Intrinsic molecular subtypes of glioma are prognostic and predict benefit from adjuvant procarbazine, lomustine, and vincristine chemotherapy in combination with other prognostic factors in anaplastic oligodendroglial brain tumors: a report from EORTC study 26951.

PURPOSE: Intrinsic glioma subtypes (IGSs) are molecularly similar tumors that can be identified based on unsupervised gene expression analysis. Here, we have evaluated the clinical relevance of these subtypes within European Organisation for Research and Treatment of Cancer (EORTC) 26951, a randomized phase III clinical trial investigating adjuvant procarbazine, lomustine, and vincristine (PCV) chemotherapy in anaplastic oligodendroglial tumors. Our study includes gene expression profiles of formalin-fixed, paraffin-embedded (FFPE) clinical trial samples. PATIENTS AND METHODS: Gene expression profiling was performed in 140 samples, 47 fresh frozen samples and 93 FFPE samples, on HU133_Plus_2.0 and HuEx_1.0_st arrays, respectively. RESULTS: All previously identified six IGSs are present in EORTC 26951. This confirms that different molecular subtypes are present within a well-defined histologic subtype. Intrinsic subtypes are highly prognostic for overall survival (OS) and progression-free survival (PFS). They are prognostic for PFS independent of clinical (age, performance status, and tumor location), molecular (1p/19q loss of heterozygosity [LOH], IDH1 mutation, and MGMT methylation), and histologic parameters. Combining known molecular (1p/19q LOH, IDH1) prognostic parameters with intrinsic subtypes improves outcome prediction (proportion of explained variation, 30% v 23% for each individual group of factors). Specific genetic changes (IDH1, 1p/19q LOH, and EGFR amplification) segregate into different subtypes. We identified one subtype, IGS-9 (characterized by a high percentage of 1p/19q LOH and IDH1 mutations), that especially benefits from PCV chemotherapy. Median OS in this subtype was 5.5 years after radiotherapy (RT) alone versus 12.8 years after RT/PCV (P = .0349; hazard ratio, 2.18; 95% CI, 1.06 to 4.50). CONCLUSION: Intrinsic subtypes are highly prognostic in EORTC 26951 and improve outcome prediction when combined with other prognostic factors. Tumors assigned to IGS-9 benefit from adjuvant PCV.

A hypermethylated phenotype is a better predictor of survival than MGMT methylation in anaplastic oligodendroglial brain tumors: a report from EORTC study 26951.

PURPOSE: The MGMT promoter methylation status has been suggested to be predictive for outcome to temozolomide chemotherapy in patients with glioblastoma (GBM). Subsequent studies indicated that MGMT promoter methylation is a prognostic marker even in patients treated with radiotherapy alone, both in GBMs and in grade III gliomas. EXPERIMENTAL DESIGN: To help determine the molecular mechanism behind this prognostic effect, we have conducted genome-wide methylation profiling and determined the MGMT promoter methylation status, 1p19q LOH, IDH1 mutation status, and expression profile on a series of oligodendroglial tumors [anaplastic oligodendrogliomas (AOD) and anaplastic oligoastrocytomas (AOA)] within EORTC study 26951. The series was expanded with tumors of the same histology and treatment from our own archive. RESULTS: Methylation profiling identified two main subgroups of oligodendroglial brain tumors of which survival in the CpG island hypermethylation phenotype (CIMP(+)) subgroup was markedly better than the survival of the unmethylated (CIMP(-)) subgroup (5.62 vs. 1.24 years; P < 0.0001). CIMP status correlated with survival, MGMT promoter methylation, 1p19q LOH, and IDH1 mutation status. CIMP status strongly increases the predictive accuracy of survival in a model including known clinical prognostic factors such as age and performance score. We validated our results on an independent data set from the Cancer Genome Atlas (TCGA). CONCLUSION: The strong association between CIMP status and MGMT promoter methylation suggests that the MGMT promoter methylation status is part of a more general, prognostically favorable genome-wide methylation profile. Methylation profiling therefore may help identify AODs and AOAs with improved prognosis.

Integrated genomic profiling identifies candidate genes implicated in glioma-genesis and a novel LEO1-SLC12A1 fusion gene.

We performed genotyping and exon-level expression profiling on 21 glioblastomas (GBMs) and 19 oligodendrogliomas (ODs) to identify genes involved in glioma initiation and/or progression. Low-copy number amplifications (2.5 < n < 7) and high-copy number amplifications (n > 7) were more frequently observed in GBMs; ODs generally have more heterozygous deletions per tumor. Four high-copy amplicons were identified in more than one sample and resulted in overexpression of the known oncogenes EGFR, MDM2, and CDK4. In the fourth amplicon, RBBP5, a member of the RB pathway, may act as a novel oncogene in GBMs. Not all hCNAs contain known genes, which may suggest that other transcriptional and/or regulatory elements are the target for amplification. Regions with most frequent allelic loss, both in ODs and GBMs, resulted in a reduced expression of known tumor suppressor genes. We identified a homozygous deletion spanning the Pragmin gene in one sample, but direct sequencing of all coding exons in 20 other glioma samples failed to detect additional genetic changes. Finally, we screened for fusion genes by identifying aberrant 5'-3' expression of genes that lie over regions of a copy number change. A fusion gene between exon 11 of LEO1 and exon 10 of SLC12A1 was identified. Our data show that integrated genomic profiling can identify genes involved in tumor initiation, and/or progression and can be used as an approach to identify novel fusion genes.

Segregation of non-p.R132H mutations in IDH1 in distinct molecular subtypes of glioma.

Mutations in the gene encoding the isocitrate dehydrogenase 1 gene (IDH1) occur at a high frequency (up to 80%) in many different subtypes of glioma. In this study, we have screened for IDH1 mutations in a cohort of 496 gliomas. IDH1 mutations were most frequently observed in low grade gliomas with c.395G>A (p.R132H) representing >90% of all IDH1 mutations. Interestingly, non-p.R132H mutations segregate in distinct histological and molecular subtypes of glioma. Histologically, they occur sporadically in classic oligodendrogliomas and at significantly higher frequency in other grade II and III gliomas. Genetically, non-p.R132H mutations occur in tumors with TP53 mutation, are virtually absent in tumors with loss of heterozygosity on 1p and 19q and accumulate in distinct (gene-expression profiling based) intrinsic molecular subtypes. The IDH1 mutation type does not affect patient survival. Our results were validated on an independent sample cohort, indicating that the IDH1 mutation spectrum may aid glioma subtype classification. Functional differences between p.R132H and non-p.R132H mutated IDH1 may explain the segregation in distinct glioma subtypes.

Intrinsic gene expression profiles of gliomas are a better predictor of survival than histology.

Gliomas are the most common primary brain tumors with heterogeneous morphology and variable prognosis. Treatment decisions in patients rely mainly on histologic classification and clinical parameters. However, differences between histologic subclasses and grades are subtle, and classifying gliomas is subject to a large interobserver variability. To improve current classification standards, we have performed gene expression profiling on a large cohort of glioma samples of all histologic subtypes and grades. We identified seven distinct molecular subgroups that correlate with survival. These include two favorable prognostic subgroups (median survival, >4.7 years), two with intermediate prognosis (median survival, 1-4 years), two with poor prognosis (median survival, <1 year), and one control group. The intrinsic molecular subtypes of glioma are different from histologic subgroups and correlate better to patient survival. The prognostic value of molecular subgroups was validated on five independent sample cohorts (The Cancer Genome Atlas, Repository for Molecular Brain Neoplasia Data, GSE12907, GSE4271, and Li and colleagues). The power of intrinsic subtyping is shown by its ability to identify a subset of prognostically favorable tumors within an external data set that contains only histologically confirmed glioblastomas (GBM). Specific genetic changes (epidermal growth factor receptor amplification, IDH1 mutation, and 1p/19q loss of heterozygosity) segregate in distinct molecular subgroups. We identified a subgroup with molecular features associated with secondary GBM, suggesting that different genetic changes drive gene expression profiles. Finally, we assessed response to treatment in molecular subgroups. Our data provide compelling evidence that expression profiling is a more accurate and objective method to classify gliomas than histologic classification. Molecular classification therefore may aid diagnosis and can guide clinical decision making.