Detailed longitudinal sampling of glioma stem cells in situ reveals Chr7 gain and Chr10 loss as repeated events in primary tumor formation and recurrence.

Intratumoral heterogeneity at the genetic, epigenetic, transcriptomic, and morphologic levels is a commonly observed phenomenon in many aggressive cancer types. Clonal evolution during tumor formation and in response to therapeutic intervention can be predicted utilizing reverse engineering approaches on detailed genomic snapshots of heterogeneous patient tumor samples. In this study, we developed an extensive dataset for a GBM case via the generation of polyclonal and monoclonal glioma stem cell lines from initial diagnosis, and from multiple sections of distant tumor locations of the deceased patient's brain following tumor recurrence.

A Core Regulatory Circuit in Glioblastoma Stem Cells Links MAPK Activation to a Transcriptional Program of Neural Stem Cell Identity.

Glioblastoma, the most common primary malignant brain tumor, harbors a small population of tumor initiating cells (glioblastoma stem cells) that have many properties similar to neural stem cells. To investigate common regulatory networks in both neural and glioblastoma stem cells, we subjected both cell types to in-vitro differentiation conditions and measured global gene-expression changes using gene expression microarrays. Analysis of enriched transcription factor DNA-binding sites in the promoters of differentially expressed genes was used to reconstruct regulatory networks involved in differentiation.

Identification of molecular pathways facilitating glioma cell invasion in situ.

Gliomas are mostly incurable secondary to their diffuse infiltrative nature. Thus, specific therapeutic targeting of invasive glioma cells is an attractive concept. As cells exit the tumor mass and infiltrate brain parenchyma, they closely interact with a changing micro-environmental landscape that sustains tumor cell invasion.

Micro-environment causes reversible changes in DNA methylation and mRNA expression profiles in patient-derived glioma stem cells.

In vitro and in vivo models are widely used in cancer research. Characterizing the similarities and differences between a patient's tumor and corresponding in vitro and in vivo models is important for understanding the potential clinical relevance of experimental data generated with these models. Towards this aim, we analyzed the genomic aberrations, DNA methylation and transcriptome profiles of five parental tumors and their matched in vitro isolated glioma stem cell (GSC) lines and xenografts generated from these same GSCs using high-resolution platforms.

Age-specific signatures of glioblastoma at the genomic, genetic, and epigenetic levels.

Age is a powerful predictor of survival in glioblastoma multiforme (GBM) yet the biological basis for the difference in clinical outcome is mostly unknown. Discovering genes and pathways that would explain age-specific survival difference could generate opportunities for novel therapeutics for GBM. Here we have integrated gene expression, exon expression, microRNA expression, copy number alteration, SNP, whole exome sequence, and DNA methylation data sets of a cohort of GBM patients in The Cancer Genome Atlas (TCGA) project to discover age-specific signatures at the transcriptional, genetic, and epigenetic levels and validated our findings on the REMBRANDT data set.