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Background. Genetic and epigenetic profiling of glioblastomas has provided a comprehensive list of altered cancer genes of which only O6- methylguanine-methyltransferase (MGMT) methylation is used thus far as a predictive marker in a clinical setting. We investigated the prognostic significance of genetic and epigenetic alterations in glioblastoma patients. Methods. We screened 98 human glioblastoma samples for genetic and epigenetic alterations in 10 genes and chromosomal loci by PCR and multiplex ligation-dependent probe amplification (MLPA). We tested the association between these genetic and epigenetic alterations and glioblastoma patient survival. Subsequently, we developed a 2-gene survival predictor. Results. Multivariate analyses revealed that mutations in isocitrate dehydrogenase 1 (IDH1), promoter methylation of MGMT, irradiation dosage, and Karnofsky Performance Status (KFS) were independent prognostic factors. A 2-gene predictor for glioblastoma survival was generated. Based on the genetic and epigenetic status of IDH1 and MGMT, glioblastoma patients were stratified into 3 clinically different genotypes: glioblastoma patients with IDH1 mt/ MGMTmet had the longest survival, followed by patients with IDH1 mt/MGMTunmet or IDH1wt/MGMTmet, and patients with IDH1wt/ MGMTunmet had the shortest survival. This 2-gene predictor was an independent prognostic factor and performed significantly better in predicting survival than either IDH1 mutations or MGMT methylation alone. The predictor was validated in 3 external datasets. Discussion. The combination of IDH1 mutations and MGMT methylation outperforms either IDH1 mutations or MGMT methylation alone in predicting survival of glioblastoma patients. This information will help to increase our understanding of glioblastoma biology, and it may be helpful for baseline comparisons in future clinical trials.

Despite similar morphological aspects, anaplastic oligodendroglial tumors (AOTs) form a heterogeneous clinical subgroup of gliomas. The chromosome arms 1p/19q codeletion has been shown to be a relevant biomarker in AOTs and to be perfectly exclusive from EGFR amplification in gliomas. To identify new genomic regions associated with prognosis, 60 AOTs from the EORTC trial 26951 were analyzed retrospectively using BAC-array-based comparative genomic hybridization. The data were processed using a binary tree method. Thirty-three BACs with prognostic value were identified distinguishing four genomic subgroups of AOTs with different prognosis (p < 0.0001). Type I tumors (25%) were characterized by: (1) an EGFR amplification, (2) a poor prognosis, (3) a higher rate of necrosis, and (4) an older age of patients. Type II tumors (21.7%) had: (1) loss of prognostic BACs located on 1p tightly associated with 19q deletion, (2) a longer survival, (3) an oligodendroglioma phenotype, and (4) a frontal location in brain. Type III AOTs (11.7%) exhibited: (1) a deletion of prognostic BACs located on 21q, and (2) a short survival. Finally, type IV tumors (41.7%) had different genomic patterns and prognosis than type I, II and III AOTs. Multivariate analysis showed that genomic type provides additional prognostic data to clinical, imaging and pathological features. Similar results were obtained in the cohort of 45 centrally reviewed-validated cases of AOTs. Whole genome analysis appears useful to screen the numerous genomic abnormalities observed in AOTs and to propose new biomarkers particularly in the non-1p/19q codeleted AOTs.