A novel methylation signature predicts radiotherapy sensitivity in glioma

Yuemei Feng,Yuanhao Chang,Haoyu Jiang,Zhongfang Shi,Renpeng Li,Zhiliang Wang,Xu Yan,Ye Chen,Fang Yuan,You Zhai,Wei Zhang,Guanzhang Li

doi:10.1038/s41598-020-77259-9

Yuemei Feng, Yuanhao Chang + Show 10 more

Open Access

https://doi.org/10.1038/s41598-020-77259-9

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Abstract

Glioblastoma (GBM) is the most common and malignant cancer of the central nervous system, and radiotherapy is widely applied in GBM treatment; however, the sensitivity to radiotherapy varies in different patients. To solve this clinical dilemma, a radiosensitivity prediction signature was constructed in the present study based on genomic methylation. In total, 1044 primary GBM samples with clinical and methylation microarray data were involved in this study. LASSO-COX, GSVA, Kaplan–Meier survival curve analysis, and COX regression were performed for the construction and verification of predictive models. The R programming language was used as the main tool for statistical analysis and graphical work. Via the integration analysis of methylation and the survival data of primary GBM, a novel prognostic and radiosensitivity prediction signature was constructed. This signature was found to be stable in prognosis prediction in the TCGA and CGGA databases. The possible mechanism was also explored, and it was found that this signature is closely related to DNA repair functions. Most importantly, this signature could predict whether GBM patients could benefit from radiotherapy. In summary, a radiosensitivity prediction signature for GBM patients based on five methylated probes was constructed, and presents great potential for clinical application.

Highlights

To determine the methylation probes associated with radiotherapy sensitivity, 50 primary
Patients with a survival time of greater than 18 months after postoperative radiotherapy were defined as long-term survivors, and those with a survival time of less than 9 months were defined as short-term survivors[17]
The results revealed that the risk score has a significant correlation with the clinical features of glioma, including TCGA transcriptome subtypes, WHO grade, IDH1 status, 1p/19q status, and MGMT promoter methylation status

Summary

Introduction

The relationships between the signature risk score and various clinical features were investigated via the TCGA and CGGA databases. Found to be an important indicator of chemosensitivity in gliomas, and the correlations between the risk score and MGMT promoter methylation status suggests that the former might be related to chemotherapeutic drug sensitivity (Fig. 3I–L). The radiosensitivity prediction signature risk score was found to be likely to be associated with genomic instability caused by DNA repair function changes, which are one of the causes of poor prognosis.

Results

Conclusion