Construction of miRNA-mRNA Regulatory Network and Prognostic Signature in Endometrial Cancer
Authors Sun R, Liu J, Nie S, Li S, Yang J, Jiang Y, Cheng W
Received 3 August 2020
Accepted for publication 10 March 2021
Published 6 April 2021 Volume 2021:14 Pages 2363—2378
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Alberto Bongiovanni
Rui Sun,* Jinhui Liu,* Sipei Nie,* Siyue Li, Jing Yang, Yi Jiang, Wenjun Cheng
Department of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Wenjun Cheng
Department of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu, People’s Republic of China
Email [email protected]
Introduction: This bioinformatic study confirmed a new miRNA-mRNA regulatory network and a prognostic signature in endometrial cancer (EC).
Materials and Methods: We downloaded RNA-seq and miRNA-seq data of EC from the TCGA database, then used EdegR package to screen differentially expressed miRNAs and mRNAs (DE-miRNAs and DE-mRNAs). Then, we constructed a regulatory network of EC-associated miRNAs and hub genes by Cytoscape, and determined the expression of unexplored miRNAs in EC tissues and normal adjacent tissues by quantitative Real-Time PCR (qRT-PCR). A prognostic signature model and a predictive nomogram were constructed. Finally, we explored the association between the prognostic model and the immune cell infiltration.
Results: A total of 11,531 DE-mRNAs and 236 DE-miRNAs, as well as 275 and 118 candidate DEGs for upregulated and downregulated DE-miRNAs were screened out. The miRNA-mRNA network included 5 downregulated and 13 upregulated DE-miRNAs. qRT-PCR proved that the expression levels of miRNA-18a-5p, miRNA-18b-5p, miRNA-449c-5p and miRNA-1224-5p and their target genes (NR3C1, CTGF, MYC, and TNS1) were consistent with our predictions. Univariate and multivariate Cox proportional hazards regression analyses of the hub genes revealed a significant prognostic value of NR3C1, EZH2, AND GATA4, and these genes were closely related to eight types of immune infiltration cells.
Conclusion: We identified three genes as candidate biomarkers for EC, which may provide a theoretical basis for targeted therapy.
Keywords: TCGA, endometrial cancer, miRNA-mRNA network, prognostic model, immune infiltration cell
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