25 October 2019 : Clinical Research
Construction of a Competitive Endogenous RNA Network in Uterine Corpus Endometrial Carcinoma
Dong Ouyang1ABCDEG*, Ruyi Li2BDEF, Yaxian Li1EF, Xueqiong Zhu2DEDOI: 10.12659/MSM.915798
Med Sci Monit 2019; 25:7998-8010
Abstract
BACKGROUND: Long non-coding RNAs (lncRNAs) affect post-transcriptional regulation by interfering with microRNAs (miRNAs), and by acting as competitive endogenous RNAs (ceRNAs). The roles and mechanisms of lncRNAs as ceRNAs in the progression and prognosis of uterine corpus endometrial carcinoma are not well understood.
MATERIAL AND METHODS: We analyzed high-throughput transcriptome data downloaded from The Cancer Genome Atlas database for 548 patients with uterine corpus endometrial carcinoma, and the we constructed a ceRNA network. Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses of differentially expressed messenger RNAs (DE-mRNAs) were performed using R software. Kaplan-Meier survival curves were generated for all RNAs in the ceRNA network.
RESULTS: We identified 2612 messenger RNAs (mRNAs), 1111 lncRNAs, and 187 miRNAs that were differentially expressed in uterine corpus endometrial carcinoma. We then identified mutual regulatory relationships between lncRNA-miRNA pairs and miRNA-mRNA pairs. A ceRNA regulatory network for uterine corpus endometrial carcinoma was successfully constructed, and consisted of 87 lncRNAs, 74 mRNAs, and 20 miRNAs. Nine lncRNAs, 3 miRNAs, and 22 mRNAs were associated with prognosis of uterine corpus endometrial carcinoma. We also analyzed the linear relationships between the expression of the 9 DE-lncRNAs and 22 DE-mRNAs with prognostic value.
CONCLUSIONS: Our study showed that the lncRNAs C2orf48 and LINC00261 might be key regulators of uterine corpus endometrial carcinoma and might serve as prognostic indicators. Our study contributes to the understanding of the molecular mechanisms of uterine corpus endometrial carcinoma, and it identifies lncRNAs that might serve as prognostic markers and therapeutic targets.
Keywords: Endometrial Neoplasms, MicroRNAs, RNA, Long Noncoding, Aged, Databases, Genetic, Gene Expression Regulation, Neoplastic, gene ontology, Gene Regulatory Networks, Kaplan-Meier Estimate, Middle Aged, Prognosis, RNA, Messenger, transcriptome, Uterine Neoplasms
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