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Neuro Oncol 2000 2(3):164-173; DOI:10.1215/15228517-2-3-164
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Duke University Press

Molecular Genetics

Comparative genetic patterns of glioblastoma multiforme: Potential diagnostic tool for tumor classification

Rodney N. Wiltshire, B.K. Ahmed Rasheed, Henry S. Friedman, Allan H. Friedman and Sandra H. Bigner1

Departments of Pathology (R.N.W., B.K.A.R., H.S.F., S.H.B.), Surgery (H.S.F., A.H.F.), and Pediatrics (H.S.F.), Duke University, Durham, NC 27710

1 Address correspondence and reprint requests to Sandra H. Bigner, Duke University Medical Center, Department of Pathology, PO Box 3712, Durham, NC 27710.

Abstract

Cytogenetic and molecular genetic studies of glioblastoma multiforme (GBM) have shown that the most frequent alterations are gains of chromosome 7, losses of 9p loci and chromosome 10, and gene amplification, primarily of the epidermal growth factor receptor (EGFR) gene. Although this profile is potentially useful in distinguishing GBM from other tumor types, the techniques used tend to be labor intensive, and some can detect only gains or losses of genetic loci. Comparative genomic hybridization (CGH) is a powerful technique capable of identifying both gains and losses of DNA sequences. The present study compares the CGH evaluation of 22 GBM with classic cytogenetics, loss of heterozygosity by allelotyping, and gene amplification by Southern blot analysis to determine the reliability of CGH in the genetic characterization of GBM. The CGH and karyotypic data were consistent in showing gain of chromosome 7 accompanied by a loss of chromosome 10 as the most frequent abnormality, followed by a loss of 9p in 17 of 22 GBM cases. Loss of heterozygosity of chromosomes 10 (19/22) and 9p (9/22) loci confirmed the underrepresentation by CGH. Genomic amplifications were observed by CGH in 5 of the 10 cases where gene amplification was detected by Southern blot analysis. The data show that CGH is equally reliable, compared with the more established genetic methods, for recognizing the prominent genetic alterations associated with GBM and support its use as a plausible adjunct to glioma classification.




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