Project description:Background: Meningiomas account for about 27% of primary brain tumors, making them one of the most common brain tumor. They are most common in people between the ages of 40 and 70 and are more common in women than in men. Most meningiomas (90%) are categorized as benign tumors, with the remaining 10% being atypical or malignant. Multiple classifications exist today, but the most commonly used is the World Health Organization’s (WHO) which classifies meningiomas into three histological grades: grade I (benign), grade II (atypical), and grade III (anaplastic) in accordance with the clinical prognosis. Most of these subtypes behave similarly, however anaplastics are the most aggressive. The ability to distinguish benign from atypical and anaplastic tumors is important because of its impact on treatment decisions. A molecular based classification system has the likelihood of being a better prognostic indicator and is useful for identifying alterations in pathways and networks that drive tumor progression and growth. The information obtained can potentially be translated into more effective and less toxic targeted therapies. We tested a method for genome wide expression profiling of formalin-fixed, paraffin-embedded tissues. We applied the method to the analysis of the clinical outcome of meningioma tumor. Materials and Methods: The training set consisted of tissue samples from 63 patients who were consecutively treated with surgery for meningioma between 1990 and 2005. For each patient data on clinical outcomes and formalin-fixed, paraffin-embedded blocks of tumor were available. The validation set included tissue samples from 189 patients with meningioma who consecutively underwent surgery between 1992 and 2006. We used a custom 60-mer amino modified oligo- array, containing 912 probes, a lot of which specific for genes commonly altered in cancer. Functional annotation was performed by means of gene set enrichment analysis (GSEA, www. broad.mit.edu/gsea/). Survival analyses were performed with the use of the log-rank test and Cox regression modeling. All analyses were performed with the use of GenePattern. Results: We investigated whether gene-expression profiles of meningioma tumors were associated with the clinical outcome. Using a standard leaveone- out cross-validation procedure, we found the meningioma signature to be significantly correlated with survival (P = 0.0001). The survival correlated signature contained 219 genes and was tested in the validation set. Conclusion: These results support the validity of the survival signature and highlight the potential role of tumoral meningioma tissue in predicting the outcome for patients with meningioma tumors.

Project description:Glioblastoma multiforme is the most common and most aggressive type of primary brain tumor. The brain-infiltrative character of glioblastoma makes complete surgical removal of the tumor impossible and neither radiation nor current chemotherapy provide cure. Recent evidence shows that glioblastoma multiforme consists of heterogeneous cell populations which differ in tumor-forming potential. Enriched tumor-initiating capacity has been linked to poorly differentiated glioblastoma cells sharing features with neural stem cells. Thus, these cells are important targets for new therapeutic strategies. We aim to identify novel targets controlling maintenance and differentiation in glioblastoma-initiating cells through high throughput screening. To this end, we utilized libraries of small chemical compounds and small interference RNAs in combination with automated imaging and data analysis. Patient-derived glioblastoma cells were expanded and characterized using neural stem cell conditions. In culture, the cells showed low differentiation but expression of neural stem cell markers such as Nestin and Sox2. Upon intracranial injection into SCID mice these cells gave rise to tumors displaying the hallmarks of the human disease. Differentiation of glioblastoma-initiating cells (for example elicited through bone morphogenetic protein, BMP) was associated with strong morphological changes. Hence, cellular morphology, as well as markers specific for differentiation or death were used as screen readout. Lentiviral RNA interference-based screening yielded several gene knockdowns leading to ‘forced’ differentiation of glioblastoma-initiating cells. For example, knockdown of TRRAP (transformation/transcription domain associated protein) led to strongly increased differentiation and loss of proliferative and self-renewing capacity in these cells. TRRAP is an adapter protein implicated in oncogenic transformation through c-MYC transcription activation, also participating in chromatin remodeling and DNA repair. Glioblastoma-initiating cells with reduced TRRAP displayed increased apoptosis upon treatment with the genotoxic agent temozolomide. In vivo, Trapp knockdown cells were not able to give rise to glioblastoma upon transplantation into the brain of SCID mice. Together, these findings support a crucial role for TRRAP in maintenance and tumorigenicity of glioblastoma-initiating cells and might offer future therapeutic options. Two treatments compared to control: two different shRNA sequences for TRRAP were compared to a control shRNA sequence in their effects on global transcription in brain tumor initiating cells

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Meningioma initiating cells (MICs) derived from primary tumors

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