Molecular Predictors of Long-Term Survival in Glioblastoma Multiforme Patients

Jie Lu,Max Shpak,Mark G. Burnett,Matthew C. Cowperthwaite

doi:10.1371/journal.pone.0154313

Abstract

Glioblastoma multiforme (GBM) is the most common and aggressive adult primary brain cancer, with <10% of patients surviving for more than 3 years. Demographic and clinical factors (e.g. age) and individual molecular biomarkers have been associated with prolonged survival in GBM patients. However, comprehensive systems-level analyses of molecular profiles associated with long-term survival (LTS) in GBM patients are still lacking. We present an integrative study of molecular data and clinical variables in these long-term survivors (LTSs, patients surviving >3 years) to identify biomarkers associated with prolonged survival, and to assess the possible similarity of molecular characteristics between LGG and LTS GBM. We analyzed the relationship between multivariable molecular data and LTS in GBM patients from the Cancer Genome Atlas (TCGA), including germline and somatic point mutation, gene expression, DNA methylation, copy number variation (CNV) and microRNA (miRNA) expression using logistic regression models. The molecular relationship between GBM LTS and LGG tumors was examined through cluster analysis. We identified 13, 94, 43, 29, and 1 significant predictors of LTS using Lasso logistic regression from the somatic point mutation, gene expression, DNA methylation, CNV, and miRNA expression data sets, respectively. Individually, DNA methylation provided the best prediction performance (AUC = 0.84). Combining multiple classes of molecular data into joint regression models did not improve prediction accuracy, but did identify additional genes that were not significantly predictive in individual models. PCA and clustering analyses showed that GBM LTS typically had gene expression profiles similar to non-LTS GBM. Furthermore, cluster analysis did not identify a close affinity between LTS GBM and LGG, nor did we find a significant association between LTS and secondary GBM. The absence of unique LTS profiles and the lack of similarity between LTS GBM and LGG, indicates that there are multiple genetic and epigenetic pathways to LTS in GBM patients.

Highlights

Glioblastoma multiforme (GBM) is the most frequent malignant form of primary brain cancer in adults
The principal goal of this study was to determine whether long-term survival (LTS) GBM tumors have genomic features that distinguish them from those found in patients with more typical survival times, i.e. to evaluate whether they constitute a biologically distinct subclass of high-grade gliomas with unique molecular characteristics, and to evaluate the relationship between LTS GBMs and low grade glioma (LGG)
In spite of the limitations on statistical power due to comparatively small samples of LTS patients and incomplete clinical data, our analyses identified molecular biomarkers that significantly predict LTS, several of which have been documented in the literature as predictors of improved response to chemotherapy and overall improved patient prognosis

Summary

Introduction

Glioblastoma multiforme (GBM) is the most frequent malignant form of primary brain cancer in adults. With advances in microarray and sequencing technologies, associations of molecular markers such as mutations, gene expression levels, DNA methylation states, and microRNAs with LTS tumors have been reported [2, 3, 11,12,13,14,15,16,17,18,19,20,21] Using these techniques, MGMT hypermethylation and mutations in isocitrate dehydrogenase (IDH1) have been the most frequently identified genomic marker of improved patient response to chemotherapy and longer patient survival [12, 22, 23]. Other analyses (e.g. [24]) have identified correlations between genomic alterations and GBM patient survival times, the analysis and markers were not specific to LTS patients

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