TMOD-04. A COMPREHENSIVE GENOMIC LANDSCAPE OF GLIOMA SPHEROID CULTURES RECAPITULATES THE HETEROGENEITY OF GLIOBLASTOMA AND IDENTIFIES DNA METHYLATION PREDICTORS OF RADIOTHERAPY RESPONSE

Abstract

Glioma sphere-forming cells (GSCs) are important in glioblastoma (GBM) initiation, maintenance, and treatment resistance. We performed whole exome and transcriptome sequencing, DNA methylation profiling, DNA copy number determination, and functional characterization of 43 GSCs and matching tumors. Comparative analyses revealed that GSCs recapitulate the molecular landscape of GBM and provide a unique means for discovering the inter- and intra-tumor heterogeneity of GBM. We performed clonogenic assays to explore the relationship between methylation status and radiation response in twelve IDH wild type GSCs irradiated with 2-, 4-, and 6-Gy ionizing radiation. The survival fraction at 4Gy and 6Gy (SF4 and SF6, respectively) were used to dichotomize GSCs as either radiation-sensitive or resistant. DNA CpG methylomes of the GSCs were profiled using Infinium 450K methylation beadchip arrays. We observed that 304,458 out of 465,844 methylation probes (65.4%) showed increased methylation in radiation-resistant relative to radiation-sensitive GSCs (Fisher's Exact Test, p < 1e-15). Using GSEA, we observed that fifteen of sixteen oxidative stress genes were methylated in radiation-resistant GSCs (p-value=0.019), suggesting an association between radiation-resistance and reactive oxygen species metabolism (ROS). To validate our finding, we derived a methylation signature differentiating the two GSC radiation response groups and used this to classify TCGA cases that received radiotherapy into a responder and non-responder group. We found that survival was significantly different between the two groups (median survival 84 vs. 61 weeks; HR 1.64 adjusting for patient age, p-value<0.008), suggesting that the methylation signature predicts clinical response to radiation treatment. This study identified a novel predictor of radiation response and confirms that the genomic landscape of GSCs can be used to determine clinical and functional properties of GBM.

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