The metabolic programs that drive T cell functions are exquisitely sensitive to cell intrinsic and extrinsic factors, allowing T cells to respond in a fine-tuned manner to a variety of immune challenges and conditions. However, many of the factors essential for effector T cell function are perturbed in the tumor microenvironment, where oncogenic mutations drive unrestrained cancer cell growth that leads to excess nutrient consumption, excess waste excretion, and insufficient oxygen delivery. This imposes metabolic constraints on infiltrating cells that result in dysfunction and loss of potential antitumor activity in both naturally occurring as well as tailored T cells introduced as part of immunotherapy. In this review, we highlight the metabolic properties that characterize tumor-infiltrating T cells, the barriers within the metabolic landscape of the tumor microenvironment, and the opportunities and challenges they present in development of new cancer therapeutics.

Oncogenic mutations that promote cancer cell proliferation do so in part by stimulating anabolic metabolism and cell growth. Cancer cells are typically characterized by high rates of nutrient uptake and glycolysis with lactate secretion even in the presence of oxygen. This metabolic program is termed the Warburg effect, or aerobic glycolysis (1). Although inefficient at ATP generation, aerobic glycolysis efficiently supports biosynthesis of essential macromolecular precursors. To fuel this program, glucose and other nutrients can be rapidly consumed, whereas waste products are secreted and accumulate, which can greatly impact the tumor microenvironment (TME). As tumors grow in size, oxygen perfusion can also become limiting, creating regions of hypoxia. Together, these genetically driven metabolic characteristics of cancer cells generate a nutrient-deficient, waste product–replete, acidic, and hypoxic microenvironment. Local conditions within tumors, therefore, can exclude or inhibit stromal cells, fibroblasts, and immune cells. If sufficient neoantigens are present, T cells may be primed in nearby lymph nodes and migrate to enter the TME in an effort to eliminate cancer cells. Recent work in the field of immunometabolism, however, has shown that immune cells essential to promote antitumor immunity, including macrophages, dendritic cells, and lymphocytes, depend on similar growth signals and nutrients as cancer cells. Metabolic reprogramming that is required for appropriate T cell functions, therefore, may not be properly induced or maintained in tumors due to resource competition. As a result, T cells that may otherwise be equipped to destroy cancer cells may find an overwhelmingly hostile environment and lose their ability to do so.

There is currently a rapid and exciting expansion of efforts to stimulate antitumor immunity as a means to eliminate cancer cells. As we better understand the metabolic properties of tumor-infiltrating lymphocytes (TILs), however, it is becoming clearer that the metabolic environment of the TME serves as a significant barrier to achieving greater treatment efficacy. A new and promising approach is to consider the effects of the TME on T cell metabolism as an avenue to improve and promote appropriate immune cell function. In this review, we will provide a brief overview of the metabolic programs of T cells and how the TME affects these programs. In doing so, we hope to shed light on the implications this has on the limitations of currently available agents, as well as the opportunities this provides to develop new therapies to complement existing therapies.

The impact of the TME on the metabolic programs of T cells has only recently been appreciated as a potentially limiting barrier to antitumor immunity as the fields of immune metabolism and immune oncology have expanded. New findings in immunometabolism have shown that metabolic states are tightly linked and critical regulators of T cell effector function such that changes in nutrient availability may impact T cell activity (Fig. 1). Thus, the effects of cancer cells and cancer cell metabolism on the TME may directly modulate essential T cell metabolic pathways and activities.

FIGURE 1.

T cell metabolic programs balance the activity of multiple pathways, including glycolysis, mitochondrial oxidation, glutaminolysis, FAO, and FA synthesis to meet its biosynthetic and bioenergetic demands. This balance is maintained by opposing and cooperative forces applied by major metabolic regulators including mTOR, HIF1α, Myc, and AMPK.

FIGURE 1.

T cell metabolic programs balance the activity of multiple pathways, including glycolysis, mitochondrial oxidation, glutaminolysis, FAO, and FA synthesis to meet its biosynthetic and bioenergetic demands. This balance is maintained by opposing and cooperative forces applied by major metabolic regulators including mTOR, HIF1α, Myc, and AMPK.

Close modal

Mature naive T (Tn) cells are mainly driven by mitochondrial oxidative phosphorylation (OXPHOS) and fatty acid (FA) oxidation (FAO) (2). Although these cells are considered to be in a quiescent state, they still require energy for housekeeping functions to maintain immune surveillance activities while preventing spurious activation and inappropriate inflammatory responses. Notably, activation of Tn cells with Ag and proper costimulation generates effector T (Teff) cells with a metabolic program resembling that of highly proliferative cancer cells. Activated T cells further differentiate into subsets with characteristic effector functions, and it is now clear that each T cell subset utilizes a program that is specific to its function. These characteristic metabolic programs are driven by nutrient-sensitive signaling pathways, such as the mechanistic target of rapamycin (mTOR) complex, and the activity of key transcription factors, including T-bet in T helper 1 (Th1), GATA-3 in T helper 2 (Th2), RORγ(t) in T helper 17 (Th17), and Foxp3 in regulatory T (Treg) cells. Importantly, if inadequate nutrients or inhibitory signaling prevent T cells from realizing the appropriate metabolic program tailored to each specific effector function, they do not perform that function and instead fail to differentiate or potentially differentiate along different paths.

Teff cell activation and differentiation.

To meet the significant bioenergetic and biosynthetic demands of clonal proliferation and effector function, activated T cells undergo major metabolic reprogramming, sharply shifting from OXPHOS and FAO that characterize Tn cells to glycolysis and glutaminolysis that characterize Teff cells (2, 3). This cascade of events requires antigenic stimulation through the TCR as well as engagement of CD28 with ligand on APCs. Costimulation both augments TCR signals and stimulates PI3K/Akt/mTOR complex 1 (mTORC1) pathway activity (4). Inadequate costimulation results in metabolic impairments and the induction of T cell anergy. Specifically, in in vitro conditions lacking CD28 signals or under conditions where these signals are suppressed, T cells fail to upregulate the glucose transporter Glut1 and induce aerobic glycolysis essential for effector function (5). A key mechanism to suppress or reverse costimulatory signals is through the CD28-related inhibitory receptors, programmed death-1 (PD-1) and CTLA-4, which can recruit phosphatases to inhibit PI3K signaling and slow or impair T cell activation (6, 7). PD-1 ligand (PD-L1) can be induced by IFN-γ signaling or hypoxia in murine models to dampen T cell activation and is frequently expressed in tumors and exploited to reduce inflammation and antitumor immunity (8, 9).

To maintain aerobic glycolysis in Teff cells, pyruvate is shunted away from the TCA cycle and toward lactate production despite sufficient oxygen levels to support respiration (2). The largest metabolic challenge of activated T cells is to rapidly generate sufficient biomass for growth and proliferation. Although the quantity of ATP produced through glycolysis is substantially less than that produced through OXPHOS, aerobic glycolysis is a highly efficient mechanism to produce biosynthetic precursors for this purpose. Moreover, this program also generates reducing agents as well as metabolic intermediates with a variety of synthetic, signaling, and epigenetic roles (2). Aerobic glycolysis may also increase T cell fitness in overwhelmingly hypoxic environments that may be encountered during development or in inflammatory and tumor settings. The increase in glycolysis is thus critical to support rapid Teff cell proliferation and inflammatory function. T cells that fail to access sufficient glucose early in activation are unable to efficiently proliferate and produce IFN-γ as shown in cells cultured in glucose-deficient conditions (1012). Consistent with this observation, deletion of Glut1 led to reduced T cell proliferation and inflammatory function in vivo (13), whereas increased Glut1 expression in a T cell–specific Glut1 transgenic promoted Teff cell–mediated inflammation and autoimmunity (14).

In aerobic glycolysis, mitochondrial metabolism does continue and the TCA cycle and OXPHOS can continue to provide ATP. However, Teff cell mitochondria undergo remodeling and fragmentation upon stimulation, and show reduced electron transport efficiency (15). At the same time, the overall rate of mitochondrial metabolism and OXPHOS does increase, and suppression of OXPHOS leads to failure of T cell activation and proliferation. In addition to ATP production, mitochondrial metabolism may support generation of essential levels of reactive oxygen species (ROS) (16) and provide biosynthetic intermediates from the TCA cycle.

To support these processes, Teff cells require access and uptake of an abundance of nutrients, including glucose, glutamine, and other amino acids. Indeed, CD28-mediated costimulation coordinates upregulated expression and trafficking to the cell surface of numerous nutrient transporters, including Glut1 (5, 11, 13), the glutamine transporters SNAT1 and SNAT2 (17), and the neutral amino acid transporters SLC1a5 and SLC7a5 (18, 19). Additionally, expression of the monocarboxylate lactate transporters MCT1 and MCT4 are increased (20) to facilitate removal of lactate produced in aerobic glycolysis. In addition to export, the monocarboxylate transporters can also facilitate lactate uptake in certain conditions. In principle, lactate can be oxidized following conversion back to pyruvate in a pathway that can inhibit glycolysis. Although increased exposure to lactate can inhibit Teff cells (21), lactate can be efficiently oxidized by Treg cells (22). As such, inadequate upregulation of nutrient transporters or failure to access these nutrients hinders T cell activation and Teff cell generation, but can support Treg cells.

The metabolic reprogramming of OXPHOS and FAO to glycolysis and glutaminolysis is driven by several key regulators. TCR engagement directly leads to the induction and activation of the PI3K/Akt/mTORC1 and Myc pathways, which are required for Teff cell activation, proliferation, and function (2). Activation of mTOR promotes glycolysis through several mechanisms, including through the upregulation of the major regulators c-Myc and hypoxia inducible factor 1α (HIF1α) (3, 5, 11, 14, 23, 24). Myc and the subsequent downstream induction of transcription factor AP4 upregulates expression of enzymes of the glycolytic pathway (25) and Myc-deficient Teff cells fail to upregulate glycolysis following in vitro activation (3). Increased HIF1α activity promotes aerobic glycolysis and reduces OXPHOS by upregulating pyruvate dehydrogenase kinase (PDK1) and lactate dehydrogenase A (26, 27), effectively shunting pyruvate away from the TCA cycle toward lactate production. HIF1α also enhances glycolysis through upregulation of the transporters Glut1 and MCT4, as well as multiple glycolytic enzymes and regulators (28). This effect is recapitulated in CD8+ T cells isolated from mice with a conditional knockout of the von Hippel-Lindau tumor suppressor, a negative regulator of HIF1α (23).

Functional refinement of Teff cells into specific subtypes is also linked to the activity of mTOR, as T cells deficient in mTOR kinase fail to generate Teff cells and can only efficiently generate Treg cells. The specific mTOR complexes also selectively influence T cell differentiation. mTORC1 activity promotes Th1 differentiation, whereas mTORC2 activity promotes Th2 differentiation. Conversely, loss of mTORC1 signaling prevents Th1 and Th17 formation, but not Th2 formation (29). mTORC1-dependent induction of HIF1α has been implicated in polarizing Th17 and inhibiting Treg cell differentiation through upregulation of IL-17 and RORγ(t)-mediated degradation of Foxp3 in in vitro and in vivo conditions (30).

Treg cell differentiation.

In contrast to Teff cells, the dominant metabolic program in Treg cells is mitochondrial oxidation of pyruvate and FAO. The rate of glycolysis is much lower in Treg cells than in Teff cells (14). AMP-activated protein kinase (AMPK), an inhibitor of the mTORC1 pathway, is a major driver of reprogramming in Treg cells. Activation of AMPK signaling by metformin-induced mitochondrial inhibition promotes Treg cell differentiation (14). Inhibition of mTORC1 by rapamycin treatment leads to accumulation of Treg cells, and genetic deletion of mTOR produces T cells that can only generate Treg cells (31). Likewise, deficiency of HIF1α and glycolysis results in increased Treg cell generation in vitro and in vivo (28, 30). Additionally, Foxp3 itself also acts as a regulator of Treg cell oxidative metabolism and suppresses PI3K/Akt signaling, Glut1 expression, and expression of glycolytic enzymes (22, 3234). Within tumors, this effectively renders Treg cells less glucose dependent and also better equipped to consume lactate as a mitochondrial fuel (22).

This oxidative metabolism generally impedes proliferation by promoting catabolism. However, Treg cells retain the capacity to divide rapidly in response to homeostatic signals as well as in response to inflammatory cues such as TLR (33). In these cases, however, Glut1 expression increases and the mTORC1 pathway is activated to elevate glycolytic rates (32). Interestingly, chronic activation of the PI3K/Akt/mTORC1 pathway can destabilize Treg cells (3537) and downregulate Foxp3 (32), leading to an inability of Treg cells to efficiently suppress inflammation. This effect is mediated in part by elevated glycolysis, as transgenic expression of Glut1 was sufficient to destabilize Foxp3 and reduce Treg cell suppressive capacity ex vivo and in vivo (32).

Memory T cell formation and persistence.

Memory T (Tmem) cells are also often found infiltrating solid tumors as effector memory cells, and may play key roles in responding to immunotherapy and eliminating cancer cells. In inflammatory reactions, Tmem cells undergo rapid activation in response to secondary challenge that is characteristically faster and greater in amplitude than that induced by the primary challenge. This is encoded in part by “priming” of the metabolic program (38, 39). More specifically, there is an increase in mitochondrial mass with a concomitant increase in spare respiratory capacity (40) that is proposed to allow rapid ATP production following restimulation.

The metabolic reprogramming that occurs in the generation of Tmem cells from Teff cells in some ways resembles the reverse process of activation as they shift from a highly anabolic proliferative program to a catabolic program suited for long-term cell survival. To accomplish this, the PI3K/Akt/mTORC1 pathway is tuned down and T cells internalize many nutrient transporters from the cell surface. In Tmem cells, OXPHOS and FAO are the primary pathways by which energy is generated (2). FAO in Tmem cells is proposed to be largely fueled by de novo FA synthesis instead of by imported exogenous FAs (41). This apparent futile cycle of energy production and consumption may be important to maintain redox balance as well as to provide an adequate pool of metabolic intermediates.

Accordingly, mTOR inhibition in Teff cells via rapamycin treatment promotes formation of Tmem cells (42, 43), an effect that is similarly induced with AMPK activation via metformin treatment (43, 44) in vitro and in vivo. At the same time, glycolysis remains required for CD4+ Tmem cell formation and to promote increased Tmem cell numbers as shown by treatment with the glycolytic inhibitor 2-deoxyglucose in culture (45). The relative contributions of glycolysis and OXPHOS seem to be complex, with glycolysis playing an anabolic role in increasing cell numbers, and OXPHOS promoting more efficient differentiation into the memory phenotype. As one example of this dynamic interplay, the provision of excess pyruvate to bypass defects in glycolysis and fuel mitochondria was sufficient to increase the activation of Tmem cells from patient samples of clear cell renal cell carcinoma (46).

T cells isolated from tumors are often in a functionally exhausted state with a metabolic signature that is distinct from both resting and acutely activated T cells (4648). In healthy tissues, an intricate regulation of nutrient import, waste export, oxygenation, pH balance, and delivery of appropriate signaling molecules are achieved by the vascular system, the lymphatic system, and the supporting stromal cells. In the TME, this balance is structurally and functionally perturbed by the growth and metabolism of cancer cells. Consequently, TILs are exposed to heterogeneous conditions that incur significant metabolic stress (Fig. 2).

FIGURE 2.

Cancer cell activity leads to altered nutrient availability, presence of immunosuppressive signals, relative hypoxia, and waste accumulation within the TME. This poses significant metabolic constraints on tumor-infiltrating T cells that in turn drive changes in their metabolic programs, and therefore antitumor activity.

FIGURE 2.

Cancer cell activity leads to altered nutrient availability, presence of immunosuppressive signals, relative hypoxia, and waste accumulation within the TME. This poses significant metabolic constraints on tumor-infiltrating T cells that in turn drive changes in their metabolic programs, and therefore antitumor activity.

Close modal

Although poorly understood, both extrinsic nutrient limitation and competition with cancer cells (49, 50) and intrinsic T cell metabolic impairments (4648, 51) that result from chronic stimulation and other microenvironmental influences can impair antitumor immunity. The TME was shown to impair T cell function by cancer cell consumption of glucose and lactate production. Increased tumor glycolysis can inhibit antitumor function of T cells (49, 50) and accumulation of lactate can impair Teff cells (21) while promoting Treg cells (52) ex vivo. At the same time, some defects in glycolysis appear to be cell intrinsic, as T cells from human clear cell renal cell carcinoma had downregulated GAPDH and failed to uptake glucose even when removed from the tumor and cultured in abundant nutrients (46). Additionally, mitochondria have been reported to be depleted from T cells in melanoma models (47). In settings where TIL mitochondrial content has been normal (46, 48), mitochondrial structure and function were nevertheless altered, suggesting a general dysregulation of mitochondria. The inability of T cells to efficiently uptake glucose and perform glycolysis combined with the ability to nevertheless partially restore TIL function with addition of pyruvate (46) suggests that, despite mitochondrial defects, TILs are programmed for oxidative metabolism. Collectively, these metabolic impairments form barriers to effective antitumor immunity. A key challenge to improve immunotherapy, therefore, is to determine what factors in the TME inhibit Teff cell metabolism.

Below, we deconstruct the TME into several components: decreased nutrient availability, hypoxia, lactate accumulation and acidosis, and checkpoint inhibition. In doing so, we aim to parse out how each component can contribute to metabolic changes in Teff cells. It should be noted, however, that the changes invoked by one factor, such as hypoxia, can further alter how the cells respond to another factor, such as glucose limitation, and thus need to be taken into consideration in combination as an additional layer of complexity. Moreover, in the context of in vitro studies, this raises the importance of testing combinations of factors, and in in vivo studies, accounting for the effect of confounding factors.

Decreased nutrient availability.

Glucose limitation.

The consumption of glucose by cancer cells can render this key nutrient limiting in poorly perfused tumors (49, 50), which may then impair Teff cells that depend on glucose. Accordingly, overexpression of Glut1 in a tumor correlates with low CD8+ T cell infiltration (53) and poor prognosis in certain cancers (54). Glucose deficiency itself may contribute to poor tumor immunity as glucose deprivation in vivo and Glut1-deficiency in vivo can promote an exhausted-like state with blunted antitumor activity in T cells that is characterized by impaired TCR signaling, proliferation, and cytokine production (10, 11, 13, 55). In addition to inhibiting mTORC1 activation and induction of Myc, failure of Teff cells to acquire sufficient glucose can also impair NFAT signaling due to the function of phosphoenolpyruvate in regulating the calcium sarco/endoplasmic reticulum Ca2+-ATPase channel (49). IFN-γ translation can also be suppressed given the regulatory role of GAPDH in this process (12). Additionally, generation of acetyl-CoA via glucose metabolism can influence histone acetylation to epigenetically regulate cytokine transcription (56). Conversely, Glut1 deficiency has limited effect on Treg cells induced in culture as well as in in vivo model of inflammatory disease, and glucose-deficient conditions instead promote Treg cell induction and suppressive activity in vitro (13, 14, 28). Thus, cancer cell–mediated depletion of glucose likely favors a shift in the balance of Teff cells and Treg cells within the TME in favor of a more anti-inflammatory state.

Altered amino acid levels.

Glutamine is a major anaplerotic fuel required for maintaining the TCA cycle as well as a vital source for lipid synthesis through reductive carboxylation in hypoxic cancer cells (1) and Teff cells (2). The major glutamine transporter SLC1a5 (ASCT2) is overexpressed in several types of cancer, including melanoma and prostate cancer (57). Like glucose, there may be resource competition for glutamine and its derivatives between cancer and immune cells. This may sharply impair antitumor immunity, as reduced glutamine levels in culture will decrease nucleotide synthesis, and blunt Teff cell activation, proliferation, and cytokine production (3, 5, 17). Further, genetic deletion of ASCT2 specifically reduces Th1 and Th17 numbers in vivo without affecting the generation of Th2 and Treg cells (19), highlighting the differential effects one nutrient can have on subsets. Likewise, deletion of the large neutral amino acid transporter SLC7a5 (LAT1) prevents mTORC1 activation, thus impairing induction of Glut1 expression and aerobic glycolysis in stimulated T cells ex vivo and in vivo (18).

Arginine metabolism is also dysregulated in various cancers. Arginine is critical to the urea cycle and polyamine synthesis pathways that are essential for supporting a variety of biochemical and potential signaling functions (58). Major enzymes involved in arginine metabolism, including NO synthase and arginase that catabolize arginine, are highly expressed in a variety of cancer cells as well as in tumor-associated alternatively activated M2 macrophages that can promote tumor progression (59). In contrast, argininosuccinate synthetase 1 is lacking in many tumors (60), increasing dependence of the cancer cells on exogenous arginine. T cells are also highly dependent on arginine, and this amino acid can rapidly become limiting for proliferation and function (61, 62).

Tryptophan metabolism is dysregulated in various cancers as well, and directly contributes to impaired antitumor immunity. IDO, an enzyme that converts tryptophan to kynurenine, has increased activity in many cancer cells with particularly high levels found in melanoma (63), pancreatic ductal adenocarcinoma (64), and ovarian cancer (65). IDO activity is linked to inhibition of glycolysis with induction of an anergic state in Teff cells. Tryptophan deficiency itself can inhibit mTORC1 activity, leading to impaired Teff cell activation and proliferation. Additionally, IDO activity leads to accumulation of kynurenine and its derivatives within the TME. Kynurenine contributes to ineffective TCR signaling and consequent T cell dysfunction, impaired proliferation, and cell death. In contrast, kynurenine is a ligand of the aryl hydrocarbon receptor and may enhance Treg cell differentiation (66).

Fatty acids.

FA synthesis is also critical to generation of macromolecules and membranes as well as to regulation of cell signaling. Many cancer cells have perturbed FA homeostasis with dysregulated lipogenesis and lipolysis that reflects the potentially conflicting pathways of simultaneous lipid synthesis and oxidation (1). Given potential differential reliance on de novo synthesized FA versus exogenous FA uptake among different subsets, changes in FA levels within the TME likely affect each subset differently, polarizing the composition of the TIL population. Notably, Tmem cells are unable to develop in the absence of FAs in culture (44). Both in vitro and in vivo studies in the gut suggest short chain FAs can induce Treg cell differentiation (67, 68), although this may be through changes in G protein–coupled receptor-mediated signaling rather than direct use as a metabolic fuel. The exact nature of FA diversity and availability within the TME is still unclear, and thus requires further investigation before the contribution of FAs to TIL function can be understood.

Hypoxia.

Regions of the TME can have inadequate oxygen delivery due to insufficient vasculature, incompetent neovasculature, robust desmoplasia obstructing perfusion, as well as anemia of chronic disease. Hypoxia and upregulation of HIF1α in tumors are both associated with poor clinical outcomes in cancer patients (69). Hypoxia may affect T cell metabolism and function in multiple ways. First, hypoxia is a potent activator of HIF1α, a critical regulator that promotes aerobic glycolysis (2). In addition to glycolytic genes, one major target of HIF1α is pyruvate dehydrogenase kinase, which reduces glucose oxidation to promote conversion of pyruvate to lactate. Under these conditions, glutaminolysis increases and glutamine becomes critical for supporting TCA cycle progression and lipid synthesis. Additionally, PD-L1 is a direct target of HIF1α in cancer cells, and, therefore, countering hypoxia in this setting may reduce PD-L1 expression and contribute to increased T cell function. Second, a reduced OXPHOS rate may contribute to decreased levels of intracellular ROS; although damaging at high levels, ROS at moderate levels are required for TCR signaling (16). Third, hypoxia can drive certain pathways that are relatively noncontributing under normoxic conditions. For instance, hypoxia in cells with highly polarized mitochondria can induce the reversal of succinate dehydrogenase activity and electron transport, leading to excess ROS production (70).

Lactate accumulation and acidosis.

Another potent factor in the TME is the effect of the excess lactate excreted by cancer cells. This can potentially affect TIL function in several ways, such as by increasing lactate concentration in the TME, increasing intracellular lactate in TILs due to inadequate export, and decreasing the pH of the TME. Treatment with excess lactic acid inhibits human CD8+ T cell activation, proliferation, and effector functions in vitro (71), whereas neutralization of TME acidosis by bicarbonate therapy improves response rates in checkpoint blockade as well as adoptive cell therapy in murine models (72). Lactic acidosis is also associated with suppression of the PI3K/Akt/mTORC1 pathway and glycolysis in culture (73). Additionally, lactate has been shown to stabilize HIF1α in macrophages (74), and can be predicted to have similar effects in T cells. Acid-sensing receptors may contribute to downregulation of Myc expression (75) as well as inhibition of glycolysis in these cells (72). Moreover, extracellular acidification has been shown to induce mitochondrial remodeling leading to metabolic adaptation (76, 77).

Checkpoint inhibition.

In addition to altered nutrients, cancer cells express ligands that can directly signal to modify and impair Teff cell metabolism. Expression of PD-L1 on tumor cells can potently modulate several different T cell metabolic pathways. PD-1 ligation leads to reduction in PI3K/Akt/mTOR pathway activity (6) with associated reduction in c-Myc expression (78, 79). This can impair metabolic reprogramming such as the upregulation of glycolysis (7) and glutaminolysis (6) that is critical to effective antitumor activity in TILs. PD-1 blockade in turn results in re-engagement of aerobic glycolysis through increased expression of Glut1 and glycolytic enzymes, with subsequent enhancement in Teff cell activation and proliferation (80). Additionally, PD-1 ligation has been shown to promote FAO (7), thereby promoting Treg cell differentiation and suppressive activity (81) as well as Tmem cell formation (82) as shown by murine adoptive transfer studies. Likewise, B7 ligands expressed on APCs within the TME can bind CTLA-4 receptors on TILs and similarly affect T cell metabolism and inhibit upregulation of glycolysis (5). As such, checkpoint inhibitors are expected to broadly affect T cell metabolism, but much remains unknown.

In considering the importance of metabolic programming in cancer cell and immune cell behavior, we can revise our understanding of therapeutics in use today. Taking this approach may allow us to better parse the differences between cases in which certain therapeutics are effective and those in which they are not. Consider PD-1 blockade, which has yielded promising results in many cancer patients, but not so in a sizeable population of patients (83). PD-1 blockade can enhance the metabolic competitiveness of T cells within the TME through interference with the immunosuppressive effects of PD-1 ligation as outlined in the previous section. However, given the multitude of metabolic programs that drive different subsets and the genetic and microenvironmental heterogeneity of tumors, it is to be expected that PD-1 blockade will have varying efficacy. Along the same lines, even nonimmune focused cancer therapies, including existing targeted small molecules as well as caloric restriction and dietary modification approaches, should be revisited to better characterize any potential indirect effects on the TME as well as potential direct and indirect effects on T cells and their antitumor activity.

It follows that better appreciation of the TME and metabolic profiling of T cells within tumors may provide more reliable predictions of therapy outcome. To this end, one potential method is sampling PBMC as proxies for TIL status. In patients with clear cell renal cell carcinoma, PBMC T cell population has been shown to phenotypically mirror the TIL population (46). As more reliable markers are discovered, more precise prediction of TIL composition will become possible. In terms of TME characterization in patients, there are a multitude of imaging techniques that are already available and expanding rapidly. These include magnetic resonance spectroscopy, dynamic nuclear polarization magnetic resonance spectroscopy, positron emission tomography, and mass spectrometry imaging for measuring various metabolic parameters (84), as well as oxygen-enriched magnetic resonance imaging for tumor hypoxia measurements in situ as shown in preclinical cancer models (85). Equipped with the information obtained from these approaches, therapy can be better tailored to the TME and T cell population status within the tumor.

Next, we look toward the development of therapeutics that work synergistically with currently available methods that is informed by better understanding of the metabolic constraints that the TME poses on T cells. Many of the more recently developed methods, including cancer vaccines, ex vivo T cell expansion, TCR engineering, and chimeric Ag receptor T cells have not shown satisfactory efficacy in solid tumors (86). Failure to appropriately account for the effect of the immunosuppressive TME is likely a major contributing factor to this problem. The efficacy of these new therapeutics may therefore be improved in one of two ways. First is the supplementation of an agent that increases the metabolic competitiveness of certain T cell subsets within the TME. Indeed, promoting T cell production of phosphoenolpyruvate or provision of pyruvate can increase TIL activation and function (46, 49). Conversely, T cell metabolism can be modulated to favor generation of Tmem cells that may enhance adoptive T cell therapy and immunotherapy (87). Examples include drugs already available on the market, such as methotrexate that inhibits dihydrofolate reductase in the one-carbon metabolism pathway, as well as drugs currently in clinical trials, such as epacadostat that inhibits IDO in the tryptophan metabolism pathway (29). The improved efficacy achieved by a combination of these approaches, including cancer vaccines and chimeric Ag receptor T cells with checkpoint blockade (86) provides strong argument for this approach. The second is to target cancer cell metabolism to shape the TME into a more favorable environment for T cell function. In these efforts, it is particularly important to keep in mind the similarities and differences between cancer cell and immune cell biology. Given the significant overlaps, potential adverse “off target” effects on otherwise valuable effectors must be avoided. By the same token, any differences, even nuanced ones, represent rich opportunities to harness the extraordinary inherent capacities of the immune system in eliminating cancer cells.

We thank members of the Rathmell laboratory.

This work was supported by a Vanderbilt-Incyte Research Alliance Program grant (to J.C.R.) and Medical Scientist Training Program Grant T32GM007347 (to A.S.).

Abbreviations used in this article:

     
  • AMPK

    AMP-activated protein kinase

  •  
  • FA

    fatty acid

  •  
  • FAO

    FA oxidation

  •  
  • HIF1α

    hypoxia inducible factor 1α

  •  
  • mTOR

    mechanistic target of rapamycin

  •  
  • mTORC1

    mTOR complex 1

  •  
  • OXPHOS

    oxidative phosphorylation

  •  
  • ROS

    reactive oxygen species

  •  
  • Teff

    effector T

  •  
  • TIL

    tumor-infiltrating lymphocyte

  •  
  • TME

    tumor microenvironment

  •  
  • Tmem

    memory T

  •  
  • Tn

    naive T

  •  
  • Treg

    regulatory T.

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The authors have no financial conflicts of interest.