Mutational profiling of kinases in glioblastoma

Background: Glioblastoma is a highly malignant brain tumor for which no cure is available. To identify new therapeutic targets, we performed a mutation analysis of kinase genes in glioblastoma.Methods: Database mining and a literature search identified 76 kinases that have been found to be mutated at least twice in multiple cancer types before. Among those we selected 34 kinase genes for mutation analysis. We also included IDH1, IDH2, PTEN, TP53 and NRAS, genes that are known to be mutated at considerable frequencies in glioblastoma. In total, 174 exons of 39 genes in 113 glioblastoma samples from 109 patients and 16 high-grade glioma (HGG) cell lines were sequenced. Results: Our mutation analysis led to the identification of 148 non-synonymous somatic mutations, of which 25 have not been reported before in glioblastoma. Somatic mutations were found in TP53, PTEN, IDH1, PIK3CA, EGFR, BRAF, EPHA3, NRAS, TGFBR2, FLT3 and RPS6KC1. Mapping the mutated genes into known signaling pathways revealed that the large majority of them plays a central role in the PI3K-AKT pathway. Conclusions: The knowledge that at least 50% of glioblastoma tumors display mutational activation of the PI3K-AKT pathway should offer new opportunities for the rational development of therapeutic approaches for glioblastomas. However, due to the development of resistance mechanisms, kinase inhibition studies targeting the PI3K-AKT pathway for relapsing glioblastoma have mostly failed thus far. Other therapies should be investigated, targeting early events in gliomagenesis that involve both kinases and non-kinases

The combination of IDH1 mutations and MGMT methylation status predicts survival in glioblastoma better than either IDH1 or MGMT alone

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