Novel amplifications in pediatric medulloblastoma identified by genome-wide copy number profiling.

Nord H, Pfeifer S, Nilsson P, Sandgren J, Popova S, Strömberg B, Alafuzoff I, Nistér M, Díaz de Ståhl T

J. Neurooncol. 107 (1) 37-49 [2012-03-00; online 2011-10-08]

Medulloblastoma (MB) is a WHO grade IV, invasive embryonal CNS tumor that mainly affects children. The aggressiveness and response to therapy can vary considerably between cases, and despite treatment, ~30% of patients die within 2 years from diagnosis. Furthermore, the majority of survivors suffer long-term side-effects due to severe management modalities. Several distinct morphological features have been associated with differences in biological behavior, but improved molecular-based criteria that better reflect the underlying tumor biology are in great demand. In this study, we profiled a series of 25 MB with a 32K BAC array covering 99% of the current assembly of the human genome for the identification of genetic copy number alterations possibly important in MB. Previously known aberrations as well as several novel focally amplified loci could be identified. As expected, the most frequently observed alteration was the combination of 17p loss and 17q gain, which was detected in both high- and standard-risk patients. We also defined minimal overlapping regions of aberrations, including 16 regions of gain and 18 regions of loss in various chromosomes. A few noteworthy narrow amplified loci were identified on autosomes 1 (38.89-41.97 and 84.89-90.76 Mb), 3 (27.64-28.20 and 35.80-43.50 Mb), and 8 (119.66-139.79 Mb), aberrations that were verified with an alternative platform (Illumina 610Q chips). Gene expression levels were also established for these samples using Affymetrix U133Plus2.0 arrays. Several interesting genes encompassed within the amplified regions and presenting with transcript upregulation were identified. These data contribute to the characterization of this malignant childhood brain tumor and confirm its genetic heterogeneity.

NGI Uppsala (SNP&SEQ Technology Platform)

National Genomics Infrastructure

PubMed 21979893

DOI 10.1007/s11060-011-0716-0

Crossref 10.1007/s11060-011-0716-0

Publications 9.5.0