title: Application of bacterial artificial chromosome array-based comparative genomic hybridization and spectral karyotyping to the analysis of glioblastoma multiforme.
abstract: Identification of genetic losses and gains is valuable in analysis of brain tumors. Locus-by-locus analyses have revealed correlations between prognosis and response to chemotherapy and loss or gain of specific genes and loci. These approaches are labor intensive and do not provide a global view of the genetic changes within the tumor cells. Bacterial artificial chromosome (BAC) arrays, which cover the genome with an average resolution of less than 1 MbP, allow defining the sum total of these genetic changes in a single comparative genomic hybridization (CGH) experiment. These changes are directly overlaid on the human genome sequence, thus providing the extent of the amplification or deletion, reflected by a megabase position, and gene content of the abnormal region. Although this array-based CGH approach (CGHa) seems to detect the extent of the genetic changes in tumors reliably, it has not been robustly tested. We compared genetic changes in four newly derived, early-passage glioma cell lines, using spectral karyotyping (SKY) and CGHa. Chromosome changes seen in cell lines under SKY analysis were also detected with CGHa. In addition, CGHa detected cryptic genetic gains and losses and resolved the nature of subtle marker chromosomes that could not be resolved with SKY, thus providing distinct advantages over previous technologies. There was remarkable general concordance between the CGHa results comparing the cell lines to the original tumor, except that the magnitude of the changes seen in the tumor sample was generally suppressed compared with the cell lines, a consequence of normal cells contaminating the tumor sample. CGHa revealed changes in cell lines that were not present in the original tumors and vice versa, even when analyzed at the earliest passage possible, which highlights the adaptation of the cells to in vitro culture. CGHa proved to be highly accurate and efficient for identifying genetic changes in tumor cells. This approach can accurately identify subtle, novel genetic abnormalities in tumors directly linked to the human genome sequence. CGHa far surpasses the resolution and information provided by conventional metaphase CGH, without relying on in vitro culture of tumors for metaphase spreads.
authors.affiliation: Department of Cancer Genetics, Roswell Park Cancer Institute, Elm and Carlton Streets, Buffalo, NY 14263 USA. John.Cowell@RoswellPark.org
authors.forename: John K
authors.initials: JK
authors.lastname: Cowell
authors.forename: Sei-Ichi
authors.initials: S
authors.lastname: Matsui
authors.forename: Yong D
authors.initials: YD
authors.lastname: Wang
authors.forename: Jeffrey
authors.initials: J
authors.lastname: LaDuca
authors.forename: Jeffrey
authors.initials: J
authors.lastname: Conroy
authors.forename: Devin
authors.initials: D
authors.lastname: McQuaid
authors.forename: Norma J
authors.initials: NJ
authors.lastname: Nowak
mesh_terms: D001932:Brain Neoplasms / Q000235:genetics*; D045744:Cell Line, Tumor; D022202:Chromosomes, Artificial, Bacterial; D005909:Glioblastoma / Q000235:genetics*; D006801:Humans; D017403:In Situ Hybridization / Q000379:methods*; D007621:Karyotyping