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Research Paper|Volume 13, Issue 6|pp 8481—8496

Construction of a ceRNA-based lncRNA-mRNA network to identify functional lncRNAs in polycystic ovarian syndrome

Yue Ma1,2,3, Linna Ma1,2,3, Yurong Cao1,2,3, Jun Zhai1,2,3
  • 1Center for Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
  • 2Henan Key Laboratory of Reproduction and Genetics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
  • 3Henan Provincial Obstetrical and Gynecological Diseases (Reproductive Medicine) Clinical Research Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
Received: October 6, 2020Accepted: December 23, 2020Published: March 10, 2021

Copyright: © 2021 Ma et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Polycystic ovary syndrome (PCOS) is a prevalent endocrine and metabolic disorder in women of childbearing age. Recent studies suggest important roles for lncRNAs in PCOS development. Based on the hypothesis that lncRNAs are able to regulate mRNA functions by competitive binding to shared miRNAs, the present work sought to construct a PCOS-related lncRNA-mRNA network (PCLMN) to identify key lncRNAs with dysregulated expression and potential prognostic and therapeutic relevance. A global background network was constructed after retrieving lncRNA-miRNA and miRNA-mRNA pairs from the lncRNASNP2, miRTarBase and StarBase databases. Based on gene expression profiles from ovarian granulosa cells from PCOS patients and controls in the GEO’s GSE95728 dataset, the PCLMN was then constructed by applying hypergeometric testing. Using topological analysis, we identified 3 lncRNAs (LINC00667, AC073172.1 and H19) ranking within the top-ten gene lists for all three centrality measures. We then explored their subcellular localization, performed functional module analyses, and identified 4 sex hormone-related transcription factors as potential regulators of their expression. Significant associations with inflammation, oxidative stress, and apoptosis-related processes and pathways were revealed for the key lncRNAs in our PCMLN. Further studies verifying the mRNA/lncRNA relationships identified herein are needed to clarify their clinical significance.