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Intravenous nanoparticle vaccination generates stem-like TCF1+ neoantigen-specific CD8+ T cells

Abstract

Personalized cancer vaccines are a promising approach for inducing T cell immunity to tumor neoantigens. Using a self-assembling nanoparticle vaccine that links neoantigen peptides to a Toll-like receptor 7/8 agonist (SNP-7/8a), we show how the route and dose alter the magnitude and quality of neoantigen-specific CD8+ T cells. Intravenous vaccination (SNP-IV) induced a higher proportion of TCF1+PD-1+CD8+ T cells as compared to subcutaneous immunization (SNP-SC). Single-cell RNA sequencing showed that SNP-IV induced stem-like genes (Tcf7, Slamf6, Xcl1) whereas SNP-SC enriched for effector genes (Gzmb, Klrg1, Cx3cr1). Stem-like cells generated by SNP-IV proliferated and differentiated into effector cells upon checkpoint blockade, leading to superior antitumor response as compared to SNP-SC in a therapeutic model. The duration of antigen presentation by dendritic cells controlled the magnitude and quality of CD8+ T cells. These data demonstrate how to optimize antitumor immunity by modulating vaccine parameters for specific generation of effector or stem-like CD8+ T cells.

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Fig. 1: The route and dose of SNP-7/8a immunization controls the magnitude and phenotype of antigen-specific CD8 T cells.
Fig. 2: IV administration of SNP-7/8a generates TCF1+CD8+ T cells with antitumor capacity on anti-PD-L1 treatment.
Fig. 3: Single-cell analysis of neoantigen+ CD8+ T cells by RNA-seq identifies stem-like gene signature in SNP-IV cells and an effector gene signature in SNP-SC cells.
Fig. 4: Therapeutic vaccination with SNP-IV generates neoantigen-specific CD8+ T cells with superior antitumor capacity.
Fig. 5: Transient vaccine distribution to the spleen and activation of migratory cDC1s and monocyte-derived DCs after SNP-IV.
Fig. 6: Prolonged antigen presentation by DCs drives CD8+ T cell responses after SNP-SC.

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Data availability

The data that support the findings of this study are available from the corresponding author upon request. The scRNA-seq data have been uploaded to the Gene Expression Omnibus (accession number GSE158240).

References

  1. Rosenberg, S. A. & Restifo, N. P. Adoptive cell transfer as personalized immunotherapy for human cancer. Science 348, 62–68 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Schumacher, T. N. & Schreiber, R. D. Neoantigens in cancer immunotherapy. Science 348, 69–74 (2015).

    CAS  PubMed  Google Scholar 

  3. Tumeh, P. C. et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 515, 568–571 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Versluis, J. M., Long, G. V. & Blank, C. U. Learning from clinical trials of neoadjuvant checkpoint blockade. Nat. Med. 26, 475–484 (2020).

    CAS  PubMed  Google Scholar 

  5. Kreiter, S. et al. Mutant MHC class II epitopes drive therapeutic immune responses to cancer. Nature 520, 692–696 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Yadav, M. et al. Predicting immunogenic tumour mutations by combining mass spectrometry and exome sequencing. Nature 515, 572–576 (2014).

    CAS  PubMed  Google Scholar 

  7. Hilf, N. et al. Actively personalized vaccination trial for newly diagnosed glioblastoma. Nature 565, 240–245 (2019).

    CAS  PubMed  Google Scholar 

  8. Melief, C. J. M. Cancer: precision T-cell therapy targets tumours. Nature 547, 165–167 (2017).

    CAS  PubMed  Google Scholar 

  9. Ott, P. A. et al. An immunogenic personal neoantigen vaccine for patients with melanoma. Nature 547, 217–221 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Sahin, U. et al. Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer. Nature 547, 222–226 (2017).

    CAS  PubMed  Google Scholar 

  11. Lynn, G. M. et al. Peptide-TLR-7/8a conjugate vaccines chemically programmed for nanoparticle self-assembly enhance CD8 T-cell immunity to tumor antigens. Nat. Biotechnol. 38, 320–332 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Eisenbarth, S. C. Dendritic cell subsets in T cell programming: location dictates function. Nat. Rev. Immunol. 19, 89–103 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Kaech, S. M. & Cui, W. Transcriptional control of effector and memory CD8+ T cell differentiation. Nat. Rev. Immunol. 12, 749–761 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. 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).

    CAS  PubMed  Google Scholar 

  15. Im, S. J. et al. Defining CD8+ T cells that provide the proliferative burst after PD-1 therapy. Nature 537, 417–421 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. He, R. et al. Follicular CXCR5 expressing CD8+ T cells curtail chronic viral infection. Nature 537, 412–428 (2016).

    CAS  PubMed  Google Scholar 

  17. Snell, L. M. et al. CD8+ T cell priming in established chronic viral infection preferentially directs differentiation of memory-like cells for sustained immunity. Immunity 49, 678–694.e5 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Chen, Z. et al. TCF-1-centered transcriptional network drives an effector versus exhausted CD8 T cell-fate decision. Immunity 51, 840–855.e5 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Hudson, W. H. et al. Proliferating transitory T cells with an effector-like transcriptional signature emerge from PD-1+ stem-like CD8+ T cells during chronic infection. Immunity 51, 1043–1058.e4 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Wu, T. et al. The TCF1-Bcl6 axis counteracts type I interferon to repress exhaustion and maintain T cell stemness. Sci. Immunol. 1, eaai8593 (2016).

    PubMed  PubMed Central  Google Scholar 

  21. Danilo, M., Chennupati, V., Silva, J. G., Siegert, S. & Held, W. Suppression of Tcf1 by inflammatory cytokines facilitates effector CD8 T cell differentiation. Cell Rep. 22, 2107–2117 (2018).

    CAS  PubMed  Google Scholar 

  22. 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).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Kamphorst, A. O. et al. Rescue of exhausted CD8 T cells by PD-1-targeted therapies is CD28-dependent. Science 355, 1423–1427 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Vodnala, S. K. et al. T cell stemness and dysfunction in tumors are triggered by a common mechanism. Science 363, eaau0135 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Li, H. et al. Dysfunctional CD8 T cells form a proliferative, dynamically regulated compartment within human melanoma. Cell 176, 775–789.e18 (2019).

    CAS  PubMed  Google Scholar 

  26. Philip, M. et al. Chromatin states define tumour-specific T cell dysfunction and reprogramming. Nature 545, 452–456 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Brummelman, J. et al. High-dimensional single cell analysis identifies stem-like cytotoxic CD8+ T cells infiltrating human tumors. J. Exp. Med. 215, 2520–2535 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Sade-Feldman, M. et al. Defining T cell states associated with response to checkpoint immunotherapy in melanoma. Cell 175, 998–1013.e20 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Thommen, D. S. et al. A transcriptionally and functionally distinct PD-1+ CD8+ T cell pool with predictive potential in non-small-cell lung cancer treated with PD-1 blockade. Nat. Med. 24, 994–1004 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Jansen, C. S. et al. An intra-tumoral niche maintains and differentiates stem-like CD8 T cells. Nature 576, 465–470 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Kurtulus, S. et al. Checkpoint blockade immunotherapy induces dynamic changes in PD-1 CD8+ tumor-infiltrating T cells. Immunity 50, 181–194.e6 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Siddiqui, I. et al. Intratumoral Tcf1+PD-1+CD8+T cells with stem-like properties promote tumor control in response to vaccination and checkpoint blockade immunotherapy. Immunity 50, 195–211.e10 (2019).

    CAS  PubMed  Google Scholar 

  33. Wherry, E. J. T cell exhaustion. Nat. Immunol. 12, 492–499 (2011).

    CAS  PubMed  Google Scholar 

  34. Aibar, S. et al. SCENIC: single-cell regulatory network inference and clustering. Nat. Methods 14, 1083–1086 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Zander, R. et al. CD4+ T cell help is required for the formation of a cytolytic CD8+ T cell subset that protects against chronic infection and cancer. Immunity 51, 1028–1042.e4 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Dominguez, C. X. et al. The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation in response to LCMV viral infection. J. Exp. Med. 212, 2041–2056 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Cedeno-Laurent, F. & Dimitroff, C. J. Galectin-1 research in T cell immunity: past, present and future. Clin. Immunol. 142, 107–116 (2012).

    CAS  PubMed  Google Scholar 

  38. Baeyens, A., Fang, V., Chen, C. & Schwab, S. R. Exit strategies: S1P signaling and T cell migration. Trends Immunol. 36, 778–787 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Schiavoni, G., Mattei, F. & Gabriele, L. Type I interferons as stimulators of DC-mediated cross-priming: impact on anti-tumor response. Front Immunol. 4, 483 (2013).

    PubMed  PubMed Central  Google Scholar 

  40. Trinchieri, G. Interleukin-12 and the regulation of innate resistance and adaptive immunity. Nat. Rev. Immunol. 3, 133–146 (2003).

    CAS  PubMed  Google Scholar 

  41. Kranz, L. M. et al. Systemic RNA delivery to dendritic cells exploits antiviral defence for cancer immunotherapy. Nature 534, 396–401 (2016).

    PubMed  Google Scholar 

  42. Lewis, S. M., Williams, A. & Eisenbarth, S. C. Structure and function of the immune system in the spleen. Sci. Immunol. 4, eaau6085 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Dorner, B. G. et al. Selective expression of the chemokine receptor XCR1 on cross-presenting dendritic cells determines cooperation with CD8+ T cells. Immunity 31, 823–833 (2009).

    CAS  PubMed  Google Scholar 

  44. Scott, A. C. et al. TOX is a critical regulator of tumour-specific T cell differentiation. Nature 571, 270–274 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Alfei, F. et al. TOX reinforces the phenotype and longevity of exhausted T cells in chronic viral infection. Nature 571, 265–269 (2019).

    CAS  PubMed  Google Scholar 

  46. Khan, O. et al. TOX transcriptionally and epigenetically programs CD8+ T cell exhaustion. Nature 571, 211–218 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Beltra, J.-C. et al. Developmental relationships of four exhausted CD8+ T cell subsets reveals underlying transcriptional and epigenetic landscape control mechanisms. Immunity 52, 825–841.e8 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Hailemichael, Y. et al. Persistent antigen at vaccination sites induces tumor-specific CD8+ T cell sequestration, dysfunction and deletion. Nat. Med. 19, 465–472 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Irvine, D. J., Swartz, M. A. & Szeto, G. L. Engineering synthetic vaccines using cues from natural immunity. Nat. Mater. 12, 978–990 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Merad, M., Sathe, P., Helft, J., Miller, J. & Mortha, A. The dendritic cell lineage: ontogeny and function of dendritic cells and their subsets in the steady state and the inflamed setting. Annu. Rev. Immunol. 31, 563–604 (2013).

    CAS  PubMed  Google Scholar 

  51. Hohl, T. M. et al. Inflammatory monocytes facilitate adaptive CD4 T cell responses during respiratory fungal infection. Cell Host Microbe 6, 470–481 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Stoeckius, M. et al. Cell Hashing with barcoded antibodies enables multiplexing and doublet detection for single cell genomics. Genome Biol. 19, 224 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Becht, E. et al. Dimensionality reduction for visualizing single-cell data using UMAP. Nat. Biotechnol. 37, 38–44 (2019).

    CAS  Google Scholar 

  54. Saelens, W., Cannoodt, R., Todorov, H. & Saeys, Y. A comparison of single-cell trajectory inference methods. Nat. Biotechnol. 37, 547–554 (2019).

    CAS  PubMed  Google Scholar 

  55. Trapnell, C. et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol. 32, 381–386 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411–420 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Reynoso, G. V. et al. Lymph node conduits transport virions for rapid T cell activation. Nat. Immunol. 20, 602–612 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank members of the Seder lab for scientific discussions; S. Darko, A. Ransier and D. Douek for scRNA-seq advice; and M. Dillon, G. Salbador, S. Rush, L. Gilliam, O. Hernandez, C. Chiedi and D. Scorpio of the Translational Research Program (Vaccine Research Center) for their valuable support with the animal studies. This work was supported by the Intramural Research Program of the U.S. NIH (R.A.S., H.D.H. and J.S.T.), EMBO YIP and Singapore Immunology Network core funding (F.G.).

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Authors

Contributions

F.B., A.S.I. and R.A.S. conceived and designed the experiments. F.B., R.A.R.-V., K.K.S.T. and H.Y. performed the experiments including animal work, flow cytometry and ELISA. R.A.R.-V., C-A.D. and A.K. performed the scRNA-seq data analysis with the support of M.P.M., A.J.M., J.S.T., X.M.Z. and F.G. F.B., G.V.R. and H.D.H. performed and analyzed the confocal microscopy data. J.A.H., J.P.F. and N.B. provided the mice and reagents for the experiments. G.M.L., V.L.C. and A.S.I. designed and prepared the vaccines for the experiments. F.B. and R.A.S. prepared the figures and wrote the manuscript with input from all authors.

Corresponding author

Correspondence to Robert A. Seder.

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Competing interests

G.M.L., V.L.C., A.S.I. and R.A.S. are listed as inventors on patents describing polymer-based vaccines. G.M.L., V.L.C. and A.S.I. are employees of Avidea Technologies, which is commercializing polymer-based drug delivery technologies for immunotherapeutic applications.

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Peer review information 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 Route and dose of SNP-7/8a immunization controls the magnitude and phenotype of antigen-specific CD8+ T cells.

a, Whole blood was collected on day 21 to measure the frequency of tetramer+ CD8+ T cells post boost. Bar graphs summarize the frequency of tetramer+ CD8+ T cells from blood (n = 10). b, Bar graphs summarize the frequency of IFNγ+ CD8+ T cells from blood (n = 10) on day 21. c, Bar graphs summarize the frequency of IFNγ+ CD4+ T cells from blood (n = 10). d, Bar graphs show proportions of MPEC/SLEC subpopulations in the blood (n = 10). e, Frequency of MPECs is negatively correlated to frequency of tetramer+ CD8+ T cells. f, g, Bar graphs show proportions of PD-1/Tim-3 subpopulations in the blood (n = 10) of tetramer+ cells (f) or IFNγ+ cells (g). Data are representative of two independent experiments. The bars represent the median (ac) or mean ± s.e.m. (d, f, g). Statistics were assessed by Kruskal-Wallis with Dunn’s correction for multiple comparisons (a, b, d, f, g) and Spearman correlation (e).

Extended Data Fig. 2 Intravenous administration of SNP-7/8a generates TCF1+ CD8+ T cells with anti-tumor capacity upon anti-PD-L1 treatment.

a, Tumor growth curves of mice unvaccinated (black) or vaccinated with SNP-SC (blue) or SNP-IV (red) with (dotted line) or without α-PD-L1 (solid line) (n = 10). b, Flow cytometric analysis of single cells from spleen (concatenated, n = 6) after SNP-SC (top panel) or SNP-IV (bottom panel). Cells were stained with Reps1 tetramer and other antibodies. Numbers indicate percentage of cell population within the gate. c, Mice were vaccinated with SNP-7/8a containing Reps1, E7, OVA or Trp1 antigens (n = 5). Spleens were collected 7 days post prime. d, Splenocytes were stained with tetramers specific for the respective antigens. Bar graph summarizes the frequencies of antigen-specific CD8+ T cells following SNP-SC (blue) or SNP-IV (red) (n = 5). e, Bar graph summarizes the frequencies of TCF1 subpopulations in the spleen (n = 5) after SNP-SC or SNP-IV. f, Frequency of TCF1+PD-1+ cells is negatively correlated to frequency of tetramer+ CD8+ T cells. g, Bar graph summarizes the frequencies of early effector cells (EEC, gray), memory precursor effector cells (MPEC, tan), double positive effector cells (DPEC, lilac) and short lived effector cells (SLEC, crimson) in the spleen (n = 5) after SNP-SC or SNP-IV. h, Frequency of MPEC is negatively correlated to frequency of tetramer+ CD8+ T cells. The bars represent mean ± s.e.m. (d,e,g). Statistics were assessed by Mann Whitney test (d, e, g) and Spearman correlation (f, h).

Extended Data Fig. 3 Single-cell analysis of neoAg+ CD8+ T cells by RNA sequencing identifies stem-like gene signature in SNP-IV and effector gene signature in SNP-SC cells.

a, C57BL/6 mice (n = 5) were vaccinated subcutaneously or intravenously at 8 nmol on day 0 and day 14 with SNP-7/8a containing Reps1. Spleens were collected on day 28 and tetramer+ CD8+ T cells were sorted by flow cytometry. Flow plots show gating strategy for cell sorting. b, Mice were individually labeled with distinct hashtag oligo-tagged antibodies and pooled for 10x and RNA sequencing. Individual UMAPs show gene expression of each mouse vaccinated SC (left panel) or IV (right panel). c, Bar graph summarizes the frequency of the twelve Monocle 3 clusters that are represented by each vaccination route (n = 5). d, Density plots to identify stability states corresponding to higher density areas on UMAP, based on 2D kernel density estimation. e, Expression of top differentially expressed genes (DEG) of naïve cells are presented in meaning plots. f, Heatmap summarizes the number of cells that share a clonotype based on paired alpha and beta complementarity-determining region 3 (CDR3) sequences in each individual animal. g, Bar graph shows numbers of stem-like cells (clusters 2 and 4) and effector cells (clusters 1, 3, 5, 7 and 8) in each clonotype from SC or IV vaccinated mice. Only clonotypes expressed by more than 100 cells are represented in the graphs. h, Heatmap of DEG expressed in each cluster organized along the pseudotime trajectory.

Extended Data Fig. 4 Therapeutic vaccination with SNP-IV generates neoAg-specific CD8+ T cells with superior anti-tumor capacity.

a, Tumor growth of mice treated with SNP-7/8a with (red) or without agonist (gray) (n = 10). b, Average tumor growth of SNP-IV (red), SNP-SC given twice (blue), once on day 7 (dotted blue) or twice at a lower dose (light blue) (n = 10). c, Total numbers of CD8+ T cells, CD4+ T cells and NK cells and d, frequency of tetramer+ CD8+ T cells from blood in mice treated with isotype control antibody (red) or blocking antibodies against CD8β (black), CD4 (blue) or NK1.1 (purple) as assessed by flow cytometry (n = 10). eh, Spleens and tumors were harvested on day 14 (n = 10) and day 21 (spleen, n = 5; tumor, n = 3). e, Stem-like cells (TCF1+PD-1+; dark blue), f, effector cells (Granzyme B+TCF1; orange) or g, exhausted cells (PD-1+Tim-3+) of tetramer+ cells were identified by flow cytometry. Bar graphs summarize the frequency of cells in the spleen and tumors on day 14 (filled bar) or day 21 (checked bar). h, Bar graphs summarize the frequency of Ki-67+ cells in different tissues on day 14 (red bar) or day 21 (checked bar) post SNP-IV. Data are representative of four independent experiments. Mean ± s.e.m. Statistics were assessed by two-way ANOVA with Bonferroni correction (a, b) and Mann Whitney test (eh).

Extended Data Fig. 5 Transient vaccine distribution to spleen and activation of migratory cDC1 and moDC in after SNP-IV.

a, Whole body images of mice following SNP-SC or SNP-IV with labeled vaccines. b, Confocal images of LN or spleen sections of an unvaccinated mouse. c, Confocal image of popliteal LN section post SNP-SC. Detailed overlay of additional markers. White, vaccine; red, ERTR7 (stroma); orange, CD11b (monocytes, macrophages or cDC2); CD11c (moDC or cDC). Scale bar, 200 µm or 50 µm (inset). Arrows show co-localization of vaccine and CD11b+CD11c+ cells. d, Gating strategy to identify various populations from popliteal LN and spleen after SNP-SC and SNP-IV: MoDC (red), monocytes (pink), subcapsular sinus macrophages, SCS (gray), red pulp macrophages, RPM (dark gray), cDC1 (maroon), cDC2 (coral). Kinetics of MNPs that are vaccine+ in e, popliteal LNs or f, spleens after SNP-SC or SNP-IV respectively (n = 3). g, Histograms show MFI of CD80, CD86, CCR7 and labeled vaccine in migratory or resident cDC1 or moDC in popliteal LN of naïve (gray) or SNP-SC mice after vaccination (concatenated, n = 3). h, i, Flow cytometric analysis of single cells stained with XCR1 and CD86 after gating on cDC1s in spleens or popliteal LNs of mice post SNP-IV or SNP-SC respectively (n = 3). Mean ± s.e.m. (i). Data are representative of two independent experiments.

Extended Data Fig. 6 Prolonged antigen presentation by DC drives CD8+ T cell responses after SNP-SC.

a, WT, Batf3–/– or Ccr2–/– mice (n = 10) were vaccinated SC or IV at 8 nmol on day 0 and day 14 with SNP-7/8a (Reps1). b, Total number of cDC1 in spleen and popliteal LN, or monocytes in popliteal LN (right panel) of WT, Batf3–/– or Ccr2–/– were measured (n = 3). c, Bone marrow (BM) chimeras were performed by irradiating WT CD45.1 mice and transferring BM from Ccr2DTR or WT CD45.2 mice. After 8 weeks of reconstitution, mice were treated with DT (n = 3). d, Total number of monocytes, cDC1 and cDC2 in spleen of Ccr2DTR mice 24 h after DT treatment was measured (n = 3). e, Kinetics of neoAg-specific CD8+ T cell responses after SNP-IV in blood of Ccr2DTR without DT treatment, or WT CD45.2 BM chimera with or without prior DT treatment showed similar responses (n = 5). f, Sera were collected after SNP-SC (blue) or SNP-IV (red). IL-12 (left panel) or IFN-α (right panel) were measured by ELISA (n = 3). g, Total number of monocytes and cDC1 in popliteal LN of WT, Ifnar–/– or Tlr7–/– were measured by flow cytometry. h, Histograms of EOMES gated on tetramer+ cells post SNP-SC in WT or IL12b–/– mice (n = 4). Mean ± s.e.m. (e–g). Data are representative of two independent experiments. Statistics were assessed by Mann Whitney test (d) or Kruskal-Wallis with Dunn’s correction for multiple comparisons (g).

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Baharom, F., Ramirez-Valdez, R.A., Tobin, K.K.S. et al. Intravenous nanoparticle vaccination generates stem-like TCF1+ neoantigen-specific CD8+ T cells. Nat Immunol 22, 41–52 (2021). https://doi.org/10.1038/s41590-020-00810-3

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