Impact Factor 3.902
2017 JCR, Clarivate Analytics 2018

The world's most-cited Neurosciences journals

Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Mol. Neurosci. | doi: 10.3389/fnmol.2019.00066

Construction of potential glioblastoma multiforme-related miRNA-mRNA regulatory network

Weiyang Lou1, bisha ding1, liang xu1 and  Weimin Fan1*
  • 1First Affiliated Hospital, College of Medicine, Zhejiang University, China

Background: Glioblastoma multiforme (GBM), the most common and aggressive human malignant brain tumor, is notorious for its limited treatment options and poor prognosis. MicroRNAs (miRNAs) are found to be involved in tumorigenesis of GBM. However, a comprehensive miRNA-mRNA regulatory network has still not been established. Methods: A miRNA microarray dataset (GSE90603) was obtained from GEO database. Then, we employed GEO2R tool to perform differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The GBM mRNA dataset were downloaded from TCGA database for identifying differentially expressed genes (DEGs). Next, GO annotation and KEGG pathway enrichment analysis was conducted. PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes was further evaluated. Results: Total 33 DE-miRNAs, consisting of 10 upregulated DE-miRNAs and 23 downregulated DE-miRNAs, were screened. SP1 was predicted to potentially regulate most of screened DE-miRNAs. 3027 and 3879 predicted target genes were obtained for upregulated and downregulated DE-miRNAs, respectively. Subsequently, 1715 upregulated DEGs and 1259 downregulated DEGs were identified. Then, 149 and 295 potential downregulated and upregulated genes commonly appeared in target genes of DE-miRNAs and DEGs were selected for GO annotation and KEGG pathway enrichment analysis. The downregulated genes were significantly enriched in cGMP-PKG signaling pathway and calcium signaling pathway whereas the upregulated genes were enriched in pathways in cancer and PI3K-Akt signaling pathway. Construction and analysis of PPI network showed that STXBP1 and TP53 were recognized as hub genes with the highest connectivity degrees. Expression analytic result of the top 20 hub genes in GBM using GEPIA database was generally identical with previous differential expression analysis for TCGA data. EGFR, PPP3CB and MYO5A expression was significantly associated with patients’ OS. Conclusions: In this study, we established a potential GBM-related miRNA-mRNA regulatory network, which explores a comprehensive understanding of the molecular mechanisms and provides key clues in seeking novel therapeutic targets for GBM. In the future, more experiments need to be performed to validate our current findings.

Keywords: Glioblastoma multiform, microRNA, GEO, TCGA, Bioinformatic analysis

Received: 12 Sep 2018; Accepted: 28 Feb 2019.

Edited by:

MICHELE PAPA, Università degli Studi della Campania Luigi Vanvitelli Caserta, Italy

Reviewed by:

Shyam Gajavelli, University of Miami, United States
Roberto Giovannoni, University of Pisa, Italy  

Copyright: © 2019 Lou, ding, xu and Fan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Weimin Fan, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China, 11718264@zju.edu.cn