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Integrated molecular genetic profiling of pediatric-high grade gliomas reveals key differences with adult disease

GSE19578 Homo sapiens Genome variation profiling by SNP array; Expression profiling by array 209 samples Submitted 2010/06/16 Platform GPL570Platform GPL3720Platform GPL3718
Summary
Purpose: To define copy number alterations and gene expression signatures underlying pediatric high-grade glioma (HGG). Patients and Methods: We conducted a high-resolution analysis of genomic imbalances in 78 de novo pediatric HGG, including 7 diffuse intrinsic pontine gliomas, and 10 HGG cases arising in children who received cranial irradiation for a previous cancer, using Affymetrix 500K GeneChips. Gene expression signatures for 53 tumors were analyzed with Affymetrix U133v2 arrays. Results were compared with publicly available data from adult tumors. Results: Pediatric and adult glioblastoma were clearly distinguished by frequent gain of chromosome 1q (30% vs 9%) and lower frequency of chromosome 7 gain (13% vs 74%), respectively. The most common focal amplifications also differed, with PDGFRA and EGFR predominant in childhood and adult populations respectively. These common alterations in pediatric HGG were detected at higher frequency in irradiation-induced tumors, suggesting that these are initiating events in childhood gliomagenesis. CDKN2A was the most common tumor suppressor gene targeted by homozygous deletion in pediatric HGG. No IDH1 hotspot mutations were found in pediatric tumors, highlighting molecular differences in pathogenesis between childhood HGG and adult secondary glioblastoma. Integrated copy number and gene expression data indicated that deregulated PDGFRA signaling plays a major role in pediatric HGG. Conclusions: Integrated molecular profiling showed substantial differences in the molecular features underlying pediatric and adult HGG, indicating that findings in adult tumors cannot be simply extrapolated to younger patients. PDGFRA may be a useful target for pediatric HGG including diffuse pontine gliomas. Keywords: disease state analysis
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Also filed as BioProject PRJNA122349. Searching any of these in the dataset finder brings you back here.

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