Identification and functional analysis of the risk microRNAs associated with cerebral low-grade glioma prognosis

Liu,Xinrui; Song,Bin; Li,Shanji; Wang,Nan; Yang,Hongfa

doi:10.3892/mmr.2017.6705

Identification and functional analysis of the risk microRNAs associated with cerebral low-grade glioma prognosis

Authors:
- Xinrui Liu
- Bin Song
- Shanji Li
- Nan Wang
- Hongfa Yang
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Affiliations: Department of Neurosurgical Oncology, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China, Department of Gastrointestinal Colorectal and Anal Surgery, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China, Second Department of Neurosurgery, The First People's Hospital of Yibin, Yibin, Sichuan 644000, P.R. China, Department of Neurotrauma, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China
Published online on: June 6, 2017 https://doi.org/10.3892/mmr.2017.6705
Pages: 1173-1179
Copyright: © Liu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Low-grade gliomas (LGGs) are associated with neurological disability. The present study used microRNA (miRNA) expression profiles to identify risk miRNAs for potential prognosis of cerebral LGGs. miRNA expression profiles and clinical data from 408 patients with cerebral LGGs were obtained from the Cancer Genome Atlas database. Risk miRNAs were identified by plotting Kaplan‑Meier curves and Cox proportional hazard regression analysis with the survival and KMsurv packages in R. A regulatory network of miRNA‑targets was constructed, followed by gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis using the Database for Annotation, Visualization and Integrated Discovery. A protein‑protein interaction (PPI) network of miRNA targets was built using Search Tool for the Retrieval of Interacting Genes software, and sub‑pathway identification was performed using the iSubpathwayMiner package in R. In total, 39 miRNAs had significant effect on survival curves. Following the Cox analysis and construction of miRNA‑targets regulatory network, hsa‑miRNA (miR)‑326 was identified to regulate 397 target genes. Additionally, targets of miR‑326 were primarily enriched in the GO terms of cell proliferation, epithelial growth factor receptor and nerve growth factor signaling pathways. Additionally, son of sevenless homolog 1 (SOS1), neuroblastoma RAS viral oncogene homolog (NRAS), vitamin D receptor (VDR) and mothers against decapentaplegic family member 3 (SMAD3) were most enriched in the PPI network. Targets of miR‑326 were primarily enriched in sub‑pathways including sphingolipid metabolism and arachidonic acid metabolism, in which sphingomyelin synthase 1 (SGMS1) and hematopoietic prostaglandin D synthase (HPGDS) were screened out. Hsa‑miR‑326 was identified as a risk miRNA for prognosis and may improve the outcome prediction of patients with cerebral LGG. This miRNA may regulate cancer cell proliferation by targeting SOS1, NRAS, VDR, SMAD3, SGMS1 and HPGDS.

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