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. 2021 Jan 6;8(5):2002577.
doi: 10.1002/advs.202002577. eCollection 2021 Mar.

Modularly Programmable Nanoparticle Vaccine Based on Polyethyleneimine for Personalized Cancer Immunotherapy

Jutaek Nam  1 , Sejin Son  1 , Kyung Soo Park  2 , James J Moon  3
Affiliations

Modularly Programmable Nanoparticle Vaccine Based on Polyethyleneimine for Personalized Cancer Immunotherapy

Jutaek Nam et al. Adv Sci (Weinh). .

Abstract

Nanoparticles (NPs) can serve as a promising vaccine delivery platform for improving pharmacological property and codelivery of antigens and adjuvants. However, NP-based vaccines are generally associated with complex synthesis and postmodification procedures, which pose technical and manufacturing challenges for tailor-made vaccine production. Here, modularly programmed, polyethyleneimine (PEI)-based NP vaccines are reported for simple production of personalized cancer vaccines. Briefly, PEI is conjugated with neoantigens by facile coupling chemistry, followed by electrostatic assembly with CpG adjuvants, leading to the self-assembly of nontoxic, sub-50 nm PEI NPs. Importantly, PEI NPs promote activation and antigen cross-presentation of antigen-presenting cells and cross-priming of neoantigen-specific CD8+ T cells. Surprisingly, after only a single intratumoral injection, PEI NPs with optimal PEGylation elicit as high as ≈30% neoantigen-specific CD8+ T cell response in the systemic circulation and sustain elevated CD8+ T cell response over 3 weeks. PEI-based nanovaccines exert potent antitumor efficacy against pre-established local tumors as well as highly aggressive metastatic tumors. PEI engineering for modular incorporation of neoantigens and adjuvants offers a promising strategy for rapid and facile production of personalized cancer vaccines.

Keywords: cancer vaccines; immunotherapy; nanoparticles; neoantigens.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Schematic illustration of PEI‐based nanovaccine. PEI was sequentially modified with PEG and neoantigens via amide and disulfide bond, respectively. Then, polycationic PEI conjugates were self‐assembled with polyanionic CpG adjuvants through electrostatic interaction to form neoantigen nanovaccine. Diverse types of antigens and adjuvants can be incorporated into the complex allowing flexible and modular design for personalized cancer vaccines. The nanovaccine can increase the cellular uptake of neoantigens and adjuvants by APCs and promote activation and antigen cross‐presentation to effectively cross‐prime antigen‐specific T cells for robust antitumor immunity and antitumor efficacy.
Figure 2
Figure 2
Synthesis and characterization of PEI conjugates and CpG‐containing nanovaccines. A–D) GPC spectra of A) PEI–Adpgk conjugates and C) PEG–PEI–Adpgk conjugates measured before and after 10 × 10−3 m DTT treatment, and B, D) their dose‐dependent cytotoxicity toward BMDCs assessed after 24 h incubation. The number denotes number of conjugated Adpgk per PEI for PEI–Adpgk conjugates and number of grafted PEG per PEI for PEG‐PEI–Adpgk conjugates. E) Zeta potential and F) hydrodynamic size of nanovaccines formed by adding CpG to PEG–PEI–Adpgk conjugates with varying weight ratio. G) TEM images of nanovaccines formulated at a weight ratio of 2 taken after 2% uranyl acetate staining for visualization of their morphology. Scale bars = 200 nm. The data show mean  ±  s.d. (n  =  5). **P  <  0.01 and ****P  <  0.0001, analyzed by two‐way ANOVA with Bonferroni multiple comparisons post‐test.
Figure 3
Figure 3
Uptake of nanovaccines by BMDCs. A–C) Time lapse uptake of PEG–PEI–Adpgk conjugates in the form of A) free polymer or B) their nanovaccines formulated by adding CpG measured over 3 days, and C) corresponding fold change in the uptake of PEG–PEI–Adpgk conjugates after CpG addition. D) Time lapse uptake of CpG and E) corresponding fold change in CpG uptake by nanovaccines, compared to soluble Adpgk + CpG. F) Confocal microscope images of BMDCs after 24 h incubation with soluble Adpgk + CpG or nanovaccine samples. Scale bar = 50 µm. The data show mean  ±  s.d. (n  =  6). ***P  <  0.001 and ****P  <  0.0001, analyzed by two‐way ANOVA with Bonferroni multiple comparisons post‐test.
Figure 4
Figure 4
Induction of TLR9‐mediated immune stimulation and antigen cross‐presentation by nanovaccines. A,B) HEK‐Blue TLR9 cells were incubated with A) free polymer form of PEG–PEI–Adpgk conjugates or B) their nanovaccines with CpG, and induction of TLR9 signaling cascade was quantified using 650 nm absorbance. Upregulation of C) CD40 and D) SIINFEKL/H‐2Kb expression by BMDCs after 24 h incubation with SIINFEKL + CpG or SIINFEKL nanovaccines. E) Confocal microscope images of BMDCs incubated with SIINFEKL + CpG or PEG(15) NP of SIINFEKL nanovaccine. Scale bar = 50 µm. The data show mean  ±  s.d. (n  =  6). *P  <  0.05, ***P  <  0.001, and ****P  <  0.0001, analyzed by one‐way ANOVA with Bonferroni multiple comparisons post‐test.
Figure 5
Figure 5
Tumor retention of the nanovaccine and immune activation in tumor‐draining LNs. A) Tumor retention of vaccines composed of various forms of Adpgk peptides and AF647‐CpG was visualized using ex vivo IVIS imaging after 24 h of intratumoral injection. Quantitative analysis of B) CpG+ cells and C) corresponding MFI of CpG in CpG+ cells in tumors. D–K) Tumor‐draining inguinal LNs were analyzed for the number and activation of D‐G) DCs and H–K) macrophages. The data show mean  ±  s.d. (n  =  5). *P  <  0.05, **P  <  0.01, ***P  <  0.001, and ****P  <  0.0001, analyzed by one‐way ANOVA with Bonferroni multiple comparisons post‐test.
Figure 6
Figure 6
Antitumor immune response of nanovaccine against pre‐established local tumors. A) Schematic of treatment regimen. B,C) Adpgk‐specific CD8+ T cells in blood were analyzed after B) intratumoral injection of various vaccine formulations or C) administration of Adpgk + CpG versus PEG(15) NP via different routes of vaccination. MC38 tumor‐bearing mice were treated by intratumoral administration of Adpgk + CpG versus PEG(15) NP on day 9, and D) tumor growth and E) animal survival were monitored. F) Adpgk‐specific CD8+ T cells in blood observed over 3 weeks after single immunization. Tumor microenvironment analysis for the frequency of G) CD8+ T cells and H) Adpgk‐specific CD8+ T cells, mean fluorescence intensity (MFI) of I) perforin and J) granzyme in total CD8+ T cells. The data show mean  ±  s.d. (n  =  5). *P  <  0.05, **P  <  0.01, ***P  <  0.001, and ****P  <  0.0001, analyzed by one‐way (B,C,G,H,I,J) or two‐way (D,F) ANOVA with Bonferroni multiple comparisons post‐test, or by E) log‐rank (Mantel–Cox) test.
Figure 7
Figure 7
Antitumor immune response of nanovaccine against highly aggressive, disseminated B16F10 melanoma. A) Schematic of treatment regimen. B) Tumor growth curves of subcutaneous flank B16F10 tumors. C) Representative images of lungs and ELISPOT wells. ELISPOT assay was performed after restimulation of splenocytes with M27 or M30. Quantitative analysis of D) lung tumor nodules and ELISPOT counts against E) M27 or F) M30 performed on day 17. G) Weight and images of spleens for assessement of splenomegaly. Scale bars = 1 cm. The data show mean  ±  s.d. (n  =  8). *P  <  0.05, **P <  0.01, and ***P  <  0.001, analyzed by D–G) one‐way or B) two‐way ANOVA with Bonferroni multiple comparisons post‐test.
Figure 8
Figure 8
Summary of the impact of PEGylation on PEG‐PEI‐Ag formulation, in vitro DC activation, and in vivo immune activation.
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References

    1. van der Burg S. H., Arens R., Ossendorp F., van Hall T., Melief C. J. M., Nat. Rev. Cancer 2016, 16, 219. - PubMed
    1. a) Schumacher T. N., Schreiber R. D., Science 2015, 348, 69; - PubMed
    2. b) Scheetz L., Park K. S., Li Q., Lowenstein P. R., Castro M. G., Schwendeman A., Moon J. J., Nat. Biomed. Eng. 2019, 3, 768. - PMC - PubMed
    1. a) Kreiter S., Vormehr M., van de Roemer N., Diken M., Löwer M., Diekmann J., Boegel S., Schrörs B., Vascotto F., Castle J. C., Tadmor A. D., Schoenberger S. P., Huber C., Türeci Ö., Sahin U., Nature 2015, 520, 692; - PMC - PubMed
    2. b) Yadav M., Jhunjhunwala S., Phung Q. T., Lupardus P., Tanguay J., Bumbaca S., Franci C., Cheung T. K., Fritsche J., Weinschenk T., Modrusan Z., Mellman I., Lill J. R., Delamarre L., Nature 2014, 515, 572. - PubMed
    1. a) Ott P. A., Hu Z., Keskin D. B., Shukla S. A., Sun J., Bozym D. J., Zhang W., Luoma A., Giobbie‐Hurder A., Peter L., Chen C., Olive O., Carter T. A., Li S., Lieb D. J., Eisenhaure T., Gjini E., Stevens J., Lane W. J., Javeri I., Nellaiappan K., Salazar A. M., Daley H., Seaman M., Buchbinder E. I., Yoon C. H., Harden M., Lennon N., Gabriel S., Rodig S. J., Barouch D. H., Aster J. C., Getz G., Wucherpfennig K., Neuberg D., Ritz J., Lander E. S., Fritsch E. F., Hacohen N., Wu C. J., Nature 2017, 547, 217; - PMC - PubMed
    2. b) Sahin U., Derhovanessian E., Miller M., Kloke B.‐P., Simon P., Löwer M., Bukur V., Tadmor A. D., Luxemburger U., Schrörs B., Omokoko T., Vormehr M., Albrecht C., Paruzynski A., Kuhn A. N., Buck J., Heesch S., Schreeb K. H., Müller F., Ortseifer I., Vogler I., Godehardt E., Attig S., Rae R., Breitkreuz A., Tolliver C., Suchan M., Martic G., Hohberger A., Sorn P., Diekmann J., Ciesla J., Waksmann O., Brück A.‐K., Witt M., Zillgen M., Rothermel A., Kasemann B., Langer D., Bolte S., Diken M., Kreiter S., Nemecek R., Gebhardt C., Grabbe S., Höller C., Utikal J., Huber C., Loquai C., Türeci Ö., Nature 2017, 547, 222; - PubMed
    3. c) Hilf N., Kuttruff‐Coqui S., Frenzel K., Bukur V., Stevanović S., Gouttefangeas C., Platten M., Tabatabai G., Dutoit V., van der Burg S. H., thor Straten P., Martínez‐Ricarte F., Ponsati B., Okada H., Lassen U., Admon A., Ottensmeier C. H., Ulges A., Kreiter S., von Deimling A., Skardelly M., Migliorini D., Kroep J. R., Idorn M., Rodon J., Piró J., Poulsen H. S., Shraibman B., McCann K., Mendrzyk R., Löwer M., Stieglbauer M., Britten C. M., Capper D., Welters M. J. P., Sahuquillo J., Kiesel K., Derhovanessian E., Rusch E., Bunse L., Song C., Heesch S., Wagner C., Kemmer‐Brück A., Ludwig J., Castle J. C., Schoor O., Tadmor A. D., Green E., Fritsche J., Meyer M., Pawlowski N., Dorner S., Hoffgaard F., Rössler B., Maurer D., Weinschenk T., Reinhardt C., Huber C., Rammensee H.‐G., Singh‐Jasuja H., Sahin U., Dietrich P.‐Y., Wick W., Nature 2019, 565, 240; - PubMed
    4. d) Keskin D. B., Anandappa A. J., Sun J., Tirosh I., Mathewson N. D., Li S., Oliveira G., Giobbie‐Hurder A., Felt K., Gjini E., Shukla S. A., Hu Z., Li L., Le P. M., Allesøe R. L., Richman A. R., Kowalczyk M. S., Abdelrahman S., Geduldig J. E., Charbonneau S., Pelton K., Iorgulescu J. B., Elagina L., Zhang W., Olive O., McCluskey C., Olsen L. R., Stevens J., Lane W. J., Salazar A. M., Daley H., Wen P. Y., Chiocca E. A., Harden M., Lennon N. J., Gabriel S., Getz G., Lander E. S., Regev A., Ritz J., Neuberg D., Rodig S. J., Ligon K. L., Suvà M. L., Wucherpfennig K. W., Hacohen N., Fritsch E. F., Livak K. J., Ott P. A., Wu C. J., Reardon D. A., Nature 2019, 565, 234. - PMC - PubMed
    1. a) Liu H., Moynihan K. D., Zheng Y., Szeto G. L., Li A. V., Huang B., Van Egeren D. S., Park C., Irvine D. J., Nature 2014, 507, 519; - PMC - PubMed
    2. b) Zhu G., Lynn G. M., Jacobson O., Chen K., Liu Y., Zhang H., Ma Y., Zhang F., Tian R., Ni Q., Cheng S., Wang Z., Lu N., Yung B. C., Wang Z., Lang L., Fu X., Jin A., Weiss I. D., Vishwasrao H., Niu G., Shroff H., Klinman D. M., Seder R. A., Chen X., Nat. Commun. 2017, 8, 1954. - PMC - PubMed

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