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.