Abstract
The nutrient environment and metabolism play a dynamic role in cellular differentiation and research is elucidating the mechanisms that contribute to this process. Metabolites serve as an effective bridge that helps to translate information about nutrient states into specific interpretations of the genome. Part of this activity relates to the role for metabolites in regulating epigenetic processes as well as a newly appreciated role for metabolites in the regulation of genome organization. In this review, we will highlight recent research that has defined roles for metabolism in the organization and interpretation of the genome and how this influences cellular differentiation decisions. We will integrate information about how nutrients, such as glutamine, regulate metabolites, such as alpha-ketoglutarate, and highlight how these pathways influence epigenetic states as well as CTCF association and genome organization. We will also discuss mechanistic similarities and differences between normal differentiation states associated with embryonic stem (ES) cells and T cells and how this might relate to dysregulated states such as those associated with tumor infiltrating lymphocytes.
Metabolism is now appreciated to be a central component of cellular differentiation. Studies in embryonic stem (ES) cells have led the way in defining how nutrient intake initiates changes in the accumulation of metabolites [1–5]. These studies have also uncovered roles for metabolites in regulating cellular differentiation programs in part through their ability to act as donors, substrates and co-factors for epigenetic modifications and epigenetic-modifying complexes [6,7]. Research in numerous developmental systems, including in the immune system, have extended these results to indicate that the mechanistic events that occur in ES cells are conserved in diverse cellular settings [8–10]. Taken together, the current state of the field indicates a striking conservation of the mechanisms that translate information about the nutrient environment into gene expression programs.
DNA methylation influences CTCF association and genome organization in cellular differentiation
DNA methylation plays an important role in regulating both normal development and pathogenic states [11–13]. For instance, in T cell differentiation, DNA methylation states are important for promoting the balance between the effector and memory program, with dysregulated DNA methylation leading to an exhausted state [14–16]. Intriguingly, DNA methylation has also been shown to play an important role for CCCTC-binding factor (CTCF) association and genome organization in several cellular settings [17–19]. In B cells and early T cell development, the expression of enhancer RNAs (eRNAs) or long noncoding RNAs (lncRNAs) can cause hypomethylation of DNA regions that promotes CTCF association and changes in genome topology [20,21]. It is now appreciated that the microenvironment can influence DNA methylation states through regulating the balance of DNA methyltransferase and DNA demethylase activities. The nutrient environment plays a role in this process by regulating the accumulation of metabolites such as S-adenosylmethionine (SAM), the donor for DNA methyltransferases, alpha-ketoglutarate (αKG), a required cofactor for DNA demethylases, and 2-hydroxyglutarate (2HG), a competitive inhibitor of αKG in DNA-demethylase activity [6,22,23]. Thus, it is possible in conditions where the nutrient environment or metabolites regulate the state of DNA methylation, this could provide a mechanistic link between metabolism, epigenetics, and genome organization events.
Metabolites αKG and 2HG influence DNA methylation, CTCF association and genome topology
The interplay between metabolism, DNA methylation and genome organization is an emerging area of interest in defining the mechanistic connections between metabolism and cellular differentiation. Recent conceptual advances in both normal and pathogenic differentiation states have identified roles for metabolic events in the regulation of CTCF association with the genome, which in turn, regulates genome topology [10,24]. For example, the dysregulated metabolic state in gliomas with mutations in the isocitrate dehydrogenase (IDH) enzyme disrupts CTCF association and genomic interactions surrounding the PDGFRA oncogene [24]. Mechanistically, mutations in IDH can cause the overproduction of the metabolite 2HG. 2HG is a competitive inhibitor of αKG, with αKG serving as a required co-factor for both histone and DNA demethylase complexes [25,26]. DNA methylation has been shown to prevent CTCF association with a subset of sites in a mechanism that contributes to the regulation of genomic organization in a cell-type specific manner [19,27,28]. The IDH-mutation-sensitive CTCF binding events observed in glioma cells are potentially related to changes in DNA methylation because enhanced methylation at select CTCF sites correlates with diminished CTCF association (Figure 1) [24]. These data suggest that dysregulated metabolic states that influence DNA methylation can play a role in CTCF association, genomic organization and pathogenic gene programming states.
Figure 1. Mechanistic connections between metabolites, epigenetics, CTCF association and genome organization events.

Shown is a schematic representation of the concepts presented in the review related to how metabolites impact CTCF association and genome organization in T cells (purple), ES cells (green), and glioma cells (blue). In the ES cell panel, different colored arrows represent the findings from multiple independent studies. The solid arrows indicate mechanistic interpretations with at least some supporting experimental evidence whereas the dashed arrows/lines indicate speculative interpretations of mechanistic steps based upon the integration of data from other cellular settings.
Connections between natural metabolic states, DNA methylation, CTCF association, and genome organization have been found within the context of the IL-2-sensitive differentiation program in CD4+ T cells [10]. In CD4+ T helper type 1 (Th1) cells, the IL-2-sensitive program is regulated by both glutamine-and αKG-sensitive events. Importantly, IL-2- and αKG-sensitive events promote CTCF association with select sites in the genome and this correlates with changes in genomic organization [10]. Similar to the mechanistic interpretations from the pathogenic state of glioma cells, it appears that at least some of the αKG-sensitive CTCF association in the context of normal T cell differentiation is regulated by changes in DNA methylation. Specifically, the IL-2- and αKG-sensitive reduction in DNA methylation surrounding loci such as Sell (encodes CD62L) in primary CD4+ Th1 cells correlates with enhanced CTCF association [10]. The DNA methylation status at the Sell promoter is also impacted by 2HG accumulation in the context of CD8+ T cell differentiation, with enhanced DNA methylation correlating with the accumulation of 2HG [9]. Thus, the metabolites αKG and 2HG reciprocally control the state of DNA methylation at the Sell promoter during normal T cell differentiation, and interestingly, the region of differential methylation overlaps with an IL-2- and αKG-sensitive CTCF site [9,10]. Together, these data indicate that the balance between the metabolites αKG and 2HG impacts normal T cell differentiation programming, while the data from CD4+ T cells lead to the speculation that these events are related to the regulation of CTCF association and genome topology at least in some circumstances (Figure 1).
Metabolic events, DNA methylation and genome organization are linked in diverse cell types
Integrating concepts and findings from several recent studies suggest that the ability of CTCF to translate metabolic events into differential organization of the genome may be a conserved mechanism for regulating differentiation in multiple cellular contexts and backgrounds. For example, induced pluripotent stem (iPS) cells derived from neural stem cells do not regain the complete genomic organization of ES cells despite the strong induction of the pluripotent program [29]. Interestingly, CTCF binding patterns and genomic organization events become more closely related to ES cells when iPS cells are maintained in 2i/Lif media. 2i/Lif media promotes pluripotency potential in ES cells at least partially through glutamine- and αKG-sensitive events [1]. In addition, 2i/Lif media promotes a hypomethylated state in iPS cells [29]. Taken together, these studies suggest the potential for a role for glutamine-, αKG-, and DNA-demethylase-sensitive events in the regulation of a subset of CTCF binding events in ES cells, although this has not been formally tested. This leads to the speculation that metabolic events in ES cells might regulate DNA methylation states, CTCF association and genome organization (Figure 1). As discussed, αKG-sensitive events are important for regulating CTCF binding events and genome organization in T cells and dysregulated metabolism impacts CTCF association and genome organization in gliomas [10,24]. In addition, CTCF is important in several developmental settings including cardiomyocyte and motor neuron differentiation [30,31]. Collectively, studies are starting to suggest that connections between metabolic events, CTCF association and genome organization may be conserved in diverse cellular differentiation settings.
Metabolite-sensitive CTCF events are influenced by the enhancer landscape
The suggestion that the ability of CTCF to translate metabolic events into changes in genome organization is a conserved mechanism in several cell types introduces the question; how can a conserved activity be translated into the specific expression of unique cellular programs in diverse cell types? Possible insight into this question is provided by the context-dependent interpretation of IL-2- and αKG-sensitive CTCF events in CD4+ T cells [10]. In CD4+ T cells, αKG-sensitive CTCF binding sites are found surrounding genes involved in the effector T cell program and this correlates with changes in gene expression. Interestingly, αKG-sensitive CTCF binding events are also found in the vicinity of genes from diverse developmental settings, but not surprisingly, there is a lack of active enhancers within those regions in CD4+ Th1 cells. Consistent with the lack of active enhancers, the genes surrounding these αKG-sensitive CTCF sites were not highly expressed in CD4+ or CD8+ T cells [10]. Intriguingly, the genes associated with ES cell development in the vicinity of αKG-sensitive CTCF sites in CD4+ T cells have αKG-sensitive gene expression in ES cells, a setting where the active enhancers for these genes would be present [10]. Together, these data suggest that αKG-sensitive CTCF events might occur in response to the nutrient environment in multiple cell types, but the enhancer landscape in each cell type is important for the appropriate cell-type and context-dependent expression of the gene programs.
Differentiation timing impacts reprogramming potential in T cells
As discussed, recent research has eloquently shown ties between metabolism and genome organization, but these organization events are interpreted in the context of the enhancer landscape of the cell. The enhancer landscape is important for appropriate cellular development, and has been shown to be dysregulated in disease states as well as in exhausted T cells [32–36]. In the tumor immunotherapy field, current therapeutics attempt to reinvigorate the effector activity of tumor infiltrating lymphocytes (TILs) through targeting inhibitory receptors associated with T cell exhaustion [37,38]. In addition, basic research has shown that alterations of the metabolic program can influence T cell differentiation and also reinvigorate TILs in mouse models of cancer [39–42]. Although some interventions restore the effector functions of exhausted TILs and ultimately limit tumor growth, most interventions do not completely rescue the effector activity of TILs and often times the rescue of effector activity is not stable. Understanding the mechanistic connections by which metabolism, active enhancers, and genome organization are linked could lead to the development of new combinatorial approaches to reinvigorate exhausted T cells with the potential for better therapeutic efficacy.
There are many concepts that are important to consider related to this research direction. A study examining CD8+ T cell differentiation in the context of the tumor microenvironment revealed that the timing and state of differentiation of the T cell is critical in defining whether the exhausted state can be reversed [35]. CD8+ T cells that are in early stages of differentiation in the tumor microenvironment have a more plastic chromatin state, and can be more easily rescued from the exhausted state through interventions that include blocking inhibitory receptors (Figure 2) [35,43]. On the other hand, CD8+ T cells exposed to the tumor microenvironment for more extensive periods of time develop a more stable exhausted chromatin state, and interventions cannot easily reverse the exhausted chromatin signature to one more similar to an effector T cell state (Figure 2) [32,33,43,44]. Interestingly, the exhausted state can be reversed if CD8+ T cells are exposed to therapeutics early in their differentiation in the tumor microenvironment, but the window of opportunity to revert the dysregulated state is narrow [35,43]. In addition, the expression of cell surface receptors such as CD38lo, CD101lo, CD30Llo, and CD5hi, distinguish the more plastic dysfunctional state that can be reprogrammed from a more fixed dysfunctional state in both mouse and human T cells [35]. Taken together, the current data suggest that the timing of the T cell exposure to a tumor microenvironment, which includes chronic antigen stimulation and a nutrient deplete environment with hypoxic conditions [43,45,46], is an important factor to consider in tumor immunotherapy strategies. Interestingly, both glutamine-deficiency and hypoxia in tumors can impact DNA methylation states, making it important to define whether these environmental conditions also impact CTCF association and genome organization in TILs [45,46].
Figure 2. Stages of potential reprogramming capacity for tumor infiltrating lymphocytes.

Tumor infiltrating lymphocytes at early stages of differentiation in the tumor microenvironment already display a dysfunctional chromatin signature relative to effector T cells, but they retain a degree of plasticity that allows them to be reprogrammed. However, TILs that have been exposed to the tumor environment for longer time periods lose this plasticity and cannot revert their chromatin signature back to the effector signature after checkpoint blockade.
Studies in CD4+ T cells strengthen the argument that both the availability and timing of the exposure to nutrients influence T cell differentiation decisions [8,10,47–50]. In CD4+ T cells, the presence of glutamine in the environment at the time of TCR activation is required for the appropriate initiation of the effector program [10]. The absence of glutamine during the initial TCR activation results in the development of less effector T cells and more T follicular helper (Tfh) cells in response to an influenza infection in comparison to the composition of cells that develop when CD4+ T cells are activated in glutamine rich conditions [10]. Collectively, many studies indicate the importance of the nutrient microenvironment in the early events of T cell differentiation, with both glucose and glutamine playing prominent roles in defining the differentiation potential of T cells [23,49,51]. The concepts from these studies also provide mechanistic insight into potential reasons for the difficulty researchers are having in the attempts to reverse differentiation states using immunotherapy approaches. Thoroughly defining mechanistic events, which will include integrating information about metabolism, epigenetics, and genome organization, is needed for a more in depth understanding of both normal and dysfunctional T cell differentiation states.
Future Directions
Much research has highlighted the connections between metabolism, epigenetics, and cellular differentiation [6,23,52]. As discussed here, research is now emerging which extends these mechanistic connections to encompass CTCF association and genome organization. DNA methylation has been shown to influence CTCF binding events in multiple cell types, and now metabolic events are being tied to the regulation of DNA methylation states and CTCF binding events [10,24,27]. The suggestion that mechanistic events associated with the regulation of CTCF localization and genome topology are conserved between cell types, but the interpretation of these events are dependent on the enhancer landscape in each cell, is an intriguing concept that is worth further exploration. One area of particular interest related to this concept in immunology is within the tumor immunotherapy field where it is important to design strategies that rescue the effector functions of exhausted T lymphocytes. Recent research has shown that the enhancer landscape is different in exhausted T cells as compared to effector and memory T cells and the chromatin landscape is not rescued with checkpoint blockade strategies [32,33,35,43]. Intriguingly, experimentally inhibiting de novo DNA methylation can enhance the effectiveness of immune-checkpoint-blockades [14], and as discussed here, DNA methylation states influence a subset of CTCF binding events and genome topology related to promoting the effector T cell program [10]. It will now be important to explore whether DNA methylation impacts CTCF association and ultimately genome organization in the context of tumor infiltrating lymphocytes. It is also worth noting that the αKG-sensitive regulation of CTCF association is regulated by additional events independent of DNA methylation [10]. Therefore, it will be important to define how this occurs and whether these events also regulate metabolite-sensitive CTCF association in the context of different cellular settings. Ultimately, a better understanding of how metabolism and the nutrient environment impact DNA methylation, CTCF association and genome organization events could provide new mechanistic insight into normal and dysfunctional T cell differentiation states.
Highlights.
Metabolite-sensitive events impact CTCF association and genome organization
Metabolite-sensitive CTCF events are interpreted in the context of enhancer landscape
Enhancer landscape of tumor-infiltrating lymphocytes impacts reprogramming capacity
Acknowledgments
We are grateful to Weinmann lab members for discussions on this research area and grant support from the NIH to A.S.W. (AI061061).
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**.Carey BW, Finley LW, Cross JR, Allis CD, Thompson CB. Intracellular alpha-ketoglutarate maintains the pluripotency of embryonic stem cells. Nature. 2015;518:413–416. doi: 10.1038/nature13981. This paper demonstrates that glutamine- and αKG-sensitive events impact the ES cell differentiation program by regulating histone and DNA-demethylase complex activity. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Shyh-Chang N, Locasale JW, Lyssiotis CA, Zheng Y, Teo RY, Ratanasirintrawoot S, Zhang J, Onder T, Unternaehrer JJ, Zhu H, et al. Influence of threonine metabolism on S-adenosylmethionine and histone methylation. Science. 2013;339:222–226. doi: 10.1126/science.1226603. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Moussaieff A, Rouleau M, Kitsberg D, Cohen M, Levy G, Barasch D, Nemirovski A, Shen-Orr S, Laevsky I, Amit M, et al. Glycolysis-mediated changes in acetyl-CoA and histone acetylation control the early differentiation of embryonic stem cells. Cell Metab. 2015;21:392–402. doi: 10.1016/j.cmet.2015.02.002. [DOI] [PubMed] [Google Scholar]
- 4.Shiraki N, Shiraki Y, Tsuyama T, Obata F, Miura M, Nagae G, Aburatani H, Kume K, Endo F, Kume S. Methionine metabolism regulates maintenance and differentiation of human pluripotent stem cells. Cell Metab. 2014;19:780–794. doi: 10.1016/j.cmet.2014.03.017. [DOI] [PubMed] [Google Scholar]
- 5.Wellen KE, Hatzivassiliou G, Sachdeva UM, Bui TV, Cross JR, Thompson CB. ATP-citrate lyase links cellular metabolism to histone acetylation. Science. 2009;324:1076–1080. doi: 10.1126/science.1164097. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.van der Knaap JA, Verrijzer CP. Undercover: gene control by metabolites and metabolic enzymes. Genes Dev. 2016;30:2345–2369. doi: 10.1101/gad.289140.116. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Kaelin WG, Jr, McKnight SL. Influence of metabolism on epigenetics and disease. Cell. 2013;153:56–69. doi: 10.1016/j.cell.2013.03.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Peng M, Yin N, Chhangawala S, Xu K, Leslie CS, Li MO. Aerobic glycolysis promotes T helper 1 cell differentiation through an epigenetic mechanism. Science. 2016;354:481–484. doi: 10.1126/science.aaf6284. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Tyrakis PA, Palazon A, Macias D, Lee KL, Phan AT, Velica P, You J, Chia GS, Sim J, Doedens A, et al. S-2-hydroxyglutarate regulates CD8+ T-lymphocyte fate. Nature. 2016;540:236–241. doi: 10.1038/nature20165. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10**.Chisolm DA, Savic D, Moore AJ, Ballesteros-Tato A, Leon B, Crossman DK, Murre C, Myers RM, Weinmann AS. CCCTC-Binding Factor Translates Interleukin 2- and alpha-Ketoglutarate-Sensitive Metabolic Changes in T Cells into Context-Dependent Gene Programs. Immunity. 2017;47:251–267 e257. doi: 10.1016/j.immuni.2017.07.015. This paper demonstrates that IL-2- and αKG-sensitive metabolic events regulate CTCF association and genome organization in CD4+ Th1 cells. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Pastor WA, Aravind L, Rao A. TETonic shift: biological roles of TET proteins in DNA demethylation and transcription. Nat Rev Mol Cell Biol. 2013;14:341–356. doi: 10.1038/nrm3589. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Ko M, An J, Rao A. DNA methylation and hydroxymethylation in hematologic differentiation and transformation. Curr Opin Cell Biol. 2015;37:91–101. doi: 10.1016/j.ceb.2015.10.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Li E, Zhang Y. DNA methylation in mammals. Cold Spring Harb Perspect Biol. 2014;6:a019133. doi: 10.1101/cshperspect.a019133. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Ghoneim HE, Fan Y, Moustaki A, Abdelsamed HA, Dash P, Dogra P, Carter R, Awad W, Neale G, Thomas PG, et al. De Novo Epigenetic Programs Inhibit PD-1 Blockade-Mediated T Cell Rejuvenation. Cell. 2017;170:142–157 e119. doi: 10.1016/j.cell.2017.06.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Youngblood B, Oestreich KJ, Ha SJ, Duraiswamy J, Akondy RS, West EE, Wei Z, Lu P, Austin JW, Riley JL, et al. Chronic virus infection enforces demethylation of the locus that encodes PD-1 in antigen-specific CD8(+) T cells. Immunity. 2011;35:400–412. doi: 10.1016/j.immuni.2011.06.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Ladle BH, Li KP, Phillips MJ, Pucsek AB, Haile A, Powell JD, Jaffee EM, Hildeman DA, Gamper CJ. De novo DNA methylation by DNA methyltransferase 3a controls early effector CD8+ T-cell fate decisions following activation. Proc Natl Acad Sci U S A. 2016;113:10631–10636. doi: 10.1073/pnas.1524490113. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Hark AT, Schoenherr CJ, Katz DJ, Ingram RS, Levorse JM, Tilghman SM. CTCF mediates methylation-sensitive enhancer-blocking activity at the H19/Igf2 locus. Nature. 2000;405:486–489. doi: 10.1038/35013106. [DOI] [PubMed] [Google Scholar]
- 18.Maurano MT, Wang H, John S, Shafer A, Canfield T, Lee K, Stamatoyannopoulos JA. Role of DNA Methylation in Modulating Transcription Factor Occupancy. Cell Rep. 2015;12:1184–1195. doi: 10.1016/j.celrep.2015.07.024. [DOI] [PubMed] [Google Scholar]
- 19.Ong CT, Corces VG. CTCF: an architectural protein bridging genome topology and function. Nat Rev Genet. 2014;15:234–246. doi: 10.1038/nrg3663. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Benner C, Isoda T, Murre C. New roles for DNA cytosine modification, eRNA, anchors, and superanchors in developing B cell progenitors. Proc Natl Acad Sci U S A. 2015;112:12776–12781. doi: 10.1073/pnas.1512995112. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21**.Isoda T, Moore AJ, He Z, Chandra V, Aida M, Denholtz M, Piet van Hamburg J, Fisch KM, Chang AN, Fahl SP, et al. Non-coding Transcription Instructs Chromatin Folding and Compartmentalization to Dictate Enhancer-Promoter Communication and T Cell Fate. Cell. 2017;171:103–119 e118. doi: 10.1016/j.cell.2017.09.001. This paper demonstrates that a long non-coding RNA regulates DNA methylation states, CTCF association and genome topology in T cell development. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Lempradl A, Pospisilik JA, Penninger JM. Exploring the emerging complexity in transcriptional regulation of energy homeostasis. Nat Rev Genet. 2015;16:665–681. doi: 10.1038/nrg3941. [DOI] [PubMed] [Google Scholar]
- 23.Chisolm DA, Weinmann AS. Connections between metabolism and epigenetics in programming cellular differentiation. Annu Rev Immunol. 2018;36:221–246. doi: 10.1146/annurev-immunol-042617-053127. [DOI] [PubMed] [Google Scholar]
- 24**.Flavahan WA, Drier Y, Liau BB, Gillespie SM, Venteicher AS, Stemmer-Rachamimov AO, Suva ML, Bernstein BE. Insulator dysfunction and oncogene activation in IDH mutant gliomas. Nature. 2016;529:110–114. doi: 10.1038/nature16490. This paper demonstrates that a dysregulated metabolic state caused by mutations in the isocitrate dehydrogenase enzyme impacts CTCF association and genome organization in a glioma cell setting. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Tahiliani M, Koh KP, Shen Y, Pastor WA, Bandukwala H, Brudno Y, Agarwal S, Iyer LM, Liu DR, Aravind L, et al. Conversion of 5-methylcytosine to 5-hydroxymethylcytosine in mammalian DNA by MLL partner TET1. Science. 2009;324:930–935. doi: 10.1126/science.1170116. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Xu W, Yang H, Liu Y, Yang Y, Wang P, Kim SH, Ito S, Yang C, Wang P, Xiao MT, et al. Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of alpha-ketoglutarate-dependent dioxygenases. Cancer Cell. 2011;19:17–30. doi: 10.1016/j.ccr.2010.12.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Teif VB, Beshnova DA, Vainshtein Y, Marth C, Mallm JP, Hofer T, Rippe K. Nucleosome repositioning links DNA (de)methylation and differential CTCF binding during stem cell development. Genome Res. 2014;24:1285–1295. doi: 10.1101/gr.164418.113. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Ghirlando R, Felsenfeld G. CTCF: making the right connections. Genes Dev. 2016;30:881–891. doi: 10.1101/gad.277863.116. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Beagan JA, Gilgenast TG, Kim J, Plona Z, Norton HK, Hu G, Hsu SC, Shields EJ, Lyu X, Apostolou E, et al. Local Genome Topology Can Exhibit an Incompletely Rewired 3D-Folding State during Somatic Cell Reprogramming. Cell Stem Cell. 2016;18:611–624. doi: 10.1016/j.stem.2016.04.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Narendra V, Bulajic M, Dekker J, Mazzoni EO, Reinberg D. CTCF-mediated topological boundaries during development foster appropriate gene regulation. Genes Dev. 2016;30:2657–2662. doi: 10.1101/gad.288324.116. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Gomez-Velazquez M, Badia-Careaga C, Lechuga-Vieco AV, Nieto-Arellano R, Tena JJ, Rollan I, Alvarez A, Torroja C, Caceres EF, Roy AR, et al. CTCF counter-regulates cardiomyocyte development and maturation programs in the embryonic heart. PLoS Genet. 2017;13:e1006985. doi: 10.1371/journal.pgen.1006985. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Sen DR, Kaminski J, Barnitz RA, Kurachi M, Gerdemann U, Yates KB, Tsao HW, Godec J, LaFleur MW, Brown FD, et al. The epigenetic landscape of T cell exhaustion. Science. 2016;354:1165–1169. doi: 10.1126/science.aae0491. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Pauken KE, Sammons MA, Odorizzi PM, Manne S, Godec J, Khan O, Drake AM, Chen Z, Sen DR, Kurachi M, et al. Epigenetic stability of exhausted T cells limits durability of reinvigoration by PD-1 blockade. Science. 2016;354:1160–1165. doi: 10.1126/science.aaf2807. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Vahedi G, Kanno Y, Furumoto Y, Jiang K, Parker SC, Erdos MR, Davis SR, Roychoudhuri R, Restifo NP, Gadina M, et al. Super-enhancers delineate disease-associated regulatory nodes in T cells. Nature. 2015;520:558–562. doi: 10.1038/nature14154. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35**.Philip M, Fairchild L, Sun L, Horste EL, Camara S, Shakiba M, Scott AC, Viale A, Lauer P, Merghoub T, et al. Chromatin states define tumour-specific T cell dysfunction and reprogramming. Nature. 2017;545:452–456. doi: 10.1038/nature22367. This paper demonstrates that tumor infiltrating lymphocytes have at least two unique stages of dysfunction that are marked by different chromatin signatures and cell surface receptor expression. The first stage of dysfunction that occurs early in differentiation is reversible with intervention, while the second stage of dysfunction is more stable and does not respond to interventions. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Vahedi G, Takahashi H, Nakayamada S, Sun HW, Sartorelli V, Kanno Y, O’Shea JJ. STATs shape the active enhancer landscape of T cell populations. Cell. 2012;151:981–993. doi: 10.1016/j.cell.2012.09.044. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Baumeister SH, Freeman GJ, Dranoff G, Sharpe AH. Coinhibitory Pathways in Immunotherapy for Cancer. Annu Rev Immunol. 2016;34:539–573. doi: 10.1146/annurev-immunol-032414-112049. [DOI] [PubMed] [Google Scholar]
- 38.Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer. 2012;12:252–264. doi: 10.1038/nrc3239. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Ho PC, Bihuniak JD, Macintyre AN, Staron M, Liu X, Amezquita R, Tsui YC, Cui G, Micevic G, Perales JC, et al. Phosphoenolpyruvate Is a Metabolic Checkpoint of Anti-tumor T Cell Responses. Cell. 2015;162:1217–1228. doi: 10.1016/j.cell.2015.08.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Chang CH, Qiu J, O’Sullivan D, Buck MD, Noguchi T, Curtis JD, Chen Q, Gindin M, Gubin MM, van der Windt GJ, et al. Metabolic Competition in the Tumor Microenvironment Is a Driver of Cancer Progression. Cell. 2015;162:1229–1241. doi: 10.1016/j.cell.2015.08.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Sukumar M, Liu J, Ji Y, Subramanian M, Crompton JG, Yu Z, Roychoudhuri R, Palmer DC, Muranski P, Karoly ED, et al. Inhibiting glycolytic metabolism enhances CD8+ T cell memory and antitumor function. J Clin Invest. 2013;123:4479–4488. doi: 10.1172/JCI69589. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Doedens AL, Phan AT, Stradner MH, Fujimoto JK, Nguyen JV, Yang E, Johnson RS, Goldrath AW. Hypoxia-inducible factors enhance the effector responses of CD8(+) T cells to persistent antigen. Nat Immunol. 2013;14:1173–1182. doi: 10.1038/ni.2714. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Schietinger A, Philip M, Krisnawan VE, Chiu EY, Delrow JJ, Basom RS, Lauer P, Brockstedt DG, Knoblaugh SE, Hammerling GJ, et al. Tumor-Specific T Cell Dysfunction Is a Dynamic Antigen-Driven Differentiation Program Initiated Early during Tumorigenesis. Immunity. 2016;45:389–401. doi: 10.1016/j.immuni.2016.07.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Mognol GP, Spreafico R, Wong V, Scott-Browne JP, Togher S, Hoffmann A, Hogan PG, Rao A, Trifari S. Exhaustion-associated regulatory regions in CD8+ tumor-infiltrating T cells. Proc Natl Acad Sci U S A. 2017;114:E2776–E2785. doi: 10.1073/pnas.1620498114. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Pan M, Reid MA, Lowman XH, Kulkarni RP, Tran TQ, Liu X, Yang Y, Hernandez-Davies JE, Rosales KK, Li H, et al. Regional glutamine deficiency in tumours promotes dedifferentiation through inhibition of histone demethylation. Nat Cell Biol. 2016;18:1090–1101. doi: 10.1038/ncb3410. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Thienpont B, Steinbacher J, Zhao H, D’Anna F, Kuchnio A, Ploumakis A, Ghesquiere B, Van Dyck L, Boeckx B, Schoonjans L, et al. Tumour hypoxia causes DNA hypermethylation by reducing TET activity. Nature. 2016;537:63–68. doi: 10.1038/nature19081. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Nakaya M, Xiao Y, Zhou X, Chang JH, Chang M, Cheng X, Blonska M, Lin X, Sun SC. Inflammatory T cell responses rely on amino acid transporter ASCT2 facilitation of glutamine uptake and mTORC1 kinase activation. Immunity. 2014;40:692–705. doi: 10.1016/j.immuni.2014.04.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Johnson MO, Siska PJ, Contreras DC, Rathmell JC. Nutrients and the microenvironment to feed a T cell army. Semin Immunol. 2016;28:505–513. doi: 10.1016/j.smim.2016.09.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.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]
- 50.Hukelmann JL, Anderson KE, Sinclair LV, Grzes KM, Murillo AB, Hawkins PT, Stephens LR, Lamond AI, Cantrell DA. The cytotoxic T cell proteome and its shaping by the kinase mTOR. Nat Immunol. 2016;17:104–112. doi: 10.1038/ni.3314. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.MacIver NJ, Michalek RD, Rathmell JC. Metabolic regulation of T lymphocytes. Annu Rev Immunol. 2013;31:259–283. doi: 10.1146/annurev-immunol-032712-095956. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Phan AT, Goldrath AW, Glass CK. Metabolic and Epigenetic Coordination of T Cell and Macrophage Immunity. Immunity. 2017;46:714–729. doi: 10.1016/j.immuni.2017.04.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
