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PLoS One. 2014 May 8;9(5):e96908. doi: 10.1371/journal.pone.0096908. eCollection 2014.

Identification of miRNA-mediated core gene module for glioma patient prediction by integrating high-throughput miRNA, mRNA expression and pathway structure.

Author information

1
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
2
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China; Department of Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
3
Department of Neurosurgery, Tiantan Hospital, Capital Medical University, Beijing, China.
4
Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-Oncology, Tianjin Neurological Institute, Laboratory of Neurotrauma, Variation and Regeneration, Ministry of Education and Tianjin Municipal Government, Tianjin, China.

Abstract

The prognosis of glioma patients is usually poor, especially in patients with glioblastoma (World Health Organization (WHO) grade IV). The regulatory functions of microRNA (miRNA) on genes have important implications in glioma cell survival. However, there are not many studies that have investigated glioma survival by integrating miRNAs and genes while also considering pathway structure. In this study, we performed sample-matched miRNA and mRNA expression profilings to systematically analyze glioma patient survival. During this analytical process, we developed pathway-based random walk to identify a glioma core miRNA-gene module, simultaneously considering pathway structure information and multi-level involvement of miRNAs and genes. The core miRNA-gene module we identified was comprised of four apparent sub-modules; all four sub-modules displayed a significant correlation with patient survival in the testing set (P-values≤0.001). Notably, one sub-module that consisted of 6 miRNAs and 26 genes also correlated with survival time in the high-grade subgroup (WHO grade III and IV), P-value = 0.0062. Furthermore, the 26-gene expression signature from this sub-module had robust predictive power in four independent, publicly available glioma datasets. Our findings suggested that the expression signatures, which were identified by integration of miRNA and gene level, were closely associated with overall survival among the glioma patients with various grades.

PMID:
24809850
PMCID:
PMC4014552
DOI:
10.1371/journal.pone.0096908
[Indexed for MEDLINE]
Free PMC Article

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