[en] In glioblastoma (GBM), tumour-associated microglia/macrophages (TAMs) represent the major cell type of the stromal compartment and contribute to tumour immune escape mechanisms. Thus, targeting TAMs is emerging as a promising strategy for immunotherapy. However, TAM heterogeneity and metabolic adaptation along GBM progression represent critical features for the design of effective TAM-targeted therapies. Here, we comprehensively study the cellular and molecular changes of TAMs in the GL261 GBM mouse model, combining single-cell RNA-sequencing with flow cytometry and immunohistological analyses along GBM progression and in the absence of Acod1 (also known as Irg1), a key gene involved in the metabolic reprogramming of macrophages towards an anti-inflammatory phenotype. Similarly to patients, we identify distinct TAM profiles, mainly based on their ontogeny, that reiterate the idea that microglia- and macrophage-like cells show key transcriptional differences and dynamically adapt along GBM stages. Notably, we uncover decreased antigen-presenting cell features and immune reactivity in TAMs along tumour progression that are instead enhanced in Acod1-deficient mice. Overall, our results provide insight into TAM heterogeneity and highlight a novel role for Acod1 in TAM adaptation during GBM progression.
Disciplines :
Oncology
Author, co-author :
Pires-Afonso, Yolanda; Neuro-Immunology Group, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg ; Doctoral School of Science and Technology, University of Luxembourg, Esch-sur-Alzette, Luxembourg
Muller, Arnaud; Quantitative Biology Unit, Bioinformatics Platform, Luxembourg Institute of Health, Luxembourg
Oudin, Anaïs; NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg
Yabo, Yahaya A; Doctoral School of Science and Technology, University of Luxembourg, Esch-sur-Alzette, Luxembourg ; NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg
SOUSA, Carole ; University of Luxembourg ; Neuro-Immunology Group, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg ; NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg
Scafidi, Andrea; Neuro-Immunology Group, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg ; Doctoral School of Science and Technology, University of Luxembourg, Esch-sur-Alzette, Luxembourg
Poli, Aurélie; Neuro-Immunology Group, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg
COSMA, Antonio ; University of Luxembourg ; Quantitative Biology Unit, National Cytometry Platform, Luxembourg Institute of Health, Luxembourg
HALDER, Rashi ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Scientific Central Services > Sequencing Platform
COOWAR, Djalil ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Scientific Central Services > Rodent facility
GOLEBIEWSKA, Anna ; University of Luxembourg ; NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg
SKUPIN, Alexander ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Integrative Cell Signalling ; National Centre for Microscopy and Imaging Research, University of California San Diego, La Jolla, CA, USA
NICLOU, Simone P. ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM) ; NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg ; KG Jebsen Brain Tumour Research Center, Department of Biomedicine, University of Bergen, Norway
MICHELUCCI, Alessandro ; University of Luxembourg ; Neuro-Immunology Group, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg
Action LIONS Vaincre le Cancer Fondation du Pélican de Mie et Pierre Hippert-Faber Fonds National de la Recherche Luxembourg Foundation for the National Institutes of Health H2020 Marie Skłodowska-Curie Actions
Funding text :
The authors thank Amandine Bernard for mouse genotyping and western blotting, Virginie Baus for helping with the MRI as well as Thomas Cerutti for the support with flow cytometry experiments. The authors are grateful to Dr Oihane Uriarte and Dr Tony Heurtaux for aiding with gentleMACS™ Dissociator. YPA and CS were supported by the Luxembourg National Research Fund (PRIDE15/10675146/CANBIO and AFR6916713, respectively) and the Fondation du Pélican de Mie et Pierre Hippert-Faber under the aegis of Fondation de Luxembourg. YAY was supported by GLIOTRAIN ITN funded by the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 766069 (The material presented and views expressed here are the responsibility of the author(s) only. The EU Commission takes no responsibility for any use made of the information set out). AS was supported by the C14/BM/7975668/CaSCAD project as well as by the National Biomedical Computation Resource (NBCR) through the NIH P41 GM103426 grant from the National Institutes of Health. AM was supported by Action Lions ‘Vaincre le Cancer’ Luxembourg. The authors acknowledge financial support by the Luxembourg Institute of Health (MIGLISYS) and the Luxembourg Centre for Systems Biomedicine.The authors thank Amandine Bernard for mouse genotyping and western blotting, Virginie Baus for helping with the MRI as well as Thomas Cerutti for the support with flow cytometry experiments. The authors are grateful to Dr Oihane Uriarte and Dr Tony Heurtaux for aiding with ™ Dissociator. YPA and CS were supported by the Luxembourg National Research Fund (PRIDE15/10675146/CANBIO and AFR6916713, respectively) and the Fondation du Pélican de Mie et Pierre Hippert‐Faber under the aegis of Fondation de Luxembourg. YAY was supported by GLIOTRAIN ITN funded by the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska‐Curie grant agreement No 766069 (The material presented and views expressed here are the responsibility of the author(s) only. The EU Commission takes no responsibility for any use made of the information set out). AS was supported by the C14/BM/7975668/CaSCAD project as well as by the National Biomedical Computation Resource (NBCR) through the NIH P41 GM103426 grant from the National Institutes of Health. AM was supported by Action Lions ‘Vaincre le Cancer’ Luxembourg. The authors acknowledge financial support by the Luxembourg Institute of Health (MIGLISYS) and the Luxembourg Centre for Systems Biomedicine. gentleMACS
Lathia JD, Heddleston JM, Venere M, Rich JN. Deadly teamwork: neural cancer stem cells and the tumor microenvironment. Cell Stem Cell. 2011;8:482–5. https://doi.org/10.1016/j.stem.2011.04.013
Venkatesan S, Swanton C. Tumor evolutionary principles: how intratumor heterogeneity influences cancer treatment and outcome. Am Soc Clin Oncol Educ Book. 2016;35:e141–9. https://doi.org/10.14694/EDBK_15893010.1200/EDBK_158930
Quail DF, Joyce JA. The microenvironmental landscape of brain tumors. Cancer Cell. 2017;31:326–41. https://doi.org/10.1016/j.ccell.2017.02.009
Ginhoux F, Greter M, Leboeuf M, Nandi S, See P, Gokhan S, et al. Fate mapping analysis reveals that adult microglia derive from primitive macrophages. Science. 2010;330:841–5. https://doi.org/10.1126/science.1194637
Schulz C, Gomez Perdiguero E, Chorro L, Szabo-Rogers H, Cagnard N, Kierdorf K, et al. A lineage of myeloid cells independent of Myb and hematopoietic stem cells. Science. 2012;336:86–90. https://doi.org/10.1126/science.1219179
Glass R, Synowitz M. CNS macrophages and peripheral myeloid cells in brain tumours. Acta Neuropathol. 2014;128:347–62. https://doi.org/10.1007/s00401-014-1274-2
Hambardzumyan D, Gutmann DH, Kettenmann H. The role of microglia and macrophages in glioma maintenance and progression. Nat Neurosci. 2016;19:20–7. https://doi.org/10.1038/nn.4185
Bowman RL, Klemm F, Akkari L, Pyonteck SM, Sevenich L, Quail DF, et al. Macrophage ontogeny underlies differences in tumor-specific education in brain malignancies. Cell Rep. 2016;17:2445–59. https://doi.org/10.1016/j.celrep.2016.10.052
Friebel E, Kapolou K, Unger S, Nunez NG, Utz S, Rushing EJ, et al. Single-cell mapping of human brain cancer reveals tumor-specific instruction of tissue-invading leukocytes. Cell. 2020;181:1626–1642.e20. https://doi.org/10.1016/j.cell.2020.04.055
Muller S, Kohanbash G, Liu SJ, Alvarado B, Carrera D, Bhaduri A, 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. 2017;18:234. https://doi.org/10.1186/s13059-017-1362-4
Szulzewsky F, Pelz A, Feng X, Synowitz M, Markovic D, Langmann T, et al. Glioma-associated microglia/macrophages display an expression profile different from M1 and M2 polarization and highly express Gpnmb and Spp1. PLoS One. 2015;10:e0116644. https://doi.org/10.1371/journal.pone.0116644
Zeiner PS, Preusse C, Golebiewska A, Zinke J, Iriondo A, Muller A, et al. Distribution and prognostic impact of microglia/macrophage subpopulations in gliomas. Brain Pathol. 2018;29:513–29. https://doi.org/10.1111/bpa.12690
MJC J, Sankowski R, Brendecke SM, Sagar, Locatelli G, Tai YH, et al. Single-cell profiling identifies myeloid cell subsets with distinct fates during neuroinflammation. Science. 2019;363:eaat7554. https://doi.org/10.1126/science.aat7554
Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, Goldman M, et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell. 2015;161:1202–14. https://doi.org/10.1016/j.cell.2015.05.002
Shalek AK, Satija R, Adiconis X, Gertner RS, Gaublomme JT, Raychowdhury R, et al. Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells. Nature. 2013;498:236–40. https://doi.org/10.1038/nature12172
Tang F, Barbacioru C, Wang Y, Nordman E, Lee C, Xu N, et al. mRNA-seq whole-transcriptome analysis of a single cell. Nat Methods. 2009;6:377–82. https://doi.org/10.1038/nmeth.1315
Darmanis S, Sloan SA, Croote D, Mignardi M, Chernikova S, Samghababi P, et al. Single-cell RNA-seq analysis of infiltrating neoplastic cells at the migrating front of human glioblastoma. Cell Rep. 2017;21:1399–410. https://doi.org/10.1016/j.celrep.2017.10.030
Michelucci A, Cordes T, Ghelfi J, Pailot A, Reiling N, Goldmann O, et al. Immune-responsive gene 1 protein links metabolism to immunity by catalyzing itaconic acid production. Proc Natl Acad Sci USA. 2013;110:7820–5. https://doi.org/10.1073/pnas.1218599110
Hooftman A, O'Neill LAJ. The immunomodulatory potential of the metabolite itaconate. Trends Immunol. 2019;40:687–98. https://doi.org/10.1016/j.it.2019.05.007
Mills EL, Ryan DG, Prag HA, Dikovskaya D, Menon D, Zaslona Z, et al. Itaconate is an anti-inflammatory metabolite that activates Nrf2 via alkylation of KEAP1. Nature. 2018;556:113–7. https://doi.org/10.1038/nature25986
Dominguez-Andres J, Novakovic B, Li Y, Scicluna BP, Gresnigt MS, Arts RJW, et al. The itaconate pathway is a central regulatory node linking innate immune tolerance and trained immunity. Cell Metab. 2019;29:211–220.e5. https://doi.org/10.1016/j.cmet.2018.09.003
Weiss JM, Davies LC, Karwan M, Ileva L, Ozaki MK, Cheng RY, et al. Itaconic acid mediates crosstalk between macrophage metabolism and peritoneal tumors. J Clin Invest. 2018;128:3794–805. https://doi.org/10.1172/JCI99169
Pires-Afonso Y, Niclou SP, Michelucci A. Revealing and harnessing tumour-associated microglia/macrophage heterogeneity in glioblastoma. Int J Mol Sci. 2020;21:689. https://doi.org/10.3390/ijms21030689
Cordes T, Wallace M, Michelucci A, Divakaruni AS, Sapcariu SC, Sousa C, et al. Immunoresponsive gene 1 and itaconate inhibit succinate dehydrogenase to modulate intracellular succinate levels. J Biol Chem. 2016;291:14274–84. https://doi.org/10.1074/jbc.M115.685792
Bougnaud S, Golebiewska A, Oudin A, Keunen O, Harter PN, Mader L, et al. Molecular crosstalk between tumour and brain parenchyma instructs histopathological features in glioblastoma. Oncotarget. 2016;7:31955–71. https://doi.org/10.18632/oncotarget.7454
Golebiewska A, Hau AC, Oudin A, Stieber D, Yabo YA, Baus V, et al. Patient-derived organoids and orthotopic xenografts of primary and recurrent gliomas represent relevant patient avatars for precision oncology. Acta Neuropathol. 2020;140:919–49. https://doi.org/10.1007/s00401-020-02226-7
Sousa C, Golebiewska A, Poovathingal SK, Kaoma T, Pires-Afonso Y, Martina S, et al. Single-cell transcriptomics reveals distinct inflammation-induced microglia signatures. EMBO Rep. 2018;19:e46171. https://doi.org/10.15252/embr.201846171
Wickham H, Averick M, Bryan J, Chang W, McGowan LDA, François R, et al. Welcome to the Tidyverse. J Open Source Softw. 2019;4:1686. https://doi.org/10.21105/joss.01686
Krijthe JH. Rtsne: T-distributed stochastic neighbor embedding using a Barnes-hut implementation. R package version 0.15; 2015.
McInnes L, Healy J, Astels S. Hdbscan: hierarchical density based clustering. J Open Source Softw. 2017;2:205. https://doi.org/10.21105/joss.00205
Qiu X, Mao Q, Tang Y, Wang L, Chawla R, Pliner HA, et al. Reversed graph embedding resolves complex single-cell trajectories. Nat Methods. 2017;14:979–82. https://doi.org/10.1038/nmeth.4402
Trapnell C, Cacchiarelli D, Grimsby J, Pokharel P, Li S, Morse M, et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat Biotechnol. 2014;32:381–6. https://doi.org/10.1038/nbt.2859
Buttini M, Orth M, Bellosta S, Akeefe H, Pitas RE, Wyss-Coray T, et al. Expression of human apolipoprotein E3 or E4 in the brains of Apoe−/− mice: isoform-specific effects on neurodegeneration. J Neurosci. 1999;19:4867–80.
Oh T, Fakurnejad S, Sayegh ET, Clark AJ, Ivan ME, Sun MZ, et al. Immunocompetent murine models for the study of glioblastoma immunotherapy. J Transl Med. 2014;12:107. https://doi.org/10.1186/1479-5876-12-107
Aslan K, Turco V, Blobner J, Sonner JK, Liuzzi AR, Nunez NG, et al. Heterogeneity of response to immune checkpoint blockade in hypermutated experimental gliomas. Nat Commun. 2020;11:931. https://doi.org/10.1038/s41467-020-14642-0
Fecci PE, Ochiai H, Mitchell DA, Grossi PM, Sweeney AE, Archer GE, et al. Systemic CTLA-4 blockade ameliorates glioma-induced changes to the CD4+ T cell compartment without affecting regulatory T-cell function. Clin Cancer Res. 2007;13:2158–67. https://doi.org/10.1158/1078-0432.CCR-06-2070
Qian J, Luo F, Yang J, Liu J, Liu R, Wang L, et al. TLR2 promotes glioma immune evasion by downregulating MHC class II molecules in microglia. Cancer Immunol Res. 2018;6:1220–33. https://doi.org/10.1158/2326-6066.CIR-18-0020
Khalsa JK, Cheng N, Keegan J, Chaudry A, Driver J, Bi WL, et al. Immune phenotyping of diverse syngeneic murine brain tumors identifies immunologically distinct types. Nat Commun. 2020;11:3912. https://doi.org/10.1038/s41467-020-17704-5
Cahoy JD, Emery B, Kaushal A, Foo LC, Zamanian JL, Christopherson KS, et al. A transcriptome database for astrocytes, neurons, and oligodendrocytes: a new resource for understanding brain development and function. J Neurosci. 2008;28:264–78. https://doi.org/10.1523/JNEUROSCI.4178-07.2008
Tasic B, Menon V, Nguyen TN, Kim TK, Jarsky T, Yao Z, et al. Adult mouse cortical cell taxonomy revealed by single cell transcriptomics. Nat Neurosci. 2016;19:335–46. https://doi.org/10.1038/nn.4216
Tabula Muris Consortium; Overall coordination; Logistical coordination; Organ collection and processing; Library preparation and sequencing; Computational data analysis; Cell type annotation; Writing group; Supplemental text writing group; Principal inves. Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. Nature. 2018;562:367–72. https://doi.org/10.1038/s41586-018-0590-4
Sankowski R, Bottcher C, Masuda T, Geirsdottir L, Sagar, Sindram E, et al. Mapping microglia states in the human brain through the integration of high-dimensional techniques. Nat Neurosci. 2019;22:2098–110. https://doi.org/10.1038/s41593-019-0532-y
Venteicher AS, Tirosh I, Hebert C, Yizhak K, Neftel C, Filbin MG, et al. Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq. Science. 2017;355:eaai8478. https://doi.org/10.1126/science.aai8478
Patel AP, Tirosh I, Trombetta JJ, Shalek AK, Gillespie SM, Wakimoto H, et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science. 2014;344:1396–401. https://doi.org/10.1126/science.1254257
Szatmari T, Lumniczky K, Desaknai S, Trajcevski S, Hidvegi EJ, Hamada H, et al. Detailed characterization of the mouse glioma 261 tumor model for experimental glioblastoma therapy. Cancer Sci. 2006;97:546–53. https://doi.org/10.1111/j.1349-7006.2006.00208.x
Schaaf MB, Garg AD, Agostinis P. Defining the role of the tumor vasculature in antitumor immunity and immunotherapy. Cell Death Dis. 2018;9:115. https://doi.org/10.1038/s41419-017-0061-0
Ochocka N, Segit P, Walentynowicz KA, Wojnicki K, Cyranowski S, Swatler J, et al. Single-cell RNA sequencing reveals functional heterogeneity of glioma-associated brain macrophages. Nat Commun. 2021;12:1151. https://doi.org/10.1038/s41467-021-21407-w
Pombo Antunes AR, Scheyltjens I, Lodi F, Messiaen J, Antoranz A, Duerinck J, et al. Single-cell profiling of myeloid cells in glioblastoma across species and disease stage reveals macrophage competition and specialization. Nat Neurosci. 2021;24:595–610. https://doi.org/10.1038/s41593-020-00789-y
Pinton L, Masetto E, Vettore M, Solito S, Magri S, D'Andolfi M, et al. The immune suppressive microenvironment of human gliomas depends on the accumulation of bone marrow-derived macrophages in the center of the lesion. J Immunother Cancer. 2019;7:58. https://doi.org/10.1186/s40425-019-0536-x
Alban TJ, Alvarado AG, Sorensen MD, Bayik D, Volovetz J, Serbinowski E, et al. Global immune fingerprinting in glioblastoma patient peripheral blood reveals immune-suppression signatures associated with prognosis. JCI Insight. 2018;3:e122264. https://doi.org/10.1172/jci.insight.122264
Zhao E, Maj T, Kryczek I, Li W, Wu K, Zhao L, et al. Cancer mediates effector T cell dysfunction by targeting microRNAs and EZH2 via glycolysis restriction. Nat Immunol. 2016;17:95–103. https://doi.org/10.1038/ni.3313
Woroniecka KI, Rhodin KE, Chongsathidkiet P, Keith KA, Fecci PE. T-cell dysfunction in glioblastoma: applying a new framework. Clin Cancer Res. 2018;24:3792–802. https://doi.org/10.1158/1078-0432.CCR-18-0047
Puchalski RB, Shah N, Miller J, Dalley R, Nomura SR, Yoon JG, et al. An anatomic transcriptional atlas of human glioblastoma. Science. 2018;360:660–3. https://doi.org/10.1126/science.aaf2666
Chen Z, Ross JL, Hambardzumyan D. Intravital 2-photon imaging reveals distinct morphology and infiltrative properties of glioblastoma-associated macrophages. Proc Natl Acad Sci USA. 2019;116:14254–9. https://doi.org/10.1073/pnas.1902366116
Cordes T, Michelucci A, Hiller K. Itaconic acid: the surprising role of an industrial compound as a mammalian antimicrobial metabolite. Annu Rev Nutr. 2015;35:451–73. https://doi.org/10.1146/annurev-nutr-071714-034243
Lampropoulou V, Sergushichev A, Bambouskova M, Nair S, Vincent EE, Loginicheva E, et al. Itaconate links inhibition of succinate dehydrogenase with macrophage metabolic remodeling and regulation of inflammation. Cell Metab. 2016;24:158–66. https://doi.org/10.1016/j.cmet.2016.06.004
Muri J, Wolleb H, Broz P, Carreira EM, Kopf M. Electrophilic Nrf2 activators and itaconate inhibit inflammation at low dose and promote IL-1beta production and inflammatory apoptosis at high dose. Redox Biol. 2020;36:101647. https://doi.org/10.1016/j.redox.2020.101647
Klemm F, Maas RR, Bowman RL, Kornete M, Soukup K, Nassiri S, et al. Interrogation of the microenvironmental landscape in brain tumors reveals disease-specific alterations of immune cells. Cell. 2020;181:1643–1660 e1617. https://doi.org/10.1016/j.cell.2020.05.007
Chen Z, Feng X, Herting CJ, Garcia VA, Nie K, Pong WW, et al. Cellular and molecular identity of tumor-associated macrophages in glioblastoma. Cancer Res. 2017;77:2266–78. https://doi.org/10.1158/0008-5472.CAN-16-2310
Zhang J, Sarkar S, Cua R, Zhou Y, Hader W, Yong VW. A dialog between glioma and microglia that promotes tumor invasiveness through the CCL2/CCR2/interleukin-6 axis. Carcinogenesis. 2012;33:312–9. https://doi.org/10.1093/carcin/bgr289
Calandra T, Roger T. Macrophage migration inhibitory factor: a regulator of innate immunity. Nat Rev Immunol. 2003;3:791–800. https://doi.org/10.1038/nri1200
Guda MR, Rashid MA, Asuthkar S, Jalasutram A, Caniglia JL, Tsung AJ, et al. Pleiotropic role of macrophage migration inhibitory factor in cancer. Am J Cancer Res. 2019;9:2760–73.
Borden EC, Sen GC, Uze G, Silverman RH, Ransohoff RM, Foster GR, et al. Interferons at age 50: past, current and future impact on biomedicine. Nat Rev Drug Discov. 2007;6:975–90. https://doi.org/10.1038/nrd2422
Taniguchi T, Ogasawara K, Takaoka A, Tanaka N. IRF family of transcription factors as regulators of host defense. Annu Rev Immunol. 2001;19:623–55. https://doi.org/10.1146/annurev.immunol.19.1.623
Lohoff M, Ferrick D, Mittrucker HW, Duncan GS, Bischof S, Rollinghoff M, et al. Interferon regulatory factor-1 is required for a T helper 1 immune response in vivo. Immunity. 1997;6:681–9. https://doi.org/10.1016/s1074-7613(00)80444-6
Ogasawara K, Hida S, Azimi N, Tagaya Y, Sato T, Yokochi-Fukuda T, et al. Requirement for IRF-1 in the microenvironment supporting development of natural killer cells. Nature. 1998;391:700–3. https://doi.org/10.1038/35636
Alsamman K, El-Masry OS. Interferon regulatory factor 1 inactivation in human cancer. Biosci Rep. 2018;38:BSR20171672. https://doi.org/10.1042/BSR20171672
Thorsson V, Gibbs DL, Brown SD, Wolf D, Bortone DS, Ou Yang TH, et al. The immune landscape of cancer. Immunity. 2018;48:812–830.e14. https://doi.org/10.1016/j.immuni.2018.03.023
Ashton-Rickardt PG. An emerging role for serine protease inhibitors in T lymphocyte immunity and beyond. Immunol Lett. 2013;152:65–76. https://doi.org/10.1016/j.imlet.2013.04.004
O'Neill LAJ, Artyomov MN. Itaconate: the poster child of metabolic reprogramming in macrophage function. Nat Rev Immunol. 2019;19:273–81. https://doi.org/10.1038/s41577-019-0128-5
Reardon DA, Brandes AA, Omuro A, Mulholland P, Lim M, Wick A, et al. Effect of nivolumab vs bevacizumab in patients with recurrent glioblastoma: the CheckMate 143 phase 3 randomized clinical trial. JAMA Oncol. 2020;6:1003–10. https://doi.org/10.1001/jamaoncol.2020.1024