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Construction and Comprehensive Analysis of a Special Competitive Endogenous RNAs Network to Reveal Potential Prognostic Biomarkers for Endometrial Carcinoma

Background: Endometrial carcinoma (EC) is one of the most common malignancies in women worldwide. For EC patients discovered at an early stage, the prognosis is good. However, the advanced EC patients (stage III-IV) have very poor prognoses. The competitive endogenous RNAs (ceRNA) regulatory network in EC remains unclear, and the relationship between hub RNAs and important clinical characters (clinical stage) has not been strictly studied yet.

Objective: In order to study the development of endometrial carcinoma and the identification of early diagnostic markers, the relationship between hub RNAs and important clinical trait (clinical stage) was strictly studied.

Method: The co-expression networks of mRNA, lncRNA and miRNA were constructed by weighted gene co-expression network analysis. Gene ontology (GO) biological process terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out for DEmRNA. A ceRNA regulated network was constructed based on miRcode, miRDB, TargetScan and miRTarBase. And survival analysis, regression analysis of mRNA-lncRNA pairs and gene set enrichment analysis were carried out.

Results: A ceRNA network containing 11 mRNAs, 4 miRNAs and 18 lncRNAs was constructed based on aberrantly expressed RNAs in the co-expression modules. In this network, 7 mRNAs, 4 lncRNAs and 1 miRNA were found closely related to the overall survival of EC. The positive correlations of 35 pairs of mRNA and lncRNA in the ceRNA network were obtained. Notably, 5 mRNAs, 3 lncRNAs and 1 miRNA were identified as potential prognostic biomarkers for EC. Single gene GSEA analysis revealed that the signal pathways related to cell cycle and cancer were highly enriched.

Conclusion: Identification of five mRNAs (CBX6, PIM1, RIMS3, SOX11 and XKR7), three lncRNA (WT1-AS, LINC00494 and LINC00501) and one miRNA (miR-195) as potential prognostic biomarkers for EC was helpful for the early diagnosis, prognosis and development of new treatment strategies of EC patients.

Journal Title: Current Bioinformatics

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