TMIC-46. TRANSCRIPTIONAL HETEROGENEITY AND MECHANISTIC PATHWAYS OF RECURRENT GLIOBLASTOMA: INSIGHTS FROM A PRE-CLINICAL RECURRENT TUMOR MODEL

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Abstract Despite aggressive therapy combining surgical resection, radiation and chemotherapy, glioblastoma (GBM) almost always recurs. Currently, there is no standard treatment for recurrent GBM, and patient inclusion in clinical trials is based on the genetic and molecular profile of the primary tumor even though the effects of chemoradiation on the transcriptional subtype in matched primary and recurrent GBM remain largely understudied. Paralleling the GLASS consortium, we sought to perform a longitudinal assessment of GBM recurrence after therapy based on molecular subtype with the hypothesis that recurrent tumors exhibit a distinct transcriptional landscape different from treatment-naive tumors. To address this, we utilized primary tumor-derived glioma stem cells (GSCs) representing classical and proneural subtypes. We then undertook in vivo intracranial implantation studies and performed standard concomitant treatment that mimics the Stupp protocol. Upon bulk RNAseq data analyses of untreated (n=21) and recurrent tumors (n=17) we identified that while the molecular subtype of recurrent tumors does not change post therapy, their transcriptional profile is more heterogenous compared to untreated tumors for both subtypes. Hierarchical cluster analyses revealed distinct sub-clusters of recurrent tumors. Common mechanisms of recurrence include upregulation of angiogenesis pathways and PI3k/Akt/mTOR signaling pathways. Interestingly, recurrent tumors exhibit upregulation of genes involved in cellular metabolism and membrane transport/ potential. The source of heterogeneity in recurrent tumors in both subtypes appears to be due to the diversity in expression of gene sets involved in hallmark of cancer pathways such as cell cycle, Notch and Wnt signaling pathways and heterogeneity in oncogenic signatures and cell states resembling fetal or neural cells. Further research into the recurrent tumor microenvironment by spatial multi-omics approaches using this pre-clinical recurrent GBM model will elucidate the linkage between cellular as well as molecular heterogeneity and enable identification of targets that can help drive therapeutic decisions for recurrent GBM patients.