Filters
Organism
Technology
Platform
GSE11859
Mus musculus
27 Downloadable Samples
Description
Origins of the brain tumor, medulloblastoma, from stem cells or restricted pro-genitor cells are unclear. To investigate this, we activated oncogenic Hedgehog signaling in multipotent and lineage-restricted CNS progenitors. We observed that normal unipo-tent cerebellar granule neuron precursors (CGNP) derive from hGFAP+ and Olig2+ rhombic lip progenitors. Hedgehog activation in a spectrum of early and late stage CNS progenitors generated similar medulloblastomas, but not other brain cancers, indicating that acquisition of CGNP identity is essential for tumorigenesis. We show in human and mouse medulloblastoma that cells expressing the glia-associated markers Gfap and Olig2 are neoplastic and that they retain features of embryonic-type granule lineage progenitors. Thus, oncogenic Hedgehog signaling promotes medulloblastoma from lineage-restricted granule cell progenitors.
Publication Title
Acquisition of granule neuron precursor identity is a critical determinant of progenitor cell competence to form Shh-induced medulloblastoma.
Alternate Accession IDs
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 1 Downloadable Sample
Description
Gene expression profiling using microarray has been limited to profiling of differentially expressed genes at comparison setting since probesets for different genes have different sensitivities. We overcome this limitation by using a very large number of varied microarray datasets as a common reference, so that statistical attributes of each probeset, such as dynamic range or a threshold between low and high expression can be reliably discovered through meta-analysis. This strategy is implemented in web-based platform named Gene Expression Commons (http://gexc.stanford.edu/ ) with datasets of 39 distinct highly purified mouse hematopoietic stem/progenitor/functional cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, any scientist can explore gene expression of any gene, search by expression pattern of interest, submit their own microarray datasets, and design their own working models.
Publication Title
Gene Expression Commons: an open platform for absolute gene expression profiling.
Alternate Accession IDs
Sample Metadata Fields
Sex, Age
View Samples