Gene expression profile for predicting survival of patients with meningioma | Zendy

Feng Chen | Zendy; Chunxiang Xiang | Zendy; Yi Zhou | Zendy; Xiang-Sheng Ao | Zendy; Daquan Zhou | Zendy; Peng Peng | Zendy; Haiquan Zhang | Zendy; Handong Liu | Zendy; Xing Huang | Zendy

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Gene expression profile for predicting survival of patients with meningioma

Author(s) -

Feng Chen,

Chunxiang Xiang,

Yi Zhou,

Xiang-Sheng Ao,

Daquan Zhou,

Peng Peng,

Haiquan Zhang,

Handong Liu,

Xing Huang

Publication year - 2014

Publication title -

international journal of oncology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.405

H-Index - 122

ISSN - 1019-6439

DOI - 10.3892/ijo.2014.2779

Subject(s) - meningioma , biology , oncogene , microarray , survival analysis , gene , proportional hazards model , dna microarray , cell cycle , molecular medicine , gene expression , microarray analysis techniques , gene expression profiling , computational biology , cancer research , bioinformatics , oncology , pathology , genetics , medicine

Current staging methods are inadequate for predicting the overall survival of meningioma. DNA microarray technologies improve the understanding of tumour progression. We analysed genome wide expression profiles of 119 meningioma samples from two previous published DNA microarray studies. The Cox proportional hazards regression models were applied to identify overall survival related gene signature. A total of 449 genes (109 upregulated and 340 downregulated) were identified as differentially expressed in meningioma. Among these differentially expressed genes, 37 genes were identified to be related to meningioma overall survival. Our 37-gene signature is closely associated with overall survival among patients with meningioma. This gene expression profile could provide an optimization of the clinical management and development of new therapeutic strategies for meningioma.

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