Identification of a DNA Repair-Related Multigene Signature as a Novel Prognostic Predictor of Glioblastoma

Highlights

• Glioblastoma treatment with temozolomide frequently results in chemoresistance.

• There is a need to develop new accurate prognostic indicators to better stratify patients.

• A novel DNA repair-related signature independently predicted overall survival.

• A 5-gene panel stratified patients with primary glioblastoma into low/high risk.

• Risk score indicates different overall survival and reaction to temozolomide.

Background

Glioblastoma (GBM) is an extremely challenging malignancy to treat. Although temozolomide (TMZ) is a standard treatment regimen, many patients with GBM develop chemoresistance. The aim of this study was to identify a DNA repair-related gene signature to better stratify patients treated with TMZ.

Methods

We selected 89 cases of primary GBM (pGBM) from the Chinese Glioma Genome Atlas RNA-seq dataset as the training cohort, whereas The Cancer Genome Atlas RNA-seq and Gene Set Enrichment (GSE) 16011 mRNA array sets were used as validation cohorts. Regression analysis and linear risk score assessment were performed to build a DNA repair-related signature. We used Kaplan–Meier analysis to evaluate the predictive value of the signature for overall survival (OS) in the different groups. Multivariate Cox regression analysis was used to determine whether the 5-gene signature could independently predict OS.

Results

Using our 5-gene signature panel of APEX1, APRT, PARP2, PMS2L2, and POLR2L, we divided patients with pGBM into high- and low-risk groups. Patients with a low-risk score were predicted to have favorable survival and greater benefit from TMZ therapy compared with patients from the high-risk group (P < 0.05). Moreover, receiver operating characteristic curves showed that the multigene signature was the most sensitive and specific model for survival prediction (P < 0.05).

Conclusions

Among patients with pGBM, classification based on a risk score determined using a 5-gene panel indicated different OS and reaction to TMZ. The findings in this study demonstrate that this unique 5-gene signature could be a novel model to predict OS and provide accurate therapy for patients with pGBM.

Introduction

Glioma is a well-known and aggressive malignant tumor associated with short survival and a uniformly fatal outcome despite the availability of advanced therapies.1, 2 According to the World Health Organization, gliomas are divided into 4 grades (I–IV).³ Grades II and III are considered lower-grade gliomas,⁴ whereas grade IV is glioblastoma multiforme (GBM) and is the most malignant type of glioma.⁵ The wide range of biological and clinical heterogeneity makes the diagnosis and treatment of gliomas an enormous challenge.⁶ One confounding factor is interobserver variability arising from a morphology-based classification of gliomas that results in suboptimal diagnostic reproducibility.⁶ Thus, there is an urgent need to develop objective and accurate methods for the diagnosis and treatment of gliomas.

With the advent of new gene profiles, many researchers have presented various overall survival (OS) prediction models4, 7, 8, 9; however, few of these studies focused on treatment selection in cases of primary glioblastoma multiforme (pGBM). In addition, why many patients with pGBM are resistant to temozolomide (TMZ) therapy remains unclear.

As a new oral alkylating agent, TMZ is currently the gold standard for adjuvant chemotherapy in patients with gliomas, especially for high-grade glioma.¹⁰ Although O-6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status is an important biomarker to divide gliomas into TMZ-chemoresistant (TCR subtype) and TMZ-chemosensitive (TCS subtype) groups,7, 11 many patients with glioma and MGMT promoter methylation do not benefit from TMZ therapy.¹² Therefore, there is the need to identify other biomarkers that better discriminate patients to provide better personalized treatment care and response to TMZ.

In the present study, we selected 89 patients with pGBM from the Chinese Glioma Genome Atlas (CGGA) RNA-seq dataset as a training set, used patients from The Cancer Genome Atlas (TCGA) RNA-seq and GSE16011 mRNA array sets as validation sets, and identified a 5-gene signature composed of APEX1, APRT, PARP2, PMS2L2, and POLR2L that reliably predicts OS of patients with glioma and identifies subtypes of pGBM with differing responses to TMZ therapy. The identification and characterization of our gene panel may provide a new method for the accurate diagnosis and effective treatment of pGBM.