• Users Online: 972
  • Print this page
  • Email this page


 
 
Table of Contents
REVIEW
Year : 2022  |  Volume : 5  |  Issue : 2  |  Page : 56-61

Overcoming T-cell exhaustion in glioblastoma: A narrative review


1 Department of Neurosurgery, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
2 Department of Neurosurgery, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China; Department of Pathology, Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Il, USA

Date of Submission16-May-2022
Date of Decision14-Jun-2022
Date of Acceptance18-Jun-2022
Date of Web Publication26-Jul-2022

Correspondence Address:
Mr. Xisen Wang
Department of Neurosurgery, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin 300052
China
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/glioma.glioma_16_22

Rights and Permissions
  Abstract 


Immunotherapy is typically ineffective against glioblastoma (GBM) due to inherent and adaptive resistance. Initial immunotherapy results for GBM have been disappointing. In this regard, T-cell exhaustion is a major barrier to successful treatment. The recognition of exhausted CD8+ T cell (Tex) pedigree is currently undergoing a paradigm shift. This review introduces major findings in this field to provide an up-to-date perspective on epigenetic, transcriptional, metabolic, and spatial heterogeneity, as well as interactions with tumor microenvironment cells of anti-tumoral CD8+ Tex from the following aspects: (i) Epigenetic and transcriptional mechanisms underlying T-cell exhaustion, (ii) Metabolic factors underpinning T-cell exhaustion, (iii) Contribution of multiple cell types to T-cell exhaustion, (iv) Occurrence of T-cell exhaustion at multiple locations, and (v) T-cell exhaustion may not always be terminal. These novel insights afford a wide range of new therapeutic approaches to overcome T-cell exhaustion in GBM.

Keywords: Brain tumor, glioblastoma, immunotherapy, T-cell exhaustion, tumor microenvironment


How to cite this article:
Wang X, Wang X, Li J. Overcoming T-cell exhaustion in glioblastoma: A narrative review. Glioma 2022;5:56-61

How to cite this URL:
Wang X, Wang X, Li J. Overcoming T-cell exhaustion in glioblastoma: A narrative review. Glioma [serial online] 2022 [cited 2022 Aug 13];5:56-61. Available from: http://www.jglioma.com/text.asp?2022/5/2/56/352257




  Introduction Top


Among primary malignant tumors of the central nervous system, glioblastoma (GBM) is the most malignant and accounts for 49.1% of all primary malignant tumors.[1] The fifth edition of the WHO classification of tumors of the central nervous system (2021) integrates GBM as “glioblastoma, wild-type IDH, WHO Grade 4.”[2] Recent developments in multimodal 3D image fusion and neuronavigation, neuroelectrophysiological monitoring and wake-up surgery, intraoperative real-time imaging, and other technologies have optimized safer resection of malignant gliomas.[3] Standard treatment of GBM includes complete resection, chemotherapy, and radiotherapy. Despite these efforts, patients survive for 15 months on average, with fewer than 5% surviving for 5 years.[3]

Adjuvant chemotherapy and radiotherapy can prolong survival time but do not prevent drug resistance.[4] Glioma stem cells have been investigated as a source of drug resistance due to their strong DNA repair mechanisms that render resistance to this traditional therapy.[5] Due to tumor heterogeneity and molecular plasticity, targeted therapy may be unsuitable for GBM.[6] As immunotherapy has the potential to overcome these challenges, immunotherapy is being active sought as a treatment for GBM. Antigen-primed T-cells act as cytotoxic cells that penetrate healthy tissue and accumulate in tumors,[7] perform cytotoxic functions with cellular precision,[8] adapt to the changing molecular characteristics of tumors,[9] and generate memory T-cells.[10] However, immunotherapy for GBM has not followed the same trajectory as that for other tumors such as melanoma, non-small cell lung cancer, and prostate cancer. This could be underpinned by the high intrinsic and adaptive resistance of GBM alongside a more severe causal T-cell exhaustion signature.[11]

T-cell exhaustion occurs after repeated or long-term exposure to antigens under chronic inflammation conditions.[12] A key feature of Tex is the expression of various co-suppressor receptors, many of which act as alternative or classical immune checkpoints, including PD-1, 2B4, TIM-3, BTLA, CTLA-4, LAG-3, CD39, CD160, TIGIT, and VISTA.[13] Antagonism or blockade of PD-1 and CTLA-4 has been recognized as an Food and Drug Administration-approved anticancer strategy, which aims to enhance the function of T-cells in many malignant tumors, including melanoma and nonsmall cell lung cancer.[14] However, in GBM, this strategy has demonstrated limited efficacy. Accordingly, there is an urgent need to better understand T-cell exhaustion to overcome this major barrier. Here, we provide an overview of our current understanding of the T-cell exhaustion in GBM, with particular emphasis on new therapeutic approaches to overcome T cell exhaustion.


  Database Search Strategy Top


Literature review was performed using PubMed database. Most of the selected English language and full-text articles were published between June 2010 and June 2022. The following combinations of keywords were used to initially select the articles to be evaluated: Brain tumor, GBM, T-cell exhaustion, immunotherapy, and immune microenvironment.


  Epigenetic and Transcriptional Mechanisms Underlying T Cell Exhaustion Top


The typical characteristics of Tex are still under investigation and remain controversial. Extant evidence indicates that Tex has unique epigenetic and transcriptomic characteristics.[15] Under long-term chronic antigen stimulation of cancer tissue, naive CD8+ T-cells first develop into CD8+ Tex precursor (Texpre) and progenitor (Texprog) cells with stemness characteristics by maintaining TCF1 expression and PD1 inhibition under the continuous activity of NFAT, Nur77, and BACH2.[16],[17],[18] TCF-1 in conjunction with FOXO1 maintain stemness by promoting the expression of ID3, Eomes, Bcl-2, Bcl-6, and c-Myb, while inhibiting effector phenotype-associated transcription factors ID2, Blimp-1, T-bet, and RUNX3. This induces Tex to exhibit a memory-prone phenotype and long survival.[19],[20] This mechanism enables the body to maintain immune ability in a state of chronic inflammation without causing pathological immunity. Tex precursor and progenitor cells have been demonstrated to be present in the tumor-infiltrating lymphocyte (TIL) fraction of human melanoma and murine B16 tumors in vivo.[18] Further, CD8+ TCF1+ Tex respond to immune checkpoint blockade (ICB) treatment.[21] After ICB treatment or other various factors to decrease TCF1 expression, a T-bet-driven effector-like transition was rapidly induced in these cells, termed CD101 KLRG-1+ CX3CR1+ PD-1lowTim-3+ (Texint), accompanied by rapid proliferation and transient production of Granzyme B. Ultimately, the cell population develops into terminal exhausted T-cells (Textm), termed CD101+ KLRG-1 CX3CR1 PD-1highTim-3+ CD8+. The main difference between these cell types is the expression of the CD101 glycoprotein.[18],[21],[22] It has been reported that although CD101 is mainly expressed on macrophages, high levels of CD101 are negatively correlated with the prognosis of patients with GBM.[23] ATAC-seq revealed robust epigenetic remodeling in the course of Tex progenitor to Texint and Texint to Textm transitions. Indeed, during the Texprog to Texint transition, genes associated with progenitor biology (Tcf7 and Il7r) were epigenetically silenced and remained off thereafter. In contrast, during the Texint to Textm transition, the OCRs of genes encoding effector-related (Cx3cr1) and exhaustion-related (Nr4a, Cd160) proteins became readily available.[18] During this process, the high mobility group box protein TOX associated with thymocyte selection is co-upregulated with PD-1.[24] TOX is a nuclear protein that binds DNA in a sequence-independent manner.[25] TOX interacts directly with histone acetyltransferase bound to ORC1 (HBO1) and indirectly coordinates activity with enhancers of DNMT3A, DNMT3B, and EZH2, thereby epigenetically regulating changes in the expression of the aforementioned genes to promote the formation of terminally exhausted PD1high Tex.[25]

Epigenetic processes in conjunction with lineage-specific transcription factors direct exhausted T cell differentiation. Nevertheless, the mechanisms and activation of the differentiation process of T cell exhaustion and maintenance of stem cell-like phenotypes warrant further investigated. In this regard, there is a need to examine signaling pathways and cellular regulation in the course of T cell differentiation in patients with tumors to produce anti-tumor immunity in a controllable manner. The expression of genes that affect the differentiation and function of T cells can be regulated by targeting epigenetic enzymes or functionally related genomic loci regulated by these factors. This targeted approach may prevent some of the negative effects of genetic or pharmacological interventions and provide guidance for current ICB immunotherapy by promoting the differentiation of memory cells or by preventing the progression of T cells to end-stage exhaustion. Collectively, this highlights the importance of epigenetic contributions to T cell exhaustion. However, other cellular changes that require epigenetic reprogramming of T cell exhaustion, such as metabolic defects and stress responses, remain to be further explored.


  Metabolic Factors Underpinning T Cell Exhaustion Top


Glucose deprivation in the tumor microenvironment (TME) occurs predominantly due to the increase in glucose consumption in tumor cells. Glucose deprivation can inhibit the tumoricidal activity of TILs.[26],[27] Furthermore, arginine and tryptophan are strongly detected in dendritic cells, MDSCs, and TAMs. Deprivation of these amino acids may further impair metabolic fitness, altering TIL activation and differentiation programs.[28],[29] Mechanistically, indoleamine 2,3-dioxygenase activity may be caused by impaired mTOR activity and activation of GCN2 kinase, which can deplete tryptophan in TME and impair T-cell function.[30],[31] Kynurenine produced by tryptophan degradation can inhibit T-cell immunity by activating the aryl hydrocarbon receptor.[32] In contrast, arginine depletion can lead to decreased T-cell receptor expression, cytokine production, and T cell proliferation.[33],[34] The activation of T-cells also requires a large amount of methionine. Methionine acts as a methyl donor during cell methylation and plays a role in epigenetic reprogramming required for T cell differentiation.[35] A recent study reported a synergistic effect of the glutamate modulator BHV-4157 with anti-PD-L1 treatment in the GL261-C57BL/6 model, whereby mice did not exhibit survival benefits from BHV-4157 with prior depletion of CD4+ and CD8+ T cells.[36] Although glucose, tryptophan, arginine, methionine, and glutamate play key roles in T-cell activation and effector function,[27] their roles in T-cell exhaustion-directed deprivation of nutrients remain unclear. In this regard, the relative contribution of epigenetic and transcriptional regulation remains unclear.

In addition to these nutrients, hypoxia is another key factor.[37] In tumor models of colon cancer and melanoma, T-cell function can be improved by controlling the oxidative metabolism of tumor cells to reduce hypoxia.[38] It has been reported that an increase in tumor oxygen consumption is associated with weakening of immune responses and T-cell exhaustion.[39] A previous study has indicated that the lipid content of PD-1high CD8+ TILs from patients with non-small cell lung cancer was higher than that of PD-1low CD8+ TILs,[40] suggesting that lipid metabolism may be a cause of T cell exhaustion. In support of this, T-cell exhaustion in the B16 melanoma model has been demonstrated to be due to an abnormal increase in cholesterol uptake in CD8+ TILs via activation of the endoplasmic reticulum stress response.[41] Furthermore, mitochondrial fitness and endoplasmic reticulum stress can affect T-cell exhaustion directly by regulating metabolism or indirectly through epigenetic regulation through metabolites such as acetyl-CoA and methionine.[42] Future studies are warranted to elucidate the metabolic factors involved in exhausted T-cell differentiation.


  Contribution of Multiple Cell Types to T Cell Exhaustion Top


In the TME, chronic T-cell receptor stimulation, nutrient depletion, metabolic adaptation, and immune cells ubiquitous in tumors play key roles in T cell exhaustion.[43] Of note, GBM is an immune desert. With the exception of microglia, macrophages, and a small population of Treg, almost no other immune cells infiltrate GBM.[44] Treg cells often congregate abnormally in the TME and express immunosuppressive molecules, such as cytokines interleukin (IL)-10, IL-35, and transforming growth factor-β, which inhibit anti-tumor T cell responses.[45],[46] In addition, myeloid-derived suppressor cells, immature dendritic cells, and plasmacytoid dendritic cells express high levels of PD-L1, and the TME contains low levels of costimulatory ligands, which may be causes of T cell exhaustion.[47],[48]

GBM is characterized by the infiltration of glioma-associated macrophages (GAMs), which may constitute as much as 30%–50% of the total number of cells and can be replenished by mobilizing bone marrow-derived monocytes.[49],[50] In the immune microenvironment of GBM, GAMs include microglia-derived and circulating blood-derived macrophages, which are classified into M1-type and M2-type with tumor-suppressive and tumor-promoting effects, respectively.[51],[52] Based on their expression of IL-10 and PD-L1, GAMs have been recognized to weaken T cell-associated anti-tumor responses and promote T cell exhaustion. Targeting the myeloid population to reverse exhaustion typically requires activation of the myeloid population, that is, suppressing the M2 phenotype and activating the antigen-presenting capacity of macrophages.[53] Research has revealed that CSF1R inhibition affected glioma progression from various aspects.[54] In a study of CSF1R-blocking antibody in a GBM preclinical model, it was observed that M2-polarized macrophages were blocked. However, phase II trials in 37 patients with recurrent GBM revealed that the oral CSF-1R inhibitor PLX3397 did not improve survival rate.[55] Moreover, CD47-blocking antibodies have been demonstrated to reprogram both microglia and TAMs to an M1 phenotype and attack tumor cells in GBM models.[56],[57],[58],[59] More studies are warranted to determine whether these strategies or other monocyte-directed methods can lead to the clinical regression of GBM.

Our current understanding of the polarization state of tumor-associated macrophages in the TME has been derived from the pregenomic era and is predominantly based on in vitro experimental systems.[60] More recent studies based on epigenetic, transcriptomic, and single-cell omics analysis have demonstrated that macrophages are highly plastic and can exhibit pro-inflammatory M (interferon-γ) and anti-inflammatory effects in response to different environmental stimuli.[61],[62] The role of M (IL-4) is an intermediate or even dual phenotype between the two extreme phenotypes.[63] Given that GBM is highly heterogeneous,[50] the infiltration and polarization of immune cells within the tumor are likely to exhibit distinct spatiotemporal characteristics and corresponding functional states. Investigations regarding the spatiotemporal impact of the functional state of GAMs on T cell exhaustion will have major therapeutic implications.


  Occurrence of T Cell Exhaustion at Multiple Locations Top


Antigen presentation by dendritic cells and macrophages as well as cytotoxic activation of CD8+ T cells occur predominantly in the lymph nodes (LNs).[64] Using TLR3 activation and synergism with anti-PD-1 in GBM promotes antigen presentation at cervical LNs but not at the tumor site.[64] Moreover, precursor Tex are positive for CD69 and localized to the LN.[18] A recent study reported that GBM tumor-bearing mice with anti-PD-L1 gel implanted locally in the deep cervical or inguinal LNs exhibited significantly better survival benefits compared to the ones with systemic anti-PD-L1 treatment.[64] This suggests that ICB therapy at LNs may be an alternative to the currently recommended systemic or tumor-localized ICB therapy. In this regard, activation of antigen-presenting cells for antigen presentation combined with sufficiently potent anti-PD-L1 therapy peripherally may relieve the highly exhausted state of T cells in GBM.


  T Cell Exhaustion May Not Always Be Terminal Top


An in-depth understanding of CD8+ Tex and its potential regulatory mechanisms may facilitate the development of novel therapeutic approaches, such as stimulating and stabilizing stem-like states or enhancing memory cell lineages.[43] This may be achieved simply by expanding CD8+ T cell responses via regulation of Texprog and Texint, and directly forcing T cells to maintain a transient state of cell lysis through pharmacological antagonism of TOX or related depletion mediators.[43] If maintaining stable anti-tumor CD8+ T cells is not possible, repeated infusion of adoptive cell therapy may be required to maximize the response.[65] Currently, autologous CD8+ T cells can be induced to express new antigen-specific T-cell receptor or chimeric antigen receptor by genetic engineering.[66] This may allow an unlimited source of artificially generated anti-tumor CD8+ T cells, thus overcoming the inevitable challenges of T-cell exhaustion. Adoptive cell therapy can also be modified by gene-editing techniques to resist fatigue or maintain stemness.[67] In an orthotopic xenograft model, the latest GD2 chimeric antigen receptor T cell therapy for diffuse midline GBM cleared the engrafted tumor, leaving a minimal amount of residual GD2-low glioma cells.[68] In a phase I clinical trial, three of the first four patients exhibited clinical and radiological improvements, with elevated levels of pro-inflammatory cytokines in plasma and cerebrospinal fluid.[69] Collectively, these findings indicate that Tex is a special differentiation state, and irreversibility constitutes a feature of only a small cluster of Tex. Further research is needed to elucidate the mechanisms underlying the functions and characteristics of other reversible populations to derive effective solutions. In this regard, exhaustion may not always be terminal.


  Limitations Top


This review has potential limitations due to the rapidly expanding field, potential gaps in the literature search and aggregation process, and author bias that may inadvertently lead to the omission of potentially relevant work.


  Conclusion Top


Currently available treatment options for GBM remain ineffective. Given widespread ICB failure, it is essential to identify innovative approaches to stimulate tumor immunity of GBM. By comparing chronic inflammation and immunotherapy features with other extracranial tumors, research progress on GBM immunotherapy may be accelerated. Notably, clinical researchers are faced with the issue of overcoming T-cell exhaustion as well as patient specificity, including specificity of the tumor itself and the body's response to therapy. More comprehensive studies on glioma tumor heterogeneity and immune signatures, including immune cell activation status and immune stimulatory/inhibitory molecular expression profiles, are urgently needed to elucidate the spatiotemporal crosstalk between tumor cells and immunity in this heterogeneous tumor.

Acknowledgments

Nil.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Ostrom QT, Cioffi G, Waite K, Kruchko C, Barnholtz-Sloan JS. CBTRUS statistical report: Primary brain and other central nervous system tumors diagnosed in the United States in 2014-2018. Neuro Oncol 2021;23:i1-105.  Back to cited text no. 1
    
2.
Louis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Figarella-Branger D, et al. The 2021 WHO Classification of Tumors of the Central Nervous System: A summary. Neuro Oncol 2021;23:1231-51.  Back to cited text no. 2
    
3.
Jiang T, Nam DH, Ram Z, Poon WS, Wang J, Boldbaatar D, et al. Clinical practice guidelines for the management of adult diffuse gliomas. Cancer Lett 2021;499:60-72.  Back to cited text no. 3
    
4.
Chen J, Li Y, Yu TS, McKay RM, Burns DK, Kernie SG, et al. A restricted cell population propagates glioblastoma growth after chemotherapy. Nature 2012;488:522-6.  Back to cited text no. 4
    
5.
Bao S, Wu Q, McLendon RE, Hao Y, Shi Q, Hjelmeland AB, et al. Glioma stem cells promote radioresistance by preferential activation of the DNA damage response. Nature 2006;444:756-60.  Back to cited text no. 5
    
6.
Schäfer N, Gielen GH, Rauschenbach L, Kebir S, Till A, Reinartz R, et al. Longitudinal heterogeneity in glioblastoma: Moving targets in recurrent versus primary tumors. J Transl Med 2019;17:96.  Back to cited text no. 6
    
7.
Li A, Wu Y, Linnoila J, Pulli B, Wang C, Zeller M, et al. Surface biotinylation of cytotoxic T lymphocytes for in vivo tracking of tumor immunotherapy in murine models. Cancer Immunol Immunother 2016;65:1545-54.  Back to cited text no. 7
    
8.
O'Rourke DM, Nasrallah MP, Desai A, Melenhorst JJ, Mansfield K, Morrissette JJ, 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 2017;9:eaaa0984.  Back to cited text no. 8
    
9.
Memarnejadian A, Meilleur CE, Shaler CR, Khazaie K, Bennink JR, Schell TD, et al. PD-1 blockade promotes epitope spreading in anticancer CD8+ T cell responses by preventing fratricidal death of subdominant clones to relieve immunodomination. J Immunol 2017;199:3348-59.  Back to cited text no. 9
    
10.
Mathios D, Kim JE, Mangraviti A, Phallen J, Park CK, Jackson CM, et al. Anti-PD-1 antitumor immunity is enhanced by local and abrogated by systemic chemotherapy in GBM. Sci Transl Med 2016;8:370ra180.  Back to cited text no. 10
    
11.
Jackson CM, Choi J, Lim M. Mechanisms of immunotherapy resistance: Lessons from glioblastoma. Nat Immunol 2019;20:1100-9.  Back to cited text no. 11
    
12.
Hellström I, Hellström KE, Pierce GE, Yang JP. Cellular and humoral immunity to different types of human neoplasms. Nature 1968;220:1352-4.  Back to cited text no. 12
    
13.
Mognol GP, Spreafico R, Wong V, Scott-Browne JP, Togher S, Hoffmann A, et al. Exhaustion-associated regulatory regions in CD8+ tumor-infiltrating T cells. Proc Natl Acad Sci U S A 2017;114:E2776-85.  Back to cited text no. 13
    
14.
Medikonda R, Dunn G, Rahman M, Fecci P, Lim M. A review of glioblastoma immunotherapy. J Neurooncol 2021;151:41-53.  Back to cited text no. 14
    
15.
Henning AN, Roychoudhuri R, Restifo NP. Epigenetic control of CD8+T cell differentiation. Nat Rev Immunol 2018;18:340-56.  Back to cited text no. 15
    
16.
McLane LM, Ngiow SF, Chen Z, Attanasio J, Manne S, Ruthel G, et al. Role of nuclear localization in the regulation and function of T-bet and Eomes in exhausted CD8 T cells. Cell Rep 2021;35:109120.  Back to cited text no. 16
    
17.
Paley MA, Kroy DC, Odorizzi PM, Johnnidis JB, Dolfi DV, Barnett BE, et al. Progenitor and terminal subsets of CD8+ T cells cooperate to contain chronic viral infection. Science 2012;338:1220-5.  Back to cited text no. 17
    
18.
Beltra JC, Manne S, Abdel-Hakeem MS, Kurachi M, Giles JR, Chen Z, et al. Developmental relationships of four exhausted CD8+T cell subsets reveals underlying transcriptional and epigenetic landscape control mechanisms. Immunity 2020;52:825-41.e8.  Back to cited text no. 18
    
19.
Pais Ferreira D, Silva JG, Wyss T, Fuertes Marraco SA, Scarpellino L, Charmoy M, et al. Central memory CD8+ T cells derive from stem-like Tcf7hi effector cells in the absence of cytotoxic differentiation. Immunity 2020;53:985- 1000.e11.  Back to cited text no. 19
    
20.
Wu T, Ji Y, Moseman EA, Xu HC, Manglani M, Kirby M, et al. The TCF1-Bcl6 axis counteracts type I interferon to repress exhaustion and maintain T cell stemness. Sci Immunol 2016;1:eaai8593.  Back to cited text no. 20
    
21.
Hudson WH, Gensheimer J, Hashimoto M, Wieland A, Valanparambil RM, Li P, et al. Proliferating transitory T cells with an effector-like transcriptional signature emerge from PD-1+ Stem-like CD8+ T cells during chronic infection. Immunity 2019;51:1043-58.e4.  Back to cited text no. 21
    
22.
Pauken KE, Sammons MA, Odorizzi PM, Manne S, Godec J, Khan O, et al. Epigenetic stability of exhausted T cells limits durability of reinvigoration by PD-1 blockade. Science 2016;354:1160-5.  Back to cited text no. 22
    
23.
Liu Y, Yao R, Shi Y, Liu Y, Liu H, Liu J, et al. Identification of CD101 in Glioma: A novel prognostic indicator expressed on M2 macrophages. Front Immunol 2022;13:845223.  Back to cited text no. 23
    
24.
Khan O, Giles JR, McDonald S, Manne S, Ngiow SF, Patel KP, et al. TOX transcriptionally and epigenetically programs CD8+ T cell exhaustion. Nature 2019;571:211-8.  Back to cited text no. 24
    
25.
Zeng Z, Wei F, Ren X. Exhausted T cells and epigenetic status. Cancer Biol Med 2020;17:923-36.  Back to cited text no. 25
    
26.
Chang CH, Qiu J, O'Sullivan D, Buck MD, Noguchi T, Curtis JD, et al. Metabolic competition in the tumor microenvironment is a driver of cancer progression. Cell 2015;162:1229-41.  Back to cited text no. 26
    
27.
Mohan AA, Tomaszewski WH, Haskell-Mendoza AP, Hotchkiss KM, Singh K, Reedy JL, et al. Targeting immunometabolism in glioblastoma. Front Oncol 2021;11:696402.  Back to cited text no. 27
    
28.
Yan Y, Zhang GX, Gran B, Fallarino F, Yu S, Li H, et al. IDO upregulates regulatory T cells via tryptophan catabolite and suppresses encephalitogenic T cell responses in experimental autoimmune encephalomyelitis. J Immunol 2010;185:5953-61.  Back to cited text no. 28
    
29.
Speiser DE, Ho PC, Verdeil G. Regulatory circuits of T cell function in cancer. Nat Rev Immunol 2016;16:599-611.  Back to cited text no. 29
    
30.
Munn DH, Sharma MD, Baban B, Harding HP, Zhang Y, Ron D, et al. GCN2 kinase in T cells mediates proliferative arrest and anergy induction in response to indoleamine 2,3-dioxygenase. Immunity 2005;22:633-42.  Back to cited text no. 30
    
31.
Metz R, Rust S, Duhadaway JB, Mautino MR, Munn DH, Vahanian NN, et al. IDO inhibits a tryptophan sufficiency signal that stimulates mTOR: A novel IDO effector pathway targeted by D-1-methyl-tryptophan. Oncoimmunology 2012;1:1460-8.  Back to cited text no. 31
    
32.
Opitz CA, Litzenburger UM, Sahm F, Ott M, Tritschler I, Trump S, et al. An endogenous tumour-promoting ligand of the human aryl hydrocarbon receptor. Nature 2011;478:197-203.  Back to cited text no. 32
    
33.
Das A, Hoare M, Davies N, Lopes AR, Dunn C, Kennedy PT, et al. Functional skewing of the global CD8 T cell population in chronic hepatitis B virus infection. J Exp Med 2008;205:2111-24.  Back to cited text no. 33
    
34.
Rodriguez PC, Ernstoff MS, Hernandez C, Atkins M, Zabaleta J, Sierra R, et al. Arginase I-producing myeloid-derived suppressor cells in renal cell carcinoma are a subpopulation of activated granulocytes. Cancer Res 2009;69:1553-60.  Back to cited text no. 34
    
35.
Sinclair LV, Howden AJ, Brenes A, Spinelli L, Hukelmann JL, Macintyre AN, et al. Antigen receptor control of methionine metabolism in T cells. Elife 2019;8:e44210.  Back to cited text no. 35
    
36.
Medikonda R, Choi J, Pant A, Saleh L, Routkevitch D, Tong L, et al. Synergy between glutamate modulation and anti-programmed cell death protein 1 immunotherapy for glioblastoma. J Neurosurg 2022;136:379-88.  Back to cited text no. 36
    
37.
Hu J, Li X, Yang L, Li H. Hypoxia, a key factor in the immune microenvironment. Biomed Pharmacother 2022;151:113068.  Back to cited text no. 37
    
38.
Scharping NE, Menk AV, Whetstone RD, Zeng X, Delgoffe GM. Efficacy of PD-1 blockade is potentiated by metformin-induced reduction of tumor hypoxia. Cancer Immunol Res 2017;5:9-16.  Back to cited text no. 38
    
39.
Najjar YG, Menk AV, Sander C, Rao U, Karunamurthy A, Bhatia R, et al. Tumor cell oxidative metabolism as a barrier to PD-1 blockade immunotherapy in melanoma. JCI Insight 2019;4:124989.  Back to cited text no. 39
    
40.
Thommen DS, Koelzer VH, Herzig P, Roller A, Trefny M, Dimeloe S, et al. A transcriptionally and functionally distinct PD-1+ CD8+ T cell pool with predictive potential in non-small-cell lung cancer treated with PD-1 blockade. Nat Med 2018;24:994-1004.  Back to cited text no. 40
    
41.
Ma X, Bi E, Lu Y, Su P, Huang C, Liu L, et al. Cholesterol induces CD8+T cell exhaustion in the tumor microenvironment. Cell Metab 2019;30:143-56.e5.  Back to cited text no. 41
    
42.
Franco F, Jaccard A, Romero P, Yu YR, Ho PC. Metabolic and epigenetic regulation of T-cell exhaustion. Nat Metab 2020;2:1001-12.  Back to cited text no. 42
    
43.
Zebley CC, Youngblood B. Mechanisms of T cell exhaustion guiding next-generation immunotherapy. Trends Cancer 2022:S2405-7.  Back to cited text no. 43
    
44.
Daubon T, Hemadou A, Romero Garmendia I, Saleh M. Glioblastoma immune landscape and the potential of new immunotherapies. Front Immunol 2020;11:585616.  Back to cited text no. 44
    
45.
Collison LW, Workman CJ, Kuo TT, Boyd K, Wang Y, Vignali KM, et al. The inhibitory cytokine IL-35 contributes to regulatory T-cell function. Nature 2007;450:566-9.  Back to cited text no. 45
    
46.
Wang H, Franco F, Ho PC. Metabolic regulation of tregs in cancer: Opportunities for immunotherapy. Trends Cancer 2017;3:583-92.  Back to cited text no. 46
    
47.
Yi JS, Cox MA, Zajac AJ. T-cell exhaustion: Characteristics, causes and conversion. Immunology 2010;129:474-81.  Back to cited text no. 47
    
48.
Kim YJ, Park SJ, Broxmeyer HE. Phagocytosis, a potential mechanism for myeloid-derived suppressor cell regulation of CD8+ T cell function mediated through programmed cell death-1 and programmed cell death-1 ligand interaction. J Immunol 2011;187:2291-301.  Back to cited text no. 48
    
49.
Quail DF, Joyce JA. The microenvironmental landscape of brain tumors. Cancer Cell 2017;31:326-41.  Back to cited text no. 49
    
50.
Chen Z, Hambardzumyan D. Immune microenvironment in glioblastoma subtypes. Front Immunol 2018;9:1004.  Back to cited text no. 50
    
51.
Markwell SM, Ross JL, Olson CL, Brat DJ. Necrotic reshaping of the glioma microenvironment drives disease progression. Acta Neuropathol 2022;143:291-310.  Back to cited text no. 51
    
52.
Tao W, Chu C, Zhou W, Huang Z, Zhai K, Fang X, et al. Dual Role of WISP1 in maintaining glioma stem cells and tumor-supportive macrophages in glioblastoma. Nat Commun 2020;11:3015.  Back to cited text no. 52
    
53.
Li M, He L, Zhu J, Zhang P, Liang S. Targeting tumor-associated macrophages for cancer treatment. Cell Biosci 2022;12:85.  Back to cited text no. 53
    
54.
Pyonteck SM, Akkari L, Schuhmacher AJ, Bowman RL, Sevenich L, Quail DF, et al. CSF-1R inhibition alters macrophage polarization and blocks glioma progression. Nat Med 2013;19:1264-72.  Back to cited text no. 54
    
55.
Butowski N, Colman H, De Groot JF, Omuro AM, Nayak L, Wen PY, 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 Oncol 2016;18:557-64.  Back to cited text no. 55
    
56.
Zhu H, Leiss L, Yang N, Rygh CB, Mitra SS, Cheshier SH, et al. Surgical debulking promotes recruitment of macrophages and triggers glioblastoma phagocytosis in combination with CD47 blocking immunotherapy. Oncotarget 2017;8:12145-57.  Back to cited text no. 56
    
57.
Zhang M, Hutter G, Kahn SA, Azad TD, Gholamin S, Xu CY, et al. Anti-CD47 treatment stimulates phagocytosis of glioblastoma by M1 and M2 polarized macrophages and promotes M1 polarized macrophages in vivo. PLoS One 2016;11:e0153550.  Back to cited text no. 57
    
58.
Feng M, Chen JY, Weissman-Tsukamoto R, Volkmer JP, Ho PY, McKenna KM, et al. Macrophages eat cancer cells using their own calreticulin as a guide: Roles of TLR and Btk. Proc Natl Acad Sci U S A 2015;112:2145-50.  Back to cited text no. 58
    
59.
Hutter G, Theruvath J, Graef CM, Zhang M, Schoen MK, Manz EM, et al. Microglia are effector cells of CD47-SIRPα antiphagocytic axis disruption against glioblastoma. Proc Natl Acad Sci U S A 2019;116:997-1006.  Back to cited text no. 59
    
60.
Mills CD, Kincaid K, Alt JM, Heilman MJ, Hill AM. M-1/M-2 macrophages and the Th1/Th2 paradigm. J Immunol 2000;164:6166-73.  Back to cited text no. 60
    
61.
Ma RY, Black A, Qian BZ. Macrophage diversity in cancer revisited in the era of single-cell omics. Trends Immunol 2022;43:546-63.  Back to cited text no. 61
    
62.
Cao X, Lai SW, Chen S, Wang S, Feng M. Targeting tumor-associated macrophages for cancer immunotherapy. Int Rev Cell Mol Biol 2022;368:61-108.  Back to cited text no. 62
    
63.
Xue J, Schmidt SV, Sander J, Draffehn A, Krebs W, Quester I, et al. Transcriptome-based network analysis reveals a spectrum model of human macrophage activation. Immunity 2014;40:274-88.  Back to cited text no. 63
    
64.
Choi J, Pant A, Medikonda R, Kim YH, Routkevitch D, Saleh L, et al. Sustained localized delivery of immunotherapy to lymph nodes reverses immunosuppression and increases long-term survival in murine glioblastoma. Oncoimmunology 2021;10:1940673.  Back to cited text no. 64
    
65.
Dolina JS, Van Braeckel-Budimir N, Thomas GD, Salek-Ardakani S. CD8+ T cell exhaustion in cancer. Front Immunol 2021;12:715234.  Back to cited text no. 65
    
66.
Jin BY, Campbell TE, Draper LM, Stevanović S, Weissbrich B, Yu Z, et al. Engineered T cells targeting E7 mediate regression of human papillomavirus cancers in a murine model. JCI Insight 2018;3:99488.  Back to cited text no. 66
    
67.
Waldman AD, Fritz JM, Lenardo MJ. A guide to cancer immunotherapy: From T cell basic science to clinical practice. Nat Rev Immunol 2020;20:651-68.  Back to cited text no. 67
    
68.
Mount CW, Majzner RG, Sundaresh S, Arnold EP, Kadapakkam M, Haile S, et al. Potent antitumor efficacy of anti-GD2 CAR T cells in H3-K27M+ diffuse midline gliomas. Nat Med 2018;24:572-9.  Back to cited text no. 68
    
69.
Majzner RG, Ramakrishna S, Yeom KW, Patel S, Chinnasamy H, Schultz LM, et al. GD2-CAR T cell therapy for H3K27M-mutated diffuse midline gliomas. Nature 2022;603:934-41.  Back to cited text no. 69
    




 

Top
 
  Search
 
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

 
  In this article
Abstract
Introduction
Database Search ...
Epigenetic and T...
Metabolic Factor...
Contribution of ...
Occurrence of T ...
T Cell Exhaustio...
Limitations
Conclusion
References

 Article Access Statistics
    Viewed444    
    Printed12    
    Emailed0    
    PDF Downloaded68    
    Comments [Add]    

Recommend this journal