Molecular classification of human gliomas using matrix-based comparative genomic hybridization
| Autor: | Bernhard Radlwimmer, Peter Lichter, Gunnar Wrobel, Guido Reifenberger, Carsten Schwaenen, Stefan Joos, Peter Roerig, Michelle Nessling |
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| Rok vydání: | 2005 |
| Předmět: |
Adult
Male Chromosomes Artificial Bacterial Cancer Research Candidate gene Computational biology Biology Polymerase Chain Reaction Loss of heterozygosity Glioma medicine Chromosomes Human Humans neoplasms Aged Chromosome Aberrations Genetics Genomic Library Bacterial artificial chromosome Brain Neoplasms Genome Human Gene Amplification Chromosome Mapping Nucleic Acid Hybridization DNA Neoplasm Middle Aged Microarray Analysis Molecular diagnostics medicine.disease nervous system diseases Oncology Female DNA microarray Anaplastic astrocytoma Comparative genomic hybridization |
| Zdroj: | International Journal of Cancer. 117:95-103 |
| ISSN: | 1097-0215 0020-7136 |
| DOI: | 10.1002/ijc.21121 |
| Popis: | Gliomas are the most frequent primary brain tumors and comprise a group of morphologically, biologically and clinically heterogeneous neoplasms. The different glioma types are associated with distinct genetic aberrations, which may provide useful information for tumor classification as well as prediction of prognosis and response to therapy. To facilitate the molecular classification of gliomas, we established a genomic microarray that consists of bacterial artificial chromosome (BAC) and P1-derived artificial chromosome (PAC) clones representing tumor suppressor genes, proto-oncogenes and chromosomal regions frequently gained or lost in gliomas. In addition, reference clones distributed evenly throughout the genome in approximately 15 Mbp intervals were spotted on the microarray. These customized microarrays were used for matrix-based comparative genomic hybridization (matrix CGH) analysis of 70 gliomas. Matrix CGH findings were validated by molecular genetic analyses of candidate genes, loss of heterozygosity studies and chromosomal CGH. Our results indicate that matrix CGH allows for the sensitive and specific detection of gene amplifications as well as low-level copy number gains and losses in clinical glioma samples. Furthermore, molecular classification based on matrix CGH data closely paralleled histological classification and was able to distinguish with few exceptions between diffuse astrocytomas and oligodendrogliomas, anaplastic astrocytomas and anaplastic oligodendrogliomas, anaplastic oligodendrogliomas and glioblastomas, as well as primary and secondary glioblastomas. Thus, matrix CGH is a powerful technique that allows for an automated genomic profiling of gliomas and represents a promising new tool for their molecular classification. |
| Databáze: | OpenAIRE |
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