Sunday April 19, 2015   
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Development of Glioblastoma Cancer Stem Cell Inhibitor

Led by Santosh Kesari, MD/PhD at the University of California, San Diego

The genetic heterogeneity in GBM is thought to foster the selective expansion and survival of tumor cells under treatment thereby enabling recurrence. Mutations identified by large-scale sequencing of GBM do not occur in all tumors but vary between patients, thus causing intertumoral heterogeneity. Mutations further occur in mosaic patterns within individual tumors, leading to intratumoral heterogeneity. Highly malignant subpopulations (SPs) isolated from GBM exhibit phenotypic differences and heightened therapy resistance when compared to cells from the same tumors. These studies combined suggest that multiple SPs coexist within a single GBM each carrying a defined set of genetic mutations, which endows them with a specific phenotype and variable capacity to survive standard therapeutic intervention. Treatment advances will require an enhanced understanding of the complex cellular and genetic landscape caused by this intertumoral and intratumoral genetic heterogeneity. To study heterogeneity, we use our novel algorithm to infer the frequency and mutational profiles of SPs within single tumors from GBM exomes available from TCGA. We compare the SP characteristics between patients and determine those SP patterns which correlate with poor outcome. To support TCGA studies, we will sequence exomes of 10 patient-matched primary and recurrent GBMs obtained from UCSF surgeries and analyze their SP composition using our algorithm. To characterize the functional consequences of SP heterogeneity, we identify markers from exomes to isolate SPs from the surgical specimen by fluorescent activated cell sorting. Profiling of gene expression and signaling pathway activation data will be compared with responses to standard therapies if individual SPs. Functional mutation analyses in cell based and in vivo assays in mice will then define critical points of disruption in therapy resistant SPs. Identifying the mutation activated signaling pathways and determining those that convey resistance to certain SPs will have profound implications for the design of efficacious personalized therapy regiments

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