IDH1 R132H decreases proliferation of glioma cell lines in vitro and in vivo.

OBJECTIVE: A high percentage of grade II and III gliomas have mutations in the gene encoding isocitrate dehydrogenase (IDH1). This mutation is always a heterozygous point mutation that affects the amino acid arginine at position 132 and results in loss of its native enzymatic activity and gain of alternative enzymatic activity (producing D-2-hydroxyglutarate). The objective of this study was to investigate the cellular effects of R132H mutations in IDH1. METHODS: Functional consequences of IDH1(R132H) mutations were examined among others using fluorescence-activated cell sorting, kinome and expression arrays, biochemical assays, and intracranial injections on 3 different (glioma) cell lines with stable overexpression of IDH1(R132H) . RESULTS: IDH1(R132H) overexpression in established glioma cell lines in vitro resulted in a marked decrease in proliferation, decreased Akt phosphorylation, altered morphology, and a more contact-dependent cell migration. The reduced proliferation is related to accumulation of D-2-hydroxyglutarate that is produced by IDH1(R132H) . Mice injected with IDH1(R132H) U87 cells have prolonged survival compared to mice injected with IDH1(wt) or green fluorescent protein-expressing U87 cells. INTERPRETATION: Our results demonstrate that IDH1(R132H) dominantly reduces aggressiveness of established glioma cell lines in vitro and in vivo. In addition, the IDH1(R132H) -IDH1(wt) heterodimer has higher enzymatic activity than the IDH1(R132H) -IDH1(R132H) homodimer. Our observations in model systems of glioma might lead to a better understanding of the biology of IDH1 mutant gliomas, which are typically low grade and often slow growing.

Isocitrate dehydrogenase-1 mutations: a fundamentally new understanding of diffuse glioma?

The discovery of somatic mutations in the gene encoding isocitrate dehydrogenase-1 (IDH1) in glioblastomas was remarkable because the enzyme was not previously identified with any known oncogenic pathway. IDH1 is mutated in up to 75% of grade II and grade III diffuse gliomas. Apart from acute myeloid leukaemia, other tumour types do not carry IDH1 mutations. Mutations in a homologous gene, IDH2, have also been identified, although they are much rarer. Although TP53 mutations and 1p/19q codeletions are mutually exclusive in gliomas, in both of these genotypes IDH1 mutations are common. IDH1 and IDH2 mutations are early events in the development of gliomas. Moreover, IDH1 and IDH2 mutations are a major prognostic marker for overall and progression-free survival in grade II-IV gliomas. Mutated IDH1 has an altered catalytic activity that results in the accumulation of 2-hydroxyglutarate. Molecularly, IDH1 and IDH2 mutations are heterozygous, affect only a single codon, and rarely occur together. Because IDH1 does not belong to a traditional oncogenic pathway and is specifically and commonly mutated in gliomas, the altered enzymatic activity of IDH1 may provide a fundamentally new understanding of diffuse glioma.

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.

Genetic alterations in glioma.

Gliomas are the most common type of primary brain tumor and have a dismal prognosis. Understanding the genetic alterations that drive glioma formation and progression may help improve patient prognosis by identification of novel treatment targets. Recently, two major studies have performed in-depth mutation analysis of glioblastomas (the most common and aggressive subtype of glioma). This systematic approach revealed three major pathways that are affected in glioblastomas: The receptor tyrosine kinase signaling pathway, the TP53 pathway and the pRB pathway. Apart from frequent mutations in the IDH1/2 gene, much less is known about the causal genetic changes of grade II and III (anaplastic) gliomas. Exceptions include TP53 mutations and fusion genes involving the BRAF gene in astrocytic and pilocytic glioma subtypes, respectively. In this review, we provide an update on all common events involved in the initiation and/or progression across the different subtypes of glioma and provide future directions for research into the genetic changes.

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.

Exon expression arrays as a tool to identify new cancer genes.

BACKGROUND: Identification of genes that are causally implicated in oncogenesis is a major goal in cancer research. An estimated 10-20% of cancer-related gene mutations result in skipping of one or more exons in the encoded transcripts. Here we report on a strategy to screen in a global fashion for such exon-skipping events using PAttern based Correlation (PAC). The PAC algorithm has been used previously to identify differentially expressed splice variants between two predefined subgroups. As genetic changes in cancer are sample specific, we tested the ability of PAC to identify aberrantly expressed exons in single samples. PRINCIPAL FINDINGS: As a proof-of-principle, we tested the PAC strategy on human cancer samples of which the complete coding sequence of eight cancer genes had been screened for mutations. PAC detected all seven exon-skipping mutants among 12 cancer cell lines. PAC also identified exon-skipping mutants in clinical cancer specimens although detection was compromised due to heterogeneous (wild-type) transcript expression. PAC reduced the number of candidate genes/exons for subsequent mutational analysis by two to three orders of magnitude and had a substantial true positive rate. Importantly, of 112 randomly selected outlier exons, sequence analysis identified two novel exon skipping events, two novel base changes and 21 previously reported base changes (SNPs). CONCLUSIONS: The ability of PAC to enrich for mutated transcripts and to identify known and novel genetic changes confirms its suitability as a strategy to identify candidate cancer genes.