GE-39 * VALIDATION OF GLIOMA SPHERE-FORMING CELLS AS MODELS OF GLIOBLASTOMA AND IDENTIFICATION OF NOVEL DRIVERS OF TUMORIGENESIS THROUGH COMPREHENSIVE GENOMIC CHARACTERIZATION

Abstract

Glioma sphere-forming cells (GSCs) play important roles in tumor maintenance and chemotherapy and radiation resistance, and thus serve as important models for the development of novel therapies and for understanding tumor biology. We hypothesized that genomic analyses of GSCs in the absence of normal stroma would identify novel somatic alterations not previously reported from whole tumor specimen analyses. We analyzed 42 GSCs, derived at the time of surgical resection, and their matched tumors of origin. Unsupervised consensus clustering by non-negative matrix factorization (CNMF) using whole transcriptome sequencing data identified 5 transcriptional classes. Comparison to published TCGA GBM subtypes using single-sample gene set enrichment analysis (ssGSEA) showed that 9 GSCs perfectly matched with TCGA mesenchymal subtype. The other 4 subgroups of GSCs mapped to proneural and/or classical subtypes, while none of the GSC classes matched with the neural TCGA subtype. Overall, 73% of GSCs matched the TCGA subtype of paried tumor, suggesting transcriptional consistency between GSCs and their parental tumor. A total of 88 candidate gene fusions were also identified in the GSCs, including the previously reported FGFR3-TACC3 and EGFR-SEP14 fusions. DNA copy number analysis indicated recurrent regions of frequent loss or gain, such as EGFR, MYC, and MYCN amplification, and deletion of PTEN and CDKN2A. Whole exome sequencing based analysis identified 3,918 somatic mutations in 22 GSCs. PTEN, TP53, EGFR and 17 additional genes were identified as significantly altered. Our results indicate genomic consistency between GSCs and their tumors of origin, suggesting the suitability of GSCs as a model for preclinical testing. Additional gene fusions and somatic mutations were detected in GSCs suggesting the important role of these cell models in identifying infrequent events only detectable in pure tumor cell populations.