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Bioinformatic analysis of gene expression and methylation regulation in glioblastoma

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Abstract

Different gene expression and methylation profiles are identified in glioblastoma (GBM). To screen the differentially expressed genes affected by DNA methylation modification and further investigate their prognostic values for GBMs. We included The Cancer Genome Atlas (TCGA) RNA sequencing (676) and DNA methylation (Illumina Human Methylation 450K; 657) databases to detect the gene expression and methylation profiles. Chinese Glioma Genome Atlas (CGGA) RNA sequencing database and TCGA DNA methylation (Illumina Human Methylation 27K; 283) was included for validation. Gene expression and DNA methylation statues were identified using principal components analysis (PCA). A total of 3365 differentially expressed genes were identified. Among them, 2940 genes showed low methylation and high expression, while 425 genes showed high methylation and low expression in GBMs. An eight-gene (C9orf64, OSMR, MDK, MARVELD1, PTRF, MYD88, BIRC3, RPP25) signature was established to divide GBM patients into two groups based on the cut-off point (27.24). The high risk group had shorter overall survival (OS) than low risk group (median OS 15.77 vs. 10.61 months; P = 0.0002). Moreover, the different clinical and molecular features were shown between two groups. These findings could be validated in additional datasets. The differentially expressed genes affected by DNA methylation modification were detected. Our results showed that the eight-gene signature has independently prognostic value for GBM patients.

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Abbreviations

GBM:

Glioblastoma

LGG:

Low-grade glioma

TCGA:

The Cancer Genome Atlas

CGGA:

Chinese Glioma Genome Atlas

OS:

Overall survival

PCA:

Principal components analysis

IDH:

Isocitrate dehydrogenase

MGMT:

O(6)-Methylguanine DNA methyltransferase

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Funding

This work was supported by grants from Ministry of Science and Technology of China Grant (2012CB825505, 2011BAI08B08); National Key Technology Research and Development Program of the Ministry of Science and Technology of China (2013BAI09B03, 2014BAI04B02); National High Technology Research and Development Program (2012AA02A508); National Natural Science Foundation of China (91229121); Beijing Municipal Administration of Hospitals’ Mission Plan (SML20150501); “13th Five-Year Plan” National Science and Technology supporting plan (2015BAI09B04).

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Authors and Affiliations

  1. Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 6 Tiantan Xili, Dongcheng District, Beijing, 100050, China

    Wen Wang, Jiangfei Wang & Jizong Zhao

  2. Department of Neurosurgery, The Second Affiliated Hospital of Soochow University, Suzhou, 215123, China

    Wen Wang, Qing Lan & Jizong Zhao

  3. Beijing Neurosurgical Institute, Capital Medical University, Beijing, 100050, China

    Zheng Zhao & Fan Wu

  4. Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China

    Haoyuan Wang

  5. Chinese Glioma Cooperative Group (CGCG), Beijing, China

    Wen Wang, Zheng Zhao, Fan Wu, Haoyuan Wang & Jiangfei Wang

  6. China National Clinical Research Center for Neurological Diseases, Beijing, China

    Wen Wang, Jiangfei Wang & Jizong Zhao

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  1. Wen Wang
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  2. Zheng Zhao
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  3. Fan Wu
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  6. Qing Lan
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Correspondence to Jizong Zhao.

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Wang, W., Zhao, Z., Wu, F. et al. Bioinformatic analysis of gene expression and methylation regulation in glioblastoma. J Neurooncol 136, 495–503 (2018). https://doi.org/10.1007/s11060-017-2688-1

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