Abstract
Upon antigen stimulation, small and quiescent naïve T cells undergo an approximately 24hr growth phase followed by rapid proliferation. Depending on the nature of the antigen and cytokine milieu, these proliferating T cells differentiate into distinctive functional subgroups that are essential for appropriate immune defense and regulation. T cells undergo a characteristic metabolic rewiring that fulfills the dramatically increased bioenergetic and biosynthetic demands during the transition between resting, activation and differentiation. Beyond this, T cells are distributed throughout the body and are able to function in a wide range of physio-pathological environments, including some with a dramatic metabolic derangement. As such, T cells must quickly respond to and adapt to fluctuations in environmental nutrient levels. We consider such responsiveness and adaptation in terms of metabolic plasticity, that is, an evolutionarilly selected process which allows T cells to illicit robust immune functions in response to either a continuous or disrupted nutrient supply. In this review, we illustrate the relevant metabolic pathways in T cells and discuss the ability of T cells to change their metabolic substrates in response to changes in the environment.
Keywords: T lymphocytes, metabolism, reprogramming, plasticity
Introduction
The reproduction and spreading of invading pathogens in vertebrates is often an extremely rapid process, resulting in acute and severe damage to the host. As such, an effective host-mediated immune response has to be fast and is energy intensive. The evolution of the vertebrate’s T cell-mediated immunity has culminated in an effective and complex response, allowing T cells to recognize foreign antigen and rapidly engage a network of signaling processes. These processes are essential in order to support the following: cell growth, proliferation and differentiation. Recent emerging evidence has revealed that there is a coordinated rewiring of the cellular metabolic program following T cell activation. Beyond supporting immediate cell size growth and clonal expansion following activation, this metabolic rewiring is also critical for T cell lineage polarization, acquisition of effector function, and eventually the engagement of T memory programs. In this review, we will update our current understanding of T cell metabolic reprogramming; discuss the signaling mechanisms that regulate metabolic reprogramming; and discuss the alternative metabolic substrates and routes that are likely required for supporting T cell function.
T cell metabolic reprogramming
As an essential component of adaptive immunity, T cells recognize foreign antigen and rapidly transition from a quiescent to an active state that is concomitant with cell growth (increase in cell size) and proliferation. In addition, activated and proliferating T cells can differentiate into various functional subsets, largely determined by the nature of antigen stimulation and the surrounding cytokine milieu; in concert with downstream signaling, metabolic rewiring, and initiation of transcription factors. This transition results in a heterogeneous T cell subset population. Activated and differentiated T cells can engage a variety of metabolic pathways including upregulation of glycolysis, glutaminolysis, and fatty acid metabolism [1–10]. Nevertheless, each subset of T cells demonstrates unique metabolic demands that contribute to subset proliferation, differentiation, effector functions, and maintenance. Following the peak of T cell expansion and antigen clearance, the vast majority of T cells undergo programmed cell death (apoptosis) during a contraction phase. The remaining population returns to a quiescent state and gives rise to the memory subset, which responds more quickly and effectively upon subsequent encounter with the same pathogen. To fulfill their bioenergetic and biosynthetic demands, coupled with various functional stages, T cells actively engage distinct signaling pathways and transcriptional modulators to alter their metabolic programs as demonstrated in Figure 1.
Figure 1.

Metabolic reprogramming in T lymphocytes
During the rapid T cell growth and proliferation process, and as a result of activation signals, T cells reprogram their metabolic profile, shifting from fatty acid oxidation (FAO) to robust aerobic glycolysis, pentose phosphate pathway (PPP) and glutaminolysis. Naïve T cells rely on oxidative phosphorylation (OXPHOS), to generate energy in order to meet the basic needs of cellular function and survival. Heightened aerobic glycolysis and glutaminolysis in activated T cells not only support ATP generation, but also provide biosynthetic intermediates that are subsequently used as building blocks for amino acids, nucleotides, and lipids. Also, glutaminolysis and glycolysis in active T cells provide carbon and nitrogen for other growth and proliferation-associated biosynthetic pathways, such as hexosamine and polyamine biosynthesis. The shunting of glucose into the PPP pathway results in the production of R5P and NADPH. While R5P is a precursor for ribonucleotides biosynthesis, NADPH determines cellular redox balance and coordinates with free fatty acid and cholesterol biosynthesis through providing reducing equivalents [2, 3, 11,12].
The rewiring of metabolic pathways upon T-cell activation is regulated by several signaling pathways, including mitogen activated protein kinase (MAPK)/extra-cellular signal-regulated kinase (ERK) and the PI3K/Akt/mTOR cascades, which varies depending on the T cell subset [2,13]. The activation of Akt signaling promotes the expression and cell surface trafficking of the glucose transporter-1 (Glut-1), facilitating glucose uptake [1, 6]. On the other hand, ERK signaling promotes glutamine uptake via modulating Sodium-dependent neutral amino acid transporter-2 (SNAT2) expression and cell membrane trafficking [15]. Beyond the regulation on glucose and glutamine uptake, T cell activation signaling drives a global metabolo-transcriptome including most of the key metabolic enzymes involved in major catabolic and biosynthetic pathways, with an example of this being the discovery that the proto-oncogene Myc is required in T cell activation driven glucose and glutamine catabolism [2, 13]. Upregulation of metabolic genes involved in lipid metabolism and de novo cholesterol biosynthesis and transport are under the dynamic control of transcription factors, nuclear receptor LXR, and the orphan steroid receptor ERRα [5, 17, 18].
Following a rapid initial growth phase, T cells enter a proliferation phase and subsequently differentiate into various phenotypic and functional subtypes. In response to distinct antigen challenge and extracellular cytokine signals, activated CD4+ T cells differentiate into immune suppressive regulatory T (Treg) cells or inflammatory T effector cells, such as T helper TH1, TH2, TH17 and follicular helper T (Tfh), each of which may engage characteristic metabolic programs. Accumulating evidences suggest that TH1, TH2 and TH17 cells all sustain heightened glycolysis, while Treg cells show enhanced FAO [5, 16, 19]. The metabolic pathways that are preferentially engaged in Tfh remain to be defined. Consistent with the metabolic preference of Teff and Treg cells, the supplementation of exogenous fatty acid inhibits TH1, TH2 and TH17 differentiation, while modestly enhances Treg differentiation [5]. In addition, Treg differentiation is preferentially induced by the commensal microbe-derived short-chain fatty acid, butyrate; however, this effect may be attributed to the inhibition of histone deacetylase activity by butyrate [20,21]. Glucose has a major effect on T cell differentiation as evidenced by the fact that the blockade of glucose catabolism significantly inhibits Teff function in vitro and in vivo[5, 16, 22]. This effect is likely due to the inhibition of glycolysis and mitochondrial-dependent oxidative phosphorylation. As the key biosynthetic and bioenergetic organelle, mitochondria are hubs of catabolic and anabolic pathways, which enable them to fulfill the various metabolic demands of immune cells ranging from generating ATP to providing precursors for macromolecule synthesis and ROS[23]. AMP-activated Protein Kinase (AMPK) is an important player in regulating mitochondrial-dependent oxidative metabolism. Recent evidence shows their immune phenotype. While genetic ablation of AMPK abolishes TH1 and TH17 development and their response to infection, the activation of AMPK by treatment with metformin can inhibit Teff cell function and promote Treg cell function in vivo [19, 24, 25]. A recent study has shown that the combination of targeting mitochondrial metabolism and glycolysis through the AMPK activator, Metformin, and the hexokinase inhibitor, 2-deoxy-d-glucose (2DG), may significantly alleviate disease phenotypes in several systemic lupus erythematosus (SLE) mouse models. These results suggest that both mitochondrial metabolism and glycolysis are required to support CD4+ T cell effector function in SLE [26].
In addition to AMPK, HIF1α has also been implicated in driving TH17 differentiation and sustaining elevated glycolysis during this process [29–31]. TH17 cell differentiation is driven by TGF-β and the proinflammatory cytokines IL-6, IL-21, and IL-23, which induce the transcription factor RAR-related orphan receptor gamma (RORγ) and activate STAT3 [29]. Recent studies have demonstrated that activation of STAT3 leads to increased expression of HIF1α [5,29, 30]. Consistent with the crucial role of mTORC1 in regulating T effector development and metabolism, the expression of HIF1α is also dependent on the function of mTORC1 during TH17 differentiation[20, 28, 31, 32]. While heightened glycolysis is necessary for TH17 differentiation and function, HIF1α appears to also directly regulate TH17 differentiation, at least in part through direct transcriptional activation of the TH17 master transcription factor RORγ, thereby enhancing TH17 differentiation [29, 30]. On the other hand, either the pharmacological inhibition of glycolysis or genetic deletion of HIF1α can enhance Treg differentiation, partially through antagonizing forkhead box protein 3 (Foxp3), the master transcription factor for Treg differentiation [29]. Consistent with the idea that glucose catabolism provides essential metabolic precursors for fatty acid synthesis, TH17 but not Treg cells, depend on acetyl-CoA carboxylase (ACC1)-mediated de novo fatty acid synthesis. The inhibition of ACC1 prevents TH17 cell differentiation whereas it promotes the development of Treg cells. Importantly, pharmacological inhibition of ACC1 suppresses TH17 cell-mediated autoimmune disease in mouse models [30]. In contrast to conventional Foxp3+ regulatory CD4+ T cells, the differentiation of type 1 regulatory T (Tr1) cells, which are Foxp3- regulatory CD4+ T cells, requires HIF1α-dependent early metabolic reprogramming [31, 32]. These studies and those of others further implicate the complex regulatory mechanisms and the essential role of the metabolic program in T cell subtype differentiation.
Similar to CD4 T cells, activated CD8 T cells also shift from fatty acid oxidation to aerobic glycolysis and glutamine oxidation, both of which are required to support CD8 T cell growth and differentiation into cytotoxic T cells [14, 37]. Following the stage of proliferation and differentiation, this shift is partially due to a decrease inmTOR signaling [38–40]. Such a metabolic switch is postulated to be required for the generation of memory CD8 T cells. Consistent with this idea, a recent study has shown that the enhancement of mitochondrial oxidative phosphorylation could improve long-term protective immunity through the promotion of CD8+ T effector and memory cell proliferation and survival in the context of viral and tumor clearance. Some of the biologic outcomes of T cells are likely attributable to the production of pro-proliferative mitochondrial reactive oxygen species (mROS) [41]. Taken together, T cell activation and differentiation are tightly coupled with metabolic reprogramming.
Metabolic plasticity
T cells are tasked with controlling invading organisms that replicate more rapidly than cellular division. It is therefore not surprising that the T cell-mediated immune response seems more like an “arms race” and that active T cells have the capacity to produce large amounts of cytokines, meanwhile undergoing replication every four to six hours, one of the shortest cell divisions in vertebrate cells [38]. In this regard, a key characteristic of the T cell is its metabolic plasticity. This is manifested by a capacity to maintain metabolic homeostasis in a wide range of conditions, including harsh microenvironments in which the T cell must continue to meet the high bioenergetic demand in order to mount a robust immune response.
T cell metabolic plasticity can be reflected by following three considerations: 1) T cells are required to function in a wide range of infection and inflammation sites throughout the body. As such, there are regional differences in the metabolic repertoire imposed by the tissues in which T cells reside, and the potential competition of nutrients with rapidly proliferating pathogens (in infection sites), tumor cells (in tumor) or other infiltrated immune cells may all tailor the T cell metabolic preference; 2) The differentiation of naive T cells into lineages with distinct functions has been considered to be of a great degree of flexibility in their lineage engaging signaling [29–32]. Such flexibility may also be a reflection of the dynamic changes on the metabolic phenotypes and fuel choices, which are associated with each lineage given the accumulating evidence showing the impact of metabolic modulation on T cell lineage commitments [3, 11, 40, 42, 43]; 3) Glucose and glutamine are considered as primary fuels for proliferating cells, such as cancer cells and active T cells. However, many other normal cells with various tissue origins use a wide range of nutrients as their primary fuels [44]. Moreover, recent emerging evidence has implicated that alternative metabolic substrates or metabolic reconstructions can compensate for the loss of glucose or glutamine in cultured cancer cells [45, 46]. Given the similarity of characteristic metabolic features between transformed cancer cells and activated T cells, we envision metabolic plasticity in terms of uptake of alternative metabolic substrates and induction of metabolic reconstruction as a built-in feature that has been evolved to allow T cells to adapt to constantly changing intra- and extracellular metabolic conditions.
While glucose is required to fuel T cell survival and proliferation, we have previously shown that some active T cells can survive in the absence of glucose, indicating that other nutrients/metabolites partially compensate for the loss of the primary nutrient in order to enable the survival of T cells [2]. This is further supported by the recent finding that galactose can replace glucose to support T cell survival and proliferation following activation [47]. There is a wide range of common naturally occurring monosaccharide sugars, such as D-glucose, D-galactose, D-fructose, D-mannose, D-lactose and D-ribose, that have similar chemical properties and bioenergetic value in terms of carbon and hydrogen numbers and chemical bonds. While the catabolic pathway of these sugars in vertebrate cells remains incompletely understood, metabolic studies in prokaryotic organisms or in eukaryotic microorganisms have revealed that many of these sugars share similar catabolic routes, raising the possibility that vertebrate cells may have a similar degree of metabolic plasticity on the choice of consuming monosaccharide sugars. The ribose salvage through nucleotide or nucleoside catabolism may also provide an important carbonaceous and bioenergetic source under the condition of nutrient scarcity [48]. Beyond the plasticity of the choice of sugar as carbonaceous and bioenergetic source, some cancer cells can also utilize acetate and ketone bodies as alternative metabolic substrates [49–51]. In addition, a wide range of abundant energy-generating carbohydrates in plasma could be a source of nutrients for T cells and other proliferative cells in vivo [46]. T cells migrate to and function in a wide range of nutrient-deficient environments, such as infectious, inflammatory and tumor sites. It is conceivable to speculate that the ability of T cells utilizing alternative nutrients in these environments is critical in supporting and shaping the T cell-mediated immune response.
Beyond glucose, glutamine is the other primary metabolic substrate for proliferative cells such as T cells and cancer cells [2, 15, 52–54]. However, asparagine, one of the nonessential amino acids, is sufficient to replace glutamine-dependent survival of proliferating cancer cells, including transformed T cells [55]. Also, we have revealed that the supplementation of naturally occurring metabolites, polyamines and nucleotides, can partially compensate for the loss of glutamine in order to continue to support T cell growth and proliferation [2]. One of the key adaptive responses following glutamine starvation is the induction of autophagy [56]. Through recycling available organelles and macromolecules into bioenergetics resources, autophagy is an essential cellular process for maintaining energy homeostasis when nutrients are limited, and thus may represent another important layer of metabolic plasticity. Supporting this idea, emerging evidence has shown that the machinery involved in autophagy is critical for T cell development, activation and differentiation [57–61]. While autophagy is required for scavenging intracellular macromolecules, proliferating cancer cells are also able to scavenge extracellular macromolecules, such as glycogen, protein and lipids, in the face of nutrient scarcity [35, 62, 63]. This is likely a shared characteristic between proliferative cancer cells and proliferative T cells.
As the end product of glycolysis, lactate is generally considered metabolic “waste”, the concentration of which ranges from 1 to 30mM under physiological and pathological conditions in vertebrate plasma [64]. Muscle cells, neurons, and some tumor cells can utilize lactate as a prominent substrate that fuels oxidative metabolism [65–67]. Interestingly, the uptake of lactate can beinduced in T cells following activation, implicating lactate as an alternative energy source by T cells (which has not been formally examined) [68]. Consistent with this idea, lactate supplementation can stimulate cytokine production in T cells following activation and differentiation [69–72]. However, the immunoregulatory effect of lactate on T cells seems to be dependent on the cellular context and the dose of lactate applied in these studies since lactate can either enhance or impair human CD4+ T cell proliferation at low or high concentrations, respectively [73].
Additional evidence implicating that T cell subset differentiation can bedriven by the microenvironment is demonstrated in specific tissues and disease states, in that even after differentiation cellular phenotypic changes can occur. T cell polarization can be dramatically affected by the surrounding metabolic environment in the central nervous system (CNS). Astrocytes produce glutamate and in CNS disease it has been noted that extracellular glutamate levels are increased, with subsequent studies showing that this results in a shift toward the TH1 phenotype and polarization of Treg cells[74]. Also, undifferentiated CD4 T cells cultured in the absence of glucose have no effect on the generation of Treg cells. Among alloreactive T cells, a reciprocal increase of the intracellular fatty acid oxidation intermediate acylcarnitines, and decrease of extracellular fatty acids has been recently revealed [75], suggesting that fatty acids may serve as a mitochondrial substrate in some T cells. Supporting this idea, fatty acids have been suggested as a preferred fuel for Treg and T memory cells [5, 33, 45]. The addition of fatty acids at initiation of activation of Treg cells increases the expression of Foxp3 [5]. Also, when fully differentiated Treg cells were exposed to a lipid rich environment the cytokine production was noted to increase [5]. Recent studies further reveal that commensal microbe-derived short-chain fatty acids, butyrate and propionate, promote the differentiation of regulatory T cells [76, 77]. While butyrate may impact T cell differentiation through inhibiting histone deacetylase (HDAC) activity, butyrate is also revealed as the primary energy source of normal colonocytes and is metabolized to acetyl-CoA, which was shown to be important for energetics and also for HAT activity [78]. In addition, the differentiation and homeostatic maintenance of memory CD8+ T cells relies on the engagement of FAO [42, 79]. However, recent studies suggest that extracellular lipids are unlikely to be the major resource for fueling memory CD8+ T cells. Instead, heightened glycerol uptake and subsequent synthesis of triglyceride are required to meet energy demands of memory CD8+ T cells [80, 81]. While glycolytic intermediates could be converted into glycerol in cells with a high rate of glycolytic flux, the direct uptake of extracellular free glycerol provides an alternative bioenergetic resource and may play an important role in maintaining cellular bioenergetics in memory CD8+ T cells. These studies implicate that the metabolic plasticity may interconnect with signaling-driven T cell lineage plasticity.
The recent breakthroughs in modulating T cell-mediated anti-tumor immune response to cure or significantly improve survivorship in some malignancies provides the exciting possibility of extending this approach to many types of tumors. However, tumors employ a plethora of immunosuppressive strategies, including fostering a deranged/hostile metabolic microenvironment, in order to counteract the anti-tumor immune response [82–84]. Heightened consumption of glucose and amino acids, such as glutamine, tryptophan, cysteine, glycine and arginine are common features in most cancer cells [85–91]. As such, the tumor microenvironment represents a dramatic example of metabolic derangement, where the highly metabolic demanding tumor cells often contribute to the depletion of glucose and essential amino acids and may compromise the function of anti-tumoral cytotoxic CD8+ T cells and CD4+ effector cells by competing for nutrients (a form of metabolic antagoism). On the other hand, the immune-checkpoint mechanism that is largely elicited through cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed cell death protein 1 (PD1) plays a key role in immune resistance. As such, the therapeutic approaches that target immune-checkpoint and therefore unleash anti-tumor immunity have achieved important clinical advances in threating several types of tumors [92–96]. Interestingly, recent studies suggest that antibody-mediated blockade or genetic deletion of CTLA-4 or PD1 could enhance glucose consumption in T effector cells [97–99]. It is therefore tempting to speculate that the strengthened anti-tumor immune response, following dampeningof the immune-checkpoint, is partially due to heightened metabolic fitness of immune cells. The adoptive transfer of naturally occurring or gene-engineered T cells has emerged as another powerful form of immunotherapy. However, in order to exert a robust anti-tumor response, adoptively transferred T cells must efficiently overcome the metabolic restrictions of the tumor microenvironment in order to survive, proliferate and remain functional [100–102]. Thus, the complete understanding of metabolic plasticity of T cells may lead to novel manipulative metabolic approaches that can skew T cells to generate robust and sustainable anti-tumor immune responses.
Conclusion and Perspective
The revived interests in T cell metabolism has revealed many fundamental biological insights and will likely generated new therapeutic strategies for immunological diseases in the near future. We summarize here that there is emerging evidence of characteristic metabolic events associated with T cell function and further vision that modulation of the T cell metabolic pathway may offer novel therapeutic regimes to improve immunological unresponsiveness or to suppress excessive immune responses in various pathological conditions. To win the battle against rapidly replicating invading pathogens, vertebrates have evolved a complex lymphatic system to rapidly deploy lymphocytes to infection and inflammation sites throughout the body. As such, T cells must respond and adapt to the wide vagaries of the metabolic landscape (nutrient pools) imposed by these infectious and inflammatory sites in different tissues. Inevitably, such responsiveness and adaptation reflects metabolic plasticity, allowing T cells to elicitrobust immune functions in a wide range of metabolic microenvironments. Finally, such knowledge may also help to reveal the impact of conditions of metabolic disease and nutritional imbalances on immune responses.
Highlights.
T cells undergo a metabolic rewiring during activation and differentiation.
T cells are capable of responding to and adapting to nutrient fluctuations.
T cells change metabolic substrates and routes in response to nutrient fluctuations.
Metabolic plasticity allows T cells to maintain metabolic homeostasis.
Acknowledgments
This work was supported byR21AI117547, the V-foundation and Elsa U. Pardee Foundation Research Grant (R.W.) and the Center for Clinical and Translational Research, Nationwide Children’s Hospital Research Institute Intramural Grant (M.S.).
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
References
- 1.Frauwirth K, Riley J, Harris M, Parry R, Rathmell J, Plas D, et al. The CD28 signaling pathway regulates glucose metabolism. Immunity. 2002;16:769–77. doi: 10.1016/s1074-7613(02)00323-0. [DOI] [PubMed] [Google Scholar]
- 2.Wang R, Dillon Christopher P, Shi Lewis Z, Milasta S, Carter R, Finkelstein D, et al. The transcription factor Myc controls metabolic reprogramming upon T lymphocyte activation. Immunity. 2011;35:871–82. doi: 10.1016/j.immuni.2011.09.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Wang R, Green DR. Metabolic reprogramming and metabolic dependency in T cells. Immunol Rev. 2012;249:14–26. doi: 10.1111/j.1600-065X.2012.01155.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.MacIver NJ, Michalek RD, Rathmell JC. Metabolic regulation of T lymphocytes. Annu Rev Immunol. 2013;31:259–8310. 1146. doi: 10.1146/annurev-immunol-032712-095956. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Michalek RD, Gerriets VA, Jacobs SR, Macintyre AN, MacIver NJ, Mason EF, et al. Cutting edge: distinct glycolytic and lipid oxidative metabolic programs are essential for effector and regulatory CD4+ T cell subsets. J Immunol. 2011;186:3299–303. doi: 10.4049/jimmunol.1003613. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Jacobs SR, Herman CE, MacIver NJ, Wofford JA, Wieman HL, Hammen JJ, et al. Glucose uptake is limiting in T cell activation and requires CD28-mediated Akt-dependent and independent pathways. J Immunol. 2008;180:4476–86. doi: 10.4049/jimmunol.180.7.4476. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Cham CM, Driessens G, O’Keefe JP, Gajewski TF. Glucose deprivation inhibits multiple key gene expression events and effector functions in CD8+ T cells. Eur J Immunol. 2008;38 doi: 10.1002/eji.200838289. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Ghesquiere B, Wong BW, Kuchnio A, Carmeliet P. Metabolism of stromal and immune cells in health and disease. Nature. 2014;511:167–76. doi: 10.1038/nature13312. [DOI] [PubMed] [Google Scholar]
- 9.Warburg O. On respiratory impairment in cancer cells. Science. 1956;124:269–70. [PubMed] [Google Scholar]
- 10.Pearce EL, Poffenberger MC, Chang CH, Jones RG. Fueling immunity: insights into metabolism and lymphocyte function. Science. 2013;342:1242454. doi: 10.1126/science.1242454. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Wang R, Green DR. Metabolic checkpoints in activated T cells. Nat Immunol. 2012;13:907–915. doi: 10.1038/ni.2386. [DOI] [PubMed] [Google Scholar]
- 12.Wang R, Green DR. The immune diet: meeting the metabolic demands of lymphocyte activation. F1000 Biol Rep. 2012;4:9. doi: 10.3410/B4-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Grumont R, Lock P, Mollinari M, Shannon FM, Moore A, Gerondakis S. The mitogen-induced increase in T cell size involves PKC and NFAT activation of Rel/NF-kappaB-dependent c-myc expression. Immunity. 2004;21:19–30. doi: 10.1016/j.immuni.2004.06.004. [DOI] [PubMed] [Google Scholar]
- 14.Cao Y, Rathmell JC, Macintyre AN. Metabolic Reprogramming towards Aerobic Glycolysis Correlates with Greater Proliferative Ability and Resistance to Metabolic Inhibition in CD8 versus CD4 T Cells. PLoS One. 2014;9(8) doi: 10.1371/journal.pone.0104104. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Carr EL, Kelman A, Wu GS, Gopaul R, Senkevitch E, Aghvanyan A, et al. Glutamine uptake and metabolism are coordinately regulated by ERK/MAPK during T lymphocyte activation. J Immunol. 2010;185:1037–1044. doi: 10.4049/jimmunol.0903586. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Shi LZ, et al. HIF1alpha-dependent glycolytic pathway orchestrates a metabolic checkpoint for the differentiation of TH17 and Treg cells. J Exp Med. 208:1367–1376. doi: 10.1084/jem.20110278. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Bensinger SJ, Bradley MN, Joseph SB, Zelcer N, Janssen EM, Hausner MA, Shih R, Parks JS, Edwards PA, Jamieson BD, Tontonoz P. LXR signaling couples sterol metabolism to proliferation in the acquired immune response. Cell. 2008;134:97–111. doi: 10.1016/j.cell.2008.04.052. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Kidani Y, Elsaesser H, Hock MB, Vergnes L, Williams KJ, Argus JP, et al. Sterol regulatory element-binding proteins are essential for the metabolic programming of effector T cells and adaptive immunity. Nat Immunol. 2013;14:489–499. doi: 10.1038/ni.2570. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Macintyre AN, Gerriets VA, Nichols AG, et al. The glucose transporter Glut1 is selectively essential for CD4 T cell activation and effector function. Cell Metab. 2014 Jul 1;20(1):61–72. doi: 10.1016/j.cmet.2014.05.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Chi H. Regulation and function of mTOR signalling in T cell fate decisions. Nat Rev Immunol. 2012;12:325–338. doi: 10.1038/nri3198. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Furusawa Y, Obata Y, Fukuda S, Endo TA, Nakato G, Takahashi D, et al. Commensal microbe-derived butyrate induces the differentiation of colonic regulatory T cells. Nature. 2013;504:446–450. doi: 10.1038/nature12721. [DOI] [PubMed] [Google Scholar]
- 22.Gerriets VA, Kishton RJ, Nichols AG, et al. Metabolic programming and PDHK1 control CD4+ T cell subsets and inflammation. J Clin Invest. 2015 Jan;125(1):194–207. doi: 10.1172/JCI76012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Weinberg SE, Sena LA, Chandel NS. Mitochondria in the regulation of innate and adaptive immunity. Immunity. 2015;42(3):406–17. doi: 10.1016/j.immuni.2015.02.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Blagih J, Coulombe F, Vincent EE, et al. The energy sensor AMPK regulates T cell metabolic adaptation and effector responses in vivo. Immunity. 2015;42(1):41–54. doi: 10.1016/j.immuni.2014.12.030. [DOI] [PubMed] [Google Scholar]
- 25.Son HJ, Lee J, Lee SY, et al. Metformin attenuates experimental autoimmune arthritis through reciprocal regulation of Th17/Treg balance and osteoclastogenesis. Mediatorsinflamm. 2014:973986. doi: 10.1155/2014/973986. Epub 2014 Aug 20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Yiming Y, Choi SC, Xu Z, et al. Normalization of CD4+ T cell metabolism reverse lupus. Sci Transl Med. 2015;7(274):274ra18. doi: 10.1126/scitranslmed.aaa0835. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.MacIver NJ, et al. The liver kinase B1 is a central regulator of T cell development, activation, and metabolism. J Immunol. 2011;187:4187–4198. doi: 10.4049/jimmunol.1100367. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Delgoffe GM, et al. The kinase mTOR regulates the differentiation of helper T cells through the selective activation of signaling by mTORC1 and mTORC2. Nature Immunol. 2011;12:295–303. doi: 10.1038/ni.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Dang EV, Barbi J, Yang HY, Jinasena D, Yu H, Zheng Y, et al. Cell. 2011;146:772–784. doi: 10.1016/j.cell.2011.07.033. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Berod L, Friedrich C, Nandan A, et al. De novo fatty acid synthesis controls the fate between regulatory T and T helper 17 cells. Nat Med. 2014;20(11):1327–33. doi: 10.1038/nm.3704. 2014. [DOI] [PubMed] [Google Scholar]
- 31.Pot C, Apetoh L, Awasthi A, Kuchroo VK. Induction of regulatory Tr1 cells and inhibition of TH17 cells by IL-27. SeminImm. 2011;23(6):438–45. doi: 10.1016/j.smim.2011.08.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Mascanfroni ID, Takenaka MC, Yeste, et al. Metabolic control of type 1 regulatory T cell differentiation by AHR and HIF1-α. Nat Med. 2015;21(6):638–46. doi: 10.1038/nm.3868. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Shi LZ, Wang R, Huang G, Vogel P, Neale G, Green DR, Chi H. HIF1 alpha-dependent glycolytic pathway orchestrates a metabolic checkpoint for the differentiation of TH17 and Treg cells. J Exp Med. 2011;208:1367–1376. doi: 10.1084/jem.20110278. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Peter C, Waldmann H, Cobbold SP. mTOR signalling and metabolic regulation of T cell differentiation. Curr Opin Immunol. 2010;22:655–661. doi: 10.1016/j.coi.2010.08.010. [DOI] [PubMed] [Google Scholar]
- 35.Yang K, Shrestha S, Zeng H, et al. T cell exit from quiescence and differentiation into Th2 cells depend on Raptor-mTORC1-mediated metabolic reprogramming. Immunity. 2013;39(6):1043–56. doi: 10.1016/j.immuni.2013.09.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Arpaia N, Campbell C, Fan X, Dikiy S, van der Veeken J, deRoos P, et al. Nature. 2013;504:451–455. doi: 10.1038/nature12726. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Finlay D, Cantrell DA. Metabolism, migration and memory in cytotoxic T cells. Nat Rev Immunol. 2011;11:109–117. doi: 10.1038/nri2888. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.vanStipdonk MJ, et al. Dynamic programming of CD8+ T lymphocyte responses. Nat Immuno. 2003;4(4):361–365. doi: 10.1038/ni912. [DOI] [PubMed] [Google Scholar]
- 39.Zhou L, Chong MM, Littman DR. Plasticity of CD4+ T cell lineage differentiation. Immunity. 2009;30(5):646–55. doi: 10.1016/j.immuni.2009.05.001. [DOI] [PubMed] [Google Scholar]
- 40.Wilson CB, Rowell E, Sekimata M. Epigenetic control of T-helper-cell differentiation. Nat Rev Immunol. 2009 Feb;9(2):91–105. doi: 10.1038/nri2487. [DOI] [PubMed] [Google Scholar]
- 41.Okoye I, Wang L, Pallmer K, et al. T cell metabolism. The protein LEM promotes CD8⁺ T cell immunity through effects on mitochondrial respiration. Science. 2015;348(6238):995–1001. doi: 10.1126/science.aaa7516. [DOI] [PubMed] [Google Scholar]
- 42.van der Windt GJ, Pearce EL. Metabolic switching and fuel choice during T-cell differentiation and memory development. Immunol Rev. 2013;249:27–42. doi: 10.1111/j.1600-065X.2012.01150.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Gerriets VA, Rathmell JC. Metabolic pathways in T cell fate and function. Trends Immunol. 2012;33(4):168–173. doi: 10.1016/j.it.2012.01.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Metallo CM, Vander Heiden MG. Understanding metabolic regulation and its influence on cell physiology. Mol Cell. 2013;49:388–398. doi: 10.1016/j.molcel.2013.01.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Boroughs LK, DeBerardinis RJ. Metabolic pathways promoting cancer cell survival and growth. Nat Cell Biol. 2015;17(4):351–359. doi: 10.1038/ncb3124. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Mayers JR, Vander Heiden MG. Famine versus feast: understanding the metabolism of tumors in vivo. Trends Biochem Sci. 2015;40(3):130–40. doi: 10.1016/j.tibs.2015.01.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Chang CH, Curtis JD, Maggi LB, Jr, Faubert B, Villarino AV, O’Sullivan D, et al. Posttranscriptional control of T cell effector function by aerobic glycolysis. Cell. 2013 Jun 6;153(6):1239–51. doi: 10.1016/j.cell.2013.05.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Xu YF, Létisse F, Absalan F, Lu W, Kuznetsova E, Brown G, et al. Nucleotide degradation and ribose salvage in yeast. MolSyst Biol. 2013 May 14;9:665. doi: 10.1038/msb.2013.21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Psychogios N, Hau DD, Peng J, Guo AC, Mandal R, Bouatra S, et al. The Human Serum Metabolome. PLoS ONE. 2011;6(2):e16957. doi: 10.1371/journal.pone.0016957. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Mashimo T, Pichumani K, Vemireddy V, Hatanpaa KJ, Singh DK, Sirasanagandla S, et al. Acetate is a bioenergetic substrate for human glioblastoma and brain metastases. Cell. 2014 Dec 18;159(7):1603–14. doi: 10.1016/j.cell.2014.11.025. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Shukla SK, Gebregiworgis T, Purohit V, Chaika NV, Gunda V, Radhakrishnan P, et al. Metabolic reprogramming induced by ketone bodies diminishes pancreatic cancer cachexia. Cancer Metab. 2014 Sep 1;2:18. doi: 10.1186/2049-3002-2-18. Erratum in: Cancer Metab. 2014; 2: 22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Wise DR, Thompson CB. Glutamine addiction: a new therapeutic target in cancer. Trends Biochem Sci. 2010 Aug;35(8):427–33. doi: 10.1016/j.tibs.2010.05.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Dang CV. Links between metabolism and cancer. Genes Dev. 2012 May 1;26(9):877–90. doi: 10.1101/gad.189365.112. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.DeBerardinis RJ, Cheng T. Q’s next: the diverse functions of glutamine in metabolism, cell biology and cancer. Oncogene. 2010 Jan 21;29(3):313–24. doi: 10.1038/onc.2009.358. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Zhang J, Fan J, Venneti S, Cross JR, Takagi T, Bhinder B, et al. Asparagine plays a critical role in regulating cellular adaptation to glutamine depletion. Mol Cell. 2014 Oct 23;56(2):205–18. doi: 10.1016/j.molcel.2014.08.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Nicklin P, Bergman P, Zhang B, Triantafellow E, Wang H, Nyfeler B, et al. Bidirectional transport of amino acids regulates mTOR and autophagy. Cell. 2009 Feb 6;136(3):521–34. doi: 10.1016/j.cell.2008.11.044. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Bronietzki AW, Schuster M, Schmitz I. Autophagy in T-cell development, activation and differentiation. Immunol Cell Biol. 2015 Jan;93(1):25–34. doi: 10.1038/icb.2014.81. [DOI] [PubMed] [Google Scholar]
- 58.He MX, McLeod IX, Jia W, He YW. Macroautophagy in T lymphocyte development and function. Front Immunol. 2012 Feb 21;3:22. doi: 10.3389/fimmu.2012.00022. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59.Delgoffe GM, Powell JD. Sugar, fat, and protein: new insights into what T cells crave. Curr Opin Immunol. 2015 Apr;33:49–54. doi: 10.1016/j.coi.2015.01.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Puleston DJ, Zhang H, Powell TJ, Lipina E, Sims LS, Panse I, et al. Autophagy is a critical regulator of memory CD8+ T cell formation. eLife. 2014;3:e03706. doi: 10.7554/eLife.03706. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61.Xu X, Araki K, Li S, Han JH, Ye L, Tan WG, et al. Autophagy is essential for effector CD8(+) T cell survival and memory formation. Nat Immunol. 2014 Dec;15(12):1152–61. doi: 10.1038/ni.3025. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Boroughs LK, DeBerardinis RJ. Metabolic pathways promoting cancer cell survival and growth. Nat Cell Biol. 2015 Apr;17(4):351–359. doi: 10.1038/ncb3124. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63.Zois CE, Favaro E, Harris AL. Glycogen metabolism in cancer. Biochem Pharmacol. 2014 Nov 1;92(1):3. doi: 10.1016/j.bcp.2014.09.001. [DOI] [PubMed] [Google Scholar]
- 64.Merezhinskaya N, Fishbein WN. Monocarboxylate transporters: past, present, and future. Histology and histopathology. 2009;24(2):243–64. doi: 10.14670/HH-24.243. [DOI] [PubMed] [Google Scholar]
- 65.Gladden LB. Lactate metabolism: a new paradigm for the third millennium. The Journal of physiology. 2004;558(Pt 1):5–30. doi: 10.1113/jphysiol.2003.058701. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Philp A, Macdonald AL, Watt PW. Lactate–a signal coordinating cell and systemic function. The Journal of experimental biology. 2005;208(Pt 24):4561–75. doi: 10.1242/jeb.01961. [DOI] [PubMed] [Google Scholar]
- 67.Dhup S, Dadhich RK, Porporato PE, Sonveaux P. Multiple biological activities of lactic acid in cancer: influences on tumor growth, angiogenesis and metastasis. Current pharmaceutical design. 2012;18(10):1319–30. doi: 10.2174/138161212799504902. [DOI] [PubMed] [Google Scholar]
- 68.Sommer F, Bischof S, Rollinghoff M, Lohoff M. Demonstration of organic anion transport in T lymphocytes. L-lactate and fluo-3 are target molecules. Journal of immunology. 1994;153(8):3523–32. [PubMed] [Google Scholar]
- 69.Roth S, Droge W. Regulation of interleukin 2 production, interleukin 2 mRNA expression and intracellular glutathione levels in ex vivo derived T lymphocytes by lactate. European journal of immunology. 1991;21(8):1933–7. doi: 10.1002/eji.1830210823. [DOI] [PubMed] [Google Scholar]
- 70.Roth S, Gmunder H, Droge W. Regulation of intracellular glutathione levels and lymphocyte functions by lactate. Cellular immunology. 1991;136(1):95–104. doi: 10.1016/0008-8749(91)90384-n. [DOI] [PubMed] [Google Scholar]
- 71.Shime H, Yabu M, Akazawa T, Kodama K, Matsumoto M, Seya T, et al. Tumor-secreted lactic acid promotes IL-23/IL-17 proinflammatory pathway. Journal of immunology. 2008;180(11):7175–83. doi: 10.4049/jimmunol.180.11.7175. [DOI] [PubMed] [Google Scholar]
- 72.Yabu M, Shime H, Hara H, Saito T, Matsumoto M, Seya T, et al. IL-23-dependent and -independent enhancement pathways of IL-17A production by lactic acid. International immunology. 2011;23(1):29–41. doi: 10.1093/intimm/dxq455. [DOI] [PubMed] [Google Scholar]
- 73.Ostroukhova M, Goplen N, Karim MZ, Michalec L, Guo L, Liang Q, et al. The role of low-level lactate production in airway inflammation in asthma. American journal of physiology Lung cellular and molecular physiology. 2012;302(3):L300–7. doi: 10.1152/ajplung.00221.2011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 74.Beurel E, Harrington LE, Buchser W, Lemmon V, Jope RS. Astrocytes modulate the polarization of CD4+ T cells to Th1 cells. PLoS One. 2014;9(1):e86257. doi: 10.1371/journal.pone.0086257. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 75.Gatza E, Wahl DR, Opipari AW, Sundberg TB, Reddy P, Liu C, et al. Manipulating the bioenergetics of alloreactive T cells causes their selective apoptosis and arrests graft-versus-host disease. Science translational medicine. 2011;3(67):67ra8. doi: 10.1126/scitranslmed.3001975. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 76.Furusawa Y, Obata Y, Fukuda S, Endo TA, Nakato G, Takahashi D, et al. Commensal microbe-derived butyrate induces the differentiation of colonic regulatory T cells. Nature. 2013 Dec 19;504(7480):446–50. doi: 10.1038/nature12721. [DOI] [PubMed] [Google Scholar]
- 77.Arpaia N, Campbell C, Fan X, Dikiy S, van der Veeken J, deRoos P, et al. Metabolites produced by commensal bacteria promote peripheral regulatory T-cell generation. Nature. 2013;504(7480):451–5. doi: 10.1038/nature12726. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 78.Donohoe DR, Garge N, Zhang X, Sun W, O’Connell TM, Bunger MK, Bultman SJ. The microbiome and butyrate regulate energy metabolism and autophagy in the mammalian colon. Cell Metab. 2011;13(5):517–26. doi: 10.1016/j.cmet.2011.02.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 79.Lochner M, Berod L, Sparwasser T. Fatty acid metabolism in the regulation of T cell function. Trends immune. 2015;36(2):81–91. doi: 10.1016/j.it.2014.12.005. [DOI] [PubMed] [Google Scholar]
- 80.O’Sullivan D, van der Windt GJ, Huang SC, et al. Memory CD8(+) T cells use cell-intrinsic lipolysis to support the metabolic programming necessary for development. Immunity. 2014 Jul 17;41(1):75–88. doi: 10.1016/j.immuni.2014.06.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81.Cui G, Staron MM, Gray SM, et al. IL-7-Induced Glycerol Transport and TAG Synthesis Promotes Memory CD8(+) T Cell Longevity. Cell. 2014;161(4):750–61. doi: 10.1016/j.cell.2015.03.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 82.Siska PJ, Rathmell JC. T cell metabolic fitness in antitumor immunity. Trends immunol. 2015;36(4):257–64. doi: 10.1016/j.it.2015.02.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 83.Wang T, Liu G, Wang R. The Intercellular Metabolic Interplay between Tumor and Immune Cells. Front Immuno. 2014;5:358. doi: 10.3389/fimmu.2014.00358. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 84.O’Sullivan D, Pearce EL. Targeting T cell metabolism for therapy. Trends Immunol. 2015;36(2):71–80. doi: 10.1016/j.it.2014.12.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 85.Hsu PP, Sabatini DM. Cancer cell metabolism: Warburg and beyond. Cell. 2008;134(5):703–7. doi: 10.1016/j.cell.2008.08.021. [DOI] [PubMed] [Google Scholar]
- 86.Cairns RA, Harris IS, Mak TW. Regulation of cancer cell metabolism. Nat Review Cancer. 2011;11(2):85–95. doi: 10.1038/nrc2981. [DOI] [PubMed] [Google Scholar]
- 87.Lob S, Konigsrainer A. Inhibitors of indoleamine-2,3-dioxygenase for cancer therapy: can we see the wood for the trees? Nat Rev Cancer. 2009;9(6):445–52. doi: 10.1038/nrc2639. [DOI] [PubMed] [Google Scholar]
- 88.Munn DH, Mellor AL. Indoleamine 2,3-dioxygenase and tumor-induced tolerance. J Clin Invest. 2007;117(5):1147–54. doi: 10.1172/JCI31178. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 89.Pilotte L, Larrieu P. Reversal of tumoral immune resistance by inhibition of tryptophan 2,3-dioxygenase. Proc Natl Acad Sci U S A. 2012;109(7):2497–02. doi: 10.1073/pnas.1113873109. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 90.Srivastava MK, Sinha P, Clements VK, Rodriguez P. Ostrand-Rosenberg. Myeloid-derived suppressor cells inhibit T-cell activation by depleting cystine and cysteine. Cancer Res. 2010;70(1):6. doi: 10.1158/0008-5472.CAN-09-2587. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 91.Lind DS. Arginine and cancer. J Nutr. 2004;134(10 Suppl):2837S–41S. doi: 10.1093/jn/134.10.2837S. [DOI] [PubMed] [Google Scholar]
- 92.Topalian SL, Drake CG, Pardoll DM. Immune checkpoint blockade: a common denominator approach to cancer therapy. Cancer Cell. 2015 Apr 13;27(4):450–61. doi: 10.1016/j.ccell.2015.03.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 93.Sharma P, Allison JP. The future of immune checkpoint therapy. Science. 2015 Apr 3;348(6230):56–61. doi: 10.1126/science.aaa8172. [DOI] [PubMed] [Google Scholar]
- 94.Miller J, Sadelain M. The journey from discoveries in fundamental immunology to cancer immunotherapy. Cancer Cell. 2015;27(4):439–49. doi: 10.1016/j.ccell.2015.03.007. [DOI] [PubMed] [Google Scholar]
- 95.Scott AM, Wolchok JD, Old LJ. Antibody therapy of cancer. Nat Rev Cancer. 2012;12(4):278–87. doi: 10.1038/nrc3236. [DOI] [PubMed] [Google Scholar]
- 96.Nguyen Lt, Ohashi Ps. Clinical blockade of PD1 and LAG3–potential mechanisms of action. Nat Rev Imm. 2015;15(1):45–56. doi: 10.1038/nri3790. [DOI] [PubMed] [Google Scholar]
- 97.Patsoukis N, Bardhan K, Chatterjee P, et al. PD-1 alters T-cell metabolic reprogramming by inhibiting glycolysis and promoting lipolysis and fatty acid oxidation. Nat Comm. 2015;6:6692. doi: 10.1038/ncomms7692. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 98.Saha A, Aoyama K, Taylor PA, et al. B Host programmed death ligand 1 is dominant over programmed death ligand 2 expression in regulating graft-versus-host disease lethality. Blood. 2013;122(7):3062–73. doi: 10.1182/blood-2013-05-500801. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 99.Parry RV, Chemnitz JM, Frauwirth KA, et al. CTLA-4 and PD-1 receptors inhibit T-cell activation by distinct mechanisms. Mol Cell Biol. 2005 Nov;25(21):9543–53. doi: 10.1128/MCB.25.21.9543-9553.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 100.Restifo NP, Dudley ME, Rosenberg SA. Adoptive immunotherapy for cancer: harnessing the T cell response. Nat Rev Immunol. 2012 Mar 22;12(4):269–81. doi: 10.1038/nri3191. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 101.Joyce JA, Fearon DT. T cell exclusion, immune privilege, and the tumor microenvironment. Science. 2015;348(6230):74–80. doi: 10.1126/science.aaa6204. [DOI] [PubMed] [Google Scholar]
- 102.June CH, Riddell SR, Schumacher TN. Adoptive cellular therapy: a race to the finish line. Sci Transl Med. 2015;7(280):280ps7. doi: 10.1126/scitranslmed.aaa3643. [DOI] [PubMed] [Google Scholar]
