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Epigenetic scars of CD8+ T cell exhaustion persist after cure of chronic infection in humans

Abstract

T cell exhaustion is an induced state of dysfunction that arises in response to chronic infection and cancer. Exhausted CD8+ T cells acquire a distinct epigenetic state, but it is not known whether that chromatin landscape is fixed or plastic following the resolution of a chronic infection. Here we show that the epigenetic state of exhaustion is largely irreversible, even after curative therapy. Analysis of chromatin accessibility in HCV- and HIV-specific responses identifies a core epigenetic program of exhaustion in CD8+ T cells, which undergoes only limited remodeling before and after resolution of infection. Moreover, canonical features of exhaustion, including super-enhancers near the genes TOX and HIF1A, remain ‘epigenetically scarred.’ T cell exhaustion is therefore a conserved epigenetic state that becomes fixed and persists independent of chronic antigen stimulation and inflammation. Therapeutic efforts to reverse T cell exhaustion may require new approaches that increase the epigenetic plasticity of exhausted T cells.

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Fig. 1: Distinct epigenetic changes underlie CD8+ T cell responses to Flu and chronic HCV infection.
Fig. 2: Epigenetic signature of T cell exhaustion is conserved across chronic viral infections.
Fig. 3: HCV-specific CD8+ T cells retain epigenetic scars of exhaustion despite cure of the chronic infection.
Fig. 4: Chronic TCR signaling, and not the inflammatory milieu, drives epigenetic scarring in exhausted CD8+ T cells.
Fig. 5: Scarred regions identify critical regulators of exhaustion.
Fig. 6: Epigenetic scars of exhaustion are retained long-term following infection cure.

Data availability

All sequencing data from this study will be made publicly available through the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/) and/or NCBI database of Genotypes and Phenotypes (dbGaP; https://www.ncbi.nlm.nih.gov/gap/). All other relevant data are available from the corresponding authors on request.

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Acknowledgements

We thank the members of the Haining laboratory for their input and the research participants for their participation. This work was supported by NIH grant no. U19 AI086230 and funding from the Parker Institute for Cancer Immunotherapy. S.A.W. was supported by NIH grant nos. T32 GM007753 and T32 CA207021; R.T.C. was supported by AI136715 and the MGH Research Scholars Program. We also thank the Center for Virology and Vaccine Research Flow Cytometry Core at Beth Israel Deaconess Medical Center for their assistance.

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Authors

Contributions

D.R.S. and W.N.H. conceived the study and designed the experiments. D.R.S., K.B.Y., G.E.M., U.G., R.A.A., D.E.C. and S.A.W. performed experiments and/or data analysis. P.T., D.W., D.C.T., R.T.C., T.M.A., A.Y.K. and G.M.L. contributed to the HCV clinical trial design, patient recruitment, sample processing, viral sequencing studies and/or transcriptional analysis. G.E.M., S.F., J. Frater. and J. Fox contributed to the HIV clinical trial design, patient recruitment and/or sample processing. D.R.S. and W.N.H. wrote the manuscript; all authors reviewed and edited the manuscript.

Corresponding authors

Correspondence to W. Nicholas Haining or Debattama R. Sen.

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Competing interests

AbbVie sponsored the clinical trial (NCT02476617) and gave input to the trial design as well as the clinical and biological sample collection schedule. W.N.H. is an employee of Merck and Company and holds equity in Tango Therapeutics and Arsenal Biosciences. The other authors declare no competing interests.

Additional information

Peer review information Nature Immunology thanks Hazem Ghoneim, Barbara Rehermann and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. Zoltan Fehervari 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 Isolation and chromatin accessibility profiling of Flu and HCV multimer+ CD8+ T cells in HCV infection.

a, Representative flow cytometry sorting strategy for Flu and HCV multimer+ CD8+ T cells. b, Recovered numbers of Flu (top) and HCV (bottom) multimer+ cells for each donor during chronic HCV infection. c, Recovered numbers of HCV multimer+ cells for each donor during resolved HCV infection. d, Combined ATAC signal across all TSSs for each biological condition from each donor. Green and range bands indicate ranges for ideal and acceptable values, respectively, for TSS enrichment per ENCODE standards. e, Boxplots of pairwise Pearson correlations for data from individual donors within each biological condition. Center, median; box limits, first and third percentiles; whiskers, min and max. N = 6 donors. f, Combined ATAC signal across all H3K27ac peaks (red), H3K27me3 (green) and H3K4me3 (purple). Histone mark peaks were determined from the following samples on ENCODE: ENCFF653OGM - H3K27ac, ENCFF285FID - H3K4me3, ENCFF367HSC - H3K27me3. g, Clustered similarity matrix between the indicated biological conditions in the chronically-infected and spontaneously resolved cohort. h, Density of overlapping GWAS SNPs per 1000 bp in Flu-specific, HCV-specific or non-differential ChARs.

Extended Data Fig. 2 Isolation and chromatin accessibility profiling of HIV multimer+ CD8+ T cells in HIV infection.

a, Representative flow cytometry sorting strategy for HIV multimer+ CD8+ T cells. b, Boxplots of pairwise Pearson correlations for data from individual donors within each biological condition. Center, median; box limits, first and third percentiles; whiskers, min and max. N = 11 donors. c, Combined principal component analysis of naïve, HIV-, HCV- and Flu- specific CD8+ T cells from the HIV and HCV cohorts.

Extended Data Fig. 3 Features of HCV-specific CD8+ T cells before and after DAA therapy.

a, PD-1 and CD39 staining on tetramer populations before (top) and after (bottom) DAA therapy. b, Partitioning of scarred and reversed regions into those overlapping promoters, UTRs, exons, introns and intergenic areas as indicated. c, Classification of SNPs falling within scarred, reversed or gained ChARs. SNPs that were subcategorized into those associated with chronic viral infection are summarized in Supplementary Table 3.

Extended Data Fig. 4 Minimal impact of the inflammatory milieu on chromatin accessibility within bystander populations in chronic HCV.

a, CCR7 and CD45RA staining on all CD8+ T cells (left) and Flu-specific T cells (right). b, Venn diagram of ChAR overlap in Flu tet+ cells (bottom) from HCV-infected donors and healthy donors. c, PD-1 and CD39 staining on tetramer populations before (top) and after (bottom) DAA therapy. d, Combined principal component analysis of naïve, effector memory, HCV-, and Flu- specific CD8+ T cells from the healthy and HCV cohorts. e, Heatmap showing pathway enrichment (rows) within clustered ChARs from Fig. 4g (columns).

Extended Data Fig. 5 Validation of ATAC-seq-based super-enhancer inference across multiple datasets.

a, H3K27ac ChIP-seq signal (top) and ATAC-seq signal (bottom) at the ETS1 gene locus. b, ROC plots of varying cutoff for ATAC-based ranking of super-enhancer to predict bona fide super-enhancers defined using matched tissue-specific H3K27ac ChIP-seq. c, Boxplots of tissue-specific mRNA expression, partitioned by genes with or without an associated super-enhancer. Center, median; box limits, first and third percentiles. d, Tox mRNA expression in HCV tetramer populations before and after DAA therapy. Mean ± s.d., two-sided Student’s t-test with Welch’s correction; *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001. N = 6 donors.

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Yates, K.B., Tonnerre, P., Martin, G.E. et al. Epigenetic scars of CD8+ T cell exhaustion persist after cure of chronic infection in humans. Nat Immunol 22, 1020–1029 (2021). https://doi.org/10.1038/s41590-021-00979-1

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