Molecular analysis of ex-vivo CD133+GBM cells revealed a common invasive and angiogenic profile but different proliferative signatures among high grade gliomas

Background: Gliomas are the most common type of primary brain tumours, and in this group glioblastomas (GBMs) are the higher-grade gliomas with fast progression and unfortunate prognosis. Two major aspects of glioma biology that contributes to its awful prognosis are the formation of new blood vessels through the process of angiogenesis and the invasion of glioma cells. Despite of advances, two-year survival for GBM patients with optimal therapy is less than 30%. Even in those patients with low-grade gliomas, that imply a moderately good prognosis, treatment is almost never curative. Recent studies have demonstrated the existence of a small fraction of glioma cells with characteristics of neural stem cells which are able to grow in vitro forming neurospheres and that can be isolated in vivo using surface markers such as CD133. The aim of this study was to define the molecular signature of GBM cells expressing CD133 in comparison with non expressing CD133 cells. This molecular classification could lead to the finding of new potential therapeutic targets for the rationale treatment of high grade GBM. Methods: Eight fresh, primary and non cultured GBMs were used in order to study the gene expression signatures from its CD133 positive and negative populations isolated by FACS-sorting. Dataset was generated with Affymetrix U133 Plus 2 arrays and analysed using the software of the Affymetrix Expression Console. In addition, genomic analysis of these tumours was carried out by CGH arrays, FISH studies and MLPA; Results: Gene expression analysis of CD133+ vs. CD133- cell population from each tumour showed that CD133+ cells presented common characteristics in all glioblastoma samples (up-regulation of genes involved in angiogenesis, permeability and down-regulation of genes implicated in cell assembly, neural cell organization and neurological disorders). Furthermore, unsupervised clustering of gene expression led us to distinguish between two groups of samples: those discriminated by tumour location and, the most importantly, the group discriminated by their proliferative potential; Conclusions: Primary glioblastomas could be sub-classified according to the properties of their CD133+ cells. The molecular characterization of these potential stem cell populations could be critical to find new therapeutic targets and to develop an effective therapy for these tumours with very dismal prognosis.