Transcriptional and Multi-Omic Heterogeneity in Glioblastoma Stem Cells
Glioblastoma Multiforme (GBM) is a disease with terrible prognosis, having a median survival time of ~12-15 months for patients undergoing current treatment regimens, and a 5-year survival rate under 10%. There is strong evidence to suggest the existence of stem like cells, which we term glioma stem cells (GSCs), that are capable of repopulating the tumor after surgery and chemotherapy. Thus, any effective treatment for GBM will likely have to target this population. Evidence of functional heterogeneity of GSCs at the level of the transcriptome and drug response motivates a full characterization of GSCs’ biological variation. In this project, I use multiple -omic data types from both bulk and single cell resolution to explore how multiple biological processes such as transcription and epigenetic regulation play into GSC heterogeneity in therapeutic vulnerabilities. With single cell/nuclei RNA-sequencing, in collaboration with the Pugh and Dirks labs and others, I establish that transcriptional heterogeneity in GSCs and more generally GBM can be decomposed into two major axes of variation: a Developmental/Injury Response transcriptional axis present in both the stem fraction of GBM tumors as well as the tumors themselves, and a stem to astrocyte differentiation gradient present only in the tumor samples. Further functional characterization with CRISPR knockout data reveals that differential functional dependencies between Developmental and Injury Response GSCs largely match their differentially expressed genes, showing that this transcriptional axis of variation translates into functional consequences that could inform development of combination therapies. Following these results, I perform an integrated analysis of genomic, transcriptomic, epigenomic, and miRNA-seq data to obtain a more complete picture of both how this transcriptional axis is regulated as well as what other heterogeneity exists independent of transcription. Here, I find four major axes in multi -omics space: one corresponding to a hypermutation phenotype largely matching one previously characterized for GBM dependent on mismatch repair deficiency and temozolomide treatment, two others corresponding to apparent latent variation in regulation of inflammatory genes, and lastly a multi-omics axis corresponding to the coordinated regulation of the Developmental/Injury Response transcriptional axis by multiple biological layers. Collectively, the results presented in this thesis provide better mechanistic understanding of GSC heterogeneity and open the door to developing novel therapies.
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