bims-malgli Biomed News
on Biology of malignant gliomas
Issue of 2021‒02‒28
ten papers selected by
Oltea Sampetrean
Keio University

  1. Glia. 2021 Feb 27.
      Gliomas are the most common primary intrinsic brain tumors occurring in adults. Of all malignant gliomas, glioblastoma (GBM) is considered the deadliest tumor type due to diffuse brain invasion, immune evasion, cellular, and molecular heterogeneity, and resistance to treatments resulting in high rates of recurrence. An extensive understanding of the genomic and microenvironmental landscape of gliomas gathered over the past decade has renewed interest in pursuing novel therapeutics, including immune checkpoint inhibitors, glioma-associated macrophage/microglia (GAMs) modulators, and others. In light of this, predictive animal models that closely recreate the conditions and findings found in human gliomas will serve an increasingly important role in identifying new, effective therapeutic strategies. Although numerous syngeneic, xenograft, and transgenic rodent models have been developed, few include the full complement of pathobiological features found in human tumors, and therefore few accurately predict bench-to-bedside success. This review provides an update on how genetically engineered rodent models based on the replication-competent avian-like sarcoma (RCAS) virus/tumor virus receptor-A (tv-a) system have been used to recapitulate key elements of human gliomas in an immunologically intact host microenvironment and highlights new approaches using this model system as a predictive tool for advancing translational glioma research.
    Keywords:  RCAS/tv-a; animal modeling; genetically engineered; glioblastoma; high-grade glioma; immunocompetent; patient-derived xenograft; preclinical testing; tumor microenvironment
  2. Acta Neuropathol Commun. 2021 Feb 22. 9(1): 29
      Glioblastoma (GBM) is the most lethal primary brain tumor characterized by significant cellular heterogeneity, namely tumor cells, including GBM stem-like cells (GSCs) and differentiated GBM cells (DGCs), and non-tumor cells such as endothelial cells, vascular pericytes, macrophages, and other types of immune cells. GSCs are essential to drive tumor progression, whereas the biological roles of DGCs are largely unknown. In this study, we focused on the roles of DGCs in the tumor microenvironment. To this end, we extracted DGC-specific signature genes from transcriptomic profiles of matched pairs of in vitro GSC and DGC models. By evaluating the DGC signature using single cell data, we confirmed the presence of cell subpopulations emulated by in vitro culture models within a primary tumor. The DGC signature was correlated with the mesenchymal subtype and a poor prognosis in large GBM cohorts such as The Cancer Genome Atlas and Ivy Glioblastoma Atlas Project. In silico signaling pathway analysis suggested a role of DGCs in macrophage infiltration. Consistent with in silico findings, in vitro DGC models promoted macrophage migration. In vivo, coimplantation of DGCs and GSCs reduced the survival of tumor xenograft-bearing mice and increased macrophage infiltration into tumor tissue compared with transplantation of GSCs alone. DGCs exhibited a significant increase in YAP/TAZ/TEAD activity compared with GSCs. CCN1, a transcriptional target of YAP/TAZ, was selected from the DGC signature as a candidate secreted protein involved in macrophage recruitment. In fact, CCN1 was secreted abundantly from DGCs, but not GSCs. DGCs promoted macrophage migration in vitro and macrophage infiltration into tumor tissue in vivo through secretion of CCN1. Collectively, these results demonstrate that DGCs contribute to GSC-dependent tumor progression by shaping a mesenchymal microenvironment via CCN1-mediated macrophage infiltration. This study provides new insight into the complex GBM microenvironment consisting of heterogeneous cells.
    Keywords:  CCN1; Differentiated glioblastoma cell; Glioblastoma; Glioblastoma stem cell; Glioma; Macrophage; Mesenchymal subtype; Microenvironment; TEAD; YAP/TAZ
  3. Cell Stem Cell. 2021 Feb 19. pii: S1934-5909(21)00016-3. [Epub ahead of print]
      Point mutations within the histone H3.3 are frequent in aggressive childhood brain tumors known as pediatric high-grade gliomas (pHGGs). Intriguingly, distinct mutations arise in discrete anatomical regions: H3.3-G34R within the forebrain and H3.3-K27M preferentially within the hindbrain. The reasons for this contrasting etiology are unknown. By engineering human fetal neural stem cell cultures from distinct brain regions, we demonstrate here that cell-intrinsic regional identity provides differential responsiveness to each mutant that mirrors the origins of pHGGs. Focusing on H3.3-G34R, we find that the oncohistone supports proliferation of forebrain cells while inducing a cytostatic response in the hindbrain. Mechanistically, H3.3-G34R does not impose widespread transcriptional or epigenetic changes but instead impairs recruitment of ZMYND11, a transcriptional repressor of highly expressed genes. We therefore propose that H3.3-G34R promotes tumorigenesis by focally stabilizing the expression of key progenitor genes, thereby locking initiating forebrain cells into their pre-existing immature state.
    Keywords:  DIPG; ZMYND11; cancer; forebrain; glioblastoma; histone H3.3; neural stem cells; neurodevelopment; pediatric high-grade glioma
  4. Proc Natl Acad Sci U S A. 2021 Mar 02. pii: e2015800118. [Epub ahead of print]118(9):
      Glioblastoma (GBM) is the most lethal primary brain tumor in adults. No treatment provides durable relief for the vast majority of GBM patients. In this study, we've tested a bispecific antibody comprised of single-chain variable fragments (scFvs) against T cell CD3ε and GBM cell interleukin 13 receptor alpha 2 (IL13Rα2). We demonstrate that this bispecific T cell engager (BiTE) (BiTELLON) engages peripheral and tumor-infiltrating lymphocytes harvested from patients' tumors and, in so doing, exerts anti-GBM activity ex vivo. The interaction of BiTELLON with T cells and IL13Rα2-expressing GBM cells stimulates T cell proliferation and the production of proinflammatory cytokines interferon γ (IFNγ) and tumor necrosis factor α (TNFα). We have modified neural stem cells (NSCs) to produce and secrete the BiTELLON (NSCLLON). When injected intracranially in mice with a brain tumor, NSCLLON show tropism for tumor, secrete BiTELLON, and remain viable for over 7 d. When injected directly into the tumor, NSCLLON provide a significant survival benefit to mice bearing various IL13Rα2+ GBMs. Our results support further investigation and development of this therapeutic for clinical translation.
    Keywords:  GBM; bispecific T cell engagers; delivery; immunotherapy; neural stem cells
  5. Cell Stem Cell. 2021 Feb 17. pii: S1934-5909(21)00053-9. [Epub ahead of print]
      H3.3G34R-mutant gliomas are lethal tumors of the cerebral hemispheres with unknown mechanisms of regional specificity and tumorigenicity. We developed a human embryonic stem cell (hESC)-based model of H3.3G34R-mutant glioma that recapitulates the key features of the tumors with cell-type specificity to forebrain interneuronal progenitors but not hindbrain precursors. We show that H3.3G34R, ATRX, and TP53 mutations cooperatively impact alternative RNA splicing events, particularly suppression of intron retention. This leads to increased expression of components of the Notch pathway, notably NOTCH2NL, a human-specific gene family. We also uncover a parallel mechanism of enhanced NOTCH2NL expression via genomic amplification of its locus in some H3.3G34R-mutant tumors. These findings demonstrate a novel mechanism whereby evolutionary pathways that lead to larger brain size in humans are co-opted to drive tumor growth.
    Keywords:  ATRX; H3.3G34R; NOTCH2NL; Pluripotent stem cells; TP53; cancer models; high-grade glioma; hindbrain progenitors; histone-mutant glioma; interneuron progenitors; ventral forebrain
  6. Drug Discov Today. 2021 Feb 18. pii: S1359-6446(21)00074-X. [Epub ahead of print]
      Gliomas are highly lethal forms of cancers occurring in the brain. Delivering the drugs into the brain is a major challenge to the treatment of gliomas because of the highly selectively permeable blood-brain barrier (BBB). Tapping the potential of receptor-mediated drug delivery systems using targeted nanoparticles (NPs) is a sought-after step forward toward successful glioma treatment. Several receptors are the focus of research for application in drug delivery. Low-density lipoprotein receptors (LDLR) are abundantly expressed in both healthy brains and diseased brains with a disrupted BBB. In this review, we discuss the LDLR and the types of NPs that have been used to target the brain via this receptor.
  7. Cancer Discov. 2021 Feb 26.
      In glioma, tumor-infiltrating cytotoxic T cells expressed the inhibitory NK-cell receptor CD161.
  8. Neurooncol Adv. 2021 Jan-Dec;3(1):3(1): vdab004
      Background: Combined whole-exome sequencing (WES) and somatic copy number alteration (SCNA) information can separate isocitrate dehydrogenase (IDH)1/2-wildtype glioblastoma into two prognostic molecular subtypes, which cannot be distinguished by epigenetic or clinical features. The potential for radiographic features to discriminate between these molecular subtypes has yet to be established.Methods: Radiologic features (n = 35 340) were extracted from 46 multisequence, pre-operative magnetic resonance imaging (MRI) scans of IDH1/2-wildtype glioblastoma patients from The Cancer Imaging Archive (TCIA), all of whom have corresponding WES/SCNA data. We developed a novel feature selection method that leverages the structure of extracted MRI features to mitigate the dimensionality challenge posed by the disparity between a large number of features and the limited patients in our cohort. Six traditional machine learning classifiers were trained to distinguish molecular subtypes using our feature selection method, which was compared to least absolute shrinkage and selection operator (LASSO) feature selection, recursive feature elimination, and variance thresholding.
    Results: We were able to classify glioblastomas into two prognostic subgroups with a cross-validated area under the curve score of 0.80 (±0.03) using ridge logistic regression on the 15-dimensional principle component analysis (PCA) embedding of the features selected by our novel feature selection method. An interrogation of the selected features suggested that features describing contours in the T2 signal abnormality region on the T2-weighted fluid-attenuated inversion recovery (FLAIR) MRI sequence may best distinguish these two groups from one another.
    Conclusions: We successfully trained a machine learning model that allows for relevant targeted feature extraction from standard MRI to accurately predict molecularly-defined risk-stratifying IDH1/2-wildtype glioblastoma patient groups.
    Keywords:  MRI; biomarkers; copy number alterations; glioblastoma; radiogenomics
  9. Sci Rep. 2021 Feb 26. 11(1): 4749
      High-grade pediatric brain tumors exhibit the highest cancer mortality rates in children. While conventional MRI has been widely adopted for examining pediatric high-grade brain tumors clinically, accurate neuroimaging detection and differentiation of tumor histopathology for improved diagnosis, surgical planning, and treatment evaluation, remains an unmet need in their clinical management. We employed a novel Diffusion Histology Imaging (DHI) approach employing diffusion basis spectrum imaging (DBSI) derived metrics as the input classifiers for deep neural network analysis. DHI aims to detect, differentiate, and quantify heterogeneous areas in pediatric high-grade brain tumors, which include normal white matter (WM), densely cellular tumor, less densely cellular tumor, infiltrating edge, necrosis, and hemorrhage. Distinct diffusion metric combination would thus indicate the unique distributions of each distinct tumor histology features. DHI, by incorporating DBSI metrics and the deep neural network algorithm, classified pediatric tumor histology with an overall accuracy of 85.8%. Receiver operating analysis (ROC) analysis suggested DHI's great capability in distinguishing individual tumor histology with AUC values (95% CI) of 0.984 (0.982-0.986), 0.960 (0.956-0.963), 0.991 (0.990-0.993), 0.950 (0.944-0.956), 0.977 (0.973-0.981) and 0.976 (0.972-0.979) for normal WM, densely cellular tumor, less densely cellular tumor, infiltrating edge, necrosis and hemorrhage, respectively. Our results suggest that DBSI-DNN, or DHI, accurately characterized and classified multiple tumor histologic features in pediatric high-grade brain tumors. If these results could be further validated in patients, the novel DHI might emerge as a favorable alternative to the current neuroimaging techniques to better guide biopsy and resection as well as monitor therapeutic response in patients with high-grade brain tumors.