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.
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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.
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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.
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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.
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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.
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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.
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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.
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Table of DEGs from RNA-seq used for GSEA analysis.
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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
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DOI: https://doi.org/10.1038/s41590-020-00834-9
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