Identification of Molecular Alterations in Medulloblastoma
Medulloblastoma is the most common brain neoplasm in children. It represents a complex genetic disease and remains poorly understood.
In order to provide unprecedented improvement in molecular classification and identification of novel therapeutic targets, the investigators are applying two genome-wide methods—high-resolution digital karyotyping, and serial analysis of gene expression (SAGE)—to simultaneously evaluate both genomic aberrations and gene expression alterations in medulloblastoma samples.
Genomic DNAs from 15 medulloblastoma cell lines, 10 xenografts, and 45 tumors have been extracted, and 30 more are being collected from collaborators. Three cell lines and nine primary tumors representing classic, large cell, and desmoplastic medulloblastoma cell subtypes, with greater than 95% purity of tumor cells, have been identified and used for digital karyotyping. Six of the libraries have been submitted and sequenced. Gene amplifications, LOH, and homozygous deletions, including some of the previously known genomic abnormalities, are revealed from the libraries. Six more libraries are being generated and the data analysis software is being updated. In addition, from the 12 samples used for digital karyotyping, six tumors have been SAGEd and the data are available from CGAP.
The multitude of gene expression changes observed by SAGE can be connected to specific genomic alterations, and the altered regions observed by digital karyotyping can be rapidly assayed for gene expression differences by SAGE to identify potential genes of interest.
The investigators will further validate the identified genetic changes by real time PCR and FISH on a series of pathologically variable clinical tissues. The correlations between the commonality of the genetic alterations and tumor responsiveness to therapies, tendency to spread, and patient survival will be further investigated. These studies will permit subgrouping of medulloblastoma with particular clusters of genomic and transcriptional targets and offer the opportunity to improve prognostic determination and development of new therapies.