Glioblastoma (GBM) exhibits populations of cells that drive tumorigenesis, treatment resistance, and disease progression. Cells with such properties have been described to express specific surface and intracellular markers or exhibit specific functional states, including being slow-cycling or quiescent with the ability to generate proliferative progenies. In GBM, each of these cellular fractions was shown to harbor cardinal features of cancer stem cells (CSCs). In this study, we focus on the comparison of these cells and present evidence of great phenotypic and functional heterogeneity in brain cancer cell populations with stemness properties, especially between slow-cycling cells (SCCs) and cells phenotypically defined based on the expression of markers commonly used to enrich for CSCs. Here, we present an integrative analysis of the heterogeneity present in GBM cancer stem cell populations using a combination of approaches including flow cytometry, bulk RNA sequencing, and single cell transcriptomics completed with functional assays. We demonstrated that SCCs exhibit a diverse range of expression levels of canonical CSC markers. Importantly, the property of being slow-cycling and the expression of these markers were not mutually inclusive. We interrogated a single-cell RNA sequencing dataset and defined a group of cells as SCCs based on the highest score of a specific metabolic signature. Multiple CSC groups were determined based on the highest expression level of CD133, SOX2, PTPRZ1, ITGB8, or CD44. Each group, composed of 22 cells, showed limited cellular overlap, with SCCs representing a unique population with none of the 22 cells being included in the other groups. We also found transcriptomic distinctions between populations, which correlated with clinicopathological features of GBM. Patients with strong SCC signature score were associated with shorter survival and clustered within the mesenchymal molecular subtype. Cellular diversity amongst these populations was also demonstrated functionally, as illustrated by the heterogenous response to the chemotherapeutic agent temozolomide. In conclusion, our study supports the cancer stem cell mosaicism model, with slow-cycling cells representing critical elements harboring key features of disseminating cells.

INTRODUCTION Glioblastoma (GBM) contains cell populations with distinct metabolic requirements, with fast-cycling cells harnessing aerobic glycolysis, and treatment-resistant slow-cycling cells (SCCs) preferentially engaging lipid metabolism. How the different tumor cells interact with immune cells and how this metabolic heterogeneity shapes the immune landscape in GBM has yet to be understood. OBJECTIVES The objectives are to unravel the various molecular signals and metabolic link that underlie the interaction of SCCs with the GBM microenvironment, in particular with the suppressive immune compartment, and to effectively target these interactions for better therapeutics. METHODS Multiple murine glioma cell lines were used to establish metabolic heterogeneity and communications, while various genetic and pharmacological approaches were applied to assess the effect of disrupting the metabolic interplay between SCCs and the immune system. RESULTS We determined that SCCs exhibit distinct metabolic dependencies, involving preferential lipid metabolism supported by enhanced fatty acid uptake. We also found that tumor progression is regulated by the interaction of SCCs with the immune system and established that SCCs recruit immune suppressive M2-like macrophages to the tumor microenvironment, which in turn work against tumor immune rejection by inhibiting T cell anti-tumor activity. The immune microenvironment shaped by SCCs is marked by specific metabolic features enhancing lipid exchange capacities that are exploited by SCCs to support their survival and functions. Importantly, disrupting lipid metabolic exchange sensitized tumors to chemotherapy. CONCLUSION Our results reveal that metabolic interactions between SCCs and tumor-associated macrophages within the GBM microenvironment play a critical role in the development of drug and immune resistant tumors. This study delineates these metabolic communications and assesses the potential therapeutic effect of disrupting these interactions to treat GBM. The insights generated from this project uncover fundamental principles of the emerging connections between the tumor microenvironment, cell metabolism, anti-tumor immunity, and associated therapeutic vulnerabilities.

INTRODUCTION Intratumoral heterogeneity is increasingly recognized as a determinant of therapy resistance and disease recurrence; this is exemplified by glioblastoma (GBM), one of the most lethal malignancies. We recently revealed that GBM contain cell subpopulations with distinct metabolic requirements, with fast-cycling cells (FCCs) harnessing aerobic glycolysis, and treatment-resistant slow-cycling cells (SCCs) preferentially engaging lipid metabolism. How the different tumor cell populations interact with immune cells and how this metabolic heterogeneity shapes the immune landscape in GBM has yet to be understood. OBJECTIVES: The objectives of this study are to understand the mechanisms of communication in the tumor microenvironment, specifically to characterize the metabolic interactions between SCCs (a therapeutically resistant population of cancer cells that drive disease progression and recurrence) and the immune compartment. METHODS The murine glioma cell line KR158 (derived from a Nf1;Trp53 mutant mouse) was used to establish the slow-cycling cell paradigm and metabolic heterogeneity in an immune-competent model of glioma. RESULTS Similar to what we observed in patient-derived specimens, mouse KR158-derived SCCs demonstrate tumorigenicity, treatment resistance and up-regulation of stemness programs and lipid metabolic pathways. We determined that tumor progression is regulated by the interaction of SCCs with the immune system and established that these cells are driving a pro-tumorigenic microenvironment via the recruitment of immune suppressive myeloid cells. Importantly, the immune microenvironment shaped by SCCs is marked by specific metabolic features showing enhanced lipid exchange capacities that we propose are exploited by SCCs to support their survival and functions. CONCLUSION Our study indicates that SCCs play a pivotal role in shifting the GBM milieu toward an immune regulatory phenotype but importantly reveals an unprecedented metabolic cooperation, which represents a novel therapeutic target to antagonize GBM.

INTRODUCTION Glioblastoma is a challenge for neuro-oncologists and current therapies are minimally effective. Standard-of- care treatment is almost inevitably followed by disease recurrence. Adoptive T cell transfer has emerged as a viable therapeutic for brain malignancies. While promising, the efficacy of this approach is often limited by a complex immunosuppressive tumor microenvironment. These complexities mean that more sophisticated T cell products are required. Objectives: The brain tumor microenvironment provides local restraints via metabolic competition suppressing antitumor immunity, specifically inhibiting infiltration and tumoricidal functions of host and adoptively transferred tumor-reactive T cells. The overall goal of this project is to test new treatments to reverse immune dysfunction in cancer through the regulation of T cell metabolic signaling. We propose that modulating the glucose pathway in T cells can potentiate their anti-tumor activity once adoptively transferred. METHODS The glucose metabolic pathway of T cells was modulated via overexpression of glucose transporters. The functionality of metabolically modified T cells was investigated in murine and human models. RESULTS We demonstrated the existence of a competition for glucose between T cells and tumor cells, with tumor cells imposing glucose restriction mediating T cell hyporesponsiveness. Overexpression of glucose transporters such as Glut1 and Glut3 increased T cell glucose utilization and provided a survival/growth advantage and enhanced T cell activation in glucose-restricted conditions. We also established that glucose transporter overexpression improves intratumoral infiltration and expansion of adoptively transferred T cells, resulting in improved survival. CONCLUSION This project integrates fundamental concepts of tumor and immune metabolism in the design of immunotherapy and confirms that immunometabolism represents a viable target for new cancer therapy to treat brain tumors.

Glioblastoma (GBM), the most common primary malignancy of the central nervous system (CNS), is almost universally fatal due to inevitable recurrence despite aggressive therapeutics. Considering the infiltrative nature of GBM, targeting residual cells after surgical tumor resection is challenging. Development of effective novel adjuvant therapies against drivers of disease recurrence is of imperative priority. Anticancer treatments most effectively eliminate rapidly dividing cells but spare dormant or infrequently dividing populations. Multiple studies have reported in numerous cancers the existence of slow-cycling cells (SCCs) that are refractory to therapies. Our laboratory identified SCCs in high-grade glioma, which represents an enriched reservoir of highly infiltrative and treatment-resistant cancer propagating cells known to drive recurrence. An effective approach to specifically eliminate this cell population is urgently required to limit recurrence and improve survival. Importantly, these cells reliably defined a cellular niche characterized by definite potentially immunogenic neoantigens, which can serve as immune targets. Our ultimate goal is to leverage the power of adoptive cellular therapy (ACT) to recognize GBM SCC-derived antigens to achieve robust tumor control through targeting of these critical drivers of recurrence. Our data revealed that dendritic cells electroporated with slow-cycling cell RNA successfully primed T cells to recognize and target glioma treatment resistant cells. These experiments demonstrated that slow cycling cell-specific T cells (SCC-T cells) exhibit enhanced activation when in presence of treatment-resistant tumor cells as shown by increased CD8 differentiation, amplified effector and memory differentiation compared to total tumor RNA-specific T cell and control groups. Additionally, SCC-T cells presented the highest anti-tumor activity, as demonstrated by the greatest decrease of tumor cell proliferation and increase of T cell apoptosis. Together these results demonstrate the efficacy and superiority of SCC-based immunotherapy platform to target treatment-resistant glioblastoma cells.