Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Peptide–TLR-7/8a conjugate vaccines chemically programmed for nanoparticle self-assembly enhance CD8 T-cell immunity to tumor antigens

Nature Biotechnology volume 38, pages 320–332 (2020)Cite this article

Subjects

Abstract

Personalized cancer vaccines targeting patient-specific neoantigens are a promising cancer treatment modality; however, neoantigen physicochemical variability can present challenges to manufacturing personalized cancer vaccines in an optimal format for inducing anticancer T cells. Here, we developed a vaccine platform (SNP-7/8a) based on charge-modified peptide–TLR-7/8a conjugates that are chemically programmed to self-assemble into nanoparticles of uniform size (~20 nm) irrespective of the peptide antigen composition. This approach provided precise loading of diverse peptide neoantigens linked to TLR-7/8a (adjuvant) in nanoparticles, which increased uptake by and activation of antigen-presenting cells that promote T-cell immunity. Vaccination of mice with SNP-7/8a using predicted neoantigens (n = 179) from three tumor models induced CD8 T cells against ~50% of neoantigens with high predicted MHC-I binding affinity and led to enhanced tumor clearance. SNP-7/8a delivering in silico-designed mock neoantigens also induced CD8 T cells in nonhuman primates. Altogether, SNP-7/8a is a generalizable approach for codelivering peptide antigens and adjuvants in nanoparticles for inducing anticancer T-cell immunity.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Peptide antigen physical form is a key determinant of CD8 T-cell immunogenicity.
Fig. 2: Self-assembling nanoparticles (SNP-7/8a) based on CM peptide–TLR-7/8a conjugates.
Fig. 3: Genome-wide analysis of LP neoantigen charge and hydropathy frequency distribution and formulation benchmarking studies validate the generalizability of SNP-7/8a based on CM conjugates.
Fig. 4: SNP-7/8a improves formulation consistency, pharmacokinetics and immunogenicity compared to conventional PCV approaches.
Fig. 5: SNP-7/8a expands the breadth of neoantigen-specific CD8 T-cell responses in mice and primates.
Fig. 6: The IV administration of SNP-7/8a induces CD8 T cells that mediate tumor regression.

Similar content being viewed by others

Data availability

The data that support the findings of this study are available from the corresponding authors upon request.

Code availability

Scripts used to determine hydropathy and charge frequency distribution of human neoantigens and to conduct machine learning analyses of CM conjugates are available from the corresponding authors upon request.

References

  1. Lennerz, V. et al. The response of autologous T cells to a human melanoma is dominated by mutated neoantigens. Proc. Natl Acad. Sci. USA 102, 16013–16018 (2005).

    PubMed  CAS  PubMed Central  Google Scholar 

  2. Tran, E. et al. Cancer immunotherapy based on mutation-specific CD4+ T cells in a patient with epithelial cancer. Science 344, 641–645 (2014).

    PubMed  PubMed Central  CAS  Google Scholar 

  3. Tran, E. et al. T-cell transfer therapy targeting mutant KRAS in cancer. N. Engl. J. Med. 375, 2255–2262 (2016).

    PubMed  PubMed Central  CAS  Google Scholar 

  4. Snyder, A. et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N. Engl. J. Med. 371, 2189–2199 (2014).

    PubMed  PubMed Central  Google Scholar 

  5. Rosenberg, J. E. et al. Atezolizumab in patients with locally advanced and metastatic urothelial carcinoma who have progressed following treatment with platinum-based chemotherapy: a single-arm, multicentre, phase 2 trial. Lancet 387, 1909–1920 (2016).

    PubMed  PubMed Central  CAS  Google Scholar 

  6. Sahin, U. & Tureci, O. Personalized vaccines for cancer immunotherapy. Science 359, 1355–1360 (2018).

    PubMed  CAS  Google Scholar 

  7. Hu, Z., Ott, P. A. & Wu, C. J. Towards personalized, tumour-specific, therapeutic vaccines for cancer. Nat. Rev. Immunol. 18, 168–182 (2018).

    PubMed  CAS  Google Scholar 

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

    PubMed  CAS  Google Scholar 

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

    PubMed  PubMed Central  CAS  Google Scholar 

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

    PubMed  PubMed Central  CAS  Google Scholar 

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

    PubMed  CAS  Google Scholar 

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

    PubMed  CAS  Google Scholar 

  13. Mehta, N. K., Moynihan, K. D. & Irvine, D. J. Engineering new approaches to cancer vaccines. Cancer Immunol. Res. 3, 836–843 (2015).

    PubMed  PubMed Central  CAS  Google Scholar 

  14. Bookstaver, M. L., Tsai, S. J., Bromberg, J. S. & Jewell, C. M. Improving vaccine and immunotherapy design using biomaterials. Trends Immunol. 39, 135–150 (2018).

    PubMed  CAS  Google Scholar 

  15. Scheetz, L. et al. Engineering patient-specific cancer immunotherapies. Nat. Biomed. 3, 768–782 (2019).

    CAS  Google Scholar 

  16. Ilyinskii, P. O. et al. Adjuvant-carrying synthetic vaccine particles augment the immune response to encapsulated antigen and exhibit strong local immune activation without inducing systemic cytokine release. Vaccine 32, 2882–2895 (2014).

    PubMed  PubMed Central  CAS  Google Scholar 

  17. Varypataki, E. M. et al. Synthetic long peptide-based vaccine formulations for induction of cell mediated immunity: a comparative study of cationic liposomes and PLGA nanoparticles. J. Control. Rel. 226, 98–106 (2016).

    CAS  Google Scholar 

  18. Kuai, R., Ochyl, L. J., Bahjat, K. S., Schwendeman, A. & Moon, J. J. Designer vaccine nanodiscs for personalized cancer immunotherapy. Nat. Mater. 16, 489–496 (2017).

    PubMed  CAS  Google Scholar 

  19. Scott, E. A. et al. Dendritic cell activation and T cell priming with adjuvant- and antigen-loaded oxidation-sensitive polymersomes. Biomaterials 33, 6211–6219 (2012).

    PubMed  CAS  Google Scholar 

  20. Fox, C. B. & Haensler, J. An update on safety and immunogenicity of vaccines containing emulsion-based adjuvants. Expert Rev. Vaccines 12, 747–758 (2013).

    PubMed  CAS  Google Scholar 

  21. Liu, H. et al. Structure-based programming of lymph-node targeting in molecular vaccines. Nature 507, 519–522 (2014).

    PubMed  PubMed Central  CAS  Google Scholar 

  22. Cho, H. I., Barrios, K., Lee, Y. R., Linowski, A. K. & Celis, E. BiVax: a peptide/poly-IC subunit vaccine that mimics an acute infection elicits vast and effective anti-tumor CD8 T-cell responses. Cancer Immunol. Immunother. 62, 787–799 (2013).

    PubMed  CAS  Google Scholar 

  23. Ignacio, B. J., Albin, T. J., Esser-Kahn, A. P. & Verdoes, M. Toll-like receptor agonist conjugation: a chemical perspective. Bioconjug. Chem. 29, 587–603 (2018).

    PubMed  CAS  Google Scholar 

  24. Zom, G. G. et al. Efficient induction of antitumor immunity by synthetic toll-like receptor ligand-peptide conjugates. Cancer Immunol. Res. 2, 756–764 (2014).

    PubMed  CAS  Google Scholar 

  25. Lu, B. L., Williams, G. M., Verdon, D. J., Dunbar, P. R. & Brimble, M. A. Synthesis and evaluation of novel TLR2 agonists as potential adjuvants for cancer vaccines. J. Med. Chem. https://doi.org/10.1021/acs.jmedchem.9b01044 (2019).

  26. Zhu, G. et al. Albumin/vaccine nanocomplexes that assemble in vivo for combination cancer immunotherapy. Nat. Commun. 8, 1954 (2017).

    PubMed  PubMed Central  Google Scholar 

  27. Nair-Gupta, P. et al. TLR signals induce phagosomal MHC-I delivery from the endosomal recycling compartment to allow cross-presentation. Cell 158, 506–521 (2014).

    PubMed  PubMed Central  CAS  Google Scholar 

  28. Wille-Reece, U. et al. HIV Gag protein conjugated to a Toll-like receptor 7/8 agonist improves the magnitude and quality of Th1 and CD8+ T cell responses in nonhuman primates. Proc. Natl Acad. Sci. USA 102, 15190–15194 (2005).

    PubMed  CAS  PubMed Central  Google Scholar 

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

    PubMed  CAS  Google Scholar 

  30. Kenter, G. G. et al. Vaccination against HPV-16 oncoproteins for vulvar intraepithelial neoplasia. N. Engl. J. Med. 361, 1838–1847 (2009).

    PubMed  CAS  Google Scholar 

  31. Melief, C. J. M. in Oncoimmunology: A Practical Guide for Cancer Immunotherapy (eds Zitvogel, L. & Kroemer, G.) 249–261 (Springer, 2018).

  32. Cavalli, S., Albericio, F. & Kros, A. Amphiphilic peptides and their cross-disciplinary role as building blocks for nanoscience. Chem. Soc. Rev. 39, 241–263 (2010).

    PubMed  CAS  Google Scholar 

  33. Lynn, G. M. et al. In vivo characterization of the physicochemical properties of polymer-linked TLR agonists that enhance vaccine immunogenicity. Nat. Biotechnol. 33, 1201–1210 (2015).

    PubMed  PubMed Central  CAS  Google Scholar 

  34. Lynn, G. M. et al. Impact of polymer-TLR-7/8 Agonist (Adjuvant) morphology on the potency and mechanism of CD8 T cell induction. Biomacromolecules 20, 854–870 (2019).

    PubMed  CAS  Google Scholar 

  35. Coffman, R. L., Sher, A. & Seder, R. A. Vaccine adjuvants: putting innate immunity to work. Immunity 33, 492–503 (2010).

    PubMed  PubMed Central  CAS  Google Scholar 

  36. Reddy, S. T., Rehor, A., Schmoekel, H. G., Hubbell, J. A. & Swartz, M. A. In vivo targeting of dendritic cells in lymph nodes with poly(propylene sulfide) nanoparticles. J. Controlled Rel. 112, 26–34 (2006).

    CAS  Google Scholar 

  37. Manolova, V. et al. Nanoparticles target distinct dendritic cell populations according to their size. Eur. J. Immunol. 38, 1404–1413 (2008).

    PubMed  CAS  Google Scholar 

  38. Nuhn, L. et al. pH-degradable imidazoquinoline-ligated nanogels for lymph node-focused immune activation. Proc. Natl Acad. Sci. USA 113, 8098–8103 (2016).

    PubMed  CAS  PubMed Central  Google Scholar 

  39. Shukla, N. M., Malladi, S. S., Mutz, C. A., Balakrishna, R. & David, S. A. Structure-activity relationships in human toll-like receptor 7-active imidazoquinoline analogues. J. Med. Chem. 53, 4450–4465 (2010).

    PubMed  PubMed Central  CAS  Google Scholar 

  40. Wilson, D. S. et al. Antigens reversibly conjugated to a polymeric glyco-adjuvant induce protective humoral and cellular immunity. Nat. Mater. 18, 175–185 (2019).

    PubMed  CAS  Google Scholar 

  41. Vasilakos, J. P. & Tomai, M. A. The use of Toll-like receptor 7/8 agonists as vaccine adjuvants. Expert Rev. Vaccines 12, 809–819 (2013).

    PubMed  CAS  Google Scholar 

  42. Liaw, A. & Wiener, M. Classification and regression by randomForest. R News 2, 18–22 (2002).

    Google Scholar 

  43. Choe, Y. et al. Substrate profiling of cysteine proteases using a combinatorial peptide library identifies functionally unique specificities. J. Biol. Chem. 281, 12824–12832 (2006).

    PubMed  CAS  Google Scholar 

  44. Kloetzel, P. M. Antigen processing by the proteasome. Nat. Rev. Mol. Cell Bio. 2, 179–187 (2001).

    CAS  Google Scholar 

  45. Jewett, J. C. & Bertozzi, C. R. Cu-free click cycloaddition reactions in chemical biology. Chem. Soc. Rev. 39, 1272–1279 (2010).

    PubMed  PubMed Central  CAS  Google Scholar 

  46. van Poelgeest, M. I. et al. Vaccination against oncoproteins of HPV16 for noninvasive vulvar/vaginal lesions: lesion clearance is related to the strength of the T-cell response. Clin. Cancer Res. 22, 2342–2350 (2016).

    PubMed  Google Scholar 

  47. Bijker, M. S. et al. Superior induction of anti-tumor CTL immunity by extended peptide vaccines involves prolonged, DC-focused antigen presentation. Eur. J. Immunol. 38, 1033–1042 (2008).

    PubMed  CAS  Google Scholar 

  48. Moutaftsi, M. et al. A consensus epitope prediction approach identifies the breadth of murine T(CD8+)-cell responses to vaccinia virus. Nat. Biotechnol. 24, 817–819 (2006).

    PubMed  CAS  Google Scholar 

  49. Rubinsteyn, A. et al. Computational pipeline for the PGV-001 neoantigen vaccine. Trial Front. Immunol. 8, 1807 (2017).

    PubMed  Google Scholar 

  50. Abelin, J. G. et al. Mass spectrometry profiling of HLA-associated peptidomes in mono-allelic cells enables more accurate epitope prediction. Immunity 46, 315–326 (2017).

    PubMed  PubMed Central  CAS  Google Scholar 

  51. Thompson, E. A. & Lore, K. Non-human primates as a model for understanding the mechanism of action of toll-like receptor-based vaccine adjuvants. Curr. Opin. Immunol. 47, 1–7 (2017).

    PubMed  CAS  Google Scholar 

  52. Moynihan, K. D. et al. Eradication of large established tumors in mice by combination immunotherapy that engages innate and adaptive immune responses. Nat. Med. 22, 1402–1410 (2016).

    PubMed  PubMed Central  CAS  Google Scholar 

  53. Qiu, F. et al. Poly(propylacrylic acid)-peptide nanoplexes as a platform for enhancing the immunogenicity of neoantigen cancer vaccines. Biomaterials 182, 82–91 (2018).

    PubMed  PubMed Central  CAS  Google Scholar 

  54. Li, A. W. et al. A facile approach to enhance antigen response for personalized cancer vaccination. Nat. Mater. 17, 528–534 (2018).

    PubMed  PubMed Central  CAS  Google Scholar 

  55. Wendorf, J. et al. A practical approach to the use of nanoparticles for vaccine delivery. J. Pharm. Sci. 95, 2738–2750 (2006).

    PubMed  CAS  Google Scholar 

  56. 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 

  57. Sultan, H. et al. Designing therapeutic cancer vaccines by mimicking viral infections. Cancer Immunol. Immunother. 66, 203–213 (2017).

    PubMed  CAS  Google Scholar 

  58. Lynn, G. M., Laga, R. & Jewell, C. M. Induction of anti-cancer T cell immunity by in situ vaccination using systemically administered nanomedicines. Cancer Lett. 459, 192–203 (2019).

    PubMed  CAS  PubMed Central  Google Scholar 

  59. Welters, M. J. et al. Vaccination during myeloid cell depletion by cancer chemotherapy fosters robust T cell responses. Sci. Transl. Med. 8, 334ra352 (2016).

    Google Scholar 

  60. Cadena, A. et al. Radiation and anti-cancer vaccines: a winning combination. Vaccines 6, https://doi.org/10.3390/vaccines6010009 (2018).

    PubMed Central  Google Scholar 

  61. Darrah, P. A. et al. Multifunctional TH1 cells define a correlate of vaccine-mediated protection against Leishmania major. Nat. Med. 13, 843–850 (2007).

    PubMed  CAS  Google Scholar 

  62. Quinn, K. M. et al. Comparative analysis of the magnitude, quality, phenotype, and protective capacity of simian immunodeficiency virus gag-specific CD8+ T cells following human-, simian-, and chimpanzee-derived recombinant adenoviral vector immunization. J. Immunol. 190, 2720–2735 (2013).

    PubMed  CAS  Google Scholar 

  63. Ishizuka, A. S. et al. Protection against malaria at 1 year and immune correlates following PfSPZ vaccination. Nat. Med. 22, 614–623 (2016).

    PubMed  CAS  Google Scholar 

  64. Roederer, M., Nozzi, J. L. & Nason, M. C. SPICE: exploration and analysis of post-cytometric complex multivariate datasets. Cytometry A 79, 167–174 (2011).

    PubMed  PubMed Central  Google Scholar 

  65. Kim, Y. et al. Immune epitope database analysis resource. Nucleic Acids Res. 40, W525–530 (2012).

    PubMed  PubMed Central  CAS  Google Scholar 

  66. Nielsen, M. et al. Reliable prediction of T-cell epitopes using neural networks with novel sequence representations. Protein Sci. 12, 1007–1017 (2003).

    PubMed  PubMed Central  CAS  Google Scholar 

  67. Peters, B. & Sette, A. Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method. BMC Bioinformatics 6, 132 (2005).

    PubMed  PubMed Central  Google Scholar 

  68. Aken, B. L. et al. Ensembl 2017. Nucleic Acids Res. 45, D635–D642 (2017).

    PubMed  CAS  Google Scholar 

  69. Liu, X., Wu, C., Li, C. & Boerwinkle, E. dbNSFP v3.0: A one-stop database of functional predictions and annotations for human nonsynonymous and splice-site SNVs. Hum. Mutat. 37, 235–241 (2016).

    PubMed  PubMed Central  Google Scholar 

  70. Kyte, J. & Doolittle, R. F. A simple method for displaying the hydropathic character of a protein. J. Mol. Biol. 157, 105–132 (1982).

    PubMed  CAS  Google Scholar 

  71. Tate, J. G. et al. COSMIC: the catalogue of somatic mutations in cancer. Nucleic Acids Res. 47, D941–D947 (2018).

    PubMed Central  Google Scholar 

Download references

Acknowledgements

We acknowledge M. Dillon, G. Salbador, L. Gilliam, S. Rush, M. Carballo, E. McCarthy, J. Noor, C. Chiedi, J.P. Todd and D. Scorpio of the Translational Research Program (VRC) as well as B. Klaunberg and V. Diaz at the Mouse Imaging Facility (MIF, NIH) for their valuable support with the animal studies; T. Abram and A. Mullen (VRC) for administrative support; S. McWhirter and C. Ndubaku (Aduro BioTech) for providing CDN-based reagents; Cytometry Platform and the Animal facilities of the Institut Curie; NSERM; Agence Nationale de la Recherche (ANR-11-LABX-0043 and ANR-10-IDEX-0001-02 PSL); Institut Curie (CIC IGR-Curie 1428); La Ligue Nationale Contre le Cancer program; SiRIC grant no. INCa-DGOS-12554; the Czech Science Foundation project 19-08176S; and the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Program II (project BIOCEV-FAR LQ1604). This work was supported by the Intramural Research Program of the US National Institutes of Health as well as NIH grant no. R01EB027143. C.M.J. is an employee of the VA Maryland Health Care System. The views reported in this paper do not reflect the views of the Department of Veterans’ Affairs or the United States Government.

Author information

Author notes

  1. Brian J. Francica

    Present address: Tempest Therapeutics, San Francisco, CA, USA

  2. Joshua D. Bernstock

    Present address: Department of Neurosurgery, Brigham and Women’s Hospital, Harvard University, Boston, MA, USA

  3. Charles G. Drake

    Present address: Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA

  4. These authors contributed equally: Geoffrey M. Lynn, Christine Sedlik.

  5. These authors jointly supervised this work: Andrew S. Ishizuka, Robert A. Seder.

Authors and Affiliations

  1. Vaccine Research Center (VRC), National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, USA

    Geoffrey M. Lynn, Faezzah Baharom, Ramiro A. Ramirez-Valdez, Kennedy Tobin, Neeha Zaidi, Nicolas J. Blobel, Justin Cheung, Hidehiro Yamane, Joseph R. Francica, Andrew S. Ishizuka & Robert A. Seder

  2. Avidea Technologies, Inc, Baltimore, MD, USA

    Geoffrey M. Lynn, Yaling Zhu, Vincent L. Coble, Sarah R. Nichols, Yaakov Itzkowitz, Brennan Decker, Mateusz Maciejewski, Joshua D. Bernstock & Andrew S. Ishizuka

  3. Institut Curie, PSL Research University, Paris, France

    Christine Sedlik, Jordan Denizeau, Philippe de la Rochere, Olivier Lantz & Eliane Piaggio

  4. Centre d’Investigation Clinique Biothérapie, Institut Curie, Paris, France

    Christine Sedlik, Jordan Denizeau, Philippe de la Rochere, Olivier Lantz & Eliane Piaggio

  5. Fischell Department of Bioengineering, University of Maryland, College Park, MD, USA

    Joshua M. Gammon & Christopher M. Jewell

  6. Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA

    Brian J. Francica & Charles G. Drake

  7. Biological Imaging Section, Research Technologies Branch, NIAID, NIH, Bethesda, MD, USA

    Margery G. Smelkinson

  8. Institute of Macromolecular Chemistry, Academy of Sciences of the Czech Republic, Prague, Czech Republic

    Richard Laga

  9. Department of Oncology, University of Oxford, Oxford, UK

    Leonard W. Seymour

Authors
  1. Geoffrey M. Lynn
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christine Sedlik
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Faezzah Baharom
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yaling Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ramiro A. Ramirez-Valdez
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Vincent L. Coble
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kennedy Tobin
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Sarah R. Nichols
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Yaakov Itzkowitz
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Neeha Zaidi
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Joshua M. Gammon
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Nicolas J. Blobel
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Jordan Denizeau
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Philippe de la Rochere
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Brian J. Francica
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Brennan Decker
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Mateusz Maciejewski
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Justin Cheung
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Hidehiro Yamane
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Margery G. Smelkinson
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Joseph R. Francica
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Richard Laga
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Joshua D. Bernstock
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Leonard W. Seymour
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Charles G. Drake
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Christopher M. Jewell
    View author publications

    You can also search for this author in PubMed Google Scholar

  27. Olivier Lantz
    View author publications

    You can also search for this author in PubMed Google Scholar

  28. Eliane Piaggio
    View author publications

    You can also search for this author in PubMed Google Scholar

  29. Andrew S. Ishizuka
    View author publications

    You can also search for this author in PubMed Google Scholar

  30. Robert A. Seder
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

G.M.L., C.S., J.D.B., O.L., E.P., A.S.I. and R.A.S. contributed to planning experiments, interpreting the data and writing the manuscript. G.M.L., Y.Z., V.L.C., S.R.N., Y.I., R.L. and A.S.I. planned and carried out the synthesis, purification, and characterization of materials described in the manuscript. J.M.G. and C.M.J. produced the PLGA particles and liposomes. G.M.L., C.S., F.B., R.A.R.-V., K.T., N.Z., N.J.B., H.Y., J.D., P.R., B.J.F., J.C., J.R.F. and A.S.I. planned and conducted many of the biological studies. B.D. conducted bioinformatics analyses, including identification of the rhesus macaque ‘mock’ neoantigens. M.G.S. conducted brightfield imaging. M.M. conducted machine learning analysis. L.W.S., C.G.D., O.L., E.P., A.S.I. and R.A.S. are lead investigators who advised the studies.

Corresponding authors

Correspondence to Geoffrey M. Lynn or Robert A. Seder.

Ethics declarations

Competing interests

G.M.L., Y.Z., V.L.C., R.L., L.W.S., A.S.I. and R.A.S. are listed as inventors on patents describing polymer-based vaccines. G.M.L., Y.Z., V.L.C., S.R.N., Y.I., B.D., J.D.B. and A.S.I. are employees/consultants of Avidea Technologies, Inc., which is commercializing polymer-based drug delivery technologies for immunotherapeutic applications. C.M.J. has an equity position in Cellth Systems, LLC. J.D.B. is a member of the POCKiT Diagnostics Board of Scientific Advisors.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Integrated supplementary information

Supplementary Figure 1 Efficiency of CD8 T cell induction depends on LP physical form.

(a) Chemical structures of both the imidazoquinoline-based Toll-like receptor-7 & -8 agonist (TLR-7/8a) that was linked to the SIINFEKL LPs (LSS-7/8a and LSP-7/8a) and the particle-forming polymer-TLR-7/8a (PP-7/8a). (b–d) C57BL/6 mice (n = 5 per group) were injected subcutaneously with LSS or LSP admixed with either PP-7/8a, CpG or polyICLC at days 0 and 14. (b) Tetramer+ CD8 T cell responses were assessed by flow cytometry on day 28 for each adjuvant. (c) Responses from panel (b) grouped according to antigen physical form (LSS or LSP). (d) C57BL/6 mice vaccinated with either LSS or LSP mixed with adjuvant (n = 15 per group) were challenged with B16.OVA on day 42 and assessed for survival. Data on log scale are reported as geometric mean with 95% c.i. Comparison of multiple groups for statistical significance was determined using Kruskal-Wallis with Dunn’s correction; statistical significance of survival was determined using Log-rank test; ns = not significant, *P < 0.05, **P ≤ 0.01.

Supplementary Figure 2 Particulate LPs prolong antigen presentation in vivo leading to higher frequencies of antigen-specific CD8 T cells.

(a–f) Three separate cohorts of C57BL/6 mice (n = 5–8 per group per time point) were injected subcutaneously with LSS or LSP, either admixed with PP-7/8a or covalently linked to TLR-7/8a (LSS-7/8a and LSP-7/8a). CFSE-labeled OT-I cells were then administered intravenously to each cohort on day 0, 3 or 7. Six days after receiving the OT-I cells, the percent of OT-I cells that fully divided (a–c) and total number of OT-I cells (d–f) were determined by flow cytometry. Data on linear scale are reported as mean ± s.e.m; data on log scale are reported as geometric mean with 95% c.i. Comparison of multiple groups for statistical significance was determined using Kruskal-Wallis with Dunn’s correction; ns = not significant, *P < 0.05, **P ≤ 0.01.

Supplementary Figure 3 Particulate but not soluble neoantigen LPs induce CD8 T cell responses.

(a–f) The amino acid residues flanking the minimal epitopes of Reps1 (AQLANDVVL) and Irgq (AALLNSAVL) neoantigens were exchanged to generate Reps1 and Irgq chimers. (a) Turbidity, as measured by the absorbance (OD, arbitrary units) at 490 nm, was used to assess whether different LPs aggregate (OD > 0.05) or are soluble (OD < 0.05) in aqueous solution. (b–f) Native and chimeric forms of Reps1 and Irgq LP neoantigens were admixed with different adjuvants (i.e. PP-7/8a, CpG or polyICLC) and subcutaneously administered to C57BL/6 mice (n = 5–10 mice per group) on days 0 and 14 and CD8 T cell responses were assessed by either (b–d) dextramer staining (AQLANDVVL-H-2Db or AALLNSAVL-H-2Db) or (e,f) IFN-γ intracellular cytokine staining of blood on day 28. Data on linear scale are reported as mean ± s.e.m; data on log scale are reported as geometric mean with 95% c.i. Comparison of multiple groups for statistical significance was determined using Kruskal-Wallis with Dunn’s correction; Mann-Whitney test was used to assess significance for comparison of compiled responses in figure panels c–f; ns = not significant, *P < 0.05, **P ≤ 0.01.

Supplementary Figure 4 Effect of enzyme degradable linker composition on antigen presentation and CD8 T cell priming.

(a, b) An MHC-I (H-2Db)-restricted epitope (SSPYSLYHL) from the MC38 tumor cell line-derived neoantigen, Cpne1, was linked at the N-terminus to a charge modifying group either directly or through enzyme (cathepsin, or cathepsin and proteasome) degradable peptide linkers, and at the C-terminus to an oligo-7/8a either directly or through enzyme (cathepsin, or cathepsin and proteasome) degradable linkers. (b) C57BL/6 mice (n = 20 per group) were injected subcutaneously with Cpne1 (SSPYSLYHL) as CM conjugates of varying degradable linker composition on day 0 and CD8 T cell responses from blood were assessed by intracellular cytokine staining on day 7. Addition of cathepsin degradable linkers significantly increased the CD8 T cell response, which was not further increased with addition of linkers that are also recognized by the proteasome. (c–e) An MHC-I (H-2Db)-restricted epitope (ASMTNMELM) from the MC38 tumor cell line neoantigen, Adpgk, was prepared as either a CM conjugate with a cathepsin degradable linker (SLVR) at the N-terminus or at both the N- and C-termini; alternatively, the cathepsin degradable linker was replaced with a non-specific sequence (GGGG) or with D amino acids (dSLVR). (d) In vitro antigen presentation as assessed by titrating the indicated CM conjugates with ASMTNMELM-specific CD8 T cells and measuring the IFN-γ response by intracellular cytokine staining. (e) In vivo priming of CD8 T cells by the indicated CM conjugates. Note: use of the D-chirality amino acid (i.e. dSLVR) abrogates activity. Data on log scale are reported as geometric mean with 95% c.i. Comparison of multiple groups for statistical significance was determined using Kruskal-Wallis with Dunn’s correction; ns = not significant, *P < 0.05, **P ≤ 0.01.

Supplementary Figure 5 Impact of the number and type of TLR-7/8a on T cell responses.

(a) Chemical structures and in vitro dose response curves for the conjugatable imidazoquinoline TLR-7/8 agonists “2B” (EC50 = 1.28 μM) and “2BXy” (EC50 = 0.02 μM). Potency was determined via a colorimetric reporter assay by incubating different concentrations of TLR-7/8a with HEK293 cells expressing human TLR-7 and a reporter enzyme, SEAP (InvivoGen cat #hkb-htlr7). R848 (“Resiquimod”) is shown for comparison. (b,c) C57BL/6 mice (n = 5 per group) were injected subcutaneously with either (b) the Adpgk minimal epitope (ASMTNMELM) or (c) a model CD4 T cell epitope (AKFVAAWTLKAAA, “PADRE”) as charge-modified (CM) conjugates comprising different compositions of oligo-7/8a. Blood was collected on day 22 and assessed for IFN-γ-producing T cells by intracellular cytokine staining. Data on log scale are reported as geometric mean with 95% c.i.

Supplementary Figure 6 Impact of net charge and vaccine regimen on CD8 T cell responses.

(a–c) An MHC-I (H-2Db)-restricted epitope (ASMTNMELM) from the MC38 tumor cell line derived neoantigen, Adpgk, was prepared as a charged-modified (CM) conjugate with either net positive (+6) or net negative (–7) charge. The positive and negatively charged CM conjugates were administered subcutaneously to mice (n = 3 per group per dose) at days 0, 14 and 28 at doses of either (a) 0.25 nmol, (b) 1 nmol or (c) 4 nmol per vaccination, and CD8 T cell responses from blood were evaluated by intracellular cytokine staining at the time points shown. (d) The LP neoantigen Adpgk as SNP-7/8a based on a CM conjugate with net positive charge was subcutaneously administered at 4 nmol per dose to C57BL/6 mice (n = 3 per group) either once (1 vaccination) or 3 times with either 3, 7 or 14 days between immunizations. CD8 T cell responses were assessed by intracellular cytokine staining at the time points shown. Data are reported as mean ± s.e.m.

Supplementary Figure 7 Manufacturing workflow for PCVs based on SNP-7/8a.

(a) Schematic of the manufacturing workflow for production of a PCV. Each CM peptide comprises a patient-specific neoantigen and is produced on-demand by solid-phase peptide synthesis. The hydrophobic block (oligo-7/8a) is the same for each patient and manufactured in bulk. Each patient-specific CM peptide is reacted with the oligo-7/8a in DMSO at room temperature for 16 hours to yield a CM conjugate product solution. The product solution is sterile filtered to produce a sterile product solution. Addition of aqueous buffer to the sterile product solution results in the CM conjugates self-assembling into nanoparticles. (b) Representative HPLC chromatograms of a CM peptide and oligo-7/8a. Representative HPLC chromatograms of a product solution (c) and sterile product solution (d). Overlaying the chromatogram prior to and after sterile filtration indicates that no significant change in composition has occurred. (e) SNP-7/8a particle size over time following addition of PBS, pH 7.4 to a sterile product solution comprising a CM conjugate.

Supplementary Figure 8 SNP-7/8a can accommodate multiple CM conjugates comprising predicted neoantigens with variable charge and hydropathy.

(a) Charge and (b) grand average of hydropathy (GRAVY) distribution plots for n = 690 LP neoantigens derived from 3 mouse tumor models (B16-F10, MC38 and SB-3123). (c) Table listing the properties of 20 different predicted neoantigens that were synthesized as CM conjugates and then mixed at equimolar ratios in DMSO followed by addition of PBS buffer to generate SNP-7/8a consisting of 20 different CM conjugates. (d) Particle size and turbidity of SNP-7/8a consisting of different CM conjugate compositions. The bar charts show the particle size (gray bars; left axis) and turbidity (black bars; right axis) of 12 SNP-7/8a formulations, each containing a unique set of 5 different CM conjugates. The properties of the CM conjugates are listed in the accompanying table. Each column lists the charge and GRAVY characteristics of the neoantigens comprising each of the 5 CM conjugates as well as the turbidity measured for the 5 CM conjugates when each are individually resuspended in PBS. For example, column 1 shows the size and turbidity of a particle (SNP-7/8a) comprised of 5 different CM conjugates; the 5 CM conjugates (1 through 5) are comprised of neoantigens with a net charge of –6, –4, 0, +1, and –1 and GRAVY of 0.02, –0.90, –0.13, –0.16, 0.03; and, those CM conjugates (1 through 5) each have turbidity < 0.04. In columns 10–12, CM conjugates that individually are prone to form aggregates incorporate into stable nanoparticle micelles when formulated with other CM conjugates that individually form stable nanoparticle micelles. (e) Different predicted neoantigens (Reps1, M39 and Cpne1) were formulated as either PLGA microparticles, liposomal particles or SNP-7/8a, and the sizes of the particulate formulations were assessed by dynamic light scattering. Data are reported as mean ± s.e.m.

Supplementary Figure 9 Anti-tumor efficacy of SNP-7/8a delivering MC38 neoantigens.

(a) C57BL/6 mice (n = 10 per group) were vaccinated subcutaneously with SNP-7/8a including different MC38 LP neoantigens or vehicle control (10% DMSO in PBS) on days 0 and 14. On day 28, mice were subcutaneously implanted with 1.0 × 105 MC38 tumor cells. Tumor growth curves (left) and area under the curve through day 20 (right) are shown. Data on linear scale are reported as mean ± s.e.m. Statistical significance was determined using Kruskal-Wallis with Dunn’s correction; ns = not significant, *P < 0.05, **P ≤ 0.01.

Supplementary Figure 10 SNP-7/8a leads to higher magnitude CD8 T cell responses and more antigen uptake by lymph node APCs than MP-7/8a.

(a, b) C57BL/6 mice (n = 5 per group) were injected subcutaneously with either (a) Cpne1 LP or (b) Adpgk LP as MP-7/8a or SNP-7/8a on days 0, 14 and 28 and CD8 T cell responses were assessed by intracellular cytokine staining at various time points. (c–f) C57BL/6 mice (n = 5 per group per time point) were immunized with AF647-labeled Adpgk Min either as the soluble peptide admixed with MP-7/8a containing an irrelevant antigen, as MP-7/8a or as SNP-7/8a. Lymph nodes draining the site of immunization were collected at serial time points and assessed for (c) total tissue fluorescence (peptide quantity), (d) antigen uptake by APCs and (e) IL-12p40 cytokine production. (f) CD8 T cell responses from blood were assessed by intracellular cytokine staining on day 14. Data on log scale are reported as geometric mean with 95% c.i., except line graphs are reported as mean ± s.e.m. Statistical significance was determined using ANOVA with Bonferroni correction; ns = not significant, *P < 0.05, **P ≤ 0.01.

Supplementary Figure 11 Effect of peptide antigen length on CD8 and CD4 T cell responses.

(a, b) C57BL/6 mice (n = 5) were vaccinated subcutaneously on days 0 and 14 with either the short or long (Min or LP) version of one of 7 different MC38 neoantigens formulated as SNP-7/8a. (a) CD8 and (b) CD4 T cell responses from blood were determined by intracellular cytokine staining on day 21. (c–e) C57BL/6 mice (n = 5) were vaccinated subcutaneously on days 0 and 14 with either the short or long (Min or LP) version of Irgq, Aatf, Reps1 and Dpagt1, wherein the LP versions contain a CD4 epitope that results in high, moderate, low or no detectable CD4 T cell responses, respectively. (c) CD8 T cell responses and (d) CD4 T cell responses were assessed by intracellular cytokine staining on days 7, 21 and 42. While CD4 T cell responses are detected in the LP version for certain antigens, no differences in the magnitude or kinetic of CD8 T responses were observed between groups of mice immunized with the LP or Min. (e) Evaluation of the phenotype of CD8 T cell responses as assessed by the % of antigen-specific (IFN-γ+) CD8 T cells that display a memory precursor effector cell (MPEC) phenotype (KLRG1lowCD127high) shows that there are no differences in the proportion of memory and effector CD8 T cells elicited by the LP as compared with the Min when delivered as SNP-7/8a. Data on log scale are reported as geometric mean with 95% c.i., except data on line graphs are reported as mean ± s.e.m. Statistical significance was determined using two-way ANOVA with Bonferroni correction; ns = not significant, *P < 0.05, **P ≤ 0.01.

Supplementary Figure 12 CD8 T cell responses to individual antigens following SNP-7/8a vaccination in primates.

(a, b) Paired pre- and post-vaccine PBMC samples were stimulated with each individual peptide antigen included in the SNP-7/8a vaccine or a control antigen (specifically, a mock neoantigen that had not been included in the vaccine) without prior ex vivo expansion and assessed by intracellular cytokine staining. Antigen-specific CD8 T cell responses to each antigen are reported for (a) pre-vaccine PBMC and (b) post-vaccine PBMC after subtracting the response to the control antigen (the assay background). An IFN-γ response threshold of 0.03% is shown by the dotted line. No rhesus had a response to any antigen above the threshold in the pre-vaccine samples. In the post-vaccine samples, the number of antigens to which the rhesus had a CD8 T cell response above the threshold were 5, 4, 5, and 2 for rhesus #1 through #4, respectively.

Supplementary Figure 13 Effect of checkpoint inhibitor on therapeutic efficacy with SNP-7/8a.

(a) C57BL/6 mice (n = 20 per group) implanted with 1.0 × 105 TC-1 tumor cells were vaccinated subcutaneously (SC) either with vehicle control (10% DMSO in PBS), SNP-7/8a delivering E7 from human papilloma virus or an irrelevant antigen (Adpgk neoantigen from MC38) as an inflammation control on days 5 and 10 after implantation. Half the animals from each group (n = 10) were treated with 200 μg anti-PD-L1 administered intraperitoneal (IP) on days 7 and 12 after implantation. CD8 T cell responses on day 12 (left) and tumor growth curves (right) are shown. (b) C57BL/6 mice (n = 20 per group) implanted with 1.0 × 105 B16-F10 tumor cells were vaccinated SC either with vehicle control (10% DMSO in PBS) or SNP-7/8a delivering Trp1 self-antigen on days 3 and 10 after implantation. Half the animals from each group (n = 10) were treated with 200 μg anti-PD-L1 administered IP concomitant with vaccination on days 3 and 10. CD8 T cell responses on day 12 (left) and tumor growth curves (right) are shown. Data on log scale are reported as geometric mean with 95% c.i.; data on linear scale are reported as mean ± s.e.m. Statistical significance was determined using one-way or two-way ANOVA with Bonferroni correction; ns = not significant, *P < 0.05, **P ≤ 0.01.

Supplementary Figure 14 IV administration of SNP-7/8a mediates tumor regression.

(a) C57BL/6 mice (n = 10 per group) implanted subcutaneously with 1.0 × 105 B16-F10 tumor cells were treated with either SNP-7/8a delivering the self-antigen Trp1 by the SC or IV route, or vehicle control (DMSO/PBS) by the IV route, which were each given along with anti-PD-L1 by the IP route on days 3, 10 and 17. Tumor growth was monitored at various time points. (b) C57BL/6 mice (n = 10 per group) implanted subcutaneously with 1.0 × 105 TC-1 tumor cells were treated with either vehicle control (DMSO/PBS) by the IV route, or SNP-7/8a delivering the virus-associated tumor antigen HPV E7 or an irrelevant antigen (Adpgk neoantigen from MC38) as an inflammation control (“control SNP-7/8a”) by the SC or IV route. Treatments were given along with anti-PD-L1 delivered by the IP route on days 7 and 14. Tumor growth was monitored at various time points. Statistical significance was determined by log-rank test.

Supplementary Figure 15 Immunogenicity and anti-tumor efficacy of SNP-7/8a.

(a) Plot of the predicted MHC-I binding affinity (IEDB consensus, any length, H2-Kb or H2-Db) versus CD8 T cell response for B16-F10 neoantigens (n = 47) included in PCVs based on LP + polyIC or RNA as described (see: Kreiter S, et al. Nature, 520; 692–696, 2015). (b) 24 of the predicted neoantigens from panel (a) with moderate to high MHC-I binding affinity (IEDB consensus score < 1.5) were screened for immunogenicity in vivo using SNP-7/8a and the relationship between binding affinity and immunogenicity is shown. (c) C57BL/6 mice (n = 10 per group) implanted subcutaneously with 1 × 105 B16-F10 cells were treated with vehicle control (DMSO/PBS) or SNP-7/8a containing either one of 4 B16-F10 LP neoantigens (M01, M07, M21 or M39), Trp1 self-antigen (positive control) or an irrelevant neoantigen (Med12 neoantigen from MC38) as an inflammation control by the IV route on days 1 and 8. All animals also received 200 μg anti-PD-L1 by the IP route on the days indicated. (c) Area under the curve of tumor growth is shown for animals vaccinated with SNP-7/8a delivering the indicated antigens. (d) C57BL/6 mice (n = 10 per group) implanted subcutaneously with 1 × 105 B16-F10 cells were treated with vehicle control (DMSO/PBS) or M39 SNP-7/8a by the IV route on days 1 and 8. An additional group of mice (n = 10) treated with M39 SNP-7/8a was conditioned with CD8 depleting antibody (250 μg IP) prior to treatment. All animals also received 200 μg anti-PD-L1 by the IP route on the days indicated. Tumor growth curves are shown (e) C57BL/6 mice (n = 10 per group) implanted subcutaneously with 1.0 × 105 B16-F10 tumor cells were treated with either the M39 neoantigen as LP admixed with polyIC by the SC route, M39 as SNP-7/8a by the IV route, an irrelevant neoantigen (Adpgk) as SNP-7/8a (“control SNP-7/8a”) by the IV route or vehicle control (DMSO/PBS) by the IV route. Treatments were given along with anti-PD-L1 delivered by the IP route on days 1,8 and 15. Tumor growth was monitored at various time points. (f) C57BL/6 mice (n = 10 per group) implanted subcutaneously with 1.0 × 105 TC-1 tumor cells were treated with either the virus-associated tumor antigen HPV E6 as an LP admixed with polyICLC by the SC route, E6 as SNP-7/8a by the IV route, an irrelevant neoantigen (Adpgk) as SNP-7/8a by the IV route (“control SNP-7/8a”); or, vehicle control (DMSO/PBS) by the IV route. Treatments were given along with anti-PD-L1 delivered by the IP route on days 7 and 14. Tumor growth was monitored at various time points and survival curves are shown. Data on linear scale are reported as mean ± s.e.m. Statistical significance was determined using Kruskal-Wallis with Dunn’s correction (c), two-way ANOVA with Bonferroni correction (d) or log-rank test (e,f); ns = not significant, *P < 0.05, **P ≤ 0.01.

Supplementary information

Supplementary information

Supplementary Figs. 1–15, Tables 1 and 2 and Notes.

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lynn, G.M., Sedlik, C., Baharom, F. 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). https://doi.org/10.1038/s41587-019-0390-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41587-019-0390-x

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer