CD8 T‐cells are an essential component of immune response to viral infections; however, in certain instances, such as chronic infections, they can reach an exhausted state, where T‐cells loose glycolytic activity together with cytotoxic capacity. Recent research has indicated that correcting this dysfunctional metabolic state could be key to reversing exhaustion and allowing for proper clearance of chronic viral infections. Here, we review current knowledge about T‐cell exhaustion during infection and discuss strategies targeting metabolism that hold promise for its reversal.

Keywords: CD8, chronic viral infection, glycolysis, metabolism, T‐cell exhaustion
Summary
CD8 T‐cells are an essential component of the adaptive immune response accountable for the clearance of virus‐infected cells via cytotoxic effector functions. Maintaining a specific metabolic profile is necessary for these T‐cells to sustain their effector functions and clear pathogens. When CD8 T‐cells are activated via T‐cell receptor recognition of viral antigen, they transition from a naïve to an effector state and eventually to a memory phenotype, and their metabolic profiles shift as the cells differentiate to accomidate different metabolic demands. However, in the context of particular chronic viral infections (CVIs), CD8 T‐cells can become metabolically dysfunctional in a state known as T‐cell exhaustion. In this state, CD8 T‐cells exhibit reduced effector functions and are unable to properly control pathogens. Clearing these chronic infections becomes progressively difficult as increasing numbers of the effector T‐cells become exhausted. Hence, reversal of this dysfunctional metabolic phenotype is vital when considering potential treatments of these infections and offers the opportunity for novel strategies for the development of therapies against CVIs. In this review we explore research implicating alteration of the metabolic state as a means to reverse CD8 T‐cell exhaustion in CVIs. These findings indicate that strategies targeting dysfunctional CD8 T‐cell metabolism could prove to be a promising option for successfully treating CVIs.
Abbreviations
- AKT
protein kinase B
- AMP
adenosine monophosphate
- AMPK
AMP‐activated protein kinase
- APCs
antigen‐presenting cells
- ATP
adenosine triphosphate
- CTLA‐4
cytotoxic T‐lymphocyte‐associated protein‐4
- CVIs
chronic viral infections
- DCs
dendritic cells
- FAO
fatty acid oxidation
- FoxO1
forkhead box protein O1
- GLS1
glutaminase 1
- GLUT
glucose transporters
- HBV
hepatitis B
- HCV
hepatitis C
- HIF1α
hypoxia‐inducible factor 1‐alpha
- HIV
human immunodeficiency virus
- IFNγ
interferon‐gamma
- IL
interleukin
- KHSV
Kaposi’s sarcoma‐associated herpesvirus
- LAG‐3
lymphocyte‐activation gene‐3
- LCMV
lymphocytic choriomeningitis virus
- MHC‐I
major histocompatibility complex class I
- miRNAs
micro‐RNAs
- mTOR
mammalian target of rapamycin
- NFAT
nuclear factor of activated T‐cells
- OXPHOS
oxidative phosphorylation
- p38 MAPK
p38 mitogen‐activated protein kinase
- PEP
phosphoenolpyruvate
- PD‐1
programmed death‐1
- PD‐L1/2
programmed death ligand‐1/2
- PI3K
phosphoinositol 3‐kinase
- SHP2
Src homology region 2‐containing tyrosine phosphatase
- SRC
spare respiratory capacity
- T‐bet
T‐box transcription factor
- TCA
tricarboxylic acid
- TCR
T‐cell receptors
- TIM‐3
T‐cell immunoglobulin mucin‐3
- TNFα
tumour necrosis factor‐alpha
- TOX
thymocyte selection‐associated high‐mobility group box protein
Introduction
T‐cell exhaustion is a depressed immune state in cytotoxic CD8 T‐cells that is observed in chronic viral infections (CVIs) caused by pathogens such as human immunodeficiency virus (HIV), hepatitis B and C (HBV and HCV) and, in mice, lymphocytic choriomeningitis virus (LCMV). 1 , 2 , 3 , 4 Although the factors that induce exhaustion are still being investigated, it is widely accepted that T‐cell exhaustion is due in part to dysfunction of normal glycolytic CD8 T‐cell metabolism. 5 In this exhausted state, CD8 T‐cells become unable to produce the factors necessary to induce apoptosis in pathogenic cells. 6 Thus, reversal of T‐cell exhaustion has emerged as a target for therapies against CVIs. Based on recent findings of the role of metabolism in T‐cell exhaustion, we explore metabolism‐related pathways that can be targeted therapeutically to reverse CD8 T‐cell exhaustion during CVIs.
T‐cell metabolism
Like almost all cells, CD8 T‐cells generate energy through glycolysis, oxidative phosphorylation (OXPHOS), and fatty acid oxidation (FAO). These processes metabolize glucose and fatty acids to generate energy by producing intermediates that enter the tricarboxylic acid (TCA) cycle that produces electron carriers that assist in adenosine triphosphate (ATP) production through the electron transport chain. In addition to these pathways, CD8 T‐cells also utilize alternate inputs to the TCA through the metabolism of glutamine and glutamate. Relying on each of these pathways has advantages that suit particular T‐cell subsets, and thus CD8 T‐cell metabolism is finely tuned to enable optimal immunological function. 7
When CD8 T‐cells are naïve, or have yet to encounter cognate antigens, survival through efficient energy production is essential, and therefore relies primarily on OXPHOS and FAO. OXPHOS produces the highest amount of ATP per molecule of glucose metabolized, and is achieved through the catabolism of glucose to pyruvate, which enters mitochondria and the TCA cycle. FAO also makes use of mitochondrial functions, breaking down fatty acids into the TCA input acetyl‐CoA. While these processes are highly efficient, they are unable to meet the bioenergetic demands of activated T‐cells. 8
During an acute viral infection, the metabolic requirements of CD8 T‐cells change from catabolic to anabolic as naïve T‐cells are activated through specific binding of viral antigens displayed by antigen‐presenting cells (APCs), including dendritic cells (DCs), to their T‐cell receptors (TCR). 9 This binding induces pyruvate dehydrogenase kinase activity, inducing a metabolic shift from OXPHOS to glycolysis. This shift is enhanced by ligation of costimulatory receptors, for example, CD28, which leads to phosphorylation of protein kinase B (AKT) through the phosphoinositol 3‐kinase (PI3K) pathway. This promotes activation of the mammalian target of rapamycin (mTOR) pathway, enhancing MYC and hypoxia‐inducible factor 1‐alpha (HIF1α) activity, which induce transcription of glucose transporters and glycolytic enzymes. 10 , 11 TCR‐based activation also results in significant upregulation of glutaminolysis and the pentose phosphate pathway, which contribute to reactive oxygen species production. This upregulates MYC activity, further enhancing the glycolytic flux during T‐cell activation 12 (Fig. 1).
Figure 1.

Chronic viral infections (CVIs) induce CD8 T‐cell exhaustion. In acute viral infections, normal levels of antigen (Ag) presented by antigen‐presenting cells (APCs), and of cytokines such as interleukin (IL)‐2 released by helper cells such as CD4 T‐cells, stimulate T‐cell receptors (TCRs) and co‐receptors such as CD28. Stimulation of these receptors enhances signalling to mammalian target of rapamycin (mTOR) via phosphoinositol 3‐kinase (PI3K) and protein kinase B (AKT), which upregulates hypoxia‐inducible factor 1‐alpha (HIF1α) and MYC, leading to an increase in glycolytic enzyme levels and glucose transporters (GLUT) expression. This shifts the cell from an oxidative phosphorylation (OXPHOS)‐ and fatty acid oxidation (FAO)‐ to a glycolytic‐based metabolism, allowing for the anabolic processes that define the activated effector state needed to clear an infection. Such processes include the production of cytotoxic factors such as cytokines, granzyme and perforin, and enhanced proliferation. In CVIs, on the other hand, an over‐abundance of antigen leads to upregulation of inhibitory receptors, such as programmed death‐1 (PD‐1), that block TCR activation, thus reducing the signalling required for the glycolytic metabolic phenotype that in turn is necessary for proper effector functions. This dysfunction is compounded by the upregulation of transcription factors that increase PD‐1 expression, the reduction of helper cell signalling for survival and proliferation (e.g. IL‐2), and enhancement of inhibitory signals. The combination of these events leads cells to metabolic dysfunction, reduced cytotoxic function and an exhausted phenotype.
The shift to glycolysis provides additional energy for activated CD8 T‐cells, also known as effector T‐cells, to clear pathogens by inducing apoptosis in infected or damaged host cells. Effector T‐cells carry this out by producing inflammatory cytokines, such as interferon‐gamma (IFNγ) and tumour necrosis factor‐alpha (TNFα), and cytotoxic factors, like granzyme B and perforin. In addition to TCR activation, the effector response is promoted by helper cells, including macrophages and CD4 T‐cells, 13 , 14 through the production of cytokines, for example, interleukin (IL)‐2, that can enhance CD8 T‐cell proliferation by activating the mTOR pathway. 15 The increased proliferation in response to acute infection provided by IL‐2 signalling is necessary to produce sufficient numbers of antigen‐specific T‐cells to respond to a given pathogen, but is also very energetically demanding, with cell cycles as brief as 2 hr. 16 This exponential growth and need to produce massive quantities and varieties of cytotoxic factors requires enhanced use of resources and rapid energy production. 17 Therefore, as CD8 T‐cells shift from a naïve to an effector state, it is necessary that they also move from an OXPHOS‐ to aerobic glycolytic‐based metabolism. IL‐2 signalling can also alter other aspects of cellular metabolism that impact CD8 effector functions, upregulating autophagy‐related pathways, 18 which has been noted to be essential for CD8 T‐cell survival and memory formation during viral infection. 19 Additionally, certain CVIs such as HCV are able to modulate autophagy to help themselves to assist in viral replication. 20 Other cytokines such as IL‐7, IL‐15 and IL‐10 also have the ability to modulate metabolic processes such as glycolysis, altering CD8 T‐cell activation and effector functions. Knockout of IL‐7 has been shown to reduce glycolysis, and IL‐10 and IL‐15 have been shown to reduce activation signalling that upregulates glycolysis. 21 , 22 , 23 Combined, these factors lead to a peak of immune activation and pathogen clearance during an acute viral infection. 24
Following successful clearance of an acute infection by effector CD8 T‐cells, a small fraction differentiate into memory T‐cells that are maintained in the absence of their specific antigens. These are resting cells, like naïve T‐cells, but are capable of responding to restimulation by the same antigen, triggering a secondary adaptive immune response far more rapid than the response of naïve cells. In order to respond in such a manner, memory T‐cells have enhanced mitochondrial spare respiratory capacity (SRC), and have been observed to have mitochondrial masses higher than those of effector CD8 T‐cells. 25 , 26 This enhanced SRC is a signature of increased reliance on OXPHOS. However, many studies have shown that memory T‐cells rely upon both FAO and OXPHOS, with drugs, metformin and rapamycin, known to enhance adenosine monophosphate (AMP)‐activated protein kinase (AMPK) activity and decrease mTOR activity, promoting the development of antigen‐specific memory CD8 T‐cells. 27 , 28 , 29 , 30 Together, the metabolic changes accompanying the shifts from naïve to effector to memory cells during T‐cell differentiation are the hallmark of the metabolic flux associated with the immune response to acute viral infections.
Chronic viral infections
While the adaptive immune response can successfully clear acute viral infections, particular infections including HIV, HBV, HCV and LCMV are capable of evading clearance, leading to chronic infections. 31 The long‐term nature of these infections often results in CD8 T‐cells reaching an exhausted state with dysfunctional metabolism, and a concomitant reduction in essential cytotoxic functions. This is largely due to the combination of continuous overstimulation, increased levels of immunosuppressive cytokines and receptors, and reduced numbers of helper cells. While the precise metabolic state of exhausted T‐cells is yet to be pinpointed, the factors known to induce exhaustion impact pathways essential to maintaining the glycolytic metabolic state necessary to T‐cell effector functions. This leads effector T‐cells to increase dependence on FAO and OXPHOS, which are unable to keep up with their energetic demands further dampening effector functions of the CD8 T‐cell response, rendering them unable to clear the CVIs. 32
Higher viral loads cause CD8 T‐cell overstimulation via TCR signalling, inducing CD8 T‐cell exhaustion and, in certain cases, apoptosis. 33 , 34 In clinical HBV cases, T‐cell exhaustion has been observed to be sparked by overstimulation from the production of an excess of non‐infectious particles. Despite their lack of pathogenicity, these particles are advantageous to HBV in that they overwhelm TCRs. 35 This constant stimulation induces an increasingly exhausted state characterized by decreasing cytokine production until the T‐cells reach an exhausted state expressing programmed death (PD)‐1, lymphocyte‐activation gene‐3 (LAG‐3), cytotoxic T‐lymphocyte‐associated protein‐4 (CTLA‐4) and T‐cell immunoglobulin mucin‐3 (TIM‐3) and, in severe cases, deleting through apoptosis. 36 Similar findings have been observed in mouse models of chronic LCMV showing that, as antigen load increases, effector T‐cells become increasingly exhausted characterized by the increasing loss of IFNγ, TNFα and IL‐2 production until the T‐cells become fully exhausted and, at certain antigen loads, undergoing apoptosis. 34 These findings show that sustained antigen presence drives T‐cell exhaustion, and have been recapitulated in a study examining T‐cell response in LCMV‐infected wild‐type mice and LCMV‐infected mice with knockout of major histocompatibility complex class I (MHC‐I). Results from this study showed that decreased antigen presentation through ablation of MHC‐I expression directly decreased the phenotypes of exhaustion in CD8 T‐cells compared with the T‐cell phenotype in wild‐type mice, but that direct interaction between antigen‐MHC complexes and cytotoxic T‐cells was necessary for clearance of CVIs. 37 Hence, inhibition of MHC‐I function or expression are not feasible therapeutic strategies. Together, these findings show that viral antigen load is a driver of CD8 T‐cell exhaustion, and that it is unlikely to be overcome via direct targeting of antigen presentation. If antigen presentation could be more finely tuned through alteration of specific pathways, antigen overstimulation could be controlled without fully preventing APC‐mediated CD8 T‐cell activation. A potential avenue for this strategy is p38 mitogen‐activated protein kinase (p38 MAPK) activation by toll‐like receptors, which has been shown to control regulation of MHC expression. 38 , 39 However, such therapies would require further understanding of p38 MAPK pathways, as inhibitors of p38 have also been shown to increase antigen uptake for presentation by MHC‐I in a Japanese encephalitis model. 40
While directly targeting antigen presentation could prove to be a difficult strategy for preventing or delaying exhaustion induced by CD8 T‐cell overstimulation, recent studies have identified another potential target: thymocyte selection‐associated high‐mobility group box protein (TOX), which is upregulated in exhausted CD8 T‐cells. Studies using HCV and LCMV showed that TOX is an early marker for, and is important for the induction of, exhaustion via reprogramming CD8 T‐cell epigenetic and transcriptional profiles. 41 Exhausted T‐cells have a distinct epigenetic profile essential to maintaining their exhausted phenotype. In the exhausted epigenetic state, the availability of chromatin regions related to inhibitory markers such as PD‐1 is enhanced, and there are widespread changes to transcription factor binding. 42 TOX plays a role in this process by reducing the transcriptional availability of genes related to CD8 effector differentiation via the binding and recruitment of proteins involved in repressive epigenetic events. 43 Evidence of the impact of TOX expression can be observed in the link between TOX and T‐cell inhibitory marker expression, as a decrease in TOX levels was shown to lead to a correlated decline in PD‐1, CD39 and TIM‐3 expression, and enhanced effector functions. 44 Additionally, knockout of TOX in mouse CD8 T‐cells during LCMV infection prevented development of CD8 T‐cell exhaustion, but TOX was not necessary for the formation of effector cells. 45 These data indicate that TOX is a very promising therapeutic target for reversing T‐cell exhaustion. It would be interesting to determine whether ablating TOX expression is also able to shift the metabolism of exhausted T‐cells to glycolysis, determine if this in turn restores T‐cell effector functions, and study the link between the epigenetic and metabolic mechanisms that drive T‐cell exhaustion.
A mechanism through which CD8 T‐cells responding to CVIs protect themselves from the high viral antigen loads accompanying such infections is expression of inhibitory receptors including PD‐1. The upregulation of PD‐1 expression has been seen in diverse CVIs, including HIV, HCV and LCMV, and is frequently used as a marker for identifying exhausted CD8 T‐cells. 46 PD‐1 expression on HIV‐specific CD8 T‐cells has been associated with decreased cytokine production and proliferative capacity. 47 PD‐1 interacts with programmed death ligand (PD‐L)1 and 2 to provide negative regulatory signalling to CD8 T‐cells through the protein tyrosine phosphatase Src homology region 2‐containing tyrosine phosphatase (SHP2), and this signalling inhibits RAS and PI3K signalling from TCR and CD28 stimulation 48 , 49 (Fig. 1). While this process protects CD8 T‐cells from overstimulation by antigen, it also reduces signalling to transcription factors that are key to a proper immune response. 50 Additionally, blocking this pathway reduces mTOR signalling from PI3K, which decreases glycolytic capacity, resulting in metabolic dysfunction, and with insufficient production of energy to meet the anabolic demands of an effector CD8 T‐cell, a state of exhaustion is induced. 51 The mechanisms controlling PD‐1 signalling are still being explored; however, it has been shown that PD‐1 expression is increased by persistent TCR stimulation, and that transcription factors including T‐box transcription factor (T‐bet) and forkhead box protein O1 (FoxO1) regulate PD‐1 expression. 52 T‐bet is responsible for repression of PD‐1 expression, and is downregulated in cases of persistent stimulation. 50 This leads to a further increase in PD‐1 expression, as this causes more severe T‐cell dysfunction; therefore, targeting such transcription factors may help to reverse T‐cell exhaustion. 50 FoxO1 plays a role opposite to that of T‐bet, upregulating expression of PD‐1 and eomesodermin, the latter of which is a transcription factor that promotes exhaustion during CVIs. 52 While PD‐1 does play an important role in preventing overstimulation‐induced apoptosis of exhausted CD8 T‐cells, the outcome of reduced TCR and costimulatory signalling is the decline of key effector functions including proliferation and cytokine production due to metabolic dysfunction related to reduction in glycolysis.
Other inhibitory receptors, including LAG‐3, also stifle the CD8 T‐cell response and are indicators of exhaustion. 53 LAG‐3 expression is associated with decreased virus‐specific CD8 T‐cell responses in LCMV infection, 54 and blockade of LAG‐3 has been shown to restore activity in chronic HBV cases. 55 Furthermore, co‐treatment with blockade of PD‐1/PD‐L1 interaction and LAG‐3 proved more effective than either treatment alone in an LCMV model. 56 Together, these studies suggest that blockade treatment of inhibitory receptors can shift T‐cell metabolism toward a glycolytic state.
In addition to inhibitory receptors, certain cytokines, including IL‐10, can also induce exhaustion in CD8 T‐cells. 57 IL‐10 can be produced by diverse cell types, and has the ability to decrease proliferation and cytokine production in CD8 T‐cells. 58 In the context of CVIs, IL‐10 has been shown to be an indicator for persistence of HIV and HCV. 59 , 60 Treatments targeted at IL‐10 also show promise, as removal of IL‐10/IL‐10 receptor (IL‐10R) interaction via antibody blockade, and knockout of IL‐10 signalling in LCMV models, have been shown to enhance clearance of CVIs. 61 , 62 Blockade of the IL‐10/IL‐10R interaction holds promise and a means to reverse exhaustion.
Chronic viral infections are also able to indirectly induce CD8 T‐cell exhaustion and metabolic dysfunction by altering helper cell function (Fig. 1). CD4 T‐cells promote CD8 T‐cell responses to CVIs by secreting cytokines, including IL‐2, that induce high levels of mTOR signalling in CD8 T‐cells. This process is essential for differentiation of CD8 T‐cells from naïve to effector, and for maintaining effector functions. Studies have shown that in chronic infections including LCMV and HCV, CD4 T‐cell capacity to both proliferate and secrete IL‐2 is diminished. 15 , 63 , 64 , 65 Other helper cells including DCs have also displayed functional impairments in the context of CVIs. DCs isolated from patients with chronic infections including HIV, HBV and HCV exhibit diminished ability to produce cytokines and induce T‐cell activation. 66 , 67 Such reductions in helper‐cell functions impair the CD8 T‐cell anti‐viral response and drive exhaustion. Hence, therapies aimed at enhancing the function of these helper cells could potentially improve the anti‐viral function of CD8 T‐cells.
Virus‐induced alteration of the metabolism of infected cells may play a role in CD8 T‐cell exhaustion. The metabolism of both infected host cells and uninfected neighbouring cells has been shown to be altered by particular viruses. 68 Kaposi’s sarcoma‐associated herpesvirus (KHSV), for example, alters infected host cell glucose metabolism by upregulating HIF1α, reducing mitochondrial capacity and releasing micro‐RNAs (miRNAs) into the microenvironment. 69 , 70 , 71 Particular secreted miRNAs have been shown to reprogramme metabolism in cells, and other miRNAs secreted by KHSV have been implicated in alteration of glycolysis through upregulation of HIF1α. 72 , 73 HBV has also been shown to impact infected host cell metabolism, by upregulating expression of glucose transporters (GLUT) through mTOR signalling, thereby enhancing glycolysis. 74 , 75 It is highly likely that alterations to the infected cell’s metabolism could impact immune function by modifying the microenvironment, reducing the levels of available nutrients, including glucose, or by producing miRNAs that induce changes to CD8 T‐cell function. This lack of available substrate could be a limiting factor even if normal glycolytic metabolism could be restored, and requires further understanding for such therapies to be successful. An additional metabolic aspect that could play a role in T‐cell exhaustion is whole‐body metabolism and nutrition. Studies have identified leptin as playing a key role in inducing CD8 effector differentiation, 76 , 77 and additional inquiry should be made to examine its role in T‐cell exhaustion. In sum, CVIs lead to exhausted phenotypes and metabolic dysfunction in CD8 T‐cells through diverse mechanisms, and therefore multifaceted approaches will be required to reverse exhaustion such that infections are successfully treated.
Metabolic targets for therapies
Multiple potential therapeutic approaches can be aimed at rescuing CD8 T‐cell exhaustion by reversing metabolic dysfunction through restoration of normal immune function (Fig. 2). Antibody blockade of inhibitory receptors, including PD‐1, LAG‐3 and IL‐10R, have shown promise in reinvigorating T‐cells. These blockades have the ability to help reverse metabolic dysfunction by restoring TCR signalling, which stimulates glycolysis‐enhancing pathways. Blockade of PD‐1 has proved to be an effective immunotherapy in many cancer models of CD8 T‐cell exhaustion, 78 , 79 and has shown promising results in the treatment of CVIs. Blockade of PD‐1/PD‐L1 interaction in HIV, HBV, HCV and LCMV have all shown enhancement of T‐cell effector capacities. 80 , 81 , 82 , 83 , 84 Blockade of PD‐1 has also been shown to have enhanced therapeutic efficacy when combined with other antibodies including LAG‐3. This combination displayed an increased ability to rescue CD8 T‐cells from an exhausted state in LCMV. 56 While these antibody therapies do not directly target metabolic processes, an important component of their efficacy is that by reducing inhibitory‐pathway activity, they help to repair metabolic dysfunction. PD‐1 inhibits glucose transport and utilization by downregulating mTOR activity, and thus inhibition of PD‐1 signalling increases glucose availability to T‐cells. 85 , 86 The importance of restoring mTOR activity has also been demonstrated in a study showing that rapamycin, an mTOR inhibitor, can reverse the positive effects of PD‐L1 blockade in an LCMV model of exhaustion. 52 Together, these findings show that a key outcome of PD‐1 blockade and reversal of CD8 T‐cell exhaustion is the return of a glycolytic metabolism.
Figure 2.

Potential therapeutic targets to reverse CD8 T‐cell exhaustion. (a) Therapies blocking or downregulating inhibitory receptors via antibody blockade or modulating transcription factor expression, enhancing T‐cell receptor (TCR) pathway signals, or directly targeting metabolism by enhancing substrate availability, could reverse T‐cell exhaustion by enhancing glycolysis in CD8 T‐cells. (b) Potential strategies for reinvigorating exhausted CD8 T‐cells to their effector state with high glycolytic metabolism via currently available methods could hold the key to reversing T‐cell exhaustion and clearing chronic viral infections (CVIs) more efficiently. PHD, prolyl hydroxylases; TCR, T‐cell receptor; VHL, Von Hippel‐Lindau protein.
Another strategy for antibody‐based therapies aimed at reversing CD8 T‐cell exhaustion is to enhance the function of cells that augment CD8 T‐cell effector functions, including CD4 T‐cells and DCs. One way to achieve this is through IL‐10 neutralization, as IL‐10 inhibits CD4 helper and DC functions, and exhibits increased expression during CVI. 21 , 62 , 87 , 88 , 89 Reduction of IL‐10 signalling has been shown to be effective in enhancing the immune response and clearance of LCMV, 61 , 62 , 88 and treatment of HIV with a combined IL‐10 and PD‐1 blockade resulted in a 10‐fold increase in IFNγ production compared with treatment via blockade of PD‐1 alone. 90 Some of the impact of IL‐10 blockade is most likely the result of a return of CD28 signalling, which induces mTOR activity and glycolysis and is directly altered by IL‐10; 91 however, studies have yet to show a direct link between IL‐10 expression and CD8 T‐cell metabolism. A potential alternative approach to reinvigorating exhausted CD8 T‐cells, beyond efforts to directly enhance helper‐cell activity, is to provide a substitute for the output of helper cells. For example, treatment of herpes virus with IL‐2 complexes targeting IL‐2 receptor (IL‐2R) has been shown to substantially improve T‐cell cytotoxicity in the context of suppressed immunity. 92 While this would not address the problem of helper‐cell dysfunction, it could help enhance the CD8 T‐cell response to clear the CVIs by enhancing the PI3K pathway.
In addition to directly targeting inhibitory factors that drive exhaustion, more precise approaches for reversing inhibitory pathways could be based on targeting transcription factors that control expression of these inhibitory factors. The functions of T‐bet, FoxO1 and TOX include controlling the expression of inhibitory receptors that induce CD8 T‐cell exhaustion. A possible mechanism to enhance T‐bet expression would be to use miRNA‐155, which has been shown to upregulate T‐bet expression and increase the CD8 T‐cell effector response to LCMV. 93 Additionally, miR‐155 is upregulated by anti‐PD‐1 treatment, and is associated with increased cytokine production and tumour control by CD8 T‐cells in melanoma. 94 However, miR‐155 has also been shown to promote exhaustion in CD8 T‐cells in a LCMV model. 95 Inhibition of FoxO1 or TOX represent additional potential therapies for reversing T‐cell exhaustion; however, these strategies will be difficult to carry out, as inhibition of these multi‐functional proteins could have off‐target effects. It is clear that therapies targeting transcription factors that could reinvigorate TCR signalling have potential, but more work must be done to elucidate the mechanisms through which these transcription factors function, in order to better understand the pathways that they effect.
While therapies aimed at reducing the expression of inhibitors, or blocking them completely, are capable of enhancing the immune response, they can render CD8 T‐cells more susceptible to overstimulation by viral antigen. An approach that could potentially achieve the same goal while avoiding this drawback is to directly target pathways that enhance CD8 T‐cell glycolysis. Upregulating the mTOR pathway via blockade of AMPK signalling, enhancing AKT activity, or upregulating the transcription factors HIF1α and MYC, could reinvigorate T‐cells and reverse exhaustion by upregulating the expression of proteins that promote an optimized glycolytic state. In addition, blocking AMPK activity would not only upregulate mTOR activity, but would also help shift the metabolic state by reducing dependence on FAO and glutamine metabolism, as AMPK activity has been shown to enhance both of these processes and reduce IFNγ production in effector CD8 T‐cells. 96 Another metabolic pathway to potentially target is glutamine metabolism, through glutaminase 1 (GLS1) blockade. In a recent study, reduced glutamine metabolism through blockade of GLS1 was shown to induce a highly activated and long‐lived state in tumour‐infiltrating CD8 T‐cells. 97 Additionally, glutaminase deficiency has been linked to increased T‐bet activity, and promoting the differentiation and effector function of effector CD8 T‐cells through sensitization of cells to IL‐2‐mediated mTOR signalling. 98 Alternative metabolism‐targeting approaches include enhancing production of particular glycolytic metabolites to promote glycolysis, such as phosphoenolpyruvate (PEP). PEP is associated with enhanced CD8 T‐cell antitumour activity, and has been shown to alter CD8 T‐cell metabolism by maintaining nuclear factor of activated T‐cells (NFAT) signalling, which enhances expression of glycolytic transcription factors. 99 , 100 This could be achieved by enhancing the activity of the glycolytic enzyme phosphoenolpyruvate carboxykinase‐1, or the concentration of its substrate oxaloacetate.
If such treatments were successful in reinvigorating glycolysis, this restoration of normal effector metabolism could produce the metabolites and energy necessary to restore effector functions. While the above strategies demonstrate the strong potential of metabolism‐based therapies to reinvigorate exhausted T‐cells, further research into the effects of such treatments as well as methods of delivery and length of treatment is needed before they can be confirmed as effective in a CVI model. However, based on our current knowledge, direct targeting of pathways to upregulate mTOR signalling and thereby upregulate glycolysis could provide a successful therapeutic strategy.
Summary
While many of the markers and phenotypes that identify exhausted CD8 T‐cell populations are well known, the mechanisms underlying the development of T‐cell exhaustion are poorly understood. Thus, any therapeutic options that target suspected mechanisms must be considered. Targeting metabolism in particular holds great promise for reversing CD8 T‐cell exhaustion and treating CVIs. There is robust evidence that reversal of the metabolic dysfunction characteristic of T‐cell exhaustion enhances effector function sufficiently to overcome CVIs in different models. Therefore, therapeutic strategies that directly target metabolic dysfunction should be strongly considered in the treatment of CVIs.
Disclosures
None.
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References
- 1. Hoffmann M, Pantazis N, Martin GE, Hickling S, Hurst J, Meyerowitz J, et al Exhaustion of activated CD8 T cells predicts disease progression in primary HIV‐1 Infection. PLOS Pathog 2016;12:e1005661. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Spangenberg HC, Viazov S, Kersting N, Neumann‐Haefelin C, McKinney D, Roggendorf M, et al Intrahepatic CD8+ T‐cell failure during chronic hepatitis C virus infection. Hepatology 2005; 42:828–37. [DOI] [PubMed] [Google Scholar]
- 3. Wedemeyer H, He X‐S, Nascimbeni M, Davis AR, Greenberg HB, Hoofnagle JH, et al Impaired effector function of hepatitis C virus‐specific CD8+ T cells in chronic hepatitis C virus infection. J Immunol 2002; 169:3447–58. [DOI] [PubMed] [Google Scholar]
- 4. Wherry EJ, Ha S‐J, Kaech SM, Haining WN, Sarkar S, Kalia V, et al Molecular signature of CD8+ T cell exhaustion during chronic viral infection. Immunity 2007; 27:670–84. [DOI] [PubMed] [Google Scholar]
- 5. Bengsch B, Johnson AL, Kurachi M, Odorizzi PM, Pauken KE, Attanasio J, et al Bioenergetic insufficiencies due to metabolic alterations regulated by the inhibitory receptor PD‐1 are an early driver of CD8(+) T cell exhaustion. Immunity 2016; 45:358–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Schurich A, Pallett LJ, Jajbhay D, Wijngaarden J, Otano I, Gill US, et al Distinct metabolic requirements of exhausted and functional virus‐specific CD8 T cells in the same host. Cell Rep 2016; 16:1243–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Chang C‐H, Pearce EL. Emerging concepts of T cell metabolism as a target of immunotherapy. Nat Immunol 2016; 17:364–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Fox CJ, Hammerman PS, Thompson CB. Fuel feeds function: energy metabolism and the T‐cell response. Nat Rev Immunol 2005; 5:844–52. [DOI] [PubMed] [Google Scholar]
- 9. Rosendahl Huber S, van Beek J, de Jonge J, Luytjes W, van Baarle D. T cell responses to viral infections ‐ opportunities for peptide vaccination. Front Immunol 2014; 5:171. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Phan AT, Goldrath AW. Hypoxia‐inducible factors regulate T cell metabolism and function. Mol Immunol 2015; 68(2 Pt C):527–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Menk AV, Scharping NE, Moreci RS, Zeng X, Guy C, Salvatore S, et al Early TCR signaling induces rapid aerobic glycolysis enabling distinct acute T cell effector functions. Cell Rep 2018; 22:1509–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Zhang E, Ma Z, Li Q, Yan H, Liu J, Wu W, et al TLR2 stimulation increases cellular metabolism in CD8+ T cells and thereby enhances CD8+ T cell activation, function, and antiviral activity. J Immunol 2019;203:2872–86. [DOI] [PubMed] [Google Scholar]
- 13. Pennock ND, White JT, Cross EW, Cheney EE, Tamburini BA, Kedl RM. T cell responses: naive to memory and everything in between. Adv Physiol Educ 2013; 37:273–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Koszinowski UH, Reddehase MJ, Jonjic S. The role of CD4 and CD8 T cells in viral infections. Curr Opin Immunol 1991; 3:471–5. [DOI] [PubMed] [Google Scholar]
- 15. Ross SH, Cantrell DA. Signaling and function of Interleukin‐2 in T lymphocytes. Annu Rev Immunol 2018; 36:411–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Yoon H, Kim TS, Braciale TJ. The cell cycle time of CD8+ T cells responding in vivo is controlled by the type of antigenic stimulus. PLoS ONE 2010; 5:e15423. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Chang C‐H, Curtis JD, Maggi LBJ, Faubert B, Villarino AV, O’Sullivan D, et al Posttranscriptional control of T cell effector function by aerobic glycolysis. Cell 2013; 153:1239–51. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Botbol Y, Patel B, Macian F. Common γ‐chain cytokine signaling is required for macroautophagy induction during CD4+ T‐cell activation. Autophagy 2015; 11:1864–77. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Xu X, Araki K, Li S, Han J‐H, Ye L, Tan WG, et al Autophagy is essential for effector CD8(+) T cell survival and memory formation. Nat Immunol 2014; 15:1152–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Guévin C, Manna D, Bélanger C, Konan KV, Mak P, Labonté P. Autophagy protein ATG5 interacts transiently with the hepatitis C virus RNA polymerase (NS5B) early during infection. Virology 2010; 405:1–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Smith LK, Boukhaled GM, Condotta SA, Mazouz S, Guthmiller JJ, Vijay R, et al Interleukin‐10 directly inhibits CD8(+) T cell function by enhancing N‐Glycan branching to decrease antigen sensitivity. Immunity 2018; 48:299–312.e5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Alizadeh D, Wong RA, Yang X, Wang D, Pecoraro JR, Kuo C‐F, et al IL15 enhances CAR‐T cell antitumor activity by reducing mTORC1 activity and preserving their stem cell memory phenotype. Cancer Immunol Res 2019; 7:759–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Jacobs SR, Michalek RD, Rathmell JC. IL‐7 is essential for homeostatic control of T cell metabolism in vivo. J Immunol 2010; 184:3461–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Maciolek JA, Pasternak JA, Wilson HL. Metabolism of activated T lymphocytes. Curr Opin Immunol 2014; 27:60–74. [DOI] [PubMed] [Google Scholar]
- 25. O’Sullivan D, van der Windt GJW, Huang SC‐C, Curtis JD, Chang C‐H, Buck MD, et al Memory CD8(+) T cells use cell‐intrinsic lipolysis to support the metabolic programming necessary for development. Immunity 2014; 41:75–88. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. van der Windt GJW, Everts B, Chang C‐H, Curtis JD, Freitas TC, Amiel E, et al Mitochondrial respiratory capacity is a critical regulator of CD8+ T cell memory development. Immunity 2012; 36:68–78. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Pearce EL, Walsh MC, Cejas PJ, Harms GM, Shen H, Wang L‐S, et al Enhancing CD8 T‐cell memory by modulating fatty acid metabolism. Nature 2009; 460:103–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. van der Windt GJW, Pearce EL. Metabolic switching and fuel choice during T‐cell differentiation and memory development. Immunol Rev 2012; 249:27–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Sipula IJ, Brown NF, Perdomo G. Rapamycin‐mediated inhibition of mammalian target of rapamycin in skeletal muscle cells reduces glucose utilization and increases fatty acid oxidation. Metabolism 2006; 55:1637–44. [DOI] [PubMed] [Google Scholar]
- 30. Araki K, Turner AP, Shaffer VO, Gangappa S, Keller SA, Bachmann MF, et al mTOR regulates memory CD8 T‐cell differentiation. Nature 2009; 460:108–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Kahan SM, Wherry EJ, Zajac AJ. T cell exhaustion during persistent viral infections. Virology 2015; 479–480:180–93. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Pallett LJ, Schmidt N, Schurich A. T cell metabolism in chronic viral infection. Clin Exp Immunol 2019; 197:143–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Wherry EJ. T cell exhaustion. Nat Immunol 2011; 12:492–9. [DOI] [PubMed] [Google Scholar]
- 34. Wherry EJ, Blattman JN, Murali‐Krishna K, van der Most R, Ahmed R. Viral persistence alters CD8 T‐cell immunodominance and tissue distribution and results in distinct stages of functional impairment. J Virol 2003; 77:4911–27. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Ganem D, Prince AM. Hepatitis B virus infection–natural history and clinical consequences. N Engl J Med 2004; 350:1118–29. [DOI] [PubMed] [Google Scholar]
- 36. Ye B, Liu X, Li X, Kong H, Tian L, Chen Y. T‐cell exhaustion in chronic hepatitis B infection: current knowledge and clinical significance. Cell Death Dis 2015; 6:e1694. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Mueller SN, Ahmed R. High antigen levels are the cause of T cell exhaustion during chronic viral infection. Proc Natl Acad Sci USA 2009; 106:8623–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Ardeshna KM, Pizzey AR, Devereux S, Khwaja A. The PI3 kinase, p38 SAP kinase, and NF‐kappaB signal transduction pathways are involved in the survival and maturation of lipopolysaccharide‐stimulated human monocyte‐derived dendritic cells. Blood 2000; 96:1039–46. [PubMed] [Google Scholar]
- 39. Rescigno M, Martino M, Sutherland CL, Gold MR, Ricciardi‐Castagnoli P. Dendritic cell survival and maturation are regulated by different signaling pathways. J Exp Med 1998; 188:2175–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. Aleyas AG, Han YW, Patil AM, Kim SB, Kim K, Eo SK. Impaired cross‐presentation of CD8alpha+ CD11c+ dendritic cells by Japanese encephalitis virus in a TLR2/MyD88 signal pathway‐dependent manner. Eur J Immunol 2012; 42:2655–66. [DOI] [PubMed] [Google Scholar]
- 41. Alfei F, Kanev K, Hofmann M, Wu M, Ghoneim HE, Roelli P, et al TOX reinforces the phenotype and longevity of exhausted T cells in chronic viral infection. Nature 2019; 571:265–9. [DOI] [PubMed] [Google Scholar]
- 42. Sen DR, Kaminski J, Barnitz RA, Kurachi M, Gerdemann U, Yates KB, et al The epigenetic landscape of T cell exhaustion. Science 2016; 354:1165–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43. 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. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44. Seo H, Chen J, Gonzalez‐Avalos E, Samaniego‐Castruita D, Das A, Wang YH, et al TOX and TOX2 transcription factors cooperate with NR4A transcription factors to impose CD8(+) T cell exhaustion. Proc Natl Acad Sci USA 2019; 116:12410–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45. Scott AC, Dundar F, Zumbo P, Chandran SS, Klebanoff CA, Shakiba M, et al TOX is a critical regulator of tumour‐specific T cell differentiation. Nature 2019; 571:270–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46. Saeidi A, Zandi K, Cheok YY, Saeidi H, Wong WF, Lee CYQ, et al T‐cell exhaustion in chronic infections: reversing the state of exhaustion and reinvigorating optimal protective immune responses. Front Immunol. 2018; 9:2569. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47. Day CL, Kaufmann DE, Kiepiela P, Brown JA, Moodley ES, Reddy S, et al PD‐1 expression on HIV‐specific T cells is associated with T‐cell exhaustion and disease progression. Nature 2006; 443:350–4. [DOI] [PubMed] [Google Scholar]
- 48. Marasco M, Berteotti A, Weyershaeuser J, Thorausch N, Sikorska J, Krausze J, et al Molecular mechanism of SHP2 activation by PD‐1 stimulation. Sci Adv 2020; 6(5):eaay4458. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49. Zhao M, Guo W, Wu Y, Yang C, Zhong L, Deng G, et al SHP2 inhibition triggers anti‐tumor immunity and synergizes with PD‐1 blockade. Acta Pharm Sin B 2019; 9:304–15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50. Kao C, Oestreich KJ, Paley MA, Crawford A, Angelosanto JM, Ali M‐AA, et al Transcription factor T‐bet represses expression of the inhibitory receptor PD‐1 and sustains virus‐specific CD8+ T cell responses during chronic infection. Nat Immunol 2011; 12:663–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51. Arasanz H, Gato‐Cañas M, Zuazo M, Ibañez‐Vea M, Breckpot K, Kochan G, et al PD1 signal transduction pathways in T cells. Oncotarget 2017; 8:51936–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52. Staron MM, Gray SM, Marshall HD, Parish IA, Chen JH, Perry CJ, et al The transcription factor FoxO1 sustains expression of the inhibitory receptor PD‐1 and survival of antiviral CD8(+) T cells during chronic infection. Immunity 2014; 41:802–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53. Hannier S, Tournier M, Bismuth G, Triebel F. CD3/TCR complex‐associated lymphocyte activation gene‐3 molecules inhibit CD3/TCR signaling. J Immunol 1998; 161:4058–65. [PubMed] [Google Scholar]
- 54. Cook KD, Whitmire JK. LAG‐3 confers a competitive disadvantage upon antiviral CD8+ T cell responses. J Immunol 2016; 197:119–27. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55. Ye B, Li X, Dong Y, Wang Y, Tian L, Lin S, et al Increasing LAG‐3 expression suppresses T‐cell function in chronic hepatitis B: A balance between immunity strength and liver injury extent. Medicine 2017; 96(1):e5275. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56. Blackburn SD, Shin H, Haining WN, Zou T, Workman CJ, Polley A, et al Coregulation of CD8+ T cell exhaustion by multiple inhibitory receptors during chronic viral infection. Nat Immunol 2009; 10:29–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57. Blackburn SD, Wherry EJ. IL‐10, T cell exhaustion and viral persistence. Trends Microbiol 2007; 15:143–6. [DOI] [PubMed] [Google Scholar]
- 58. Moore KW, de Waal MR, Coffman RL, O'Garra A. Interleukin‐10 and the interleukin‐10 receptor. Annu Rev Immunol 2001; 19:683–765. [DOI] [PubMed] [Google Scholar]
- 59. Flynn JK, Dore GJ, Hellard M, Yeung B, Rawlinson WD, White PA, et al Early IL‐10 predominant responses are associated with progression to chronic hepatitis C virus infection in injecting drug users. J Viral Hepat 2011; 18:549–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60. Brockman MA, Kwon DS, Tighe DP, Pavlik DF, Rosato PC, Sela J, et al IL‐10 is up‐regulated in multiple cell types during viremic HIV infection and reversibly inhibits virus‐specific T cells. Blood 2009; 114:346–56. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61. Ejrnaes M, Filippi CM, Martinic MM, Ling EM, Togher LM, Crotty S, et al Resolution of a chronic viral infection after interleukin‐10 receptor blockade. J Exp Med 2006; 203:2461–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62. Brooks DG, Trifilo MJ, Edelmann KH, Teyton L, McGavern DB, Oldstone MBA. Interleukin‐10 determines viral clearance or persistence in vivo. Nat Med 2006; 12:1301–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63. Salmond RJ. mTOR regulation of glycolytic metabolism in T cells. Front cell Dev Biol 2018; 25:122. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 64. Pipkin ME, Sacks JA, Cruz‐Guilloty F, Lichtenheld MG, Bevan MJ, Rao A. Interleukin‐2 and inflammation induce distinct transcriptional programs that promote the differentiation of effector cytolytic T cells. Immunity 2010; 32:79–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65. Ray JP, Staron MM, Shyer JA, Ho P‐C, Marshall HD, Gray SM, et al The Interleukin‐2‐mTORc1 kinase axis defines the signaling, differentiation, and metabolism of T Helper 1 and Follicular B Helper T cells. Immunity 2015; 43:690–702. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66. van Montfoort N, van der Aa E, Woltman AM. Understanding MHC class I presentation of viral antigens by human dendritic cells as a basis for rational design of therapeutic vaccines. Front Immunol 2014; 5:182. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67. Liu B, Woltman AM, Janssen HLA, Boonstra A. Modulation of dendritic cell function by persistent viruses. J Leukoc Biol 2009; 85:205–14. [DOI] [PubMed] [Google Scholar]
- 68. Moreno‐Altamirano MMB, Kolstoe SE, Sánchez‐García FJ. Virus control of cell metabolism for replication and evasion of host immune responses. Front Cell Infect Microbiol 2019; 9:95. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69. Yogev O, Henderson S, Hayes MJ, Marelli SS, Ofir‐Birin Y, Regev‐Rudzki N, et al Herpesviruses shape tumour microenvironment through exosomal transfer of viral microRNAs. PLoS Pathog 2017; 13:e1006524. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70. Serquina AKP, Kambach DM, Sarker O, Ziegelbauer JM. Viral MicroRNAs repress the cholesterol pathway, and 25‐Hydroxycholesterol inhibits infection. mBio 2017; 8:e00576‐17. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 71. Ma T, Patel H, Babapoor‐Farrokhran S, Franklin R, Semenza GL, Sodhi A, et al KSHV induces aerobic glycolysis and angiogenesis through HIF‐1‐dependent upregulation of pyruvate kinase 2 in Kaposi’s sarcoma. Angiogenesis 2015; 18:477–88. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 72. Fong MY, Zhou W, Liu L, Alontaga AY, Chandra M, Ashby J, et al Breast‐cancer‐secreted miR‐122 reprograms glucose metabolism in premetastatic niche to promote metastasis. Nat Cell Biol 2015; 17:183–94. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 73. Yogev O, Lagos D, Enver T, Boshoff C. Kaposi’s sarcoma herpesvirus microRNAs induce metabolic transformation of infected cells. PLoS Pathog 2014; 10:e1004400. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 74. Teng C‐F, Hsieh W‐C, Wu H‐C, Lin Y‐J, Tsai H‐W, Huang W, et al Hepatitis B virus Pre‐S2 mutant induces aerobic glycolysis through mammalian target of rapamycin signal cascade. PLoS One 2015; 10:e0122373. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 75. Masson JJ, Billings HW, Palmer CS. Metabolic reprogramming during hepatitis B disease progression offers novel diagnostic and therapeutic opportunities. Antivir Chem Chemother 2017; 25:53–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 76. Cohen S, Danzaki K, MacIver NJ. Nutritional effects on T‐cell immunometabolism. Eur J Immunol 2017; 47:225–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 77. Gerriets VA, Danzaki K, Kishton RJ, Eisner W, Nichols AG, Saucillo DC, et al Leptin directly promotes T‐cell glycolytic metabolism to drive effector T‐cell differentiation in a mouse model of autoimmunity. Eur J Immunol 2016; 46:1970–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 78. Motzer RJ, Escudier B, McDermott DF, George S, Hammers HJ, Srinivas S, et al Nivolumab versus Everolimus in advanced renal‐cell carcinoma. N Engl J Med 2015; 373:1803–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 79. Garon EB, Rizvi NA, Hui R, Leighl N, Balmanoukian AS, Eder JP, et al Pembrolizumab for the treatment of non‐small‐cell lung cancer. N Engl J Med 2015; 372:2018–28. [DOI] [PubMed] [Google Scholar]
- 80. Velu V, Shetty RD, Larsson M, Shankar EM. Role of PD‐1 co‐inhibitory pathway in HIV infection and potential therapeutic options. Retrovirology 2015; 12:14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81. Peligero C, Argilaguet J, Güerri‐Fernandez R, Torres B, Ligero C, Colomer P, et al PD‐L1 blockade differentially impacts regulatory T cells from HIV‐Infected individuals depending on plasma viremia. PLOS Pathog 2015; 11:e1005270. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 82. Fisicaro P, Valdatta C, Massari M, Loggi E, Biasini E, Sacchelli L, et al Antiviral intrahepatic T‐cell responses can be restored by blocking programmed death‐1 pathway in chronic hepatitis B. Gastroenterology 2010; 138:682–93, 693.e1–4. [DOI] [PubMed] [Google Scholar]
- 83. Gardiner D, Lalezari J, Lawitz E, DiMicco M, Ghalib R, Reddy KR, et al A randomized, double‐blind, placebo‐controlled assessment of BMS‐936558, a fully human monoclonal antibody to programmed death‐1 (PD‐1), in patients with chronic hepatitis C virus infection. PLoS One 2013; 8:e63818. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 84. Kato T, Nishida T, Ito Y, Murase M, Murata M, Naoe T. Correlations of programmed death 1 expression and serum IL‐6 level with exhaustion of cytomegalovirus‐specific T cells after allogeneic hematopoietic stem cell transplantation. Cell Immunol. 2014; 288:53–9. [DOI] [PubMed] [Google Scholar]
- 85. Patsoukis N, Bardhan K, Chatterjee P, Sari D, Liu B, Bell LN, et al PD‐1 alters T‐cell metabolic reprogramming by inhibiting glycolysis and promoting lipolysis and fatty acid oxidation. Nat Commun. 2015; 6:6692. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 86. Chang C‐H, 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. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 87. Rojas JM, Avia M, Martin V, Sevilla N. IL‐10: a multifunctional cytokine in viral infections. J Immunol Res 2017; 2017:6104054. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 88. Maris CH, Chappell CP, Jacob J. Interleukin‐10 plays an early role in generating virus‐specific T cell anergy. BMC Immunol 2007;8:8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 89. Kajino K, Nakamura I, Bamba H, Sawai T, Ogasawara K. Involvement of IL‐10 in exhaustion of myeloid dendritic cells and rescue by CD40 stimulation. Immunology 2007; 120:28–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 90. Porichis F, Hart MG, Zupkosky J, Barblu L, Kwon DS, McMullen A, et al Differential impact of PD‐1 and/or Interleukin‐10 Blockade on HIV‐1‐Specific CD4 T cell and antigen‐presenting cell functions. J Virol 2014; 88:2508–2518. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 91. Joss A, Akdis M, Faith A, Blaser K, Akdis CA. IL‐10 directly acts on T cells by specifically altering the CD28 co‐stimulation pathway. Eur J Immunol 2000; 30:1683–90. [DOI] [PubMed] [Google Scholar]
- 92. Molloy MJ, Zhang W, Usherwood EJ. Cutting edge: IL‐2 immune complexes as a therapy for persistent virus infection. J Immunol 2009; 182:4512–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 93. Hope JL, Stairiker CJ, Spantidea PI, Gracias DT, Carey AJ, Fike AJ, et al The transcription factor T‐Bet is regulated by MicroRNA‐155 in murine Anti‐Viral CD8(+) T cells via SHIP‐1. Front Immunol 2017; 8:1696. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 94. Martinez‐Usatorre A, Sempere LF, Carmona SJ, Carretero‐Iglesia L, Monnot G, Speiser DE, et al MicroRNA‐155 expression is enhanced by T‐cell receptor stimulation strength and correlates with improved tumor control in melanoma. Cancer Immunol Res 2019; 7:1013–24. [DOI] [PubMed] [Google Scholar]
- 95. Stelekati E, Chen Z, Manne S, Kurachi M, Ali M‐A, Lewy K, et al Long‐term persistence of exhausted CD8 T cells in chronic infection is regulated by MicroRNA‐155. Cell Rep 2018; 23:2142–56. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 96. Blagih J, Coulombe F, Vincent EE, Dupuy F, Galicia‐Vazquez G, Yurchenko E, et al The energy sensor AMPK regulates T cell metabolic adaptation and effector responses in vivo. Immunity 2015; 42:41–54. [DOI] [PubMed] [Google Scholar]
- 97. Leone RD, Zhao L, Englert JM, Sun I‐M, Oh M‐H, Sun I‐H, et al Glutamine blockade induces divergent metabolic programs to overcome tumor immune evasion. Science 2019; 366:1013–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 98. Johnson MO, Wolf MM, Madden MZ, Andrejeva G, Sugiura A, Contreras DC, et al Distinct regulation of Th17 and Th1 cell differentiation by glutaminase‐dependent metabolism. Cell 2018; 175:1780–95.e19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 99. Ho P‐C, Bihuniak JD, Macintyre AN, Staron M, Liu X, Amezquita R, et al phosphoenolpyruvate is a metabolic checkpoint of anti‐tumor T cell responses. Cell 2015; 162:1217–28. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 100. Vaeth M, Feske S. NFAT control of immune function: new Frontiers for an Abiding Trooper. F1000Res 2018; 7:260. [DOI] [PMC free article] [PubMed] [Google Scholar]
