Screening of Prognostic Biomarkers for Endometrial Carcinoma Based on a CeRNA Network

Overview

Journal PeerJ

Specialties Biology
Environmental Health
General Medicine

Date 2018 Dec 25

PMID 30581678

Citations 8

Authors

Ming-Jun Zheng

Rui Gou

Wen-Chao Zhang

Xin Nie

Jing Wang

Ling-Ling Gao

Juan-Juan Liu

Xiao Li

Bei Lin

Affiliations

Soon will be listed here.

Abstract

Objective: This study aims to reveal the regulation network of lncRNAs-miRNAs-mRNA in endometrial carcinoma (EC), to investigate the underlying mechanisms of EC occurrence and progression, to screen prognostic biomarkers.

Methods: RNA-seq and miRNA-seq data of endometrial carcinoma were downloaded from the TCGA database. Edge.R package was used to screen differentially expressed genes. A database was searched to determine differentially expressed lncRNA-miRNA and miRNA-mRNA pairs, to construct the topological network of ceRNA, and to elucidate the key RNAs that are for a prognosis of survival.

Results: We screened out 2632 mRNAs, 1178 lncRNAs and 189 miRNAs that were differentially expressed. The constructed ceRNA network included 97 lncRNAs, 20 miRNAs and 73 mRNAs. Analyzing network genes for associations with prognosies revealed 169 prognosis-associated RNAs, including 92 lncRNAs, 16miRNAs and 61 mRNAs.

Conclusion: Our results reveal new potential mechanisms underlying the carcinogenesis and progression of endometrial carcinoma.

Citing Articles

Advancements in Minimally Invasive Techniques and Biomarkers for the Early Detection of Endometrial Cancer: A Comprehensive Review of Novel Diagnostic Approaches and Clinical Implications.

Asaturova A, Zaretsky A, Rogozhina A, Tregubova A, Badlaeva A J Clin Med. 2025; 13(24.

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Mechanism of regulation of KIF23 on endometrial cancer cell growth and apoptosis.

Zhuang R, Liu H Discov Oncol. 2024; 15(1):83.

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The interplay of sex steroid hormones and microRNAs in endometrial cancer: current understanding and future directions.

Thakur L, Thakur S Front Endocrinol (Lausanne). 2023; 14:1166948.

PMID: 37152960 PMC: 10161733. DOI: 10.3389/fendo.2023.1166948.

Establishment of a prognostic-related microRNAs risk model for glioma by bioinformatics analysis.

Wang Y, Zhang C, Lu W, Chen R, Yu M Ann Transl Med. 2021; 9(12):1022.

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