SLUG Directs the Precursor State of Human Brain Tumor Stem Cells.

In glioblastoma (GBM), brain tumor stem cells (BTSCs) encompass heterogenous populations of multipotent, self-renewing, and tumorigenic cells, which have been proposed to be at the root of therapeutic resistance and recurrence. While the functional significance of BTSC heterogeneity remains to be fully determined, we previously distinguished relatively quiescent stem-like precursor state from the more aggressive progenitor-like precursor state. In the present study, we hypothesized that progenitor-like BTSCs arise from stem-like precursors through a mesenchymal transition and drive post-treatment recurrence. We first demonstrate that progenitor-like BTSCs display a more mesenchymal transcriptomic profile. Moreover, we show that both mesenchymal GBMs and progenitor-like BTSCs are characterized by over-activated STAT3/EMT pathways and that SLUG is the primary epithelial to mesenchymal transition (EMT) transcription factor directly regulated by STAT3 in BTSCs. SLUG overexpression in BTSCs enhances invasiveness, promotes inflammation, and shortens survival. Importantly, SLUG overexpression in a quiescent stem-like BTSC line enhances tumorigenesis. Finally, we report that recurrence is associated with SLUG-induced transcriptional changes in both BTSCs and GBM patient samples. Collectively, our findings show that a STAT3-driven precursor state transition, mediated by SLUG, may prime BTSCs to initiate more aggressive mesenchymal recurrence. Targeting the STAT3/SLUG pathway may maintain BTSCs in a quiescent stem-like precursor state, delaying recurrence and improving survival in GBM.

Comprehensive genomic profiling of glioblastoma tumors, BTICs, and xenografts reveals stability and adaptation to growth environments.

Glioblastoma multiforme (GBM) is the most deadly brain tumor, and currently lacks effective treatment options. Brain tumor-initiating cells (BTICs) and orthotopic xenografts are widely used in investigating GBM biology and new therapies for this aggressive disease. However, the genomic characteristics and molecular resemblance of these models to GBM tumors remain undetermined. We used massively parallel sequencing technology to decode the genomes and transcriptomes of BTICs and xenografts and their matched tumors in order to delineate the potential impacts of the distinct growth environments. Using data generated from whole-genome sequencing of 201 samples and RNA sequencing of 118 samples, we show that BTICs and xenografts resemble their parental tumor at the genomic level but differ at the mRNA expression and epigenomic levels, likely due to the different growth environment for each sample type. These findings suggest that a comprehensive genomic understanding of in vitro and in vivo GBM model systems is crucial for interpreting data from drug screens, and can help control for biases introduced by cell-culture conditions and the microenvironment in mouse models. We also found that lack of MGMT expression in pretreated GBM is linked to hypermutation, which in turn contributes to increased genomic heterogeneity and requires new strategies for GBM treatment.