRNA regulatory genes in BP, CC, and MF.
Fig. 5: Top ten enriched KEGG pathways of circRNA regulatory genes in BP, CC, and MF.
Fig. 6: Cox regression analysis of circRNA regulatory gene.
Fig. 7: The expression of three prognosis-related gene and circRNA regulatory network.
Fig. 8: GSEA analysis of SERPINE1, TMEM200A and MANEAL.

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Acknowledgements

This study was supported by the Science and Technology project of Hunan Province (number S2017JJMSXM1443).

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TH conceived and designed research. ZC performed experiments and interpreted results of experiments. WC analyzed data and prepared figures. LY drafted the paper. BL edited and revised manuscript. All authors read and approved final version of manuscript.

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Correspondence to Bo Liu.

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Han, T., Chen, Z., Chen, W. et al. The prognostic value of circular RNA regulatory genes in competitive endogenous RNA network in gastric cancer. Cancer Gene Ther (2021). https://doi.org/10.1038/s41417-020-00270-9

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