bims-malgli Biomed News
on Biology of malignant gliomas
Issue of 2024–04–21
eleven papers selected by
Oltea Sampetrean, Keio University



  1. Neurooncol Adv. 2024 Jan-Dec;6(1):6(1): vdae005
       Background: Non-enhancing (NE) infiltrating tumor cells beyond the contrast-enhancing (CE) bulk of tumor are potential propagators of recurrence after gross total resection of high-grade glioma.
    Methods: We leveraged single-nucleus RNA sequencing on 15 specimens from recurrent high-grade gliomas (n = 5) to compare prospectively identified biopsy specimens acquired from CE and NE regions. Additionally, 24 CE and 22 NE biopsies had immunohistochemical staining to validate RNA findings.
    Results: Tumor cells in NE regions are enriched in neural progenitor cell-like cellular states, while CE regions are enriched in mesenchymal-like states. NE glioma cells have similar proportions of proliferative and putative glioma stem cells relative to CE regions, without significant differences in % Ki-67 staining. Tumor cells in NE regions exhibit upregulation of genes previously associated with lower grade gliomas. Our findings in recurrent GBM paralleled some of the findings in a re-analysis of a dataset from primary GBM. Cell-, gene-, and pathway-level analyses of the tumor microenvironment in the NE region reveal relative downregulation of tumor-mediated neovascularization and cell-mediated immune response, but increased glioma-to-nonpathological cell interactions.
    Conclusions: This comprehensive analysis illustrates differing tumor and nontumor landscapes of CE and NE regions in high-grade gliomas, highlighting the NE region as an area harboring likely initiators of recurrence in a pro-tumor microenvironment and identifying possible targets for future design of NE-specific adjuvant therapy. These findings also support the aggressive approach to resection of tumor-bearing NE regions.
    Keywords:  contrast enhancing; glioblastoma; magnetic resonance imaging; non-enhancing
    DOI:  https://doi.org/10.1093/noajnl/vdae005
  2. Neurooncol Adv. 2024 Jan-Dec;6(1):6(1): vdae012
      Glioblastoma is an aggressive and incurable brain cancer. This cancer establishes both local and systemic immunosuppression that creates a major obstacle to effective immunotherapies. Many studies point to tumor-resident myeloid cells (primarily microglia and macrophages) as key mediators of this immunosuppression. Myeloid cells exhibit a high level of plasticity with respect to their phenotype and are capable of both stimulating and repressing immune responses. How glioblastomas recruit myeloid cells and exploit them to avoid the immune system is an active area of research. Macrophages can acquire an immunosuppressive phenotype as a consequence of exposure to cytokines such as TGFB1 or IL4; in addition, macrophages can acquire an immunosuppressive phenotype as a consequence of the engulfment of apoptotic cells, a process referred to as efferocytosis. There is substantial evidence that glioblastoma cells are able to secrete cytokines and other factors that induce an immunosuppressive phenotype in macrophages and microglia. However, less is known about the contribution of efferocytosis to immunosuppression in glioblastoma. Here I review the literature in this area and discuss the potential of efferocytosis inhibition to improve glioblastoma response to immunotherapy.
    Keywords:  efferocytosis; glioblastoma; glioma; immune; macrophage; phagocytosis
    DOI:  https://doi.org/10.1093/noajnl/vdae012
  3. medRxiv. 2024 Apr 07. pii: 2024.04.05.24305380. [Epub ahead of print]
      Grade IV glioma, formerly known as glioblastoma multiforme (GBM) is the most aggressive and lethal type of brain tumor, and its treatment remains challenging in part due to extensive interpatient heterogeneity in disease driving mechanisms and lack of prognostic and predictive biomarkers. Using mechanistic inference of node-edge relationship (MINER), we have analyzed multiomics profiles from 516 patients and constructed an atlas of causal and mechanistic drivers of interpatient heterogeneity in GBM (gbmMINER). The atlas has delineated how 30 driver mutations act in a combinatorial scheme to causally influence a network of regulators (306 transcription factors and 73 miRNAs) of 179 transcriptional "programs", influencing disease progression in patients across 23 disease states. Through extensive testing on independent patient cohorts, we share evidence that a machine learning model trained on activity profiles of programs within gbmMINER significantly augments risk stratification, identifying patients who are super-responders to standard of care and those that would benefit from 2 nd line treatments. In addition to providing mechanistic hypotheses regarding disease prognosis, the activity of programs containing targets of 2 nd line treatments accurately predicted efficacy of 28 drugs in killing glioma stem-like cells from 43 patients. Our findings demonstrate that interpatient heterogeneity manifests from differential activities of transcriptional programs, providing actionable strategies for mechanistically characterizing GBM from a systems perspective and developing better prognostic and predictive biomarkers for personalized medicine.
    DOI:  https://doi.org/10.1101/2024.04.05.24305380
  4. bioRxiv. 2024 Apr 06. pii: 2024.04.04.588167. [Epub ahead of print]
      Hyaluronic acid (HA), the primary component of brain extracellular matrix, is increasingly used to model neuropathological processes, including glioblastoma (GBM) tumor invasion. While elastic hydrogels based on crosslinked low-molecular-weight (LMW) HA are widely exploited for this purpose and have proven valuable for discovery and screening, brain tissue is both viscoelastic and rich in high-MW (HMW) HA, and it remains unclear how these differences influence invasion. To address this question, hydrogels comprised of either HMW (1.5 MDa) or LMW (60 kDa) HA are introduced, characterized, and applied in GBM invasion studies. Unlike LMW HA hydrogels, HMW HA hydrogels relax stresses quickly, to a similar extent as brain tissue, and to a greater extent than many conventional HA-based scaffolds. GBM cells implanted within HMW HA hydrogels invade much more rapidly than in their LMW HA counterparts and exhibit distinct leader-follower dynamics. Leader cells adopt dendritic morphologies, similar to invasive GBM cells observed in vivo. Transcriptomic, pharmacologic, and imaging studies suggest that leader cells exploit hyaluronidase, an enzyme strongly enriched in human GBMs, to prime a path for followers. This study offers new insight into how HA viscoelastic properties drive invasion and argues for the use of highly stress-relaxing materials to model GBM.
    DOI:  https://doi.org/10.1101/2024.04.04.588167
  5. bioRxiv. 2024 Apr 03. pii: 2024.04.02.587608. [Epub ahead of print]
       Background: Glioblastoma (GBM) has a highly immunosuppressive tumor immune microenvironment (TIME), largely mediated by myeloid-derived suppressor cells (MDSCs). Here, we utilized a retroviral replicating vector (RRV) to deliver Interferon Regulatory Factor 8 (IRF8), a master regulator of type 1 conventional dendritic cell (cDC1) development, in a syngeneic murine GBM model. We hypothesized that RRV-mediated delivery of IRF8 could "reprogram" intratumoral MDSCs into antigen-presenting cells (APCs) and thereby restore T-cell responses.
    Methods: Effects of RRV-IRF8 on survival and tumor growth kinetics were examined in the SB28 murine GBM model. Immunophenotype was analyzed by flow cytometry and gene expression assays. We assayed functional immunosuppression and antigen presentation by ex vivo T-cell-myeloid co-culture.
    Results: Mice with RRV-IRF8 pre-transduced intracerebral tumors had significantly longer survival and slower tumor growth compared to controls. RRV-IRF8 treated tumors exhibited significant enrichment of cDC1s and CD8+ T-cells. Additionally, myeloid cells derived from RRV-IRF8 tumors showed decreased expression of the immunosuppressive markers Arg1 and IDO1 and demonstrated reduced suppression of naïve T-cell proliferation in e x vivo co-culture, compared to controls. Furthermore, DCs from RRV-IRF8 tumors showed increased antigen presentation compared to those from control tumors. In vivo treatment with azidothymidine (AZT), a viral replication inhibitor, showed that IRF8 transduction in both tumor and non-tumor cells is necessary for survival benefit, associated with a reprogrammed, cDC1- and CD8 T-cell-enriched TIME.
    Conclusions: Our results indicate that reprogramming of glioma-infiltrating myeloid cells by in vivo expression of IRF8 may reduce immunosuppression and enhance antigen presentation, achieving improved tumor control.
    Key points: GBM intra-tumoral myeloid cells are proliferative and targets for RRV therapy.Expression of IRF8 significantly improves survival and slows tumor growth in murine GBM. IRF8 expression in MDSCs reduces immunosuppression and enriches cDC1s in vivo .
    Importance of the study: Recent publications have presented conflicting studies regarding the role of IRF8 in GBM. While some studies showed IRF8 as a negative prognostic factor, others demonstrated the conversion of tumor cells into DCs using IRF8. Here, we show that RRV-mediated delivery of IRF8, a clinically relevant modality, allows for transduction of both tumor and immune cells in vivo . We show that a significant survival effect relies heavily on the infection and modulation of both populations, and that even a modest number of reprogrammed intra-tumoral MDSCs can have a substantial impact on the immunological milieu, significantly enriching and activating cytotoxic T-cells. Further, this work reveals intra-tumoral myeloid cells as a target for other RRV-based gene therapies.
    DOI:  https://doi.org/10.1101/2024.04.02.587608
  6. Clin Cancer Res. 2024 Apr 19.
       PURPOSE: Glioblastoma (GBM) patient outcomes remain poor despite multimodality treatment with surgery, radiation, and chemotherapy. There are few immunotherapy options due to the lack of tumor immunogenicity. Several clinical trials have reported promising results with cancer vaccines. To date, studies have used data from a single tumor site to identify targetable antigens, but this approach limits the antigen pool and is antithetical to the heterogeneity of GBM. We have implemented multisector sequencing to increase the pool of neoantigens across the GBM genomic landscape that can be incorporated into personalized peptide vaccines called NeoVax.
    PATIENTS AND METHODS: Here, we report the findings of four subjects enrolled onto the NeoVax clinical trial (NCT0342209).
    RESULTS: Immune reactivity to NeoVax neoantigens was assessed in peripheral blood mononuclear cells (PBMCs) pre- and post-NeoVax for subjects 1-3 using IFNg-ELISPOT assay. A statistically significant increase in IFNg producing T cells at the post-NeoVax time point for several neoantigens was observed. Furthermore, a post-NeoVax tumor biopsy was obtained from subject 3 and, upon evaluation, revealed evidence of infiltrating, clonally expanded T cells.
    CONCLUSIONS: Collectively, our findings suggest NeoVax did stimulate expansion of neoantigen-specific effector T cells and provide encouraging results to aid in the development of future neoantigen vaccine-based clinical trials in patients with GBM. Herein, we demonstrate the feasibility of incorporating multisector sampling in cancer vaccine design and provide information on the clinical applicability of clonality, distribution, and immunogenicity of the neoantigen landscape in GBM patients.
    DOI:  https://doi.org/10.1158/1078-0432.CCR-23-3077
  7. Cancer Cell. 2024 Apr 16. pii: S1535-6108(24)00119-3. [Epub ahead of print]
      Monocyte-derived tumor-associated macrophages (Mo-TAMs) intensively infiltrate diffuse gliomas with remarkable heterogeneity. Using single-cell transcriptomics, we chart a spatially resolved transcriptional landscape of Mo-TAMs across 51 patients with isocitrate dehydrogenase (IDH)-wild-type glioblastomas or IDH-mutant gliomas. We characterize a Mo-TAM subset that is localized to the peri-necrotic niche and skewed by hypoxic niche cues to acquire a hypoxia response signature. Hypoxia-TAM destabilizes endothelial adherens junctions by activating adrenomedullin paracrine signaling, thereby stimulating a hyperpermeable neovasculature that hampers drug delivery in glioblastoma xenografts. Accordingly, genetic ablation or pharmacological blockade of adrenomedullin produced by Hypoxia-TAM restores vascular integrity, improves intratumoral concentration of the anti-tumor agent dabrafenib, and achieves combinatorial therapeutic benefits. Increased proportion of Hypoxia-TAM or adrenomedullin expression is predictive of tumor vessel hyperpermeability and a worse prognosis of glioblastoma. Our findings highlight Mo-TAM diversity and spatial niche-steered Mo-TAM reprogramming in diffuse gliomas and indicate potential therapeutics targeting Hypoxia-TAM to normalize tumor vasculature.
    Keywords:  adrenomedullin; dabrafenib; glioblastoma; glioma; hypoxia; necrosis; single-cell transcriptomics; spatial transcriptomics; tumor-associated macrophages; vasculature normalization
    DOI:  https://doi.org/10.1016/j.ccell.2024.03.013
  8. Cell Death Dis. 2024 Apr 13. 15(4): 262
      Gliomas are among the most fatal tumors, and the available therapeutic options are very limited. Additionally, the blood-brain barrier (BBB) prevents most drugs from entering the brain. We designed and produced a ferritin-based stimuli-sensitive nanocarrier with high biocompatibility and water solubility. It can incorporate high amounts of the potent topoisomerase 1 inhibitor Genz-644282. Here, we show that this nanocarrier, named The-0504, can cross the BBB and specifically deliver the payload to gliomas that express high amounts of the ferritin/transferrin receptor TfR1 (CD71). Intranasal or intravenous administration of The-0504 both reduce tumor growth and improve the survival rate of glioma-bearing mice. However, nose-to-brain administration is a simpler and less invasive route that may spare most of the healthy tissues compared to intravenous injections. For this reason, the data reported here could pave the way towards a new, safe, and direct ferritin-based drug delivery method for brain diseases, especially brain tumors.
    DOI:  https://doi.org/10.1038/s41419-024-06653-2
  9. Nat Commun. 2024 Apr 15. 15(1): 3226
    iMAXT Consortium
      The tumor microenvironment plays a crucial role in determining response to treatment. This involves a series of interconnected changes in the cellular landscape, spatial organization, and extracellular matrix composition. However, assessing these alterations simultaneously is challenging from a spatial perspective, due to the limitations of current high-dimensional imaging techniques and the extent of intratumoral heterogeneity over large lesion areas. In this study, we introduce a spatial proteomic workflow termed Hyperplexed Immunofluorescence Imaging (HIFI) that overcomes these limitations. HIFI allows for the simultaneous analysis of > 45 markers in fragile tissue sections at high magnification, using a cost-effective high-throughput workflow. We integrate HIFI with machine learning feature detection, graph-based network analysis, and cluster-based neighborhood analysis to analyze the microenvironment response to radiation therapy in a preclinical model of glioblastoma, and compare this response to a mouse model of breast-to-brain metastasis. Here we show that glioblastomas undergo extensive spatial reorganization of immune cell populations and structural architecture in response to treatment, while brain metastases show no comparable reorganization. Our integrated spatial analyses reveal highly divergent responses to radiation therapy between brain tumor models, despite equivalent radiotherapy benefit.
    DOI:  https://doi.org/10.1038/s41467-024-47185-9
  10. Cancer Res. 2024 Apr 18.
      Metabolic subtypes of glioblastoma have different prognoses and responses to treatment. Deuterium metabolic imaging with 2H-labeled substrates is a potential approach to stratify patients into metabolic subtypes for targeted treatment. Here, we used 2H magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) measurements of [6,6'-2H2]glucose metabolism to identify metabolic subtypes and their responses to chemoradiotherapy in patient-derived glioblastoma xenografts in vivo. The metabolism of patient-derived cells was first characterized in vitro by measuring the oxygen consumption rate, a marker of mitochondrial TCA cycle activity, as well as the extracellular acidification rate and 2H-labeled lactate production from [6,6'-2H2]glucose, which are markers of glycolytic activity. Two cell lines representative of a glycolytic subtype and two representative of a mitochondrial subtype were identified. 2H MRS and MRSI measurements showed similar concentrations of 2H-labeled glucose from [6,6'-2H2]glucose in all four tumor models when implanted orthotopically in mice. The glycolytic subtypes showed higher concentrations of 2H-labeled lactate than the mitochondrial subtypes and normal-appearing brain tissue, whereas the mitochondrial subtypes showed more glutamate/glutamine labeling, a surrogate for TCA cycle activity, than the glycolytic subtypes and normal-appearing brain tissue. The response of the tumors to chemoradiation could be detected within 24 hours of treatment completion, with the mitochondrial subtypes showing a decrease in both 2H-labeled glutamate/glutamine and lactate concentrations and glycolytic tumors showing a decrease in 2H-labeled lactate concentration. This technique has the potential to be used clinically for treatment selection and early detection of treatment response.
    DOI:  https://doi.org/10.1158/0008-5472.CAN-23-2552
  11. Sci Rep. 2024 04 16. 14(1): 8738
      Brain tumor glioblastoma is a disease that is caused for a child who has abnormal cells in the brain, which is found using MRI "Magnetic Resonance Imaging" brain image using a powerful magnetic field, radio waves, and a computer to produce detailed images of the body's internal structures it is a standard diagnostic tool for a wide range of medical conditions, from detecting brain and spinal cord injuries to identifying tumors and also in evaluating joint problems. This is treatable, and by enabling the factor for happening, the factor for dissolving the dead tissues. If the brain tumor glioblastoma is untreated, the child will go to death; to avoid this, the child has to treat the brain problem using the scan of MRI images. Using the neural network, brain-related difficulties have to be resolved. It is identified to make the diagnosis of glioblastoma. This research deals with the techniques of max rationalizing and min rationalizing images, and the method of boosted division time attribute extraction has been involved in diagnosing glioblastoma. The process of maximum and min rationalization is used to recognize the Brain tumor glioblastoma in the brain images for treatment efficiency. The image segment is created for image recognition. The method of boosted division time attribute extraction is used in image recognition with the help of MRI for image extraction. The proposed boosted division time attribute extraction method helps to recognize the fetal images and find Brain tumor glioblastoma with feasible accuracy using image rationalization against the brain tumor glioblastoma diagnosis. In addition, 45% of adults are affected by the tumor, 40% of children and 5% are in death situations. To reduce this ratio, in this study, the Brain tumor glioblastoma is identified and segmented to recognize the fetal images and find the Brain tumor glioblastoma diagnosis. Then the tumor grades were analyzed using the efficient method for the imaging MRI with the diagnosis result of partially high. The accuracy of the proposed TAE-PIS system is 98.12% which is higher when compared to other methods like Genetic algorithm, Convolution neural network, fuzzy-based minimum and maximum neural network and kernel-based support vector machine respectively. Experimental results show that the proposed method archives rate of 98.12% accuracy with low response time and compared with the Genetic algorithm (GA), Convolutional Neural Network (CNN), fuzzy-based minimum and maximum neural network (Fuzzy min-max NN), and kernel-based support vector machine. Specifically, the proposed method achieves a substantial improvement of 80.82%, 82.13%, 85.61%, and 87.03% compared to GA, CNN, Fuzzy min-max NN, and kernel-based support vector machine, respectively.
    Keywords:  Fetal brain tumor; Glioblastoma; Max rationalizing; Min rationalizing; Segmentation; Time attribute extraction
    DOI:  https://doi.org/10.1038/s41598-024-59111-6