Oncotarget

Research Papers:

Identification of high risk anaplastic gliomas by a diagnostic and prognostic signature derived from mRNA expression profiling

Chuan-Bao Zhang _, Ping Zhu, Pei Yang, Jin-Quan Cai, Zhi-Liang Wang, Qing-Bin Li, Zhao-Shi Bao, Wei Zhang and Tao Jiang

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Oncotarget. 2015; 6:36643-36651. https://doi.org/10.18632/oncotarget.5421

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Abstract

Chuan-Bao Zhang1,2,3,4,*, Ping Zhu5,*, Pei Yang1,2,3,4, Jin-Quan Cai6, Zhi-Liang Wang2,3,4, Qing-Bin Li6, Zhao-Shi Bao2,4, Wei Zhang2,4, Tao Jiang1,2,3,4

1Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China

2Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China

3Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China

4China National Clinical Research Center for Neurological Diseases, Beijing, China

5Department of Otolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

6Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China

*These authors have contributed equally to this work

Correspondence to:

Tao Jiang, e-mail: taojiang1964@163.com

Keywords: anaplastic glioma, mRNA, signature, diagnosis, prognosis

Received: June 05, 2015     Accepted: September 16, 2015     Published: September 28, 2015

ABSTRACT

Anaplastic gliomas are characterized by variable clinical and genetic features, but there are few studies focusing on the substratification of anaplastic gliomas. To identify a more objective and applicable classification of anaplastic gliomas, we analyzed whole genome mRNA expression profiling of four independent datasets. Univariate Cox regression, linear risk score formula and receiver operating characteristic (ROC) curve were applied to derive a gene signature with best prognostic performance. The corresponding clinical and molecular information were further analyzed for interpretation of the different prognosis and the independence of the signature. Gene ontology (GO), Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA) were performed for functional annotation of the differences. We found a three-gene signature, by applying which, the anaplastic gliomas could be divided into low risk and high risk groups. The two groups showed a high concordance with grade II and grade IV gliomas, respectively. The high risk group was more aggressive and complex. The three-gene signature showed diagnostic and prognostic value in anaplastic gliomas.


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