Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Glial and myeloid heterogeneity in the brain tumour microenvironment

Nature Reviews Cancer volume 21, pages 786–802 (2021)Cite this article

Subjects

Abstract

Brain cancers carry bleak prognoses, with therapeutic advances helping only a minority of patients over the past decade. The brain tumour microenvironment (TME) is highly immunosuppressive and differs from that of other malignancies as a result of the glial, neural and immune cell populations that constitute it. Until recently, the study of the brain TME was limited by the lack of methods to de-convolute this complex system at the single-cell level. However, novel technical approaches have begun to reveal the immunosuppressive and tumour-promoting properties of distinct glial and myeloid cell populations in the TME, identifying new therapeutic opportunities. Here, we discuss the immune modulatory functions of microglia, monocyte-derived macrophages and astrocytes in brain metastases and glioma, highlighting their disease-associated heterogeneity and drawing from the insights gained by studying these malignancies and other neurological disorders. Lastly, we consider potential approaches for the therapeutic modulation of the brain TME.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Microglia, MDM and astrocyte diversity in brain tumours.
Fig. 2: Mechanisms of cell communication involved in tumour establishment, invasion and immune escape.

Similar content being viewed by others

References

  1. Tawbi, H. A. et al. Combined nivolumab and ipilimumab in melanoma metastatic to the brain. N. Engl. J. Med. 379, 722–730 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Long, G. V. et al. Combination nivolumab and ipilimumab or nivolumab alone in melanoma brain metastases: a multicentre randomised phase 2 study. Lancet Oncol. 19, 672–681 (2018).

    Article  CAS  PubMed  Google Scholar 

  3. Goldberg, S. B. et al. Pembrolizumab for patients with melanoma or non-small-cell lung cancer and untreated brain metastases: early analysis of a non-randomised, open-label, phase 2 trial. Lancet Oncol. 17, 976–983 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Fecci, P. E. et al. Increased regulatory T-cell fraction amidst a diminished CD4 compartment explains cellular immune defects in patients with malignant glioma. Cancer Res. 66, 3294–3302 (2006).

    Article  CAS  PubMed  Google Scholar 

  5. Kwok, D. & Okada, H. T-cell based therapies for overcoming neuroanatomical and immunosuppressive challenges within the glioma microenvironment. J. Neurooncol. 147, 281–295 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Mathewson, N. D. et al. Inhibitory CD161 receptor identified in glioma-infiltrating T cells by single-cell analysis. Cell 184, 1281–1298.e26 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Friebel, E. et al. Single-cell mapping of human brain cancer reveals tumor-specific instruction of tissue-invading leukocytes. Cell 181, 1626–1642.e20 (2020). This paper, published simultaneously with Klemm et al.10, demonstrated that the brain tumour immune microenvironment differs among human IDHwt glioma, IDHmut glioma and BrMs.

    Article  CAS  PubMed  Google Scholar 

  8. Goswami, S. et al. Immune profiling of human tumors identifies CD73 as a combinatorial target in glioblastoma. Nat. Med. 26, 39–46 (2020). This publication highlights the potential of targeting purinergic signalling as an immunotherapeutic approach for GBM.

    Article  CAS  PubMed  Google Scholar 

  9. Fujita, M. et al. COX-2 blockade suppresses gliomagenesis by inhibiting myeloid-derived suppressor cells. Cancer Res. 71, 2664–2674 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Klemm, F. et al. Interrogation of the microenvironmental landscape in brain tumors reveals disease-specific alterations of immune cells. Cell 181, 1643–1660.e17 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Pyonteck, S. M. et al. CSF-1R inhibition alters macrophage polarization and blocks glioma progression. Nat. Med. 19, 1264–1272 (2013). This paper was the first major publication demonstrating that modulation of the CSF1R axis in TAMs in a mouse model of glioma can impact tumour growth and survival.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Priego, N. et al. STAT3 labels a subpopulation of reactive astrocytes required for brain metastasis. Nat. Med. 24, 1024–1035 (2018). This paper demonstrated in mouse models that modulation of a subpopulation of BrM-associated astrocytes through STAT3 inhibition can alter the immune microenvironment and extend survival in mice, and that an early-phase clinical trial demonstrated STAT3 inhibition can slow the growth of BrMs in patients.

    Article  CAS  PubMed  Google Scholar 

  13. Quail, D. F. & Joyce, J. A. The microenvironmental landscape of brain tumors. Cancer Cell 31, 326–341 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Valiente, M. et al. Brain metastasis cell lines panel: a public resource of organotropic cell lines. Cancer Res. 80, 4314–4323 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Masmudi-Martin, M. et al. Brain metastasis models: What should we aim to achieve better treatments? Adv. Drug Deliv. Rev. 169, 79–99 (2021).

    Article  CAS  PubMed  Google Scholar 

  16. Pombo Antunes, A. R. et al. Single-cell profiling of myeloid cells in glioblastoma across species and disease stage reveals macrophage competition and specialization. Nat. Neurosci. 24, 595–610 (2021). This publication demonstrated, with scRNA-seq and CITE-seq, subsets of glioma-associated microglia, MDMs and dendritic cells in mouse models and patients.

    Article  CAS  PubMed  Google Scholar 

  17. Yan, J. et al. FGL2 promotes tumor progression in the CNS by suppressing CD103+ dendritic cell differentiation. Nat. Commun. 10, 448 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Zhang, L. et al. Blocking immunosuppressive neutrophils deters pY696-EZH2-driven brain metastases. Sci. Transl. Med. 12, eaaz5387 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Castriconi, R. et al. NK cells recognize and kill human glioblastoma cells with stem cell-like properties. J. Immunol. 182, 3530–3539 (2009).

    Article  CAS  PubMed  Google Scholar 

  20. Alvarez-Breckenridge, C. A. et al. NK cells impede glioblastoma virotherapy through NKp30 and NKp46 natural cytotoxicity receptors. Nat. Med. 18, 1827–1834 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Bowman, R. L. et al. Macrophage ontogeny underlies differences in tumor-specific education in brain malignancies. Cell Rep. 17, 2445–2459 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Sankowski, R. et al. Mapping microglia states in the human brain through the integration of high-dimensional techniques. Nat. Neurosci. 22, 2098–2110 (2019). This publication described microglial subsets in patients with glioma for the first time using scRNA-seq and CyTOF.

    Article  CAS  PubMed  Google Scholar 

  23. Guldner, I. H. et al. CNS-native myeloid cells drive immune suppression in the brain metastatic niche through Cxcl10. Cell 183, 1234–1248.e25 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Akkari, L. et al. Dynamic changes in glioma macrophage populations after radiotherapy reveal CSF-1R inhibition as a strategy to overcome resistance. Sci. Transl. Med. 12, eaaw7843 (2020).

    Article  CAS  PubMed  Google Scholar 

  25. Heiland, D. H. et al. Tumor-associated reactive astrocytes aid the evolution of immunosuppressive environment in glioblastoma. Nat. Commun. 10, 2541 (2019). This publication describes a subset of glioma-associated astrocytes characterized by the upregulation of STAT3 in surgical specimen-derived cultures, with some evidence that induction of immune-suppressive cytokines requires interactions with microglia.

    Article  Google Scholar 

  26. Phillips, J. P., Eremin, O. & Anderson, J. R. Lymphoreticular cells in human brain tumours and in normal brain. Br. J. Cancer 45, 61–69 (1982).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Darmanis, S. et al. Single-cell RNA-Seq analysis of infiltrating neoplastic cells at the migrating front of human glioblastoma. Cell Rep. 21, 1399–1410 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Gieryng, A. et al. Immune microenvironment of experimental rat C6 gliomas resembles human glioblastomas. Sci. Rep. 7, 17556 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Venteicher, A. S. et al. Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq. Science 355, eaai8478 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Kohanbash, G. et al. GM-CSF promotes the immunosuppressive activity of glioma-infiltrating myeloid cells through interleukin-4 receptor-alpha. Cancer Res. 73, 6413–6423 (2013).

    Article  CAS  PubMed  Google Scholar 

  31. Ginhoux, F. et al. Fate mapping analysis reveals that adult microglia derive from primitive macrophages. Science 330, 841–845 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Chen, Z. et al. Cellular and molecular identity of tumor-associated macrophages in glioblastoma. Cancer Res. 77, 2266–2278 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Prinz, M., Jung, S. & Priller, J. Microglia biology: one century of evolving concepts. Cell 179, 292–311 (2019).

    Article  CAS  PubMed  Google Scholar 

  34. Ayata, P. et al. Epigenetic regulation of brain region-specific microglia clearance activity. Nat. Neurosci. 21, 1049–1060 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Gosselin, D. et al. Environment drives selection and function of enhancers controlling tissue-specific macrophage identities. Cell 159, 1327–1340 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Mildner, A. et al. Microglia in the adult brain arise from Ly-6ChiCCR2+ monocytes only under defined host conditions. Nat. Neurosci. 10, 1544–1553 (2007).

    Article  CAS  PubMed  Google Scholar 

  37. Linnerbauer, M., Wheeler, M. A. & Quintana, F. J. Astrocyte crosstalk in CNS inflammation. Neuron 108, 608–622 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Broekman, M. L. et al. Multidimensional communication in the microenvirons of glioblastoma. Nat. Rev. Neurol. 14, 482–495 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Hambardzumyan, D., Gutmann, D. H. & Kettenmann, H. The role of microglia and macrophages in glioma maintenance and progression. Nat. Neurosci. 19, 20–27 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Pires-Afonso, Y., Niclou, S. P. & Michelucci, A. Revealing and harnessing tumour-associated microglia/macrophage heterogeneity in glioblastoma. Int. J. Mol. Sci. 21, 689 (2020).

    Article  CAS  PubMed Central  Google Scholar 

  41. Gabrusiewicz, K. et al. Glioblastoma-infiltrated innate immune cells resemble M0 macrophage phenotype. JCI Insight 1, e85841 (2016).

    Article  PubMed Central  Google Scholar 

  42. Szulzewsky, F. et al. Glioma-associated microglia/macrophages display an expression profile different from M1 and M2 polarization and highly express Gpnmb and Spp1. PLoS One 10, e0116644 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Müller, S. et al. Single-cell profiling of human gliomas reveals macrophage ontogeny as a basis for regional differences in macrophage activation in the tumor microenvironment. Genome Biol. 18, 234 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Takenaka, M. C. et al. Control of tumor-associated macrophages and T cells in glioblastoma via AHR and CD39. Nat. Neurosci. 22, 729–740 (2019). This study demonstrated in detail a specific immune-suppressive mechanism in mouse glioma-associated MDMs: activation of AHR by tumour-derived kynurenine, resulting in the upregulation of CD39 and production of T cell-suppressive adenosine.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Poon, C. C. et al. Differential microglia and macrophage profiles in human IDH-mutant and -wild type glioblastoma. Oncotarget 10, 3129–3143 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Amankulor, N. M. et al. Mutant IDH1 regulates the tumor-associated immune system in gliomas. Genes Dev. 31, 774–786 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Schulz, M. et al. Cellular and molecular changes of brain metastases-associated myeloid cells during disease progression and therapeutic response. iScience 23, 101178 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Osuka, S. & Van Meir, E. G. Overcoming therapeutic resistance in glioblastoma: the way forward. J. Clin. Invest. 127, 415–426 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  49. O’Rourke, D. M. et al. A single dose of peripherally infused EGFRvIII-directed CAR T cells mediates antigen loss and induces adaptive resistance in patients with recurrent glioblastoma. Sci. Transl. Med. 9, eaaa0984 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Neftel, C. et al. An integrative model of cellular states, plasticity, and genetics for glioblastoma. Cell 178, 835–849.e21 (2019). This publication demonstrated with scRNA-seq that human GBM cells exist in four plastic cellular states, which are analogous to the GBM subtypes previously described with bulk RNA sequencing, and that the mesenchymal state is associated with TAMs.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Patel, A. P. et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 344, 1396–1401 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Capper, D. et al. DNA methylation-based classification of central nervous system tumours. Nature 555, 469–474 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Orozco, J. I. J. et al. Epigenetic profiling for the molecular classification of metastatic brain tumors. Nat. Commun. 9, 4627 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Wenger, A. et al. Intratumor DNA methylation heterogeneity in glioblastoma: implications for DNA methylation-based classification. Neuro-Oncology 21, 616–627 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Wang, Q. et al. Tumor evolution of glioma-intrinsic gene expression subtypes associates with immunological changes in the microenvironment. Cancer Cell 32, 42–56.e6 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Elmore, M. R. et al. Colony-stimulating factor 1 receptor signaling is necessary for microglia viability, unmasking a microglia progenitor cell in the adult brain. Neuron 82, 380–397 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Huang, Y. et al. Repopulated microglia are solely derived from the proliferation of residual microglia after acute depletion. Nat. Neurosci. 21, 530–540 (2018).

    Article  CAS  PubMed  Google Scholar 

  58. Wilton, D. K., Dissing-Olesen, L. & Stevens, B. Neuron-glia signaling in synapse elimination. Annu. Rev. Neurosci. 42, 107–127 (2019).

    Article  CAS  PubMed  Google Scholar 

  59. Li, Q. et al. Developmental heterogeneity of microglia and brain myeloid cells revealed by deep single-cell RNA sequencing. Neuron 101, 207–223.e10 (2019).

    Article  CAS  PubMed  Google Scholar 

  60. Hammond, T. R. et al. Single-cell RNA sequencing of microglia throughout the mouse lifespan and in the injured brain reveals complex cell-state changes. Immunity 50, 253–271.e6 (2019).

    Article  CAS  PubMed  Google Scholar 

  61. Masuda, T. et al. Spatial and temporal heterogeneity of mouse and human microglia at single-cell resolution. Nature 566, 388–392 (2019).

    Article  CAS  PubMed  Google Scholar 

  62. Böttcher, C. et al. Human microglia regional heterogeneity and phenotypes determined by multiplexed single-cell mass cytometry. Nat. Neurosci. 22, 78–90 (2019).

    Article  PubMed  Google Scholar 

  63. Marschallinger, J. et al. Lipid-droplet-accumulating microglia represent a dysfunctional and proinflammatory state in the aging brain. Nat. Neurosci. 23, 194–208 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Safaiyan, S. et al. White matter aging drives microglial diversity. Neuron 109, 1100–1117.e10 (2021).

    Article  CAS  PubMed  Google Scholar 

  65. Geirsdottir, L. et al. Cross-species single-cell analysis reveals divergence of the primate microglia program. Cell 179, 1609–1622.e16 (2019).

    Article  CAS  PubMed  Google Scholar 

  66. Jordão, M. J. C. et al. Single-cell profiling identifies myeloid cell subsets with distinct fates during neuroinflammation. Science 363, eaat7554 (2019).

    Article  PubMed  Google Scholar 

  67. Keren-Shaul, H. et al. A unique microglia type associated with restricting development of Alzheimer’s disease. Cell 169, 1276–1290.e17 (2017).

    Article  CAS  PubMed  Google Scholar 

  68. Zhou, Y. et al. Human and mouse single-nucleus transcriptomics reveal TREM2-dependent and TREM2-independent cellular responses in Alzheimer’s disease. Nat. Med. 26, 131–142 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Schirmer, L. et al. Neuronal vulnerability and multilineage diversity in multiple sclerosis. Nature 573, 75–82 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Krasemann, S. et al. The TREM2-APOE pathway drives the transcriptional phenotype of dysfunctional microglia in neurodegenerative diseases. Immunity 47, 566–581.e9 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Gosselin, D. et al. An environment-dependent transcriptional network specifies human microglia identity. Science 356, eaal3222 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  72. Miyauchi, J. T. et al. Deletion of neuropilin 1 from microglia or bone marrow–derived macrophages slows glioma progression. Cancer Res. 78, 685–694 (2018).

    Article  CAS  PubMed  Google Scholar 

  73. Glinka, Y. & Prud’homme, G. J. Neuropilin-1 is a receptor for transforming growth factor beta-1, activates its latent form, and promotes regulatory T cell activity. J. Leukoc. Biol. 84, 302–310 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Gelfand, M. V. et al. Neuropilin-1 functions as a VEGFR2 co-receptor to guide developmental angiogenesis independent of ligand binding. eLife 3, e03720 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  75. Nissen, J. C., Selwood, D. L. & Tsirka, S. E. Tuftsin signals through its receptor neuropilin-1 via the transforming growth factor beta pathway. J. Neurochem. 127, 394–402 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Majed, H. H. et al. A novel role for Sema3A in neuroprotection from injury mediated by activated microglia. J. Neurosci. 26, 1730–1738 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Friese, M. A. et al. RNA interference targeting transforming growth factor-beta enhances NKG2D-mediated antiglioma immune response, inhibits glioma cell migration and invasiveness, and abrogates tumorigenicity in vivo. Cancer Res. 64, 7596–7603 (2004).

    Article  CAS  PubMed  Google Scholar 

  78. Uhl, M. et al. SD-208, a novel transforming growth factor beta receptor I kinase inhibitor, inhibits growth and invasiveness and enhances immunogenicity of murine and human glioma cells in vitro and in vivo. Cancer Res. 64, 7954–7961 (2004).

    Article  CAS  PubMed  Google Scholar 

  79. Miyauchi, J. T. et al. Ablation of Neuropilin 1 from glioma-associated microglia and macrophages slows tumor progression. Oncotarget 7, 9801–9814 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  80. Leclerc, M. et al. Regulation of antitumour CD8 T-cell immunity and checkpoint blockade immunotherapy by Neuropilin-1. Nat. Commun. 10, 3345 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  81. Vinnakota, K. et al. Toll-like receptor 2 mediates microglia/brain macrophage MT1-MMP expression and glioma expansion. Neuro-Oncology 15, 1457–1468 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Hu, F. et al. Glioma-derived versican promotes tumor expansion via glioma-associated microglial/macrophages Toll-like receptor 2 signaling. Neuro-Oncology 17, 200–210 (2015).

    Article  CAS  PubMed  Google Scholar 

  83. Triller, P., Bachorz, J., Synowitz, M., Kettenmann, H. & Markovic, D. O-Vanillin attenuates the TLR2 mediated tumor-promoting phenotype of microglia. Int. J. Mol. Sci. 21, 2959 (2020).

    Article  CAS  PubMed Central  Google Scholar 

  84. El Andaloussi, A., Sonabend, A. M., Han, Y. & Lesniak, M. S. Stimulation of TLR9 with CpG ODN enhances apoptosis of glioma and prolongs the survival of mice with experimental brain tumors. Glia 54, 526–535 (2006).

    Article  PubMed  Google Scholar 

  85. Benbenishty, A. et al. Prophylactic TLR9 stimulation reduces brain metastasis through microglia activation. PLoS Biol. 17, e2006859 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Huang, Y. et al. Synergistic toll-like receptor 3/9 signaling affects properties and impairs glioma-promoting activity of microglia. J. Neurosci. 40, 6428–6443 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Maas, S. L. N. et al. Glioblastoma hijacks microglial gene expression to support tumor growth. J. Neuroinflammation 17, 120 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Kopatz, J. et al. Siglec-h on activated microglia for recognition and engulfment of glioma cells: Siglec-h on activated microglia. Glia 61, 1122–1133 (2013).

    Article  PubMed  Google Scholar 

  89. Hickman, S. E. et al. The microglial sensome revealed by direct RNA sequencing. Nat. Neurosci. 16, 1896–1905 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Zhu, X. et al. Poly-ICLC promotes the infiltration of effector T cells into intracranial gliomas via induction of CXCL10 in IFN-alpha and IFN-gamma dependent manners. Cancer Immunol. Immunother. 59, 1401–1409 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Zhu, X., Fujita, M., Snyder, L. A. & Okada, H. Systemic delivery of neutralizing antibody targeting CCL2 for glioma therapy. J. Neurooncol. 104, 83–92 (2011).

    Article  CAS  PubMed  Google Scholar 

  92. Mercurio, L. et al. Targeting CXCR4 by a selective peptide antagonist modulates tumor microenvironment and microglia reactivity in a human glioblastoma model. J. Exp. Clin. Cancer Res. 35, 55 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  93. Watkins, S. et al. Disruption of astrocyte-vascular coupling and the blood-brain barrier by invading glioma cells. Nat. Commun. 5, 4196 (2014).

    Article  CAS  PubMed  Google Scholar 

  94. Sørensen, M. D., Dahlrot, R. H., Boldt, H. B., Hansen, S. & Kristensen, B. W. Tumour-associated microglia/macrophages predict poor prognosis in high-grade gliomas and correlate with an aggressive tumour subtype. Neuropathol. Appl. Neurobiol. 44, 185–206 (2018).

    Article  PubMed  Google Scholar 

  95. De Boeck, A. et al. Glioma-derived IL-33 orchestrates an inflammatory brain tumor microenvironment that accelerates glioma progression. Nat. Commun. 11, 4997 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  96. Abels, E. R. et al. GlioM&M: Web-based tool for studying circulating and infiltrating monocytes and macrophages in glioma. Sci. Rep. 10, 9898 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Aslan, K. et al. Heterogeneity of response to immune checkpoint blockade in hypermutated experimental gliomas. Nat. Commun. 11, 931 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Quail, D. F. et al. The tumor microenvironment underlies acquired resistance to CSF-1R inhibition in gliomas. Science 352, aad3018 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  99. Lavin, Y. et al. Tissue-resident macrophage enhancer landscapes are shaped by the local microenvironment. Cell 159, 1312–1326 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Ochocka, N. et al. Single-cell RNA sequencing reveals functional heterogeneity of glioma-associated brain macrophages. Nat. Commun. 12, 1151 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Raychaudhuri, B. et al. Myeloid derived suppressor cell infiltration of murine and human gliomas is associated with reduction of tumor infiltrating lymphocytes. J. Neurooncol. 122, 293–301 (2015).

    Article  CAS  PubMed  Google Scholar 

  102. Gabrusiewicz, K., Colwell, N. A. & Heimberger, A. B. in Translational Immunotherapy of Brain Tumors 63–82 (Elsevier, 2017).

  103. Katzenelenbogen, Y. et al. Coupled scRNA-seq and intracellular protein activity reveal an immunosuppressive role of TREM2 in cancer. Cell 182, 872–885.e19 (2020).

    Article  CAS  PubMed  Google Scholar 

  104. Opitz, C. A. et al. An endogenous tumour-promoting ligand of the human aryl hydrocarbon receptor. Nature 478, 197–203 (2011). This publication, together with Takenaka et al.106 and Sadik et al.105 reported important roles for AHR in GBM, guiding new lines of research and potential therapeutic approaches.

    Article  CAS  PubMed  Google Scholar 

  105. Sadik, A. et al. IL4I1 is a metabolic immune checkpoint that activates the AHR and promotes tumor progression. Cell 182, 1252–1270.e34 (2020).

    Article  CAS  PubMed  Google Scholar 

  106. Takenaka, M. C., Robson, S. & Quintana, F. J. Regulation of the T cell response by CD39. Trends Immunol. 37, 427–439 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Apetoh, L. et al. The aryl hydrocarbon receptor interacts with c-Maf to promote the differentiation of type 1 regulatory T cells induced by IL-27. Nat. Immunol. 11, 854–861 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Mascanfroni, I. D. et al. Metabolic control of type 1 regulatory T cell differentiation by AHR and HIF1-α. Nat. Med. 21, 638–646 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Li, Z., Liu, X., Guo, R. & Wang, P. CD4+Foxp3− type 1 regulatory T cells in glioblastoma multiforme suppress T cell responses through multiple pathways and are regulated by tumor-associated macrophages. Int. J. Biochem. Cell Biol. 81, 1–9 (2016).

    Article  PubMed  Google Scholar 

  110. Ene, C. I. et al. Anti-PD-L1 antibody direct activation of macrophages contributes to a radiation-induced abscopal response in glioblastoma. Neuro-Oncology 22, 639–651 (2020).

    Article  CAS  PubMed  Google Scholar 

  111. Bloch, O. et al. Gliomas promote immunosuppression through induction of B7-H1 expression in tumor-associated macrophages. Clin. Cancer Res. 19, 3165–3175 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Berghoff, A. S. et al. Tumor infiltrating lymphocytes and PD-L1 expression in brain metastases of small cell lung cancer (SCLC). J. Neurooncol. 130, 19–29 (2016).

    Article  CAS  PubMed  Google Scholar 

  113. Dusoswa, S. A. et al. Glioblastomas exploit truncated O-linked glycans for local and distant immune modulation via the macrophage galactose-type lectin. Proc. Natl Acad. Sci. USA 117, 3693–3703 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Chen, Q. et al. Immunogenomic analysis reveals LGALS1 contributes to the immune heterogeneity and immunosuppression in glioma. Int. J. Cancer 145, 517–530 (2019).

    Article  CAS  PubMed  Google Scholar 

  115. Ruffell, B. et al. Macrophage IL-10 blocks CD8+ T cell-dependent responses to chemotherapy by suppressing IL-12 expression in intratumoral dendritic cells. Cancer Cell 26, 623–637 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Rodriguez, P. C. et al. Arginase I production in the tumor microenvironment by mature myeloid cells inhibits T-cell receptor expression and antigen-specific T-cell responses. Cancer Res. 64, 5839–5849 (2004).

    Article  CAS  PubMed  Google Scholar 

  117. Movahedi, K. et al. Different tumor microenvironments contain functionally distinct subsets of macrophages derived from Ly6C(high) monocytes. Cancer Res. 70, 5728–5739 (2010).

    Article  CAS  PubMed  Google Scholar 

  118. Verkhratsky, A. & Nedergaard, M. Physiology of astroglia. Physiol. Rev. 98, 239–389 (2018).

    Article  CAS  PubMed  Google Scholar 

  119. Sofroniew, M. V. & Vinters, H. V. Astrocytes: biology and pathology. Acta Neuropathol. 119, 7–35 (2010).

    Article  PubMed  Google Scholar 

  120. Yao, P.-S. et al. Glutamate/glutamine metabolism coupling between astrocytes and glioma cells: Neuroprotection and inhibition of glioma growth. Biochem. Biophys. Res. Commun. 450, 295–299 (2014).

    Article  CAS  PubMed  Google Scholar 

  121. Mayo, L. et al. Regulation of astrocyte activation by glycolipids drives chronic CNS inflammation. Nat. Med. 20, 1147–1156 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Rothhammer, V. et al. Type I interferons and microbial metabolites of tryptophan modulate astrocyte activity and central nervous system inflammation via the aryl hydrocarbon receptor. Nat. Med. 22, 586–597 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Rothhammer, V. et al. Sphingosine 1-phosphate receptor modulation suppresses pathogenic astrocyte activation and chronic progressive CNS inflammation. Proc. Natl Acad. Sci. USA 114, 2012–2017 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Rothhammer, V. et al. Microglial control of astrocytes in response to microbial metabolites. Nature 557, 724–728 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Chao, C.-C. et al. Metabolic control of astrocyte pathogenic activity via cPLA2-MAVS. Cell 179, 1483–1498.e22 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Wheeler, M. A. et al. Environmental control of astrocyte pathogenic activities in CNS inflammation. Cell 176, 581–596.e18 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Wheeler, M. A. et al. MAFG-driven astrocytes promote CNS inflammation. Nature 578, 593–599 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  128. Sanmarco, L. M. et al. Gut-licensed IFNγ+ NK cells drive LAMP1+TRAIL+ anti-inflammatory astrocytes. Nature 590, 473–479 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Gibson, E. M. et al. Methotrexate chemotherapy induces persistent tri-glial dysregulation that underlies chemotherapy-related cognitive impairment. Cell 176, 43–55.e13 (2019).

    Article  CAS  PubMed  Google Scholar 

  130. Bardehle, S. et al. Live imaging of astrocyte responses to acute injury reveals selective juxtavascular proliferation. Nat. Neurosci. 16, 580–586 (2013).

    Article  CAS  PubMed  Google Scholar 

  131. Saijo, K. et al. A Nurr1/CoREST pathway in microglia and astrocytes protects dopaminergic neurons from inflammation-induced death. Cell 137, 47–59 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Kano, S.-I. et al. Glutathione S-transferases promote proinflammatory astrocyte-microglia communication during brain inflammation. Sci. Signal. 12, eaar2124 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Frik, J. et al. Cross-talk between monocyte invasion and astrocyte proliferation regulates scarring in brain injury. EMBO Reports 19, e45294 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  134. Ito, M. et al. Brain regulatory T cells suppress astrogliosis and potentiate neurological recovery. Nature 565, 246–250 (2019).

    Article  CAS  PubMed  Google Scholar 

  135. Mayo, L. et al. IL-10-dependent Tr1 cells attenuate astrocyte activation and ameliorate chronic central nervous system inflammation. Brain 139, 1939–1957 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  136. Valiente, M. et al. Serpins promote cancer cell survival and vascular co-option in brain metastasis. Cell 156, 1002–1016 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Mega, A. et al. Astrocytes enhance glioblastoma growth. Glia 68, 316–327 (2020).

    Article  PubMed  Google Scholar 

  138. Okolie, O. et al. Reactive astrocytes potentiate tumor aggressiveness in a murine glioma resection and recurrence model. Neurooncology 18, 1622–1633 (2016).

    CAS  Google Scholar 

  139. Kim, J.-K. et al. Tumoral RANKL activates astrocytes that promote glioma cell invasion through cytokine signaling. Cancer Lett. 353, 194–200 (2014).

    Article  CAS  PubMed  Google Scholar 

  140. Loeffler, S., Fayard, B., Weis, J. & Weissenberger, J. Interleukin-6 induces transcriptional activation of vascular endothelial growth factor (VEGF) in astrocyte sin vivo and regulates VEGF promoter activity in glioblastoma cells via direct interaction between STAT3 and Sp1. Int. J. Cancer 115, 202–213 (2005).

    Article  CAS  PubMed  Google Scholar 

  141. Wurm, J. et al. Astrogliosis releases pro-oncogenic chitinase 3-Like 1 causing MAPK signaling in glioblastoma. Cancers 11, 1437 (2019).

    Article  CAS  PubMed Central  Google Scholar 

  142. John Lin, C.-C. et al. Identification of diverse astrocyte populations and their malignant analogs. Nat. Neurosci. 20, 396–405 (2017). This paper described subsets of astrocytes for the first time, using fluorescence-activated cell sorting, and compared transcriptomes of astrocytes to those of mouse and human glioma cells.

    Article  CAS  PubMed  Google Scholar 

  143. Batiuk, M. Y. et al. Identification of region-specific astrocyte subtypes at single cell resolution. Nat. Commun. 11, 1220 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. Morel, L. et al. Molecular and functional properties of regional astrocytes in the adult brain. J. Neurosci. 37, 8706–8717 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Bayraktar, O. A. et al. Astrocyte layers in the mammalian cerebral cortex revealed by a single-cell in situ transcriptomic map. Nat. Neurosci. 23, 500–509 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  146. Zeisel, A. et al. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 347, 1138–1142 (2015).

    Article  CAS  PubMed  Google Scholar 

  147. Rusnakova, V. et al. Heterogeneity of astrocytes: from development to injury – single cell gene expression. PLoS One 8, e69734 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Tsai, H. H. et al. Regional astrocyte allocation regulates CNS synaptogenesis and repair. Science 337, 358–362 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  149. Molofsky, A. V. et al. Astrocyte-encoded positional cues maintain sensorimotor circuit integrity. Nature 509, 189–194 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  150. Chai, H. et al. Neural circuit-specialized astrocytes: transcriptomic, proteomic, morphological, and functional evidence. Neuron 95, 531–549.e9 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  151. Hasel, P. et al. Neurons and neuronal activity control gene expression in astrocytes to regulate their development and metabolism. Nat. Commun. 8, 15132 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  152. Lanjakornsiripan, D. et al. Layer-specific morphological and molecular differences in neocortical astrocytes and their dependence on neuronal layers. Nat. Commun. 9, 1623 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  153. Martin, R., Bajo-Graneras, R., Moratalla, R., Perea, G. & Araque, A. Circuit-specific signaling in astrocyte-neuron networks in basal ganglia pathways. Science 349, 730–734 (2015).

    Article  CAS  PubMed  Google Scholar 

  154. Farmer, W. T. & Murai, K. Resolving astrocyte heterogeneity in the CNS. Front. Cell. Neurosci. 11, 300 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  155. Farmer, W. T. et al. Neurons diversify astrocytes in the adult brain through sonic hedgehog signaling. Science 351, 849–854 (2016).

    Article  CAS  PubMed  Google Scholar 

  156. Herrmann, J. E. et al. STAT3 is a critical regulator of astrogliosis and scar formation after spinal cord injury. J. Neurosci. 28, 7231–7243 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Ben Haim, L. et al. The JAK/STAT3 pathway is a common inducer of astrocyte reactivity in Alzheimer’s and Huntington’s diseases. J. Neurosci. 35, 2817–2829 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  158. Liddelow, S. A. et al. Neurotoxic reactive astrocytes are induced by activated microglia. Nature 541, 481–487 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  159. Roy Choudhury, G. et al. Involvement of p38 MAPK in reactive astrogliosis induced by ischemic stroke. Brain Res. 1551, 45–58 (2014).

    Article  CAS  PubMed  Google Scholar 

  160. Wang, X. et al. Astrocytic A20 ameliorates experimental autoimmune encephalomyelitis by inhibiting NF-κB- and STAT1-dependent chemokine production in astrocytes. Acta Neuropathol. 126, 711–724 (2013).

    Article  CAS  PubMed  Google Scholar 

  161. Wang, X. et al. OTUB1 inhibits CNS autoimmunity by preventing IFN-γ-induced hyperactivation of astrocytes. EMBO J. 38, e100947 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  162. Qin, H., Niyongere, S. A., Lee, S. J., Baker, B. J. & Benveniste, E. N. Expression and functional significance of SOCS-1 and SOCS-3 in astrocytes. J. Immunol. 181, 3167–3176 (2008).

    Article  CAS  PubMed  Google Scholar 

  163. Yeste, A. et al. Tolerogenic nanoparticles inhibit T cell-mediated autoimmunity through SOCS2. Sci. Signal. 9, ra61–ra61 (2016).

    Article  PubMed  Google Scholar 

  164. Okada, S. et al. Conditional ablation of Stat3 or Socs3 discloses a dual role for reactive astrocytes after spinal cord injury. Nat. Med. 12, 829–834 (2006).

    Article  CAS  PubMed  Google Scholar 

  165. Norris, C. M. et al. Calcineurin triggers reactive/inflammatory processes in astrocytes and is upregulated in aging and Alzheimer’s models. J. Neurosci. 25, 4649–4658 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  166. Fernandez, A. M. et al. Regulation of the phosphatase calcineurin by insulin-like growth factor I unveils a key role of astrocytes in Alzheimer’s pathology. Mol. Psychiatry 17, 705–718 (2012).

    Article  CAS  PubMed  Google Scholar 

  167. Habib, N. et al. Disease-associated astrocytes in Alzheimer’s disease and aging. Nat. Neurosci. 23, 701–706 (2020).

    Article  CAS  PubMed  Google Scholar 

  168. Gril, B. et al. Reactive astrocytic S1P3 signaling modulates the blood-tumor barrier in brain metastases. Nat. Commun. 9, 2705 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  169. Contreras-Zarate, M. J. et al. Estradiol induces BDNF/TrkB signaling in triple-negative breast cancer to promote brain metastases. Oncogene 38, 4685–4699 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  170. Gril, B. et al. Pazopanib inhibits the activation of PDGFRbeta-expressing astrocytes in the brain metastatic microenvironment of breast cancer cells. Am. J. Pathol. 182, 2368–2379 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  171. Krupinski, J. et al. A putative role for platelet-derived growth factor in angiogenesis and neuroprotection after ischemic stroke in humans. Stroke 28, 564–573 (1997).

    Article  CAS  PubMed  Google Scholar 

  172. Norazit, A. et al. Vascular endothelial growth factor and platelet derived growth factor modulates the glial response to a cortical stab injury. Neuroscience 192, 652–660 (2011).

    Article  CAS  PubMed  Google Scholar 

  173. Thies, K. A. et al. Stromal platelet-derived growth factor receptor-beta signaling promotes breast cancer metastasis in the brain. Cancer Res. 81, 606–618 (2021).

    Article  CAS  PubMed  Google Scholar 

  174. Hung, M. H. et al. Effect of age and biological subtype on the risk and timing of brain metastasis in breast cancer patients. PLoS One 9, e89389 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  175. Chen, Q. et al. Carcinoma–astrocyte gap junctions promote brain metastasis by cGAMP transfer. Nature 533, 493–498 (2016). This publication provided novel and transformative insights on the role of astrocytes in BrMs.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  176. Sin, W. C. et al. Astrocytes promote glioma invasion via the gap junction protein connexin43. Oncogene 35, 1504–1516 (2016).

    Article  CAS  PubMed  Google Scholar 

  177. Flippot, R. et al. Safety and efficacy of nivolumab in brain metastases from renal cell carcinoma: results of the GETUG-AFU 26 NIVOREN multicenter phase II study. J. Clin. Oncol. 37, 2008–2016 (2019).

    Article  CAS  PubMed  Google Scholar 

  178. Reardon, D. A. et al. Effect of nivolumab vs bevacizumab in patients with recurrent glioblastoma: the checkmate 143 phase 3 randomized clinical trial. JAMA Oncol. 6, 1003 (2020).

    Article  PubMed  Google Scholar 

  179. Cloughesy, T. F. et al. Neoadjuvant anti-PD-1 immunotherapy promotes a survival benefit with intratumoral and systemic immune responses in recurrent glioblastoma. Nat. Med. 25, 477–486 (2019). Unlike numerous preceding studies, this clinical report demonstrated that anti-PD1 therapy given in a neoadjuvant fashion (prior to re-operation) could lead to a survival benefit in recurrent GBM. This study is currently being validated with larger trials.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  180. Qian, J. et al. The IFN-γ/PD-L1 axis between T cells and tumor microenvironment: hints for glioma anti-PD-1/PD-L1 therapy. J. Neuroinflammation 15, 290 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  181. McLaughlin, J. et al. Quantitative assessment of the heterogeneity of PD-L1 expression in non-small-cell lung cancer. JAMA Oncol. 2, 46–54 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  182. Prima, V., Kaliberova, L. N., Kaliberov, S., Curiel, D. T. & Kusmartsev, S. COX2/mPGES1/PGE2 pathway regulates PD-L1 expression in tumor-associated macrophages and myeloid-derived suppressor cells. Proc. Natl Acad. Sci. USA 114, 1117–1122 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  183. Lamano, J. B. et al. Glioblastoma-derived IL6 induces immunosuppressive peripheral myeloid cell PD-L1 and promotes tumor growth. Clin. Cancer Res. 25, 3643–3657 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  184. Butte, M. J., Keir, M. E., Phamduy, T. B., Sharpe, A. H. & Freeman, G. J. Programmed death-1 ligand 1 interacts specifically with the B7-1 costimulatory molecule to inhibit T cell responses. Immunity 27, 111–122 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  185. Ahmed, F. S. et al. PD-L1 protein expression on both tumor cells and macrophages are associated with response to neoadjuvant durvalumab with chemotherapy in triple-negative breast cancer. Clin. Cancer Res. 26, 5456–5461 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  186. Liu, Y. et al. Immune cell PD-L1 colocalizes with macrophages and is associated with outcome in PD-1 pathway blockade therapy. Clin. Cancer Res. 26, 970–977 (2020).

    Article  CAS  PubMed  Google Scholar 

  187. Holtzhausen, A. et al. TAM family receptor kinase inhibition reverses MDSC-mediated suppression and augments anti-PD-1 therapy in melanoma. Cancer Immunol. Res. 7, 1672–1686 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  188. Sadahiro, H. et al. Activation of the receptor tyrosine kinase AXL regulates the immune microenvironment in glioblastoma. Cancer Res. 78, 3002–3013 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  189. Wu, J. et al. MerTK as a therapeutic target in glioblastoma. Neuro-Oncology 20, 92–102 (2018).

    Article  CAS  PubMed  Google Scholar 

  190. US National Library of Medicine. Clinicaltrials.gov https://www.clinicaltrials.gov/ct2/show/NCT03965494 (2019).

  191. Ott, M. et al. Profiling of patients with glioma reveals the dominant immunosuppressive axis is refractory to immune function restoration. JCI Insight 5, e134386 (2020). This publication, in contrast to other studies, showed that modulating the adenosine axis was ineffective in a mouse model of GBM, potentially due to T cell exhaustion.

    Article  PubMed Central  Google Scholar 

  192. Turiello, R. et al. Serum CD73 is a prognostic factor in patients with metastatic melanoma and is associated with response to anti-PD-1 therapy. J. Immunother. Cancer 8, e001689 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  193. Mayer, A. et al. Role of hypoxia and the adenosine system in immune evasion and prognosis of patients with brain metastases of melanoma: a multiplex whole slide immunofluorescence study. Cancers 12, 3753 (2020).

    Article  CAS  PubMed Central  Google Scholar 

  194. Zhai, L. et al. Infiltrating T cells increase IDO1 expression in glioblastoma and contribute to decreased patient survival. Clin. Cancer Res. 23, 6650–6660 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  195. Brenk, M. et al. Tryptophan deprivation induces inhibitory receptors ILT3 and ILT4 on dendritic cells favoring the induction of human CD4+CD25+Foxp3+T regulatory cells. J. Immunol. 183, 145–154 (2009).

    Article  CAS  PubMed  Google Scholar 

  196. Wainwright, D. A. et al. IDO expression in brain tumors increases the recruitment of regulatory T cells and negatively impacts survival. Clin. Cancer Res. 18, 6110–6121 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  197. Ladomersky, E. et al. IDO1 inhibition synergizes with radiation and PD-1 blockade to durably increase survival against advanced glioblastoma. Clin. Cancer Res. 24, 2559–2573 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  198. Reardon, D. A. et al. A phase 1 study of PF-06840003, an oral indoleamine 2,3-dioxygenase 1 (IDO1) inhibitor in patients with recurrent malignant glioma. Invest. New Drugs 38, 1784–1795 (2020).

    Article  CAS  PubMed  Google Scholar 

  199. US National Library of Medicine. Clinicaltrials.gov https://clinicaltrials.gov/ct2/show/NCT03532295 (2018).

  200. US National Library of Medicine. Clinicaltrials.gov https://clinicaltrials.gov/ct2/show/NCT04047706 (2019).

  201. Gabriely, G. & Quintana, F. J. Role of AHR in the control of GBM-associated myeloid cells. Semin. Cancer Biol. 64, 13–18 (2020).

    Article  CAS  PubMed  Google Scholar 

  202. Rothhammer, V. & Quintana, F. J. The aryl hydrocarbon receptor: an environmental sensor integrating immune responses in health and disease. Nat. Rev. Immunol. 19, 184–197 (2019).

    Article  CAS  PubMed  Google Scholar 

  203. Yan, D. et al. Inhibition of colony stimulating factor-1 receptor abrogates microenvironment-mediated therapeutic resistance in gliomas. Oncogene 36, 6049–6058 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  204. Butowski, N. et al. Orally administered colony stimulating factor 1 receptor inhibitor PLX3397 in recurrent glioblastoma: an Ivy Foundation Early Phase Clinical Trials Consortium phase II study. Neuro-Oncology 18, 557–564 (2016).

    Article  PubMed  Google Scholar 

  205. Qiao, S., Qian, Y., Xu, G., Luo, Q. & Zhang, Z. Long-term characterization of activated microglia/macrophages facilitating the development of experimental brain metastasis through intravital microscopic imaging. J. Neuroinflammation 16, 4 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  206. Lecoultre, M., Dutoit, V. & Walker, P. R. Phagocytic function of tumor-associated macrophages as a key determinant of tumor progression control: a review. J. Immunother. Cancer 8, e001408 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  207. Gholamin, S. et al. Disrupting the CD47-SIRPalpha anti-phagocytic axis by a humanized anti-CD47 antibody is an efficacious treatment for malignant pediatric brain tumors. Sci. Transl. Med. 9, eaaf2968 (2017).

    Article  PubMed  Google Scholar 

  208. Tsai, R. K. & Discher, D. E. Inhibition of “self” engulfment through deactivation of myosin-II at the phagocytic synapse between human cells. J. Cell Biol. 180, 989–1003 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  209. Hutter, G. et al. Microglia are effector cells of CD47-SIRPalpha antiphagocytic axis disruption against glioblastoma. Proc. Natl Acad. Sci. USA 116, 997–1006 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  210. Gowda, P., Patrick, S., Singh, A., Sheikh, T. & Sen, E. Mutant isocitrate dehydrogenase 1 disrupts PKM2-beta-catenin-BRG1 transcriptional network-driven CD47 expression. Mol. Cell Biol. 38, e00001–18 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  211. von Roemeling, C. A. et al. Therapeutic modulation of phagocytosis in glioblastoma can activate both innate and adaptive antitumour immunity. Nat. Commun. 11, 1508 (2020).

    Article  Google Scholar 

  212. Zhang, M. et al. Anti-CD47 treatment stimulates phagocytosis of glioblastoma by M1 and M2 polarized macrophages and promotes M1 polarized macrophages in vivo. PLoS One 11, e0153550 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  213. US National Library of Medicine. Clinicaltrials.gov https://clinicaltrials.gov/ct2/show/NCT03990233 (2019).

  214. Kong, L. Y. et al. A novel phosphorylated STAT3 inhibitor enhances T cell cytotoxicity against melanoma through inhibition of regulatory T cells. Cancer Immunol. Immunother. 58, 1023–1032 (2009).

    Article  CAS  PubMed  Google Scholar 

  215. US National Library of Medicine. Clinicaltrials.gov https://clinicaltrials.gov/ct2/show/NCT01904123 (2013).

  216. US National Library of Medicine. Clinicaltrials.gov https://clinicaltrials.gov/ct2/show/NCT02429570 (2015).

  217. Duffy, C. P. et al. Enhancement of chemotherapeutic drug toxicity to human tumour cells in vitro by a subset of non-steroidal anti-inflammatory drugs (NSAIDs). Eur. J. Cancer 34, 1250–1259 (1998).

    Article  CAS  PubMed  Google Scholar 

  218. Osswald, M. et al. Brain tumour cells interconnect to a functional and resistant network. Nature 528, 93–98 (2015).

    Article  CAS  PubMed  Google Scholar 

  219. Maire, C. L. et al. Glioma escape signature and clonal development under immune pressure. J. Clin. Invest. 130, 5257–5271 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  220. Paik, P. K. et al. Next-generation sequencing of stage IV squamous cell lung cancers reveals an association of PI3K aberrations and evidence of clonal heterogeneity in patients with brain metastases. Cancer Discov. 5, 610–621 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  221. Hara, T. et al. Interactions between cancer cells and immune cells drive transitions to mesenchymal-like states in glioblastoma. Cancer Cell 39, 779–792.e11 (2021).

    Article  CAS  PubMed  Google Scholar 

  222. Clark, I. C. et al. Barcoded viral tracing of single-cell interactions in central nervous system inflammation. Science 372, eabf1230 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  223. Khalsa, J. K. et al. Immune phenotyping of diverse syngeneic murine brain tumors identifies immunologically distinct types. Nat. Commun. 11, 3912 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  224. Thomas, R. P. et al. Macrophage exclusion after radiation therapy (MERT): a first in human phase I/II trial using a CXCR4 inhibitor in glioblastoma. Clin. Cancer Res. 25, 6948–6957 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  225. Schalper, K. A. et al. Neoadjuvant nivolumab modifies the tumor immune microenvironment in resectable glioblastoma. Nat. Med. 25, 470–476 (2019).

    Article  CAS  PubMed  Google Scholar 

  226. Pasqualini, C. et al. Modeling the interaction between the microenvironment and tumor cells in brain tumors. Neuron 108, 1025–1044 (2020).

    Article  CAS  PubMed  Google Scholar 

  227. Fossati, G. et al. Neutrophil infiltration into human gliomas. Acta Neuropathol. 98, 349–354 (1999).

    Article  CAS  PubMed  Google Scholar 

  228. Barletta, K. E., Ley, K. & Mehrad, B. Regulation of neutrophil function by adenosine. Arterioscler. Thromb. Vasc. Biol. 32, 856–864 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  229. Glodde, N. et al. Reactive neutrophil responses dependent on the receptor tyrosine kinase c-MET limit cancer immunotherapy. Immunity 47, 789–802.e9 (2017).

    Article  CAS  PubMed  Google Scholar 

  230. Yee, P. P. et al. Neutrophil-induced ferroptosis promotes tumor necrosis in glioblastoma progression. Nat. Commun. 11, 5424 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  231. Wculek, S. K. et al. Dendritic cells in cancer immunology and immunotherapy. Nat. Rev. Immunol. 20, 7–24 (2020).

    Article  CAS  PubMed  Google Scholar 

  232. Bailey, S. L., Schreiner, B., McMahon, E. J. & Miller, S. D. CNS myeloid DCs presenting endogenous myelin peptides ‘preferentially’ polarize CD4+ TH-17 cells in relapsing EAE. Nat. Immunol. 8, 172–180 (2007).

    Article  CAS  PubMed  Google Scholar 

  233. Faget, J. et al. ICOS-ligand expression on plasmacytoid dendritic cells supports breast cancer progression by promoting the accumulation of immunosuppressive CD4+ T cells. Cancer Res. 72, 6130–6141 (2012).

    Article  CAS  PubMed  Google Scholar 

  234. Oh, S. A. et al. PD-L1 expression by dendritic cells is a key regulator of T-cell immunity in cancer. Nat. Cancer 1, 681–691 (2020).

    Article  PubMed  Google Scholar 

  235. Huntington, N. D., Cursons, J. & Rautela, J. The cancer-natural killer cell immunity cycle. Nat. Rev. Cancer 20, 437–454 (2020).

    Article  CAS  PubMed  Google Scholar 

  236. Fares, J., Fares, M. Y. & Fares, Y. Natural killer cells in the brain tumor microenvironment: Defining a new era in neuro-oncology. Surg. Neurol. Int. 10, 43 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  237. Miyai, M. et al. Current trends in mouse models of glioblastoma. J. Neurooncol. 135, 423–432 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  238. Ben-David, U. et al. Patient-derived xenografts undergo mouse-specific tumor evolution. Nat. Genet. 49, 1567–1575 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  239. Morton, J. J., Bird, G., Refaeli, Y. & Jimeno, A. Humanized mouse xenograft models: narrowing the tumor–microenvironment gap. Cancer Res. 76, 6153–6158 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  240. Lawson, D. A., Kessenbrock, K., Davis, R. T., Pervolarakis, N. & Werb, Z. Tumour heterogeneity and metastasis at single-cell resolution. Nat. Cell Biol. 20, 1349–1360 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  241. Eyler, C. E. et al. Single-cell lineage analysis reveals genetic and epigenetic interplay in glioblastoma drug resistance. Genome Biol. 21, 174 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  242. Li, Y. et al. Murine models of IDH-wild-type glioblastoma exhibit spatial segregation of tumor initiation and manifestation during evolution. Nat. Commun. 11, 3669 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  243. Guilhamon, P. et al. Single-cell chromatin accessibility profiling of glioblastoma identifies an invasive cancer stem cell population associated with lower survival. eLife 10, e64090 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  244. Gularyan, S. K. et al. Investigation of inter- and intratumoral heterogeneity of glioblastoma using TOF-SIMS. Mol. Cell Proteom. 19, 960–970 (2020).

    Article  Google Scholar 

  245. Svensson, V., Vento-Tormo, R. & Teichmann, S. A. Exponential scaling of single-cell RNA-seq in the past decade. Nat. Protoc. 13, 599–604 (2018).

    Article  CAS  PubMed  Google Scholar 

  246. Zhang, J. et al. Single-cell transcriptome-based multilayer network biomarker for predicting prognosis and therapeutic response of gliomas. Brief. Bioinforma. 21, 1080–1097 (2020).

    Article  CAS  Google Scholar 

  247. Saelens, W., Cannoodt, R., Todorov, H. & Saeys, Y. A comparison of single-cell trajectory inference methods. Nat. Biotechnol. 37, 547–554 (2019).

    Article  CAS  PubMed  Google Scholar 

  248. Tanay, A. & Regev, A. Scaling single-cell genomics from phenomenology to mechanism. Nature 541, 331–338 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  249. Rodriques, S. G. et al. Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. Science 363, 1463–1467 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  250. Wang, X. et al. Three-dimensional intact-tissue sequencing of single-cell transcriptional states. Science 361, eaat5691 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  251. Keren, L. et al. A structured tumor-immune microenvironment in triple negative breast cancer revealed by multiplexed ion beam imaging. Cell 174, 1373–1387.e19 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  252. Eng, C.-H. L. et al. Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+. Nature 568, 235–239 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  253. Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902.e21 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  254. Saunders, A. et al. Molecular diversity and specializations among the cells of the adult mouse brain. Cell 174, 1015–1030.e16 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  255. Kennedy, D. W. & Abkowitz, J. L. Kinetics of central nervous system microglial and macrophage engraftment: analysis using a transgenic bone marrow transplantation model. Blood 90, 986–993 (1997).

    Article  CAS  PubMed  Google Scholar 

  256. Hoeffel, G. et al. C-Myb+ erythro-myeloid progenitor-derived fetal monocytes give rise to adult tissue-resident macrophages. Immunity 42, 665–678 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  257. Gomez Perdiguero, E. et al. Tissue-resident macrophages originate from yolk-sac-derived erythro-myeloid progenitors. Nature 518, 547–551 (2015).

    Article  PubMed  Google Scholar 

  258. Akashi, K., Traver, D., Miyamoto, T. & Weissman, I. L. A clonogenic common myeloid progenitor that gives rise to all myeloid lineages. Nature 404, 193–197 (2000).

    Article  CAS  PubMed  Google Scholar 

  259. Wendeln, A.-C. et al. Innate immune memory in the brain shapes neurological disease hallmarks. Nature 556, 332–338 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  260. Hussain, S. F. et al. A novel small molecule inhibitor of signal transducers and activators of transcription 3 reverses immune tolerance in malignant glioma patients. Cancer Res. 67, 9630–9636 (2007).

    Article  CAS  PubMed  Google Scholar 

  261. Grassivaro, F. et al. Convergence between microglia and peripheral macrophages phenotype during development and neuroinflammation. J. Neurosci. 40, 784–795 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  262. Shemer, A. et al. Engrafted parenchymal brain macrophages differ from microglia in transcriptome, chromatin landscape and response to challenge. Nat. Commun. 9, 5206 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was supported by grants NS102807, ES02530, ES029136, AI126880 and AI149699 from the NIH; RG4111A1 and JF2161-A-5 from the NMSS, PA-1604-08459 from the International Progressive MS Alliance and the Jennifer Oppenheimer Cancer Research Initiative to F.J.Q. B.M.A. was supported by grant K12CA090354 from NIH. C.F.A. was supported by a scholarship from the German Academic Exchange Service (DAAD). M.A.W. was supported by NIH (1K99NS114111, F32NS101790), a training grant from the NIH and Dana-Farber Cancer Institute (T32CA207201), a traveling neuroscience fellowship from the Program in Interdisciplinary Neuroscience at BWH, and the Women’s Brain Initiative at BWH. EAC acknowledges support from R01NS110942, P01CA163205, P01CA069246, P01CA236749 and DoD WB1XWIH2010017. DAR acknowledges support from the Jennifer Oppenheimer Cancer Research Initiative, the Ben and Catherine Ivy Foundation, and PO1CA236749.

Author information

Author notes

  1. These authors contributed equally: Brian M. Andersen, Camilo Faust Akl.

Authors and Affiliations

  1. Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Brian M. Andersen, Camilo Faust Akl, Michael A. Wheeler & Francisco J. Quintana

  2. Center for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA

    Brian M. Andersen & David A. Reardon

  3. Department of Neurosurgery, Brigham and Women’s Hospital, Boston, MA, USA

    E. Antonio Chiocca

  4. Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Michael A. Wheeler & Francisco J. Quintana

Authors
  1. Brian M. Andersen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Camilo Faust Akl
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michael A. Wheeler
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. E. Antonio Chiocca
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. David A. Reardon
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Francisco J. Quintana
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

B.M.A., C.F.A., and F.J.Q. conceptualized the review. B.M.A. and C.F.A. performed literature research and wrote the manuscript. B.M.A., C.F.A., F.J.Q., D.A.R., E.A.C. and M.A.W. read and edited the review.

Corresponding author

Correspondence to Francisco J. Quintana.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information

Nature Reviews Cancer thanks S. Mitra, who co-reviewed with S. Lakschmanachetty, M. Valiente, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

Adult Astrocyte RNA-Seq Explorer: http://astrocyternaseq.org

Brain Immune Atlas: http://www.brainimmuneatlas.org

Brain TIME: https://joycelab.shinyapps.io/braintime

DropViz: http://dropviz.org

GBMseq: http://GBMseq.org

Glioma Microglia RNA Expression: http://www.glioma-microglia.com

Myeloid Single-cell RNA-Seq: https://myeloidsc.appspot.com

RecuR: http://recur.bioinfo.cnio.es/

Single Cell Portal at the Broad Institute: https://singlecell.broadinstitute.org/single_cell/study/SCP393/single-cell-rna-seq-of-adult-and-pediatric-glioblastoma

UCSC Cell Browser: http://gbm.cells.ucsc.edu

Glossary

Brain tumour microenvironment

(TME). The dynamic, heterogeneous mixture of extracellular matrix and malignant and non-malignant cells, including neurons, glia, leukocytes and endothelial cells, that make up the gross brain tumour mass. Half or more of the cells within the brain tumour microenvironment, in particular in glioma, are non-neoplastic.

Cell types

The stable identities of cells, primarily defined by intrinsic gene expression programmes, which contain permanent traits, including the potential to express certain genes and exert certain functions in response to external signals.

Cell states

Within cell types, states are defined by the current gene expression, metabolic or functional conditions, which are a product of external signals from infection, inflammation, ageing or other disease. The duration of each cell state may be a function of ongoing signalling.

Microglia

CNS-resident phagocytic cells primarily derived from the yolk sac with multiple roles in the development of disease, including synapse, surveillance and cell debris engulfment, cytokine production, and cross-talk with astrocytes and oligodendrocytes.

Multi-omic studies

Approaches that include the quantification and characterization of data from various molecular domains such as the genome, transcriptome, proteome, metabolome and epigenome.

Isocitrate dehydrogenase

(IDH1 or IDH2). Enzymes in the tricarboxylic acid cycle that catalyse the decarboxylation of isocitrate, producing alpha-ketoglutarate and carbon dioxide. Some mutations in IDH lead to the production of 2-hydroxyglutarate, a metabolite whose accumulation leads to genomic instability of glial cells through DNA methylation.

Mesenchymal-like

One of the four transcriptional meta-signatures of GBM defined by bulk RNA sequencing featuring loss of neurofibromin 1 (NF1) expression and increased expression of mesenchymal-related, hypoxia-response, stress and glycolytic genes. It was associated with increased tumour-associated macrophage infiltration and a more immunosuppressive tumour-associated macrophage phenotype, suggesting its relevance for tumour–tumour microenvironment cross-talk.

Extracellular membrane particles

Subcellular particles shed from malignant or non-malignant cells that are composed of a lipid bilayer with variable size and cargo, including proteins, metabolites and nucleic acids. Communication with neighbouring and sometimes distant cells is possible through their contents.

Mass cytometry

A cytometric technique that quantifies protein expression at the single-cell level by combining the use of rare earth metal isotope-conjugated antibodies and cytometry by time of flight (CyTOF).

Cellular indexing of transcriptomes and epitopes by sequencing

(CITE-seq). Combining DNA barcode-conjugated antibody labelling with single-cell RNA sequencing to enable immunophenotyping and unbiased transcriptome analysis.

Blood–brain barrier

A variety of features specific to brain vasculature that limit the influx of chemicals or immune cells in addition to the active efflux of chemical molecules, thereby limiting neurotoxicity.

Myeloid-derived suppressor cells

(MDSCs). A heterogeneous group of immature myeloid cells that contain monocyte-like and granulocyte-like subsets, which inhibit anti-tumour T cell responses through ARG1, IL-10 and TGFβ.

Ectoenzyme

An extracellular enzyme that can be membrane bound or secreted.

Blood–tumour barrier

Heterogeneous impairment of the blood–brain barrier and the interface between the blood and tumour due to tissue destruction by tumour growth and neoangiogenesis, resulting in altered but not necessarily efficient penetration of drug molecules and immune molecules.

Ontogenies

The origins and development of specific cell types.

Proneural subtype of GBM

One of four subtypes defined by bulk RNA sequencing of GBM through the Cancer Genome Atlas (TCGA), characterized by elevated expression of PDGFRA and CDK4. Originally, it was thought that each tumour represents a distinct subtype, but single-cell RNAseq of GBM revealed that all four subtypes can be detected within each tumour with varying proportions. More recently, the proneural subtype has been hypothesized to coincide with the oligodendrocyte-like and neural progenitor-like cellular states identified by single-cell RNA sequencing.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Andersen, B.M., Faust Akl, C., Wheeler, M.A. et al. Glial and myeloid heterogeneity in the brain tumour microenvironment. Nat Rev Cancer 21, 786–802 (2021). https://doi.org/10.1038/s41568-021-00397-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41568-021-00397-3

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer