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Accession IconGSE31545

Stem-like glioma-propagating cells contribute to molecular heterogeneity and survival outcome in oligodendroglial tumors

Organism Icon Homo sapiens
Sample Icon 14 Downloadable Samples
Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

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Brain tumors are among the most malignant cancers and can arise from neural stem cells or oligodendrocyte progenitor cells (OPCs). Glioma-propagating cells (GPCs) that have stem-like properties have been derived from tumor variants such as glioblastoma multiforme (GBM) and oligodendroglial tumors, the latter being more chemosensitive with better prognosis. It has been suggested that such differences in chemosensitivity arise from the different profiles of OPCs versus neural stem cells. We thus explored if GPCs derived from these glioma variants can serve as reliable in vitro culture systems for studies. We utilized gene expression analyses, since GBM and oligodendrogliomas can be molecularly classified. Accordingly, we derived a gene signature distinguishing oligodendroglial GPCs from GBM GPCs collated from different studies, which was enriched for the Wnt, Notch and TGF-beta pathways. Using a novel method in glioma biology, the Connectivity Map, we mapped the strength of gene signature association with patient gene expression profiles in 2 independent glioma databases [GSE16011, http://caintegrator-info.nci.nih.gov/rembrandt]. Our gene signature consistently stratified survival in glioma patients. This data would suggest that in vitro low passage GPCs are similarly driven by transcriptomic changes that characterize the favorable outcome of oligodendrogliomas over GBM. Additionally, the gene signature was associated with the 1p/19q co-deletion status, the current clinical indicator of chemosensitivity. Our gene signature detects molecular heterogeneity in oligodendroglioma patients that cannot be accounted for by histology or the 1p/19q status alone, and highlights the limitation of morphology-based histological analyses in tumor classification, consequently impacting on treatment decisions.
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