Dataset Information

SAMSN1 is highly expressed and associated with a poor survival in glioblastoma multiforme.

ABSTRACT:

Objectives

To study the expression pattern and prognostic significance of SAMSN1 in glioma.

Methods

Affymetrix and Arrystar gene microarray data in the setting of glioma was analyzed to preliminarily study the expression pattern of SAMSN1 in glioma tissues, and Hieratical clustering of gene microarray data was performed to filter out genes that have prognostic value in malignant glioma. Survival analysis by Kaplan-Meier estimates stratified by SAMSN1 expression was then made based on the data of more than 500 GBM cases provided by The Cancer Genome Atlas (TCGA) project. At last, we detected the expression of SAMSN1 in large numbers of glioma and normal brain tissue samples using Tissue Microarray (TMA). Survival analysis by Kaplan-Meier estimates in each grade of glioma was stratified by SAMSN1 expression. Multivariate survival analysis was made by Cox proportional hazards regression models in corresponding groups of glioma.

Results

With the expression data of SAMSN1 and 68 other genes, high-grade glioma could be classified into two groups with clearly different prognoses. Gene and large sample tissue microarrays showed high expression of SAMSN1 in glioma particularly in GBM. Survival analysis based on the TCGA GBM data matrix and TMA multi-grade glioma dataset found that SAMSN1 expression was closely related to the prognosis of GBM, either PFS or OS (P<0.05). Multivariate survival analysis with Cox proportional hazards regression models confirmed that high expression of SAMSN1 was a strong risk factor for PFS and OS of GBM patients.

Conclusion

SAMSN1 is over-expressed in glioma as compared with that found in normal brains, especially in GBM. High expression of SAMSN1 is a significant risk factor for the progression free and overall survival of GBM.

SUBMITTER: Yan Y

PROVIDER: S-EPMC3838348 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Publications

SAMSN1 is highly expressed and associated with a poor survival in glioblastoma multiforme.

Yan Yong Y Zhang Lei L Xu Tao T Zhou Jinxu J Qin Rong R Chen Chao C Zou Yongxiang Y Fu Da D Hu Guohan G Chen Juxiang J Lu Yicheng Y

PloS one 20131122 11

<h4>Objectives</h4>To study the expression pattern and prognostic significance of SAMSN1 in glioma.<h4>Methods</h4>Affymetrix and Arrystar gene microarray data in the setting of glioma was analyzed to preliminarily study the expression pattern of SAMSN1 in glioma tissues, and Hieratical clustering of gene microarray data was performed to filter out genes that have prognostic value in malignant glioma. Survival analysis by Kaplan-Meier estimates stratified by SAMSN1 expression was then made based ...[more]

PMID: 24278465

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Project description:Glioblastoma multiforme (GBM) is the most malignant primary tumour type of the central nervous system with limited therapeutic options and poor prognosis, and its pathogenic mechanisms have remained to be fully elucidated. Aberrant DNA methylation is involved in multiple biological processes and may contribute to the occurrence and development of GBM by affecting the expression of certain genes. However, the specific molecular mechanisms remain to be fully elucidated. The present study focused on uncovering differentially expressed genes with altered methylation status in GBM and aimed to discover novel biomarkers for the diagnosis and treatment of GBM. These genes were identified by combined analysis of multiple gene expression and methylation datasets from gene expression omnibus (GSE16011, GSE50161 and GSE 50923) to increase the reliability. In addition, The Cancer Genome Atlas (TCGA) dataset for GBM was used to test the stability of the results. Overall, 251 hypomethylated upregulated genes (Hypo-UGs) and 199 hypermethylated downregulated genes (Hyper-DGs) were identified in the present study. Functional enrichment analysis revealed that the Hypo-UGs are involved in the regulation of immune- and infection-associated signalling, while the Hyper-DGs are involved in the regulation of synaptic transmission. The three hub genes for Hyper-DGs (somatostatin, neuropeptide Y and adenylate cyclase 2) and five hub genes for Hypo-UGs [interleukin-8, matrix metalloproteinase (MMP)9, cyclin-dependent kinase 1, 2'-5'-oligoadenylate synthetase 1, C-X-C motif chemokine ligand 10 and MMP2] were identified by protein-protein interaction network analysis. Among the Hypo-UGs and Hyper-DGs, overexpression of C-type lectin domain containing 5A, epithelial membrane protein 3, solute carrier family 43 member 3, STEAP3 metalloreductase, tumour necrosis factor α-induced protein 6 and apolipoprotein B mRNA editing enzyme catalytic subunit 3G was significantly associated with poor prognosis in the TCGA and GSE16011 datasets (P<0.001). In conclusion, the present study uncovered numerous novel aberrantly methylated genes and pathways associated with GBM. Methylation-based markers, including the hub genes and prognostic genes identified, may potentially serve as markers for the diagnosis of GBM and targets for its treatment.

Dataset Information

SAMSN1 is highly expressed and associated with a poor survival in glioblastoma multiforme.

Objectives

Methods

Results

Conclusion

Publications

SAMSN1 is highly expressed and associated with a poor survival in glioblastoma multiforme.

Similar Datasets

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