ABSTRACT
Glioblastomas are malignant tumors of the central nervous system hallmarked by subclonal diversity and dynamic adaptation amid developmental hierarchies. The source of dynamic reorganization within the spatial context of these tumors remains elusive. Here, we characterized glioblastomas by spatially resolved transcriptomics, metabolomics, and proteomics. By deciphering regionally shared transcriptional programs across patients, we infer that glioblastoma is organized by spatial segregation of lineage states and adapts to inflammatory and/or metabolic stimuli, reminiscent of the reactive transformation in mature astrocytes. Integration of metabolic imaging and imaging mass cytometry uncovered locoregional tumor-host interdependence, resulting in spatially exclusive adaptive transcriptional programs. Inferring copy-number alterations emphasizes a spatially cohesive organization of subclones associated with reactive transcriptional programs, confirming that environmental stress gives rise to selection pressure. A model of glioblastoma stem cells implanted into human and rodent neocortical tissue mimicking various environments confirmed that transcriptional states originate from dynamic adaptation to various environments.
Subject(s)
Brain Neoplasms , Glioblastoma , Brain Neoplasms/pathology , Glioblastoma/pathology , Humans , Metabolomics/methodsABSTRACT
Despite recent advances in cancer immunotherapy, certain tumor types, such as Glioblastomas, are highly resistant due to their tumor microenvironment disabling the anti-tumor immune response. Here we show, by applying an in-silico multidimensional model integrating spatially resolved and single-cell gene expression data of 45,615 immune cells from 12 tumor samples, that a subset of Interleukin-10-releasing HMOX1+ myeloid cells, spatially localizing to mesenchymal-like tumor regions, drive T-cell exhaustion and thus contribute to the immunosuppressive tumor microenvironment. These findings are validated using a human ex-vivo neocortical glioblastoma model inoculated with patient derived peripheral T-cells to simulate the immune compartment. This model recapitulates the dysfunctional transformation of tumor infiltrating T-cells. Inhibition of the JAK/STAT pathway rescues T-cell functionality both in our model and in-vivo, providing further evidence of IL-10 release being an important driving force of tumor immune escape. Our results thus show that integrative modelling of single cell and spatial transcriptomics data is a valuable tool to interrogate the tumor immune microenvironment and might contribute to the development of successful immunotherapies.
Subject(s)
Brain Neoplasms/immunology , Glioblastoma/immunology , Interleukin-10/metabolism , Myeloid Cells/metabolism , T-Lymphocytes/immunology , Adult , Aged , Brain Neoplasms/drug therapy , Brain Neoplasms/pathology , Cell Communication/immunology , Cell Line, Tumor , Female , Glioblastoma/drug therapy , Glioblastoma/pathology , Healthy Volunteers , Heme Oxygenase-1/metabolism , Humans , Immunotherapy/methods , Janus Kinase Inhibitors/pharmacology , Janus Kinase Inhibitors/therapeutic use , Janus Kinases/antagonists & inhibitors , Janus Kinases/metabolism , Male , Middle Aged , Neocortex/cytology , Neocortex/immunology , Neocortex/pathology , Primary Cell Culture , RNA-Seq , STAT Transcription Factors/metabolism , Signal Transduction/drug effects , Signal Transduction/immunology , Single-Cell Analysis , T-Lymphocytes/drug effects , T-Lymphocytes/metabolism , Tissue Culture Techniques , Tumor Escape , Tumor Microenvironment/immunologyABSTRACT
BACKGROUND: Glioblastoma cells assemble to a syncytial communicating network based on tumor microtubes (TMs) as ultra-long membrane protrusions. The relationship between network architecture and transcriptional profile remains poorly investigated. Drugs that interfere with this syncytial connectivity such as meclofenamate (MFA) may be highly attractive for glioblastoma therapy. METHODS: In a human neocortical slice model using glioblastoma cell populations of different transcriptional signatures, three-dimensional tumor networks were reconstructed, and TM-based intercellular connectivity was mapped on the basis of two-photon imaging data. MFA was used to modulate morphological and functional connectivity; downstream effects of MFA treatment were investigated by RNA sequencing and fluorescence-activated cell sorting (FACS) analysis. RESULTS: TM-based network morphology strongly differed between the transcriptional cellular subtypes of glioblastoma and was dependent on axon guidance molecule expression. MFA revealed both a functional and morphological demolishment of glioblastoma network architectures which was reflected by a reduction of TM-mediated intercellular cytosolic traffic as well as a breakdown of TM length. RNA sequencing confirmed a downregulation of NCAM and axon guidance molecule signaling upon MFA treatment. Loss of glioblastoma communicating networks was accompanied by a failure in the upregulation of genes that are required for DNA repair in response to temozolomide (TMZ) treatment and culminated in profound treatment response to TMZ-mediated toxicity. CONCLUSION: The capacity of TM formation reflects transcriptional cellular heterogeneity. MFA effectively demolishes functional and morphological TM-based syncytial network architectures. These findings might pave the way to a clinical implementation of MFA as a TM-targeted therapeutic approach.
