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Integrated mRNAseq and microRNAseq data analysis for grade III gliomas

The World Health Organization classification distinguishes four grades for gliomas. Grade III gliomas, which are brain malignant brain tumors with variable biological behavior and propensity, have been not widely investigated. The objective of the present study was to identify specific gene modules...

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Detalles Bibliográficos
Autores principales: Dai, Junqiang, Bing, Zhitong, Zhang, Yinian, Li, Qiao, Niu, Liang, Liang, Wentao, Yuan, Guoqiang, Duan, Lei, Yin, Hang, Pan, Yawen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5865882/
https://www.ncbi.nlm.nih.gov/pubmed/28944855
http://dx.doi.org/10.3892/mmr.2017.7545
Descripción
Sumario:The World Health Organization classification distinguishes four grades for gliomas. Grade III gliomas, which are brain malignant brain tumors with variable biological behavior and propensity, have been not widely investigated. The objective of the present study was to identify specific gene modules and valuable hubs associated with gliomagenesis and molecular signatures to assist in determining grade III glioma prognosis. mRNAseq and micro (mi)RNAseq data were used to construct a co-expression network of gliomas using weight gene co-expression network analysis, and revealed the prognostic molecular signature of grade III gliomas. The differently expressed miRNAs and mRNAs were identified. A total of 37 mRNAs and 10 miRNAs were identified, which were closely associated with the survival rates of patients with grade III glioma. To further understand the tumorigenesis, Cytoscape software was used to construct a network containing these differently expressed molecules. The result suggested that both the downregulated genes and upregulated genes are vital in the process of glioma deterioration, and certain genes are closely associated with clinical prognosis.