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. 2015 Nov 3;6(34):36643-51.
doi: 10.18632/oncotarget.5421.

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

Chuan-Bao Zhang  1   2   3   4 , Ping Zhu  5 , Pei Yang  1   2   3   4 , Jin-Quan Cai  6 , Zhi-Liang Wang  2   3   4 , Qing-Bin Li  6 , Zhao-Shi Bao  2   4 , Wei Zhang  2   4 , Tao Jiang  1   2   3   4
Affiliations

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

Chuan-Bao Zhang et al. Oncotarget. .

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.

Keywords: anaplastic glioma; diagnosis; mRNA; prognosis; signature.

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Conflict of interest statement

CONFLICTS OF INTEREST

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1. Prognostic value of the signature in training and validation sets and the grade II and grade IV like properties of anaplastic gliomas
Patients in low risk group showed a better prognosis than those in high risk group. The two groups also respectively showed similar prognosis with grade II and grade IV gliomas. A, D. CGGA data; B, E. GSE16011 data; C, F. REMBRANDT data; L, low risk group; H, high risk group; II, WHO grade II; IV, WHO grade IV.
Figure 2
Figure 2. Distribution of risk score, OS, gene expression and clinical or molecular pathological features in CGGA, GSE16011 and REMBRANDT datasets
Figure 3
Figure 3. Unsupervised hierarchical clustering of WHO grade II–IV glioma patients based on the expression of the three genes
Grade II and grade IV gliomas clustered distinctively while grade III gliomas showed a mix of both branches. The vast majority of low risk anaplastic gliomas (green in risk group) clustered closely to grade II gliomas (green in grade) while the high risk ones (red in risk group) clustered in the branch of grade IV (red in grade). A. CGGA data; B. GSE16011 data; C. REMBRANDT data.
Figure 4
Figure 4. Functional annotation of risk groups
A. GO analysis revealed the significant association of the genes with increased expression in high risk group with six main pathways. Column height: gene counts; point height: enrichment p value. B. Gene set variation analysis of proliferation associated genes in three datasets. The risk score (upper panel) was calculated with the formula described above and ranked from left to right. Gene set enrichment score (lower panel) of proliferation was analyzed by GSVA package of R. These genes showed higher expression with the risk score going from low to high. C. The top ten enriched pathways in high risk group, analyzed by gene set enrichment analysis of TCGA RNAseq data. D. three representative plots of GSEA from C.
See this image and copyright information in PMC

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