Dataset Information

The genetic landscape of anaplastic astrocytoma.

ABSTRACT: Anaplastic astrocytoma WHO grade III (A3) is a lethal brain tumor that often occurs in middle aged patients. Clinically, it is challenging to distinguish A3 from glioblastoma multiforme (GBM) WHO grade IV. To reveal the genetic landscape of this tumor type, we sequenced the exome of a cohort of A3s (n=16). For comparison and to illuminate the genomic landscape of other glioma subtypes, we also included in our study diffuse astrocytoma WHO grade II (A2, n=7), oligoastrocytoma WHO grade II (OA2, n=2), anaplastic oligoastrocytoma WHO grade III (OA3, n=4), and GBM (n=28). Exome sequencing of A3s identified frequent mutations in IDH1 (75%, 12/16), ATRX (63%, 10/16), and TP53 (82%, 13/16). In contrast, the majority of GBMs (75%, 21/28) did not contain IDH1 or ATRX mutations, and displayed a distinct spectrum of mutations. Finally, our study also identified novel genes that were not previously linked to this tumor type. In particular, we found mutations in Notch pathway genes (NOTCH1, NOTCH2, NOTCH4, NOTCH2NL), including a recurrent NOTCH1-A465Tmutation, in 31% (5/16) of A3s. This study suggests genetic signatures will be useful for the classification of gliomas.

SUBMITTER: Killela PJ

PROVIDER: S-EPMC4039223 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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The genetic landscape of anaplastic astrocytoma.

Killela Patrick J PJ Pirozzi Christopher J CJ Reitman Zachary J ZJ Jones Sian S Rasheed B Ahmed BA Lipp Eric E Friedman Henry H Friedman Allan H AH He Yiping Y McLendon Roger E RE Bigner Darell D DD Yan Hai H

Oncotarget 20140301 6

Anaplastic astrocytoma WHO grade III (A3) is a lethal brain tumor that often occurs in middle aged patients. Clinically, it is challenging to distinguish A3 from glioblastoma multiforme (GBM) WHO grade IV. To reveal the genetic landscape of this tumor type, we sequenced the exome of a cohort of A3s (n=16). For comparison and to illuminate the genomic landscape of other glioma subtypes, we also included in our study diffuse astrocytoma WHO grade II (A2, n=7), oligoastrocytoma WHO grade II (OA2, n ...[more]

PMID: 24140581

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Project description:Pleomorphic xanthoastrocytoma (PXA) is an astrocytic neoplasm that is typically well circumscribed and can have a relatively favorable prognosis. Tumor progression to anaplastic PXA (WHO grade III), however, is associated with a more aggressive biologic behavior and worse prognosis. The factors that drive anaplastic progression are largely unknown. We performed comprehensive genomic profiling on a set of 23 PXAs from 19 patients, including 15 with anaplastic PXA. Four patients had tumor tissue from multiple recurrences, including two with anaplastic progression. We find that PXAs are genetically defined by the combination of CDKN2A biallelic inactivation and RAF alterations that were present in all 19 cases, most commonly as CDKN2A homozygous deletion and BRAF p.V600E mutation but also occasionally BRAF or RAF1 fusions or other rearrangements. The third most commonly altered gene in anaplastic PXA was TERT, with 47% (7/15) harboring TERT alterations, either gene amplification (n = 2) or promoter hotspot mutation (n = 5). In tumor pairs analyzed before and after anaplastic progression, two had increased copy number alterations and one had TERT promoter mutation at recurrence. Less commonly altered genes included TP53, BCOR, BCORL1, ARID1A, ATRX, PTEN, and BCL6. All PXA in this cohort were IDH and histone H3 wildtype, and did not contain alterations in EGFR. Genetic profiling performed on six regions from the same tumor identified intratumoral genomic heterogeneity, likely reflecting clonal evolution during tumor progression. Overall, anaplastic PXA is characterized by the combination of CDKN2A biallelic inactivation and oncogenic RAF kinase signaling as well as a relatively small number of additional genetic alterations, with the most common being TERT amplification or promoter mutation. These data define a distinct molecular profile for PXA and suggest additional genetic alterations, including TERT, may be associated with anaplastic progression.

Project description:Anaplastic astrocytoma (AA) and its more aggressive counterpart, glioblastoma multiforme (GBM), are the most common intrinsic brain tumors in adults and are almost universally fatal. A deeper understanding of the molecular relationship of these tumor types is necessary to derive insights into the diagnosis, prognosis, and treatment of gliomas. Although genomewide profiling of expression levels with microarrays can be used to identify differentially expressed genes between these tumor types, comparative studies so far have resulted in gene lists that show little overlap.To achieve a more accurate and stable list of the differentially expressed genes and pathways between primary GBM and AA, we performed a meta-analysis using publicly available genome-scale mRNA data sets. There were four data sets with sufficiently large sample sizes of both GBMs and AAs, all of which coincidentally used human U133 platforms from Affymetrix, allowing for easier and more precise integration of data. After scoring genes and pathways within each data set, we combined the statistics across studies using the nonparametric rank sum method to identify the features that differentiate GBMs and AAs. We found >900 statistically significant probe sets after correction for multiple testing from the >22,000 tested. We also used the rank sum approach to select >20 significant Biocarta pathways after correction for multiple testing out of >175 pathways examined. The most significant pathway was the hypoxia-inducible factor (HIF) pathway. Our analysis suggests that many of the most statistically significant genes work together in a HIF1A/VEGF-regulated network to increase angiogenesis and invasion in GBM when compared to AA.We have performed a meta-analysis of genome-scale mRNA expression data for 289 human malignant gliomas and have identified a list of >900 probe sets and >20 pathways that are significantly different between GBM and AA. These feature lists could be utilized to aid in diagnosis, prognosis, and grade reduction of high-grade gliomas and to identify genes that were not previously suspected of playing an important role in glioma biology. More generally, this approach suggests that combined analysis of existing data sets can reveal new insights and that the large amount of publicly available cancer data sets should be further utilized in a similar manner.

Dataset Information

The genetic landscape of anaplastic astrocytoma.

Publications

The genetic landscape of anaplastic astrocytoma.

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