Abstract
Cancer and chronic infections induce T cell exhaustion, a hypofunctional fate carrying distinct epigenetic, transcriptomic and metabolic characteristics. However, drivers of exhaustion remain poorly understood. As intratumoral exhausted T cells experience severe hypoxia, we hypothesized that metabolic stress alters their responses to other signals, specifically, persistent antigenic stimulation. In vitro, although CD8+ T cells experiencing continuous stimulation or hypoxia alone differentiated into functional effectors, the combination rapidly drove T cell dysfunction consistent with exhaustion. Continuous stimulation promoted Blimp-1-mediated repression of PGC-1α-dependent mitochondrial reprogramming, rendering cells poorly responsive to hypoxia. Loss of mitochondrial function generated intolerable levels of reactive oxygen species (ROS), sufficient to promote exhausted-like states, in part through phosphatase inhibition and the consequent activity of nuclear factor of activated T cells. Reducing T cell–intrinsic ROS and lowering tumor hypoxia limited T cell exhaustion, synergizing with immunotherapy. Thus, immunologic and metabolic signaling are intrinsically linked: through mitigation of metabolic stress, T cell differentiation can be altered to promote more functional cellular fates.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
RNA-seq data have been deposited to the Gene Expression Omnibus (GEO) with accession no. GSE155192. Source data for Fig. 3, and Extended Data Fig. 3a,b are available in the GEO repository, accession no. GSE122713; and source data for Extended Data Fig. 9e,f are available in the GEO repository, accession no. GSE109125. The data that support the findings of the present study are available from the corresponding authors upon request. Source data are provided with this paper.
References
Taniuchi, I. CD4 helper and CD8 cytotoxic T cell differentiation. Annu. Rev. Immunol. 36, 579–601 (2018).
Chang, J. T., Wherry, E. J. & Goldrath, A. W. Molecular regulation of effector and memory T cell differentiation. Nat. Rev. Immunol. 15, 1104–1115 (2014).
McLane, L. M., Abdel-Hakeem, M. S. & Wherry, E. J. CD8 T cell exhaustion during chronic viral infection and cancer. Annu. Rev. Immunol. 37, 457–495 (2019).
Paley, M. A. et al. Progenitor and terminal subsets of CD8+ T cells cooperate to contain chronic viral infection. Science 338, 1220–1225 (2012).
Shin, H. et al. A role for the transcriptional repressor Blimp-1 in CD8+ T cell exhaustion during chronic viral infection. Immunity 31, 309–320 (2009).
Chihara, N. et al. Induction and transcriptional regulation of the co-inhibitory gene module in T cells. Nature 558, 454–459 (2018).
Martinez, G. J. et al. The transcription factor NFAT promotes exhaustion of activated CD8+ T cells. Immunity 42, 265–278 (2015).
Mann, T. H. & Kaech, S. M. Tick-TOX, it’s time for T cell exhaustion. Nat. Immunol. 20, 1092–1094 (2019).
Sen, D. R. et al. The epigenetic landscape of T cell exhaustion. Science 354, 1165–1169 (2016).
Pauken, K. E. et al. Epigenetic stability of exhausted T cells limits durability of reinvigoration by PD-1 blockade. Science 354, 1160–1165 (2016).
Philip, M. et al. Chromatin states define tumour-specific T cell dysfunction and reprogramming. Nature 545, 452–456 (2017).
Blank, C. U. et al. Defining ‘T cell exhaustion’. Nat. Rev. Immunol. https://doi.org/10.1038/s41577-019-0221-9 (2019).
Scharping, N. & Delgoffe, G. Tumor microenvironment metabolism: a new checkpoint for anti-tumor immunity. Vaccines 4, 46 (2016).
Martinez-Outschoorn, U. E., Peiris-Pagés, M., Pestell, R. G., Sotgia, F. & Lisanti, M. P. Cancer metabolism: a therapeutic perspective. Nat. Rev. Clin. Oncol. https://doi.org/10.1038/nrclinonc.2016.60 (2016).
Scharping, N. E. et al. The tumor microenvironment represses T cell mitochondrial biogenesis to drive intratumoral T cell metabolic insufficiency and dysfunction. Immunity 45, 374–388 (2016).
Scharping, N. E., Menk, A. V., Whetstone, R. D., Zeng, X. & Delgoffe, G. M. Efficacy of PD-1 blockade is potentiated by metformin-induced reduction of tumor hypoxia. Cancer Immunol. Res. 5, 9–16 (2017).
Menk, A. V. et al. 4-1BB costimulation induces T cell mitochondrial function and biogenesis enabling cancer immunotherapeutic responses. J. Exp. Med. 215, 1091–1100 (2018).
Najjar, Y. G. et al. Tumor cell oxidative metabolism as a barrier to PD-1 blockade immunotherapy in melanoma. JCI Insight 4, e124989 (2019).
Chang, C. H. et al. Metabolic competition in the tumor microenvironment is a driver of cancer progression. Cell 162, 1229–1241 (2015).
Leone, R. D. et al. Glutamine blockade induces divergent metabolic programs to overcome tumor immune evasion. Science https://doi.org/10.1126/science.aav2588 (2019).
Miller, B. C. et al. Subsets of exhausted CD8+ T cells differentially mediate tumor control and respond to checkpoint blockade. Nat. Immunol. 20, 326–336 (2019).
Sade-Feldman, M. et al. Defining T cell states associated with response to checkpoint immunotherapy in melanoma. Cell 175, 998–1013.e20 (2018).
Doedens, A. L. et al. Hypoxia-inducible factors enhance the effector responses of CD8+ T cells to persistent antigen. Nat. Immunol. 14, 1173–1182 (2013).
Gropper, Y. et al. Culturing CTLs under hypoxic conditions enhances their cytolysis and improves their anti-tumor function. Cell Rep. 20, 2547–2555 (2017).
Li, Y., Patel, S. P., Roszik, J. & Qin, Y. Hypoxia-driven immunosuppressive metabolites in the tumor microenvironment: new approaches for combinational immunotherapy. Front. Immunol. 9, 1591 (2018).
Horton, B. L., Williams, J. B., Cabanov, A., Spranger, S. & Gajewski, T. F. Intratumoral CD8+ T-cell apoptosis is a major component of T-cell dysfunction and impedes antitumor immunity. Cancer Immunol. Res. 6, 14–24 (2018).
Crawford, A. et al. Molecular and transcriptional basis of CD4+ T cell dysfunction during chronic infection. Immunity 40, 289–302 (2014).
Sawant, D. V. et al. Adaptive plasticity of IL-10+ and IL-35+ Treg cells cooperatively promotes tumor T cell exhaustion. Nat. Immunol. 20, 724–735 (2019).
Liu, C. et al. Neuropilin-1 is a T cell memory checkpoint limiting long-term antitumor immunity. Nat. Immunol. https://doi.org/10.1038/s41590-020-0733-2 (2020).
Chinopoulos, C. Which way does the citric acid cycle turn during hypoxia? The critical role of α-ketoglutarate dehydrogenase complex. J. Neurosci. Res. 91, 1030–1043 (2013).
Sukumar, M. et al. Mitochondrial membrane potential identifies cells with enhanced stemness for cellular therapy. Cell Metab. 23, 63–76 (2016).
Siska, P. J. et al. Mitochondrial dysregulation and glycolytic insufficiency functionally impair CD8 T cells infiltrating human renal cell carcinoma. JCI Insight 2, e93411 (2017).
Hurst, K. E. et al. Endoplasmic reticulum stress contributes to mitochondrial exhaustion of CD8+ T cells. Cancer Immunol. Res. 7, 476–486 (2019).
Dröse, S. & Brandt, U. The mechanism of mitochondrial superoxide production by the cytochrome bc1 complex. J. Biol. Chem. 283, 21649–21654 (2008).
Li, N. et al. Mitochondrial complex I inhibitor rotenone induces apoptosis through enhancing mitochondrial reactive oxygen species production. J. Biol. Chem. 278, 8516–8525 (2003).
Chandel, N. S. et al. Mitochondrial reactive oxygen species trigger hypoxia-induced transcription. Proc. Natl Acad. Sci. USA 95, 11715–11720 (1998).
Acín-Pérez, R. et al. Mitochondrial respiration controls lysosomal function during inflammatory T cell responses. Cell Metab. 22, 485–498 (2015).
Schieber, M. & Chandel, N. S. ROS function in redox signaling and oxidative stress. Curr. Biol. 24, R453–R462 (2014).
Sena, L. A. et al. Mitochondria are required for antigen-specific T cell activation through reactive oxygen species signaling. Immunity 38, 225–236 (2013).
St-Pierre, J. et al. Suppression of reactive oxygen species and neurodegeneration by the PGC-1 transcriptional coactivators. Cell 127, 397–408 (2006).
Schaaf, M. B., Garg, A. D. & Agostinis, P. Defining the role of the tumor vasculature in antitumor immunity and immunotherapy. Cell Death Dis. 9, 115 (2018).
Motzer, R. J. et al. Avelumab plus axitinib versus sunitinib for advanced renal-cell carcinoma. N. Engl. J. Med. 380, 1103–1115 (2019).
Bengsch, B. et al. Bioenergetic insufficiencies due to metabolic alterations regulated by the inhibitory receptor PD-1 are an early driver of CD8+ T cell exhaustion. Immunity 45, 358–373 (2016).
Ho, P. C. et al. Phosphoenolpyruvate is a metabolic checkpoint of anti-tumor T cell responses. Cell 162, 1217–1228 (2015).
Phan, A. T. et al. Constitutive glycolytic metabolism supports CD8+ T cell effector memory differentiation during viral infection. Immunity 45, 1024–1037 (2016).
Mehta, M. M., Weinberg, S. E. & Chandel, N. S. Mitochondrial control of immunity: beyond ATP. Nat. Rev. Immunol. 17, 608–620 (2017).
Mach, W. J., Thimmesch, A. R., Pierce, J. T. & Pierce, J. D. Consequences of hyperoxia and the toxicity of oxygen in the lung. Nurs. Res. Pract. 2011, 260482 (2011).
Blaser, H., Dostert, C., Mak, T. W. & Brenner, D. TNF and ROS crosstalk in inflammation. Trends Cell Biol. 26, 249–261 (2016).
Wellen, K. E. & Thompson, C. B. Cellular metabolic stress: considering how cells respond to nutrient excess. Mol. Cell 40, 323–332 (2010).
Vardhana, S. A. et al. Impaired mitochondrial oxidative phosphorylation limits the self-renewal of T cells exposed to persistent antigen. Nat. Immunol. https://doi.org/10.1038/s41590-020-0725-2 (2020).
Voron, T. et al. VEGF-A modulates expression of inhibitory checkpoints on CD8+ T cells in tumors. J. Exp. Med. 212, 139–148 (2015).
Palazon, A. et al. An HIF-1α/VEGF-A axis in cytotoxic T cells regulates tumor progression. Cancer Cell 32, 669–683.e5 (2017).
Bacik, I., Cox, J. H., Anderson, R., Yewdell, J. W. & Bennink, J. R. TAP (transporter associated with antigen processing)-independent presentation of endogenously synthesized peptides is enhanced by endoplasmic reticulum insertion sequences located at the amino- but not carboxyl-terminus of the peptide. J. Immunol. 152, 381–387 (1994).
Delgoffe, G. M. et al. The mTOR kinase differentially regulates effector and regulatory T cell lineage commitment. Immunity 30, 832–844 (2009).
Monsalve, M. et al. Direct coupling of transcription and mRNA processing through the thermogenic coactivator PGC-1. Mol. Cell 6, 307–316 (2000).
Poholek, A. C. et al. IL-10 induces a STAT3-dependent autoregulatory loop in TH2 cells that promotes Blimp-1 restriction of cell expansion via antagonism of STAT5 target genes. Sci. Immunol. 1, eaaf8612 (2016).
Acknowledgements
We thank members of the Delgoffe Laboratory for helpful discussions, as well as K. M. Vignali and D. A. A. Vignali for the gift of E8I–GFP–CreERT2 mice. Trainees on this work were supported by the NCI Predoctoral to Postdoctoral Fellow Transition Award (F99/K00) (no. F99CA222711 to N.E.S.), T32CA082084 to P.D.A.V. and K.D, F30CA247034 to P.D.A.V., F31CA247129 to. K.D. and T32AI089443 to R.P. This work was supported by an NIH New Innovator Award (nos. DP2AI136598 and R21AI135367), the UPMC Hillman Cancer Center Melanoma/Skin Cancer (no. P50CA121973) and Head and Neck Cancer SPORE (no. P50CA097190), a SU2C-AACR Innovative Research grant (no. SU2C-AACR-IRG-04-16), the US Army/Department of Defense (no. CA170483), the Alliance for Cancer Gene Therapy, the Mark Foundation for Cancer Research Emerging Leader Award, the Cancer Research Institute Lloyd J. Old STAR Award and the Sy Holzer Endowed Cancer Immunotherapy Fund (all to G.M.D.). This work utilized flow cytometry and animal facilities at UPMC Hillman Cancer Center, supported by grant no. P30CA047904.
Author information
Authors and Affiliations
Contributions
N.E.S. designed and performed experiments, analyzed data and helped write the manuscript; D.B.R., A.V.M. and P.D.A.V. designed and performed experiments and analyzed data. B.R.F and N.L.R. analyzed transcriptomic data. R.P. imaged microscopy experiments. Yiyang W. cloned overexpression plasmids. Yupeng W. aided Rho0 experiments. K.D. performed critical mouse experiments. A.C.P. oversaw bioinformatics research and provided crucial insight into Blimp-1-deficient experiments. G.M.D. conceived of, oversaw and directed the research; performed initial experiments; analyzed data; obtained research funding; and wrote the manuscript.
Corresponding author
Ethics declarations
Competing interests
G.M.D. declares competing financial interests and has submitted patents covering the use of PGC-1α in cell therapies that are licensed or pending and is entitled to a share in net income generated from licensing of these patent rights for commercial development. He consults for and/or is on the scientific advisory board of BlueSphere Bio, Century Therapeutics, Novasenta, Pieris Pharmaceuticals and Western Oncolytics/Kalivir; has grants from bluebird bio, Novasenta, Pfizer, Pieris Pharmaceuticals, TCR2 and Western Oncolytics/Kalivir; and owns stock in Novasenta.
Additional information
Peer review information Nature Immunology thanks Guangyong Peng, Doreen Cantrell and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. L. A. Dempsey was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Antigen-specific tumor co-culture under hypoxia induces an exhausted-like dysfunctional state.
a, Lymph node (LN) and Tumor-infiltrating lymphocyte (TIL) gating strategy. b, PD1 vs Tim3 expression in gp100 specific Pmel TIL (red) overlaid on endogenous WT TIL (black) in in vivo B16 melanoma. c, Schematic of in vitro T cell+tumor cell exhaustion assay. Spleen and lymph node preparations from OT-I mice were stimulated with SIINFEKL peptide and IL-2 for 24 hours. T cells were then plated either alone, 1:1 with B16, or 1:1 with B16OVA, and placed in normoxia (atmospheric O2) or hypoxia (1.5% O2), all with IL-2 for 5-7 d. d, OT1 T cell fold expansion generated using the schematic in c, each group n = 3. e, Cytokine production after CD3/CD28 restimulation in CD8+ T cells as a function of their coculture status. All restimulations were done in atmospheric oxygen. Each group n = 5. f, Representative flow cytograms (left) and quantitated data (right) of CD8+ T cells PD-1 vs Tim3 expression generated using the schematic in c, each group n = 4. All data are representative of 3-5 independent experiments. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001 by one-way ANOVA with Dunnett’s multiple comparison test. Error bars indicate SEM.
Extended Data Fig. 2 In vitro continuous stimulation under hypoxia does not significantly affect proliferation but affects accumulation.
a, TNF and IFN-γ production of d10 in vitro CD8+ T cells, either acutely or continuously activated with anti-CD3/CD28 beads for d2-5 in hypoxia or normoxia, then cultured additionally for 5 d in the presence of normoxia or hypoxia. b, Representative flow histograms and division analyses (right) of day 3 CD8+ T cells CTV dilution generated using the stimulation protocol used in Fig. 2. Both % divided and proliferation index are reported. Each group n = 3. c, Expansion (left) and cumulative doublings right) of CD8+ T cells as in Fig. 2. each group n = 4. d, Dye dilution (proliferation) versus cell death (live/dead) staining of day 3 or day 4 CD8+ T cells generated as in Fig. 2. e, Mean fluorescence intensity of PD-1 in division 4 CD8+ T cells. Each group n = 3. f-h, Representative flow cytograms of day 3 CD8+ T cells generated as in Fig. 2. each group n = 4. All data are representative of 3-6 independent experiments. ∗p < 0.05 by one-way ANOVA with Dunnett’s multiple comparison test. Error bars indicate SEM.
Extended Data Fig. 3 Continuous activation under hypoxia results in enrichment of genes related to terminal exhaustion and repression of genes from more progenitor-like exhausted cells.
a, Heatmap of selected genes from Fig. 3d (genes specifically enriched in progenitor exhausted T cells) from all four in vitro conditions detailed in Fig. 2. Each group n = 3 b, Heatmap of selected genes from Fig. 3e (genes specifically enriched in terminally exhausted T cells) from all four in vitro conditions detailed in Fig. 2. Each group n = 3.
Extended Data Fig. 4 HIF-1α is dispensable for continuous stimulation under hypoxia-induced dysfunction, although hypoxia signaling is active in response to hypoxia.
a, PD-1 and Tim-3 staining in WT or HIF-1α-deficient CD8+ T cells continuously stimulated under hypoxia as in Fig. 2. each group n = 6. b, Cytokine production of restimulated WT and HIF-deficient T cells as in a. WT AN n = 4, CH n = 7; HIF-deficient AN n = 4, CH n = 8. c, Quantification of 2-NBDG staining as in Fig. 2. each group n = 5. d, Heatmap of known HIF-1α target genes from the transcriptional analyses in Fig. 3. Each group n = 3. All data are representative of 3–6 independent experiments. ∗p < 0.05 by one-way ANOVA with Dunnett’s multiple comparison test (c). Error bars indicate SEM.
Extended Data Fig. 5 Blimp-1 represses metabolic sufficiency in a HIF-1α-independent manner.
a, Viability of 293T cells from Fig. 4d assessed by flow. b, Schematic of antigen-specific Blimp-1 T cell deletion: Mice bearing 3 mm diameter B16OVA tumors received 2 × 106 naïve OT-I Prdm1f/fCd4Cre or Prdm1f/f T cells. Nine days later, mice were sacrificed and analyzed, transferred cells identified by Thy1.1+. c, MitoTracker geometric MFI of OT-I T cells transferred as in b. WT n = 7 mice, Blimp-1-deficient n = 8 mice. d, E8ICreERT2Prdm1f/fR26LSL.Tomato (Prdm1iKO) TIL flow cytogram of CD8 vs Tomato expression after 5 days of tamoxifen. e, WT and Prdm1iKO TIL flow cytogram of PD-1 vs Tim3 after 5 days of tamoxifen, with accompanying quantification. WT n = 7 mice, Blimp-1-deficient n = 6 mice. f, Prdm1iKO TIL Tomato expression after 5 days of tamoxifen, gated on CD8+ PD-1+ Tim3+ g, WT and Prdm1iKO TIL Blimp-1 staining after 5 days of tamoxifen, gated on CD8+ PD1+ Tim3+ TIL. h, Quantification of Hif1af/fCd4Cre or Cre negative littermate control CD8+ LN and CD8+ PD1hiTim3+ TIL Blimp-1 geometric mean fluorescent intensity. WT n = 6 mice, HIF-deficient n = 5 mice. i, Quantification of Prdm1f/fCd4Cre or Cre negative littermate control CD8+ LN CD8+ PD1hiTim3+ TIL Hif-1α geometric mean fluorescent intensity, fold change from LN. WT n = 10 mice, Blimp-1-deficient n = 10 mice. All data are representative of 3-8 independent experiments. ∗p < 0.05 by unpaired T test (c,e,h,i). Error bars indicate SEM.
Extended Data Fig. 6 PGC1α diverts differentiation from exhaustion by mitigating reactive oxygen species.
a, Geneset enrichment analysis of EV (n = 3) or PGC1αOE (n = 3) retrovirally transduced Pmel T cells sorted from B16-F10 as in Fig. 5a. Genesets are previously published comparing to progenitor exhausted T cells as in Fig. 3d. b, As in A but for terminally exhausted T cells. c, Metascape analysis of differentially upregulated pathways in PGC1αOE Pmel T cells sorted directly from the tumor microenvironment. EV n = 3, PGC1αOE n = 3. d, MitoSOX staining of T cells, normalized to control, cultured 0.04 µM AA, or cultured in the indicated amounts of rotenone, for either 5 hr or 6 days. Each group n = 2. e, CellTrace Violet dye dilution of day 3 CD8+ T cells cultured in either antimycin A, rotenone, or both. Each group n = 3. f, CTV dilution vs live/dead staining of day 3 CD8. T cells in e. g, Quantification of fold expansion of control cells and those cultured in 0.04 µM antimycin A, 0.4 µM rotenone, or AA + rot, 10 mM NAC, or NAC + AA. Each group n = 5. h, Fold expansion of CD8+ T cells in the continuous stimulation under hypoxia assay, ± antioxidant NAC, quantitation normalized to acute stim in normoxia. Each group n = 5. All data are representative of 2-5 independent experiments. ∗p < 0.05, ∗∗p < 0.01 by unpaired T test (h). Error bars indicate SEM.
Extended Data Fig. 7 Progressive loss of mtDNA in T cells induces high levels of reactive oxygen species and an exhausted-like state.
a, Schematic of generation of Rho0 T cells. b, Cellular ROS (DCFDA) staining of Rho0 T cells. c, Control and Rho0 T cell mitochondrial DNA (mtDNA) qPCR of ndufs4 (ND4), mt-dloop1 (Dloop1), and mt-rnr2 (16 S), normalized to nuclear DNA. Each group n = 3. d, Immunoblot of Control and Rho0 for mitochondrial proteins CV- ATP5A, CIII- UQCRC2, and CII- SDHB. Each group n = 3. e, (Left) basal oxygen consumption rate (OCR) versus basal extracellular acidification rate (ECAR) of control vs Rho0 CD8+ T cells. (Right) spare respiratory capacity quantification (difference between basal and FCCP-uncoupled OCR) of control vs Rho0 T cells. Control n = 5, Rho0 n = 3. f, Quantification of fold expansion of control and Rho0 T cells. Each group n = 6. g, PD-1, Tim3, and TIGIT staining on Control and Rho0 OT-I T cells. h, Flow cytogram of target splenocytes cells differentially labeled with CFSE loaded with SIINFEKL or control peptides, transferred into WT mice along with 1 ×105 WT or Rho0 OT-I T cells generated as in b. each group n = 3. i, Quantification of ROS staining of Rho0 T cells, cultured in the presence or absence of different concentrations of NAC. Each group n = 2. j, (Left) representative flow cytograms of TNF vs IFN-γ production of OT-I T generated as in a (± NAC) and stimulated overnight with cognate peptide. (Right) Quantification of percent TNF+ IFN-γ+. Each group n = 2. k, Quantification of Tox MFI in CD8+ T cells in control, Rho0, and Rho0 + 10 mM NAC. Each group n = 4. All data are representative of 3-5 independent experiments. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001 by two-way ANOVA with Sidak’s multiple comparison test (c), one-way ANOVA with Dunnett’s multiple comparison test (k) and by unpaired T test (e,f, h-j). Error bars indicate SEM.
Extended Data Fig. 8 Enforced elevation of phosphotyrosine signaling via tyrosine phosphorylation inhibition in isolation can drive an exhausted-like state.
a, (Left) global phosphotyrosine staining of CD8+ T cells cultured in vitro with 50 µM sodium orthovanadate, (right) quantification of p-Tyr100 MFI. Each group n = 6. b, Quantification of fold expansion of control and Na3VO4-cultured cells. Each group n = 3 c, (Left) representative flow cytograms of PD1 vs Tim3 expression in cells cultured in B, (right) quantification of percent PD1+ Tim3+. Each group n = 6. d, Quantification of IFN-γ production of Na3VO4-cultured cells after an overnight restimulation with anti-CD3/anti-CD28, golgiplug included in the last 5 hours. Control n = 2, Na3VO4 n = 4. e, (Left) representative flow histogram of Blimp-1 expression in cells cultured in a, (right) quantification of Blimp-1 MFI. Each group n = 5. f, (Left) representative flow histogram of Tox expression in cells cultured in a, (right) quantification of Tox MFI. Each group n = 5. All data are representative of 3-5 independent experiments. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001 by unpaired T test. Error bars indicate SEM.
Extended Data Fig. 9 CD8+ T cells infiltrating tumors engineered to be less hypoxic differentiate away from exhaustion toward effector/memory cells.
a, Immunoblot of the mitochondrial complex I subunit Ndufs4 in B16-F10 melanoma cells or those in which Ndufs4 has been disrupted using CRISPR-Cas9. n = 1. b, Tumor area at d14 (time of analysis) for WT or Ndufs4-deficient B16-F10. WT n = 13 mice, Ndufs4-deficient n = 14 mice. c, Percent CD8+ T cells infiltrating WT or Ndufs4-deficient B16-F10 tumors. WT n = 6 mice, Ndufs4-deficient n = 7 mice. d, Leading edge plot of Regulation of Reactive Oxygen Species Metabolic Process (GO:2000377) produced via GSEA analysis of PD-1hiTim3+ CD8+ T cells infiltrating WT or Ndufs4-deficient B16.F10. WT n = 3 mice, Ndufs4-deficient n = 2 mice. e, as in d, but comparing effector to exhausted T cells, including heatmap. f, as in d, but comparing memory to exhausted T cells, including heatmap. ∗p < 0.05, ∗∗p < 0.01 by unpaired T Test (b,c). Error bars indicate SEM.
Supplementary information
Supplementary Table
Table of DEGs from RNA-seq used for GSEA analysis.
Source data
Source Data Fig. 3
Unprocessed immunoblots
Source Data Fig. 6
Unprocessed immunoblots
Source Data Extended Data Fig. 7
Unprocessed immunoblots
Source Data Extended Data Fig. 9
Unprocessed immunoblots
Rights and permissions
About this article
Cite this article
Scharping, N.E., Rivadeneira, D.B., Menk, A.V. et al. Mitochondrial stress induced by continuous stimulation under hypoxia rapidly drives T cell exhaustion. Nat Immunol 22, 205–215 (2021). https://doi.org/10.1038/s41590-020-00834-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41590-020-00834-9
- Springer Nature America, Inc.
This article is cited by
-
1-Pyrroline-5-carboxylate inhibit T cell glycolysis in prostate cancer microenvironment by SHP1/PKM2/LDHB axis
Cell Communication and Signaling (2024)
-
Mitochondrial metabolism sustains CD8+ T cell migration for an efficient infiltration into solid tumors
Nature Communications (2024)
-
Take my breath away—mitochondrial dysfunction drives CD8+ T cell exhaustion
Genes & Immunity (2024)
-
The pleiotropic functions of reactive oxygen species in cancer
Nature Cancer (2024)
-
A second-generation M1-polarized CAR macrophage with antitumor efficacy
Nature Immunology (2024)