Channing Pooley

Diffusely infiltrating gliomas - including glioblastoma (GBM), isocitrate dehydrogenase (IDH) mutant gliomas, and histone 3 (H3) altered gliomas - are primary brain tumors with an invariably fatal outcome. Despite advances in the understanding of their biology, standard, targeted and immune checkpoint inhibitor immunotherapies have proven ineffective in arresting their inexorable progression and associated morbidity and mortality. Recognizing the unique aspects of the immunogenicity of cancer cells, the last decade has seen the development and evaluation of vaccine-based therapies for the treatment of solid tumors, including gliomas. Here we review the current vaccine strategies for the treatment of GBM, IDH-mutant gliomas and diffuse midline glioma H3 K27M-altered. We discuss potential benefits and challenges of vaccine therapies in these specific patient populations.

Abstract BACKGROUND Glioblastoma (GBM) is an incurable and aggressive brain cancer marked by profound intra-tumoral heterogeneity. Malignant cells exist in four core transcriptional states: stem-like (OPC-like and NPC-like) and more differentiated astrocytic (AC-like) or mesenchymal (MES-like) states. Using spatial transcriptomics, we previously identified a layered tumor structure of these states, with hypoxia emerging as an organizing driver, implicating oxygen availability as a central factor in cell state dynamics. However, how these cellular states interact with each other and with the tumor microenvironment remains incompletely understood. METHODS To uncover state-specific vulnerabilities for reducing GBM cell state diversity, we conducted a small-molecule screen in gliomasphere models using over 1,600 cysteine-reactive covalent inhibitors, assessing their effects on cell states via RNA-seq. We then employed the Sonar metabolic reporter to visualize NAD+ and NADH levels in gliomaspheres. Through experiments with orthotopic xenografts in mice and co-culture with human cortical organoids, we characterized distinct redox profiles across GBM cell states by single-cell and bulk RNA-seq. Spatial single-cell transcriptomics and mass spectrometry imaging (MSI) metabolomics on adjacent sections of frozen patient samples were used to identify preferential metabolic programs in specific cell states. RESULTS Our small-molecule screen identified compounds that promote differentiation and are enriched for NRF2 activation, a master regulator of the antioxidant response. Spatial single-cell transcriptomics and mass spectrometry metabolomics experiments confirmed that MES-like cells exhibit a heightened glycolytic signature, whereas stem-like states preferentially depend on oxidative phosphorylation (OXPHOS) for their energetic needs. Finally, pharmacologic perturbations revealed that mitochondrial and glycolysis inhibition selectively deplete different cell state populations in gliomaspheres. CONCLUSION Our findings provide deeper insight into the metabolic underpinnings of GBM cell states and support the rationale for combinatorial therapies aimed at reducing intratumoral heterogeneity that exploit their divergent dependencies.

BACKGROUND: Cellular heterogeneity is a defining feature of glioblastoma (GBM), shaping tumor progression and therapeutic response. While single-cell profiling resolves this heterogeneity, it remains impractical for large-cohort studies and clinical implementation. Conversely, DNA methylation-based classification is widely used for GBM diagnostics but does not provide cellular resolution. METHODS: We introduce a hierarchical non-negative matrix factorization approach (ITHresolveGBM) to deconvolute bulk DNA methylation profiles, inferring the abundance of glial, immune, and neuronal cells of the microenvironment, and further distinguishing differentiation states of malignant cells. RESULTS: Using ITHresolveGBM, we find that low tumor cell content impairs methylation-based classification, most notably linking the mesenchymal subtype with high immune cell infiltration. By integrating multi-omic single-cell data, we show that epigenetic deconvolution captures a malignant differentiation continuum ranging from stem-like to more differentiated tumors. This continuum aligns prior GBM classification systems and is associated with distinct molecular drivers (eg, PDGFRA, TP53, EGFR) and survival outcomes. CONCLUSIONS: Our framework reconciles DNA methylation- and RNA-based classification systems and provides a blueprint for unifying bulk tumor profiles with single-cell biology, thereby refining molecular stratification and enhancing GBM diagnostics.

Abstract Glioblastoma (GBM) is an incurable and aggressive brain cancer characterized by profound intra- and intertumoral heterogeneity and remarkable cellular plasticity. Single-cell transcriptomic analyses have revealed several major cell states, including NPC-like, OPC-like, GPC-like, AC-like and MES/Hypoxia-like. However, the cis-regulatory networks that govern GBM cell state transitions remain poorly understood. In this study, we performed single-cell chromatin accessibility profiling and multi-omics analysis on 35 GBM IDHwt samples. Firstly, we developed a new scATAC-seq data analysis framework and reconstructed six malignant consensus cis-regulatory element (CRE) modules. Four of these modules were specifically associated with malignant cell states corresponding to the MES/Hypoxia-like, AC-like, OPC-like, and NPC-like identities. Interestingly, cycling cells exhibited broadly open chromatin across all four CRE modules, while GPC-like cells showed accessibility in both the AC-like and OPC-like states, suggesting a role as an intermediate or hybrid regulatory state. Further epigenetic information quantification revealed that NPC-like malignant cells harbor higher regulatory information content compared with other cell states. Master regulator enrichment analysis identified AP-1 transcription factors as key regulators of differentiated (MES/AC-like) malignant state-associated CRE modules, whereas neuronal-development transcription factors were enriched in stem-like (NPC/OPC-like) state-associated modules. Through in vitro gain- and loss-of-function experiments, we screened and validated several transcription factors that modulate malignant cell-state transitions. Additionally, our scATAC-seq-based copy number alteration (CNA) analysis captured hallmark GBM genomic events at high resolution, including EGFR focal amplification, CDKN2A/B deletion, and CDK4 and MDM2 amplifications. Leveraging these CNA profiles, we successfully constructed a high-resolution phylogenetic tree, capturing the clonal architecture and evolutionary trajectory of GBM. By integrating transcriptomic, chromatin accessibility, and genetic CNA data, we elucidated the evolutionary landscape of GBM progression and cellular plasticity. Our findings provide significant insights into the regulatory architecture of GBM and establish a foundational framework for precision therapies targeting distinct cell states. Citation Format: Min Yang, Nicolas L. Gonzalez Castro, Alexander Jucht, Sophia Kovatsis, Channing Pooley, Sydney Dumont, Kevin Johnson, Julie Laffy, Bo Xia, Roel Verhaak, Itay Tirosh, Mario Suva. Dissecting gene regulation of cellular states in glioblastoma using single-cell multi-omics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5919.