|
 
 |
| REVIEW ARTICLE |
|
| Year : 2018 | Volume
: 1
| Issue : 3 | Page : 72-79 |
|
Immunometabolomics: The metabolic landscape of immune cells in tumor microenvironment
Subhanki Dhar, Sayantan Bose, Gaurisankar Sa
Division of Molecular Medicine, Bose Institute, Kolkata, West Bengal, India
| Date of Submission | 11-Mar-2020 |
| Date of Decision | 15-Jun-2020 |
| Date of Acceptance | 25-Aug-2020 |
| Date of Web Publication | 04-Jan-2021 |
Correspondence Address:
Gaurisankar Sa
Division of Molecular Medicine, Bose Institute, P-1/12, CIT Scheme VII M, Kolkata - 700 054, West Bengal
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/tme.tme_2_20
The tumor microenvironment is composed of a diverse milieu of cells such as the stromal cells, various types of immune cells as well the neoplastic cells. Substantial research in the last few decades has provided a detailed picture of the nature and content of the tumor microenvironment. Apart from the diverse composition, the recent focus has been on the altered state of metabolism seen in the cells of the tumor microenvironment. Cancer cells show increased uptake of available nutrients, and they are also highly active in generating metabolic by-products, which creates a unique microenvironment. Such aggressive metabolism of cancer cells highly affects the viability and function of the surrounding cells, specially the immune cells. The nutrient-deprived tumor microenvironment along with toxic metabolic by-products hinders immune cell activation and fosters the generation of a tolerogenic immune response. The dynamic interaction between immune cells and the tumor microenvironment has proved to be a fertile area of research. This has led to the development of immunotherapy, which has been highly successful in treating malignancies. Metabolism plays a pivotal role in determining this interaction as evident from the increasing number of studies that have emerged in this new area of immunometabolism in the tumor microenvironment. In this review, we aim to summarize the current information on the metabolic pathways operational in the tumor microenvironment and the detailed mechanisms through which the function of tumor-infiltrating immune cells get affected by the tumor cells. The review also tries to outline the importance of exploring this area to design novel, targeted immunotherapy. Keywords: Immune cells, immunometabolism, metabolism, tumor microenvironment
How to cite this article:
Dhar S, Bose S, Sa G. Immunometabolomics: The metabolic landscape of immune cells in tumor microenvironment. Tumor Microenviron 2018;1:72-9 |
| Introduction | |  |
One of the main hallmarks of cancer is the “deregulation of cellular energetics” to support uncontrolled growth of cancer cells.[1],[2],[3] The cancer cells undergo various “micro-evolutions” and incorporate many changes in their metabolism to produce the required amount of energy for their hyperproliferation. These metabolic adaptations make the cancer cells more robust and resistant to various therapies.[4]
The tumor microenvironment also consists of various immune cells such as macrophages, lymphocytes, dendritic cells, natural killer (NK), and NKT cells besides the metabolically reprogrammed cancer cells and these cells also have an extremely important role in the progression of tumor.[5],[6] Many studies have supported this and showed the influence of tumor infiltrating macrophages on the persistence of cancer cells, their metastasis and angiogenesis.[7] Similarly, the influence of other tumor site residing immune cells in the course of progression of tumor has also been shown in several other studies[8],[9] and this interaction between these cells is termed as “immune-editing” and this is crucial in shaping the outcome of the tumor. However, the altered metabolic state of cancer cells poses a challenge to the survival of immune cells in the tumor microenvironment. The cancer cells use available nutrients in the microenvironment for their rapid proliferation and growth and this makes the nutrients unavailable for immune cell proliferation. The differentiation and role of immune cells also be determined by the availability of the key components such as micronutrients, amino acids, lipids, and glucose.[5] Apart from the scarcity of nutrients, the presence of various metabolic by-products[10] of cancer cells like lactate also alters the function and survival of immune cells. The metabolic byproducts of tumor cells make the tumor micro-environment acidic and that significantly affects the averse functions of T cells for cancer cells. This also shapes the differentiation of macrophages and dendritic cells in the favor for tumor progression. The tumor microenvironment is hypoxic and that has profound effect on the antigen presentation properties of myeloid cells. Hypoxia induces the expression of HIF1[11] which results in higher expression of inhibitory ligand PDL1[12] on cancer cells and promotes the differentiation of Treg cells.[13]
All these information suggest that these alterations induced by cancer cells also affect the differentiation and functions of immune cells in tumor microenvironment. Hence, the metabolism of these cancer cells can be targeted and used for treatments for improved antitumor immunity. Recent research has thus focused on the dynamic interaction of tumor cells and immune cells and the effect of the tumor microenvironment on the metabolism and bioenergetics of infiltrating immune cells. This combination of targeting metabolism with immunotherapy may give better therapeutic approaches and in this review, we try to integrate the information available about the mechanisms operational in the tumor microenvironment that shapes the metabolic landscape of immune cells.
| A Glimpse of the Tumor Microenvironment | | |
The tumor microenvironment is highly populated by tumor cells, and these tumor-induced interactions have a profound effect on the development and progression of cancer. The tumor-derived signals result in recruitment of various immune effector cells with reduced anti-tumoral activity to the tumor site. Human tumors are found to be highly-enriched in regulatory T cells (Treg) as well as myeloid-derived suppressor cells (MDSCs) [Figure 1].[14] | Figure 1: A diagrammatic representation of tumor microenvironment. Immune cells infiltrate into the tumor microenvironment and play a complex role in shaping the progression of tumor. Antigen presenting cells (dendritic cells and macrophages) capture tumor antigens and activate the immune system by recruiting T cells, B cells, and NK cells. However, the presence of suppressive cells like myeloid derived suppressor cells and regulatory T cells (Tregs) can hamper this process. Tumor cells deploy several mechanisms to inhibit the action of antitumor immune cells and escape from immune-surveillance
Click here to view |
The immune cells residing in the tumor microenvironment deviate from their normal physiological conditions and functions, which results in their reduced capability to perform their antitumor effector functions, but also help in the promotion of tumor growth.[15] Tumor microenvironment is different from the normal tissue environment in multiple aspects such as hypoxia, acidosis, and increased stiffness of the extracellular matrix. These are the hallmarks of tumor microenvironment.[16],[17],[19],[20] This tissue microenvironment is extremely important for cancer metastasis as described by Stephen Paget in his “seed and soil” hypothesis.[21] Multiple microenvironmental factors have important roles in the progression of cancer and these factors help to reprogram the metabolisms of immune cells and cancer cells. Almost 100 years ago, Otto Warburg observed an interesting factor in cancer cells. He observed that cancer cells favorably convert glucose to lactate despite the presence of oxygen and that opened the horizon for cancer metabolism as a new field of research.[22] This preferential conversion of glucose to lactic acid by tumor cells acidifies the tumor microenvironment and thus tumor microenvironment becomes extremely acidic.[23] This metabolic adaptations by cancer cells further deprive the immune cells present in that microenvironment. The consequences of metabolic reprogramming at tumor site not only affect tumor cells but also have potent effect on the survival and function of immune cells and cancer immunity.
| The Immune Cells Inhabiting in the Tumor Microenvironment | | |
Tumor microenvironment is not only diverse in terms of genetic and functional heterogeneity of tumor cells but also a wide and diverse range of immune cells that can be found in human tumor tissue. Among them the T- and B-cell are the principle mediators of the adaptive immune response. These tumor infiltrating T cells are also heterogeneous and various subpopulations have been identified. These T cells can enact their anti-tumoral property by either directly acting against the growth of tumor cells or by stimulating other cells in tumor microenvironment to perform their function. The role of tumor infiltrating B cells is yet to be fully understood[24],[25] and needs to be extensively studied in future.
Alongside these adaptive immune cells, innate immune cells are also often found in tumor microenvironment. A productive well-regulated immune response is generated by the interaction of these adaptive and immune cells. The first immune cells to be described in tumor environment are macrophages and they are the main player to remove pathogen-infected cells.[26] The stimulatory cytokines play an important role in determining the polarization of the macrophages. Interferon-γ (IFNγ) and toll-like receptor ligands stimulate the macrophages and they get polarized to a pro-inflammatory anti-tumoral (M1) phenotype.[27] Whereas, if stimulated by interleukin 4 (IL4) and IL10, macrophages polarize toward pro-tumoral, anti-inflammatory M2 phenotype. Both of these macrophages modulate tissue homeostasis and are highly plastic to adapt their function in response to infection and tissue damage.[28] These M1 and M2 macrophages require distinct metabolic pathways to get activated[29] and contribute their functions in the tumor microenvironment. Other innate immune cells such as NK cells play important roles in tumor microenvironment [Figure 1] as they can identify and kill foreign cells and thus can destroy cancer cells.[30] The detailed metabolic adaptation of NK cells in tumor micro-environment is not well documented. It is hypothesized that there are different metabolic preferences of tumor-infiltrating immune cells, and they are mutually linked to each other.[24]
| Metabolism, a Key Aspect of the Survival of Every Cell | | |
To sustain, grow, and perform any kind of function, cells require energy and this energy comes from ATP and macromolecules generated by different metabolic pathways such as glycolysis, tricarboxylic acid (TCA) cycle, and oxidative phosphorylation (OXPHOS). These metabolic pathways are compartmentalized in a way that glycolysis takes place in the cytoplasm, whereas the latter two are restricted to the mitochondria. Now, the main source of energy, the glucose enters cells through the glucose transporters and gets confined into cells in the form of glucose-6-phosphate. After getting converted into glucose-6-phosphate by hexokinase, it can either go for glycolysis or can start the branch pentose-phosphate pathway, which results in generation of fatty acid. In case of glycolysis, the fate of the end product pyruvate depends solely on the availability of oxygen. In the presence of oxygen, the pyruvate gets fully oxidized to generate CO2 and H2O through the TCA cycle and generates ATP and NAD + by oxidation of NADH through the OXPHOS. In contrast, in the absence of oxygen, pyruvate gets converted into lactate and NAD+;[31],[32] thus, glycolysis serves as the major energy source for the activation of innate and adaptive immune systems and provide the raw materials to synthesize macromolecules. TCA cycle performs the complete oxidation of all the nutrients (carbohydrates, amino acids, and fatty acids) and provides the reducing equivalent NADH, which then generates ATP via OXPHOS [Figure 2]. All those nutrients enter the TCA cycle after being catabolized to acetyl-coA and this acetyl-coA gets oxidized in TCA cycle to generate CO2 and NADH. This NADH and an intermediate of TCA cycle succinate help to generate ATP via OXPHOS. Thus, in aerobic conditions, glycolysis is the most favorable way to generate not only ATP but also many intermediates for the biosynthesis of macromolecules. Since this synthesis of the macromolecules relies on the extraction of intermediates from glycolysis and the TCA cycle, they need to be continuously replenished to maintain the essential metabolic pathways.[3] The innate and adaptive immune cells meet this need by increasing the metabolic flux through increased rate of glycolysis.[33] These immune cells uptake excess amounts of glucose and the glucose does not get completely oxidized to generate ATP. Rather, it maintains the excess flux through these pathways and pyruvate gets oxidized to lactate [Figure 2].[34],[35] This process generates the necessary NAD + to maintain both glycolysis and the TCA cycle. This preferential dependence on glycolysis to maintain high generation of ATP in cells is referred to as “Warburg Effect.”  | Figure 2: Overview of metabolism of normal cells and the reprogrammed metabolism of cancer cells. Under normal condition, cells mainly depend on OXPHOS for the generation of ATP. Without the presence of external stimulus, the PI3K-AKT pathway remains inactive and the low level activity of AMPK keeps the action of mTOR and HIF1α in check. Cancer cells reprogram their metabolism in a way that they mainly depend on glucose and glycolysis for ATP generation. Oncogenic signals act as the stimuli to promote PI3K-AKT pathway and suppress AMPK activity and thus induce the expression of glycolytic genes. Hypoxia also induces the expression of HIF1α and thus increases the expression of glucose transporters and other glycolytic genes. Besides this the expression of IDO induces catabolism of tryptophan and that in a way increase the nucleotide, amino acid, and lipid biosynthesis and thus help in the rapid proliferation of cancer cells. Akt1: Protein kinase B, AMPK: AMP-activated protein kinase, ASCT2: alanine, serine, and cysteine system amino acids transporter-2, ATP: Adenosine triphosphate, Glut1/4: Glucose transporter1/4, HIF1α: Hypoxia-inducible factor-1α, HK: Hexokinase, IDO: Indoleamine-pyrrole 2,3-dioxygenase, Mtor: Mechanistic/mammalian target of rapamycin, PI3K: Phosphatidylinositol-4,5-bisphosphate 3-kinase, OXPHOS: Oxidative phosphorylation
Click here to view |
| Metabolic Adaptations of Immune Cells in Tumor Micro-Environment | | |
As the factors of tumor microenvironment can affect the metabolism of immune cells residing in that environment and thus can affect their pro- and anti-tumorigenic functions, it is important to understand the metabolic changes of immune cells in tumor microenvironment [Figure 3]. | Figure 3: The metabolic changes in tumor microenvironment and the effect of that on the differentiation function of immune cells and cancer cells. The metabolic properties of a tumor are influenced by both intrinsic and extrinsic factors. Cell intrinsic factors are the metabolic programs active in each cell type. Extrinsic variables are the nutrient availability, waste and pH gradients, oxygen (O2) tension, and oxidative pressures
Click here to view |
T cells
T cells are the key players of the adaptive immune system and are central regulators of immune-mediated anti-tumor response.[36],[37] The activated cytotoxic CD8+T cells act directly against the tumor cells, whereas on activation CD4+T cells get differentiated into different subtypes which either support (Th2, Treg cells) or suppress (Th1) tumor progression. The other subtype of CD4+T cells, Th17 cells can either support or suppress the tumor progression depending on the microenvironment.[38]
Metabolic pathways control the differentiation and function of immune cells. The energy sources for T cells are mainly glucose. The resting T cells (naïve, memory, and anergic T cells) need lower degree of metabolism and thus maintain a metabolic balance to supports their sustainability. In resting thymocytes, almost entire energy requirement attained by mitochondrial OXPHOS.[39],[40],[41] On the other hand, stimulated T cells differentiate in to various subsets of T cell and each subset utilizes different metabolic pathways. During proliferation, the cells must increase ATP production and produce raw materials such as nucleic acids, lipids and to meet that requirement and shift from catabolic mitochondrial OXPHOS to glycolysis and other anabolic pathways. Aerobic glycolysis is way less efficient from OXPHOS in terms of ATP generated per molecule of glucose consumed and it represents the unusual “Warburg effect” of proliferating T cells and cancer cells. The less-efficient unusual metabolic patterns provide materials that are essential to the synthesis of nucleic acids and phospholipids.[42],[43],[44] Furthermore, distinct energetic and biosynthetic pathways are required to support the specific functional needs of functionally distinct T-cell subsets. Recent studies have shown that T-cell activation does not lead to a uniform metabolic reprogramming in all conditions. The conventional T-effector cells such as Th1, Th2, and Th17[45],[46],[47],[48] mainly depend on aerobic glycolysis whereas the induced Treg cells have been shown to utilize mainly lipid metabolic pathways.[49],[50],[51],[52],[53],[54],[55] In glucose-depleted conditions, due to higher aerobic glycolysis by tumor cells, lactate accumulation occurs in the microenvironment. The low nutrient availability suppresses the effector T cells activity, whereas Treg cells survive this inhospitable environment and support the growth of tumor.
Hence, recent studies have focused on studying the metabolism of Treg cells in tumor microenvironment. Although several immunotherapeutic strategies are being tested worldwide, the precise combinations that can result in reduction of immune tolerance and generation of robust immune response against cancer remains the holy grail of investigation.
B cells
Beside T cells, another key player of adaptive immune system is the B cells. Similar to T cells, B cells are also composed of a heterogeneous population and can be pro- or anti-tumorigenic depending on the different conditions during tumor development.[56]
B cells can produce antibody and immune complexes and they can support tumor progression by modulating myeloid cell functions.[57],[58] The metabolic requirements of B cells are distinctly different from that of T cells. The B cells do not favor glycolysis from their initial point rather when gets activated by antigen or B-cell activation factors (BAFF), can trigger an ordered increase in both mitochondrial metabolic activity and glycolysis.[59] However, the activation of B cells results in higher rate of aerobic glycolysis and it reprograms its metabolism in GLUT1-dependent manner that results in antibody production. Mechanistically, HIF1α does not play any role in metabolic changes of B cell but cMyc mainly mediates the metabolic changes in B cells. HIF1α plays a role during the initial B cell development in bone marrow where many B-cell precursors are dependent on the HIF1α-mediated glycolytic processes. Studies have shown that a decreased expression of these results in GLUT1 expression deficiency and thus hampers the glucose dependent transition of many pro-B cells stage to pre-B-cell stage.[60],[61] The role of HIF1α though has been shown to be dispensable in many cases of B-cell reprogramming. Moreover, this indicates that there may be other important factors involved in regulating metabolic reprogramming of these B cells. Such a critical regulator of B-cell metabolism is tumor necrosis factor (TNF) receptor associated factor-3 (TRAF3). The deficiencies of these factors have shown to results in abnormal up-regulation of genes involved in glycolysis. The loss of these factors may increase mitochondrial respiration without increasing reactive oxygen species production. The final activation of B cells requires the stimulation of BAFF. Many tumors express BAFF, and that's why it will be important to see how metabolism of B cells is affected in tumor environment and the contribution of that change to tumor progression.
Myeloid-derived suppressor cell
MDSC or MDSCs are a group of immune cells of the myeloid lineage, and they suppress the functions of T cells.[62] Tumor microenvironment is highly enriched with these cells. Two types of MDSCs, monocytic MDSCs, and granulocytic MDSCs are found to be enriched in tumor microenvironment, and both can suppress cytotoxic effect of CD8+T cells. The suppressive actions of MDSCs are supported by their amino acid metabolism. They can suppress the T-cell function either by depriving T cells of essential amino acids or by generating oxidative stress.[62] MDSCs sequester L-arginine and L-cysteine[63] and the depletion of these nutrients generates a scarcity in nutrient availability to T cells and thus can restrict T-cell proliferation. MDSCs such as macrophages and dendritic cells express some enzymes which catalyze different pathways for amino acid metabolism; specifically, they express the enzyme IDO to reduce tryptophan and thus constrain T-cell function and induce the expansion of Treg cells.[64],[65] MDSCs express ARG1, NADPH oxidase[62] and induce the generation of reactive species and thus down-regulates the z-chain of TCR and IL2 signaling pathways. In other words, by all these ways, the MDSCs modulate the differentiation of T cells. Tumor-infiltrating MDSCs also uptake high amount of fatty acid and higher fatty acid oxidation also occurs in MDSCs and that regulates the immunosuppressive function of these cells.[66]
Macrophages
Macrophages are the “protector” of the host system in various defense mechanisms. Macrophages mediate direct anti-tumor functions and also regulate anti tumoral T-cell immune responses and thus have a central role in anti-tumor immunity. Macrophages have two distinct activation or polarization phenotypes. When activated by both inflammatory stimuli and LPS, macrophages get induced to an M1 phenotype and lead to secretion of inflammatory cytokines, for example, IL12 and TNF.[67],[68] On the other hand, when anti-inflammatory signals and immune complexes along with LPS induce macrophages, it gets differentiated to M2 phenotype and these are characterized by decreased production of inflammatory cytokines and increased generation of anti-inflammatory cytokines. These macrophages largely infiltrate in tumor tissue and play crucial role in tumor progression.[7],[69],[70] Macrophages, on the one hand, can produce inflammatory cytokines and generate reactive species that help in genetic alterations leading to tumorigenesis.[70],[71],[72] On the other hand, M2 macrophages in tumor tissue produce anti-inflammatory cytokines, promotes immune suppression, extravasation, and metastasis of tumor cells.[70],[71],[72],[73],[74] Macrophages not only help in the metastasis but also promote angiogenesis by producing various proangiogenic molecules.[69] Mostly tumor-associated macrophages (TAM) are considered to be of M2 phenotype but recent studies showed that TAM also shows M1 phenotype or at least show some overlapping phenotypes.[7],[75],[76] Macrophages on their polarization show distinct modes of metabolism.
Most studies have indicated that M1 macrophages favorably uptake glucose and depend on glucose metabolism while M2 macrophages depend on fatty acid metabolism and OXPHOS.[77],[79],[79],[80] The M1 macrophages increase the expression of GLUT1[81] and the M2 macrophages have higher expression of CD36 (lipid scavenger) to preferentially uptake glucose and fatty acid, respectively.[82] Recent studied showed a much more complex utilization of nutrients by macrophages than clear cut preferences for glucose and fatty acid. According to recent findings, M2 macrophages show higher rate of glucose consumption and thus sustain glycolysis and also glucose oxidation.[83],[84],[85] AKT and IFN regulatory factor-4 stimulate glucose uptake and they also regulate metabolism-driven macrophage activation by controlling ATP citrate lyase.[86],[87] These complex metabolic changes in macrophages play important role in the decision of their differentiation and function. And thus, it is expected that tumor microenvironment and its different factors affect the metabolism of macrophages and thus regulates its differentiation. Glycolysis results in the accumulation of succinate, an intermediate of TCA cycle, which induces the expression of HIF1α, and thus can produce IL1β and promote an inflammatory macrophage phenotype. Thus, metabolism-dependent differentiation of macrophages will be altered depending on the utilization of nutrients and the production of metabolites.[80] Besides glucose and HIF1α signaling, another important factor for macrophage differentiation is regulation of cholesterol metabolism, it increases cholesterol import in response to type-I IFN-signaling but reduce cholesterol biosynthesis. This metabolic shift supports the expression of genes that get induced by IFN and provide resistance to viral infection.[88]
Dendritic cells
The bridge between the innate and adaptive immune system are the dendritic cells. Immature dendritic cells upon activation through pathogen-associated or tissue-damage-related stimuli undergo maturation. These matured dendritic cells act as the antigen presenting cells and migrate to lymphoid organs to activate T-cell response. Dendritic cells can also act in the exactly opposite ways and promote immune tolerance in some cases like tumor-associated dendritic cells show ability to promote immune suppression.[89],[90],[91] Many human cancers have been reported with accumulated immature DCs or matured DCs with impaired function.[62] The exact reason for this impaired function of tumor-associated DC is not well known but a new perspective to this problem comes with the recent understanding of metabolic regulation of the function of dendritic cells.[92],[93] Under resting conditions, DCs depend on OXPHOS but on activation its metabolism shifts toward glycolysis and shows decreased rate of OXPHOS. These studies show that DC activation solely depends on glycolysis and in tumor microenvironment various factors might affect the activation, maturation of DCs. Moreover, in the tumor microenvironment, the cancer cells rapidly proliferate and use most of the available nutrients and impose nutrient competition and accumulation of metabolites like adenosine. This nutrient deprivation and accumulation of some metabolites trigger the AMP-activated protein kinase (AMPK) in tumor-associated DCs. The AMPK acts as a metabolic sensor. It promotes OXPHOS and inhibits glycolysis and this might offer a possible explanation for the impaired maturation, function of tumor-associated DCs.
Natural killer cells
NK cells who play an extremely important role in activating an anti-tumor T-cell response mainly utilize OXPHOS under resting conditions to meet their energy requirement.[94] However, the activated NK cells showed increased glycolytic metabolism. In these activated NK cells, the glycolysis pathway regulates granzyme-B and IFNγ expression. The detailed effect of tumor microenvironment on the activation and function of NK cells is not known and it will be interesting to know the regulation imposed by tumor micro-environment on the activation and function of NK cells.
| Can Targeting the Metabolism of Cells Provide a Better Means of Immunotherapy? | | |
The tumor cells adapt their metabolism to sustain their growth under adverse conditions and show resistance to any kind of treatment. Such drug-resistant tumors show altered phenotype concerning the treatment-naïve tumor cells. One of the therapeutic approaches for the treatment of pancreatic cancer aims to target the oncogenic KRASG12D and the inactivation of this gene results in the regression of cancer.[95] However, some metabolically modified cancer cells can endure in a quiescent state and reactivate KRASG12D leading to cancer relapse. Although such dormant cells have robust mitochondrial respiration, their glycolysis rate is considerably reduced. Due to the inability to enhance the glycolytic rate, these cells become susceptible to respiration inhibitors. Other studies also suggest that mitochondrial respiration empower cells to bypass the therapies, thus indicating that targeting mitochondrial respiration would be an effective strategy to increase relapse-free survival in cancer patients.[96],[97]
A comprehensive understanding of the metabolic processes in the tumor microenvironment is necessary for designing therapies that target such pathways. For example, although several chemotherapeutic drugs inhibit nucleotide metabolism, tumor cells often show resistance to them by utilizing alternate pathways to replenish nucleotide pools. A deeper understanding of such differential metabolic pathways may help in designing more rational and specific metabolism-targeted therapies.
Apart from targeting cancer cells and their metabolism, rejuvenation of the immune cells is a major goal for modern immunotherapy. A novel approach for immunotherapy is to generate functionally active tumor-specific effector T cells and memory T cells. The enhanced viability of memory T cells and their ability of rapid response to neoantigens on re-exposure are critical in a long-term anti-tumor immune response. Since T-cell differentiation and function highly depends on the metabolism, targeting metabolism of T cells by modulating various immune checkpoints seems to be a promising strategy that might result in generation and maintenance of potent tumor-antigen-specific effector and memory T-cells.
To combine metabolism-targeted therapies with immunotherapies, a clear understanding of the communications between metabolism of cancer and immune cells is essential. Cancer cells make the tumor microenvironment hypoxic and nutrient deprived which affects T-cell and macrophage differentiation, raising the possibility that if tumor cell metabolisms are targeted, it may promote anti-cancer immune responses. The excess use of available glucose by cancer cells restricts the availability of glucose to T cells and thus causes lymphocyte exhaustion.[98],[99] Thus, therapies that can limit such excess use of glucose by cancer cells can make the glucose available for T cells, which would help sustained anti-tumor effector functions to inhibit tumor growth. However, the caveat lies in designing specific inhibitors that target glucose metabolism in tumor cells but do not simultaneously restrict the glucose metabolism of T cells. Apart from glucose, other pathways involving amino acid and fatty acid metabolism also affect both cancer and immune cells and detailed studies are necessary to identify more novel metabolic targets for cancer therapy.
To answer the ever more complex questions in this field, several points need to be considered. These include: How internal and external influences put together create utilizable metabolic phenotypes in cancer, the metabolic preferences of cancer cells by the tissue of origin, the communications between benign and malignant cells within the microenvironment and effects of the diet and host micro biota. The influence of an individual's diet on tumor development and progression by affecting metabolic pathways is a very less explored area and might prove to be extremely important in designing personalized therapies integrating metabolism and cancer.
Acknowledgments
Authors are thankful to Tania Sarkar and Dia Roy of Bose Institute for editorial assistance of the manuscript.
Financial support and sponsorship
This work was supported by research grants from the Department of Biotechnology and University Grant Commission Government of India.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | Cairns RA, Harris IS, Mak TW. Regulation of cancer cell metabolism. Nat Rev Cancer 2011;11:85-95.  |
| 2. | Viale A, Corti D, Draetta GF. Tumors and mitochondrial respiration: A neglected connection. Cancer Res 2015;75:3685-6. |
| 3. | DeBerardinis RJ, Lum JJ, Hatzivassiliou G, Thompson CB. The biology of cancer: Metabolic reprogramming fuels cell growth and proliferation. Cell Metab 2008;7:11-20. |
| 4. | Viale A, Draetta GF. Metabolic features of cancer treatment resistance. Recent Results Cancer Res 2016;207:135-56. |
| 5. | Herbel C, Patsoukis N, Bardhan K, Seth P, Weaver JD, Boussiotis VA. Clinical significance of T cell metabolic reprogramming in cancer. Clin Transl Med 2016;5:29. |
| 6. | Biswas SK. Metabolic reprogramming of immune cells in cancer progression. Immunity 2015;43:435-49. |
| 7. | Qian BZ, Pollard JW. Macrophage diversity enhances tumor progression and metastasis. Cell 2010;141:39-51. |
| 8. | Hanahan D, Coussens LM. Accessories to the crime: Functions of cells recruited to the tumor microenvironment. Cancer Cell 2012;21:309-22. |
| 9. | Bindea G, Mlecnik B, Tosolini M, Kirilovsky A, Waldner M, Obenauf AC, et al. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity 2013;39:782-95. |
| 10. | Cairns RA, Mak TW. Fire and water: Tumor cell adaptation to metabolic conditions. Exp Cell Res 2017;356:204-8. |
| 11. | Funes JM, Quintero M, Henderson S, Martinez D, Qureshi U, Westwood C, et al. Transformation of human mesenchymal stem cells increases their dependency on oxidative phosphorylation for energy production. Proc Natl Acad Sci U S A 2007;104:6223-8. |
| 12. | Noman MZ, Desantis G, Janji B, Hasmim M, Karray S, Dessen P, et al. PD-L1 is a novel direct target of HIF-1α, and its blockade under hypoxia enhanced MDSC-mediated T cell activation. J Exp Med 2014;211:781-90. |
| 13. | Ben-Shoshan J, Maysel-Auslender S, Mor A, Keren G, George J. Hypoxia controls CD4+CD25+regulatory T-cell homeostasis via hypoxia-inducible factor-1alpha. Eur J Immunol 2008;38:2412-8. |
| 14. | Whiteside TL. The tumor microenvironment and its role in promoting tumor growth. Oncogene 2008;27:5904-12. |
| 15. | Hanahan D, Weinberg RA. Hallmarks of cancer: The next generation. Cell 2011;144:646-74. |
| 16. | Cairns R, Papandreou I, Denko N. Overcoming physiologic barriers to cancer treatment by molecularly targeting the tumor microenvironment. Mol Cancer Res 2006;4:61-70. |
| 17. | Gatenby RA, Gillies RJ. Why do cancers have high aerobic glycolysis? Nat Rev Cancer 2004;4:891-9. |
| 18. | Justus CR, Dong L, Yang LV. Acidic tumor microenvironment and pH-sensing G protein-coupled receptors. Front Physiol 2013;4:354. |
| 19. | Justus CR, Sanderlin EJ, Yang LV. Molecular connections between cancer cell metabolism and the tumor microenvironment. Int J Mol Sci 2015;16:11055-86. |
| 20. | Yang LV. Tumor microenvironment and metabolism. Int J Mol Sci 2017;18:2729. |
| 21. | Paget S. The distribution of secondary growths in cancer of the breast. 1889. Cancer Metastasis Rev 1989;8:98-101. |
| 22. | Koppenol WH, Bounds PL, Dang CV. Otto Warburg's contributions to current concepts of cancer metabolism. Nat Rev Cancer 2011;11:325-37. |
| 23. | Anderson KG, Stromnes IM, Greenberg PD. Obstacles posed by the tumor microenvironment to T cell activity: A case for synergistic therapies. Cancer Cell 2017;31:311-25. |
| 24. | Singer K, Cheng WC, Kreutz M, Ho PC, Siska PJ. Immunometabolism in cancer at a glance. Dis Model Mech 2018;11:dmm034272. |
| 25. | Tsou P, Katayama H, Ostrin EJ, Hanash SM. The emerging role of B cells in tumor immunity. Cancer Res 2016;76:5597-601. |
| 26. | Lewis CE, Pollard JW. Distinct role of macrophages in different tumor microenvironments. Cancer Res 2006;66:605-12. |
| 27. | Yuan A, Hsiao YJ, Chen HY, Chen HW, Ho CC, Chen YY, et al. Opposite effects of M1 and M2 macrophage subtypes on lung cancer progression. Sci Rep 2015;5:14273. |
| 28. | Martinez FO, Gordon S. The M1 and M2 paradigm of macrophage activation: Time for reassessment. F1000Prime Rep 2014;6:13. |
| 29. | 29. Ho PC, Liu PS. Metabolic communication in tumors: A new layer of immunoregulation for immune evasion. J Immunother Cancer 2016;4:4. |
| 30. | Marcus A, Gowen BG, Thompson TW, Iannello A, Ardolino M, Deng W, et al. Recognition of tumors by the innate immune system and natural killer cells. Adv Immunol 2014;122:91-128. |
| 31. | Parlo RA, Coleman PS. Continuous pyruvate carbon flux to newly synthesized cholesterol and the suppressed evolution of pyruvate-generated CO2 in tumors: Further evidence for a persistent truncated Krebs cycle in hepatomas. Biochim Biophys Acta 1986;886:169-76. |
| 32. | Chang LO, Morris HP. Enzymatic and immunological studies on pyruvate carboxylase in livers and liver tumors. Cancer Res 1973;33:2034-41. |
| 33. | Ganeshan K, Chawla A. Metabolic regulation of immune responses. Annu Rev Immunol 2014;32:609-34. |
| 34. | Brand K. Glutamine and glucose metabolism during thymocyte proliferation. Pathways of glutamine and glutamate metabolism. Biochem J 1985;228:353-61. |
| 35. | DeBerardinis RJ, Mancuso A, Daikhin E, Nissim I, Yudkoff M, Wehrli S, et al. Beyond aerobic glycolysis: Transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis. Proc Natl Acad Sci U S A 2007;104:19345-50. |
| 36. | Lu YC, Yao X, Crystal JS, Li YF, El-Gamil M, Gross C, et al. Efficient identification of mutated cancer antigens recognized by T cells associated with durable tumor regressions. Clin Cancer Res 2014;20:3401-10. |
| 37. | Chandran SS, Paria BC, Srivastava AK, Rothermel LD, Stephens DJ, Dudley ME, et al. Persistence of CTL clones targeting melanocyte differentiation antigens was insufficient to mediate significant melanoma regression in humans. Clin Cancer Res 2015;21:534-43. |
| 38. | Bailey SR, Nelson MH, Himes RA, Li Z, Mehrotra S, Paulos CM. Th17 cells in cancer: The ultimate identity crisis. Front Immunol 2014;5:276. |
| 39. | 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;153:1239-51. |
| 40. | Wang R, Dillon CP, Shi LZ, Milasta S, Carter R, Finkelstein D, et al. The transcription factor Myc controls metabolic reprogramming upon T lymphocyte activation. Immunity 2011;35:871-82. |
| 41. | Zeng H, Chi H. mTOR signaling and transcriptional regulation in T lymphocytes. Transcription 2014;5:e28263. |
| 42. | 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;185:1037-44. |
| 43. | Frauwirth KA, Riley JL, Harris MH, Parry RV, Rathmell JC, Plas DR, et al. The CD28 signaling pathway regulates glucose metabolism. Immunity 2002;16:769-77. |
| 44. | Frauwirth KA, Thompson CB. Regulation of T lymphocyte metabolism. J Immunol Baltim Md 1950 2004;172:4661-5. |
| 45. | Sinclair LV, Rolf J, Emslie E, Shi YB, Taylor PM, Cantrell DA. Control of amino-acid transport by antigen receptors coordinates the metabolic reprogramming essential for T cell differentiation. Nat Immunol 2013;14:500-8. |
| 46. | Nakaya M, Xiao Y, Zhou X, Chang JH, Chang M, Cheng X, et al. Inflammatory T cell responses rely on amino acid transporter ASCT2 facilitation of glutamine uptake and mTORC1 kinase activation. Immunity 2014;40:692-705. |
| 47. | Berod L, Friedrich C, Nandan A, Freitag J, Hagemann S, Harmrolfs K, et al. De novo fatty acid synthesis controls the fate between regulatory T and T helper 17 cells. Nat Med 2014;20:1327-33. |
| 48. | Lochner M, Berod L, Sparwasser T. Fatty acid metabolism in the regulation of T cell function. Trends Immunol 2015;36:81-91. |
| 49. | Semenza GL. HIF-1: Upstream and downstream of cancer metabolism. Curr Opin Genet Dev 2010;20:51-6. |
| 50. | Doedens AL, Phan AT, Stradner MH, Fujimoto JK, Nguyen JV, Yang E, et al. Hypoxia-inducible factors enhance the effector responses of CD8(+) T cells to persistent antigen. Nat Immunol 2013;14:1173-82. |
| 51. | Le Bourgeois T, Strauss L, Aksoylar HI, Daneshmandi S, Seth P, Patsoukis N, et al. Targeting T cell metabolism for improvement of cancer immunotherapy. Front Oncol 2018;8:237. |
| 52. | 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. |
| 53. | MacIver NJ, Michalek RD, Rathmell JC. Metabolic regulation of T lymphocytes. Annu Rev Immunol 2013;31:259-83. |
| 54. | Blagih J, Coulombe F, Vincent EE, Dupuy F, Galicia-Vázquez G, Yurchenko E, et al. The energy sensor AMPK regulates T cell metabolic adaptation and effector responses in vivo. Immunity 2015;42:41-54. |
| 55. | Siska PJ, Beckermann KE, Mason FM, Andrejeva G, Greenplate AR, Sendor AB, et al. Mitochondrial dysregulation and glycolytic insufficiency functionally impair CD8 T cells infiltrating human renal cell carcinoma. JCI Insight 2017;2:e93411. |
| 56. | Martin F, Chan AC. B cell immunobiology in disease: Evolving concepts from the clinic. Annu Rev Immunol 2006;24:467-96. |
| 57. | 57. de Visser KE, Korets LV, Coussens LM. De novo carcinogenesis promoted by chronic inflammation is B lymphocyte dependent. Cancer Cell 2005;7:411-23. |
| 58. | Andreu P, Johansson M, Affara NI, Pucci F, Tan T, Junankar S, et al.FcRγ activation regulates inflammation-associated squamous carcinogenesis. Cancer Cell 2010;17:121-34. |
| 59. | Caro-Maldonado A, Wang R, Nichols AG, Kuraoka M, Milasta S, Sun LD, et al. Metabolic reprogramming is required for antibody production that is suppressed in anergic but exaggerated in chronically BAFF-exposed B cells. J Immunol 2014;192:3626-36. |
| 60. | Jellusova J. Metabolic control of B cell immune responses. Curr Opin Immunol 2020;63:21-8. |
| 61. | Teng X, Li W, Cornaby C, Morel L. Immune cell metabolism in autoimmunity. Clin Exp Immunol 2019;197:181-92. |
| 62. | Gabrilovich DI, Ostrand-Rosenberg S, Bronte V. Coordinated regulation of myeloid cells by tumours. Nat Rev Immunol 2012;12:253-68. |
| 63. | Srivastava MK, Sinha P, Clements VK, Rodriguez P, Ostrand-Rosenberg S. Myeloid-derived suppressor cells inhibit T-cell activation by depleting cystine and cysteine. Cancer Res 2010;70:68-77. |
| 64. | Grohmann U, Bronte V. Control of immune response by amino acid metabolism. Immunol Rev 2010;236:243-64. |
| 65. | Saxena V, Ondr JK, Magnusen AF, Munn DH, Katz JD. The countervailing actions of myeloid and plasmacytoid dendritic cells control autoimmune diabetes in the nonobese diabetic mouse. J Immunol 2007;179:5041-53. |
| 66. | Hossain KM, Anwar MS. Influence of foundry sand and natural pozzolans on the mechanical, durability and micro-structural properties of lightweight concrete. Br J Appl Sci Technol 2015;10:1-12. |
| 67. | Biswas SK, Mantovani A. Macrophage plasticity and interaction with lymphocyte subsets: Cancer as a paradigm. Nat Immunol 2010;11:889-96. |
| 68. | Xue J, Schmidt SV, Sander J, Draffehn A, Krebs W, Quester I, et al. Transcriptome-based network analysis reveals a spectrum model of human macrophage activation. Immunity 2014;40:274-88. |
| 69. | Murdoch C, Muthana M, Coffelt SB, Lewis CE. The role of myeloid cells in the promotion of tumour angiogenesis. Nat Rev Cancer 2008;8:618-31. |
| 70. | Biswas SK, Allavena P, Mantovani A. Tumor-associated macrophages: Functional diversity, clinical significance, and open questions. Semin Immunopathol 2013;35:585-600. |
| 71. | Mantovani A, Allavena P, Sica A, Balkwill F. Cancer-related inflammation. Nature 2008;454:436-44. |
| 72. | Grivennikov SI, Greten FR, Karin M. Immunity, inflammation, and cancer. Cell 2010;140:883-99. |
| 73. | Quail DF, Joyce JA. Microenvironmental regulation of tumor progression and metastasis. Nat Med 2013;19:1423-37. |
| 74. | Ruffell B, Chang-Strachan D, Chan V, Rosenbusch A, Ho CM, Pryer N, et al. Macrophage IL-10 blocks CD8+T cell-dependent responses to chemotherapy by suppressing IL-12 expression in intratumoral dendritic cells. Cancer Cell 2014;26:623-37. |
| 75. | Mantovani A, Sozzani S, Locati M, Allavena P, Sica A. Macrophage polarization: Tumor-associated macrophages as a paradigm for polarized M2 mononuclear phagocytes. Trends Immunol 2002;23:549-55. |
| 76. | Franklin RA, Liao W, Sarkar A, Kim MV, Bivona MR, Liu K, et al. The cellular and molecular origin of tumor-associated macrophages. Science 2014;344:921-5. |
| 77. | Cheng SC, Quintin J, Cramer RA, Shepardson KM, Saeed S, Kumar V, et al. mTOR- and HIF-1α-mediated aerobic glycolysis as metabolic basis for trained immunity. Science 2014;345:1250684. |
| 78. | Vats D, Mukundan L, Odegaard JI, Zhang L, Smith KL, Morel CR, et al. Oxidative metabolism and PGC-1β attenuate macrophage-mediated inflammation. Cell Metab 2006;4:13-24. |
| 79. | Rodríguez-Prados JC, Través PG, Cuenca J, Rico D, Aragonés J, Martín-Sanz P, et al. Substrate fate in activated macrophages: A comparison between innate, classic, and alternative activation. J Immunol 2010;185:605-14. |
| 80. | Tannahill GM, Curtis AM, Adamik J, Palsson-McDermott EM, McGettrick AF, Goel G, et al. Succinate is an inflammatory signal that induces IL-1β through HIF-1α. Nature 2013;496:238-42. |
| 81. | 81. Fukuzumi M, Shinomiya H, Shimizu Y, Ohishi K, Utsumi S. Endotoxin-induced enhancement of glucose influx into murine peritoneal macrophages via GLUT1. Infect Immun 1996;64:108-12. |
| 82. | Odegaard JI, Ricardo-Gonzalez RR, Goforth MH, Morel CR, Subramanian V, Mukundan L, et al. Macrophage-specific PPARgamma controls alternative activation and improves insulin resistance. Nature 2007;447:1116-20. |
| 83. | 83. Thapa B, Lee K. Metabolic influence on macrophage polarization and pathogenesis. BMB Rep 2019;52:360-72. |
| 84. | 84. Koo SJ, Garg NJ. Metabolic programming of macrophage functions and pathogens control. Redox Biol 2019;24:101198. |
| 85. | Tabas I, Bornfeldt K E. Intracellular and intercellular aspects of macrophage immuno metabo-lism in atherosclerosis.Circulat Res 2020;126:1209-27. |
| 86. | 86. Huang SC, Smith AM, Everts B, Colonna M, Pearce EL, Schilling JD, et al. Metabolic reprogramming mediated by the mTORC2-IRF4 signaling axis is essential for macrophage alternative activation. Immunity 2016;45:817-30. |
| 87. | 87. Covarrubias AJ, Aksoylar HI, Yu J, Snyder NW, Worth AJ, Iyer SS. Akt-mTORC1 signaling regulates Acly to integrate metabolic input to control of macrophage activation. Elife 2016;5. pii: E11612. |
| 88. | York AG, Williams KJ, Argus JP, Zhou QD, Brar G, Vergnes L. Limiting cholesterol biosynthetic flux spontaneously engages type I IFN signaling. Cell 2015;163:1716-29. |
| 89. | Apetoh L, Locher C, Ghiringhelli F, Kroemer G, Zitvogel L. Harnessing dendritic cells in cancer. Semin Immunol 2011;23:42-9. |
| 90. | Hsu YL, Chen YJ, Chang WA, Jian SF, Fan HL, Wang JY, et al. Interaction between tumor-associated dendritic cells and colon cancer cells contributes to tumor progression via CXCL1. Int J Mol Sci 2018;19:2427. |
| 91. | Janco JM, Lamichhane P, Karyampudi L, Knutson KL. Tumor-infiltrating dendritic cells in cancer pathogenesis. J Immunol 2015;194:2985-91. |
| 92. | Malinarich F, Duan K, Hamid RA, Bijin A, Lin WX, Poidinger M, et al.High mitochondrial respiration and glycolytic capacity represent a metabolic phenotype of human tolerogenic dendritic cells . J Immunol 2015;194:5174-86. |
| 93. | Ravindran R, Khan N, Nakaya H I, Li S, Loebbermann J, Maddur MS, et al. Vaccine activation of the nutrient sensor GCN2 in dendritic cells enhances antigen presentation. Science 2013;343:313-17. |
| 94. | Keppel MP, Saucier N, Mah AY, Vogel TP, Cooper MA. Activation-specific metabolic requirements for NK cell IFN-γ production. J Immunol 2015;194:1954-62. |
| 95. | Viale A, Pettazzoni P, Lyssiotis CA, Ying H, Sánchez N, Marchesini M. Oncogene ablation-resistant pancreatic cancer cells depend on mitochondrial function. Nature 2014;514:628-32. |
| 96. | Navarro P, Bueno MJ, Zagorac I, Mondejar T, Sanchez J, Mourón S. Targeting tumor mitochondrial metabolism overcomes resistance to antiangiogenics. Cell Rep 2016;15:2705-18. |
| 97. | Zhang G, Frederick DT, Wu L, Wei Z, Krepler C, Srinivasan S, et al. Targeting mitochondrial biogenesis to overcome drug resistance to MAPK inhibitors. J Clin Invest 2016;126:1834-56. |
| 98. | Chang CH, Qiu J, O'Sullivan D, Buck MD, Noguchi T, Curtis JD, et al. Metabolic competition in the tumor microenvironment is a driver of cancer progression. Cell 2015;162:1229-41. |
| 99. | Ho PC, Bihuniak JD, Macintyre AN, Staron M, Liu X, Amezquita R. Phosphoenolpyruvate is a metabolic checkpoint of anti-tumor T cell responses. Cell. 2015 162:1217-28. |
[Figure 1], [Figure 2], [Figure 3]
|
Search Pubmed for