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PLoS One. 2015 May 7;10(5):e0124178. doi: 10.1371/journal.pone.0124178. eCollection 2015.

Identification of variants in primary and recurrent glioblastoma using a cancer-specific gene panel and whole exome sequencing.

Author information

1
Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, USA.
2
University Hospital Translational Laboratory, University Hospitals Case Medical Center, Cleveland, Ohio, USA.
3
University Hospital Translational Laboratory, University Hospitals Case Medical Center, Cleveland, Ohio, USA; Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio, USA; Department of Pathology, Case Western Reserve University, Cleveland, Ohio, USA.
4
Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio, USA.

Abstract

Glioblastoma (GBM) is an aggressive, malignant brain tumor typically resulting in death of the patient within one year following diagnosis; and those who survive beyond this point usually present with tumor recurrence within two years (5-year survival is 5%). The genetic heterogeneity of GBM has made the molecular characterization of these tumors an area of great interest and has led to identification of molecular subtypes in GBM. The availability of sequencing platforms that are both fast and economical can further the adoption of tumor sequencing in the clinical environment, potentially leading to identification of clinically actionable genetic targets. In this pilot study, comprised of triplet samples of normal blood, primary tumor, and recurrent tumor samples from three patients; we compared the ability of Illumina whole exome sequencing (ExomeSeq) and the Ion AmpliSeq Comprehensive Cancer Panel (CCP) to identify somatic variants in patient-paired primary and recurrent tumor samples. Thirteen genes were found to harbor variants, the majority of which were exclusive to the ExomeSeq data. Surprisingly, only two variants were identified by both platforms and they were located within the PTCH1 and NF1 genes. Although preliminary in nature, this work highlights major differences in variant identification in data generated from the two platforms. Additional studies with larger samples sizes are needed to further explore the differences between these technologies and to enhance our understanding of the clinical utility of panel based platforms in genomic profiling of brain tumors.

PMID:
25950952
PMCID:
PMC4423782
DOI:
10.1371/journal.pone.0124178
[Indexed for MEDLINE]
Free PMC Article

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