bims-malgli Biomed News
on Biology of malignant gliomas
Issue of 2025–07–13
six papers selected by
Oltea Sampetrean, Keio University



  1. JCI Insight. 2025 Jul 08. pii: e187684. [Epub ahead of print]10(13):
      Glioblastoma (GBM) is a lethal brain tumor containing a subpopulation of GBM stem cells (GSCs) that interaction with surrounding cells, including infiltrating tumor-associated macrophages and microglia (TAMs). While GSCs and TAMs are in close proximity and likely interact to coordinate tumor growth, a limited number of mechanisms have been identified that support their communication. Here, we identified glycoprotein NMB (GPNMB) as a key factor mediating a unique bidirectional interaction between GSCs and TAMs in GBM. Specifically, GSCs educated macrophages and microglia to preferentially express GPNMB in the GBM tumor microenvironment. As a result, TAM-secreted GPNMB interacted with its receptor CD44 on GSCs to promote their glycolytic and self-renewal abilities via activating the PYK2/RSK2 signaling axis. Disrupting GPNMB-mediated GSC-TAM interplay suppressed tumor progression and self-renewal in GBM mouse models. Our study found a protumor function of GPNMB-mediated GSC-TAM bidirectional communication and supports GPNMB as a promising therapeutic target for GBM.
    Keywords:  Brain cancer; Immunology; Oncology
    DOI:  https://doi.org/10.1172/jci.insight.187684
  2. Proc Natl Acad Sci U S A. 2025 Jul 15. 122(28): e2500004122
      Glioma is the most common primary malignant brain tumor and preoperative genetic profiling is essential for the management of glioma patients. Our study focused on tumor regions segmentation and predicting the World Health Organization (WHO) grade, isocitrate dehydrogenase (IDH) mutation, and 1p/19q codeletion status using deep learning models on preoperative MRI. To achieve accurate tumor segmentation, we developed an optimal mass transport (OMT) approach to transform irregular MRI brain images into tensors. In addition, we proposed an algebraic preclassification (APC) model utilizing multimode OMT tensor singular value decomposition (SVD) to estimate preclassification probabilities. The fully automated deep learning model named OMT-APC was used for multitask classification. Our study incorporated preoperative brain MRI data from 3,565 glioma patients across 16 datasets spanning Asia, Europe, and America. Among these, 2,551 patients from 5 datasets were used for training and internal validation. In comparison, 1,014 patients from 11 datasets, including 242 patients from The Cancer Genome Atlas (TCGA), were used as independent external test. The OMT segmentation model achieved mean lesion-wise Dice scores of 0.880. The OMT-APC model was evaluated on the TCGA dataset, achieving accuracies of 0.855, 0.917, and 0.809, with AUC scores of 0.845, 0.908, and 0.769 for WHO grade, IDH mutation, and 1p/19q codeletion, respectively, which outperformed the four radiologists in all tasks. These results highlighted the effectiveness of our OMT and tensor SVD-based methods in brain tumor genetic profiling, suggesting promising applications for algebraic and geometric methods in medical image analysis.
    Keywords:  OMT; SVD; deep learning; glioma
    DOI:  https://doi.org/10.1073/pnas.2500004122
  3. bioRxiv. 2025 Jul 03. pii: 2025.07.02.662811. [Epub ahead of print]
      Brain tumors, in particular glioblastoma multiforme (GBM), are among the most aggressive and difficult to treat human neoplasms. Even with combined surgery, radiation and chemotherapy, the 5-year survival rate for GBM is only ∼7%. Thus, new treatment approaches are needed. We previously found that the fatty acid metabolism enzyme "very long-chain acyl-CoA synthetase 3" (ACSVL3) is overproduced in human glioma tissue and in glioblastoma cell lines such as U87MG cells. These cells exhibited malignant growth properties in culture and were tumorigenic in nude mice. When either knockdown or knockout strategies were used to deplete U87MG cells of ACSVL3, they adopted a more normal growth rate and produced significantly fewer, slower growing tumors in mice. An inhibitor of ACSVL3, if identified, could prove to be a valuable pharmacotherapeutic agent in GBM. Therefore, we sought to identify small molecule compounds that decrease or block the enzyme activity of ACSVL3, as measured by the formation of stearoyl-CoA from the 18-carbon saturated fatty acid stearic acid, a preferred substrate for ACSVL3. We approached this in two ways. First, we tested several compounds that were previously shown to inhibit the activity of a structurally and functionally related enzyme, ACSVL1. Several compounds tested showed inhibition of stearoyl-CoA formation in U87MG cells when added to an in vitro enzyme assay. These included drugs triflupromazine, phenazopyridine, chlorpromazine, emodin, and perphenazine which are approved for treating other conditions. Also inhibitory to stearoyl-CoA production were several compounds from a ChemBridge Corporation library designated CB2, CB5, CB6 and CB 16.2. One caveat regarding interpretation of these results is that in addition to ACSVL3, all cells including U87MG contain other acyl-CoA synthetases capable of using stearic acid as substrate. Therefore, we also measured stearoyl-CoA synthetase activity in ACSVL3-deficient U87MG cells (U87-KO). If a drug or compound is an ACSVL3 inhibitor, it should decrease total conversion of stearate to stearoyl-CoA more in U87MG than in U87-KO cells. By this criterion, most of the tested compounds showed some ACSVL3-specific inhibition. At the screening concentration of 80μM drug, CB5 and CB16.2 showed the greatest potency to inhibit ACSVL3 enzyme activity; at 10 μM, CB5 still showed significant inhibition but CB16.2 did not. We conclude that these compounds are worthy of further investigation as potential therapeutic agents in GBM, but additional drugs that have greater specificity and are effective at significantly lower concentrations must also be identified. Therefore, our second strategy was to develop a high-throughput library screening assay. For this, we took advantage of the fatty acid transport capability of some ACSVL family members. ACSVL1, when heterologously expressed in COS-1 cells, promotes cellular uptake of the fluorescent fatty acid analog C 1 -BODIPY-C 12 ; in contrast, overexpressed ACSVL3 does not. We used a domain-swapping strategy to replace the N-terminal 210 amino acids of ACSVL3 with the N-terminal 100 amino acids of ACSVL1, producing ACSVL1/3. Unlike ACSVL3, ACSVL1/3 robustly promoted C 1 -BODIPY-C 12 uptake while retaining the catalytically active C-terminus of ACSVL3. Most of the drugs and compounds that decreased stearoyl-CoA synthetase inhibition also inhibited C 1 -BODIPY-C 12 uptake in a concentration-dependent manner. Catalytically defective ACSVL1/3 mutants lost their ability to promote C 1 -BODIPY-C 12 uptake. Thus, we conclude that chimeric ACSVL1/3 gained the fatty acid transport function of ACSVL1 while retaining the catalytic properties of ACSVL3. A pilot screening study of >1280 drugs from an approved drug library and >880 compounds from a library of drugs predicted to cross the blood-brain barrier detected more than 50 molecules that lowered C 1 -BODIPY-C 12 by more than 3 standard deviations. Although secondary screening will likely exclude many or all of these, our findings support the notion that we have developed a viable method for detecting potential ACSVL3 inhibitors. Further characterization may reveal candidate pharmacologic agents for treatment of GBM and other cancers.
    DOI:  https://doi.org/10.1101/2025.07.02.662811
  4. Front Immunol. 2025 ;16 1601656
      Glioma is the most common primary malignant brain tumor, which faces great challenges in clinical treatment due to its high invasiveness and resistance to existing treatments. In recent years, the zebrafish model has gradually become an important tool for glioma research due to its advantages such as easy genetic manipulation, strong optical transparency, and suitability for high-throughput imaging and drug screening. This article systematically reviews the three main strategies for zebrafish glioma modeling - chemical mutagenesis, genetic engineering and xenotransplantation, and describes their research applications in tumorigenesis, invasion process and treatment response. At the same time, this article deeply analyzes the limitations of the zebrafish model in terms of temperature differences, delayed development of the blood-brain barrier and immature immune system, and introduces the cutting-edge progress in recent years in the fields of CRISPR-mediated immune regulation, construction of high-temperature resistant strains and development of humanized models. Through a comprehensive review of current research applications, key challenges and future development directions, this article emphasizes the potential value of the zebrafish model as an important supplement to the mammalian model in exploring the immune mechanism of glioma and developing innovative treatment strategies.
    Keywords:  gene editing; glioma; tumor microenvironment; xenografting; zebrafish
    DOI:  https://doi.org/10.3389/fimmu.2025.1601656
  5. Neuro Oncol. 2025 Jul 08. pii: noaf160. [Epub ahead of print]
       BACKGROUND: Despite extensive research efforts, glioblastoma (GBM) remains a deadly disease with poor prognosis. Although previous studies have identified various cell states within GBM tumors, the molecular mechanism underlying adaptive GBM cell plasticity induced by conventional therapy remains unclear.
    METHODS: We used fluorescent reporters for proneural (PN) and mesenchymal (MES) subtypes to monitor GBM cell plasticity in real-time across multiple patient-derived cell lines. This approach revealed cells that concurrently expressed both proneural and mesenchymal markers. To investigate this unique hybrid population, we implemented a comprehensive methodological approach encompassing bulk and single-cell RNA sequencing, single-cell ChIP sequencing, nuclear proteomics, high-resolution imaging, orthotopic mouse models, clinical dataset analysis, and pharmacological and genetic techniques. This multifaceted strategy allowed us to gain functional and molecular insights into this distinct cellular population.
    RESULTS: We showed that these hybrid cells are increased by conventional therapies, and are resistant to these therapies. At the molecular level, hybrid cells display significant alterations in chromatin structure and nuclear protein composition, elevated transcriptional activity, Myc activation, and improved transport between the nucleus and cytoplasm. Genetic and pharmaceutical inhibition of the nuclear import/export shuttling machinery, increased in hybrid cells, effectively suppressed adaptive GBM cell plasticity and hybrid identity, thereby enhancing the sensitivity of GBM cells to therapies.
    CONCLUSION: Our results indicate that GBM hybrid cells play a crucial role in chemoradiation resistance. The nuclear transport machinery presents a potential therapeutic target for hybrid cells, offering a way to counteract the typical resistance to treatment observed in GBM.
    Keywords:  Glioblastoma; cell plasticity; hybrid; nuclear transport; resistance mechanisms
    DOI:  https://doi.org/10.1093/neuonc/noaf160