Mining the Immunopeptidome for Antigenic Peptides in Cancer: Comparison
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Harnessing the immune system for cancer therapy has shown success, however the response to immunotherapy has been limited. Deciphering the immunopeptidome repertoire of cancer cells is crucial for identifying neoantigens. To date the emphasis has been on mutations. However, there is more to neoantigens than mutations. Thus, there is a need to identify other types of neoantigens that are commonly expressed in a cancer type that are presented by MHC class I and class II, to induce a cytotoxic CD8+ T and CD4+ T response, respectively. The immunopeptidome encompasses protein post-translation modifications (PTMs), which are overlooked by genome or transcriptome profiling. This entreviewy covers how the immunopeptidome can yield novel cancer-specific antigens, focusing on PTMs and their applications.

  • immunopeptidome
  • PTM
  • immunotherapy
  • cancer vaccine

1. Introduction

Identifying novel antigens in cancer is highly relevant for immunotherapeutic applications including chimeric antigen receptor (CAR)-T and NK cell, pulsed-dendritic cell therapy, and therapeutic and preventative cancer vaccines [1]. Mass spectrometry provides an important means for deciphering the immunopeptidome repertoire of tumor cells [2]. Whereas much emphasis has been placed on mutations as a source of neoantigens, the occurrence of specific mutations in peptides bound to the major histocompatibility complex (MHC) is quite variable from patient to patient [3][4][5]. Thus, there is a need to identify antigenic peptides that are commonly expressed in a cancer type that are presented through MHC class I for activation of cytotoxic CD8+ T cells [6][7]. Moreover, there is also an emerging interest in immune peptides bound to MHC class II that induce a B cell response [8][9][10].
Since the early days of profiling the immunopeptidome using mass spectrometry (MS) some three decades ago [11], there has been substantial improvement in the overall approach, including the application of machine learning [12][13][14]. The detection and prediction of immunogenic peptides through genomic and transcriptomic data is challenging and overlooks protein aberrations that occur after transcription. These include translational errors, post-translational modifications (PTMs) and peptide splicing that can be uncovered through analysis of the immunopeptidome [15][16][17]. Remarkably, PTMs have been discovered to induce immunogenicity more than their unmodified counterparts. Prior studies by outhe researchers' group have identified citrullination as a source of immunogenicity in cancer [18]. Other notable PTMs include phosphorylation, acetylation, deamination, and glycosylation [19][20][21][22]. However, not all PTMs are stable and presented by MHC, given their enzymatic reversibility as in the case of acetylation [23].

2. The Immunopeptidome as a Source of Different Types of Neoantigens

The immunoediting concept has been critical for our understanding of the mechanisms through which the immune system responds to cancer and how tumor cells can evade the immune response [24]. A key factor in the immune response is the recognition of tumor antigens. T cells, through their TCRs, can interact with the myriad of peptides bound to MHC, sorting out self from non-self. Non-canonical tumor antigens, derived from sequences outside of exons or by alternate protein-processing mechanisms, are of increasing interest for immunotherapy [25]. PTMs are mediated by multiple enzymes, some of which may be dysregulated in tumor cells, rendering them potentially tumor specific. Post-translationally modified proteins undergo processing through the proteasome, resulting in peptides that bind to MHC-I for endogenous proteins or MHC-II for exogenous proteins [26]. Dendritic cells (DCs) are antigen-presenting cells (APCs) in cancer that are essential for T and B cell responses via immunopeptides and native protein presentation, respectively [27][28]. PTMs that are restricted to tumor cells have potential as a source of immunopeptides for immunotherapy.

3. Post-Translational Modifications as a Source of Tumor Antigens

Whereas a multitude of PTMs are known to occur, most have not been previously investigated in cancer. Nanoscale liquid chromatography coupled mass spectrometry (nanoLC-MS) has contributed significantly to the identification of PTMs in the immunopeptidome through matching the peptide parent mass (MS1) and the fragment mass (MS2) to sequences in the human genome database, allowing for mass shift due to modified amino acids (e.g., +0.984 Da on Arg) for citrullination; (+97.976 Da on Ser, Thr, and Tyr) for phosphorylation; and (+203.079 Da on Ser and Thr) for O-GlcNAc. PTMs that have been identified in the immunopeptidome with demonstrated immunogenicity in cancer (Figure 1).
Figure 1. Post-translationally modified peptide-based cancer vaccine workflow. The figure depicts cancer cell antigen processing of intracellular and extracellular proteins, subsequently as peptides bound to MHC-I or MHC-II. Some of the proteins have PTMs in their structure, which are sketched in colors (citrullination: red; phosphorylation: blue; glycosylation: green) as well as in MHC-bound peptides. The MHC-bound peptides are identified by means of liquid chromatography-mass spectrometry (LC/MS), to derive the cancer cell immunopeptidome. From the immunopeptidome data, peptides with PTMs can be selected as antigens for cancer vaccines.

4. Peptide PTMs as a Source of Cancer Vaccines

Taking into account that the immunopeptidome represents the whole spectrum of peptides presented in a cell, there is a need to identify the most promising cancer targets. Thus, there is a need to determine the structure of an MHC-bound peptide and its level of expression for vaccine development. There are numerous ongoing clinical trials utilizing different antigens and adjuvants as therapeutic cancer vaccines. Focusing on peptides with PTMs as vaccines, promising findings have resulted from the use of citrullinated peptides (Table 1). A citrullinated VIM peptide has been utilized as an antigen in combination with an adjuvant induced IFN-γ and granzyme B-secreting CD4+ T cells. Citrullinated VIM-specific Th1 cells induced by the vaccine had a potent antitumor response against established skin and lung tumors, as well as a long-term memory response [29]. Similarly, a citrullinated ENO1 peptide-based vaccine elicited a potent citrulline-specific Th1 cell response in pancreatic, skin, and lung cancers [30]. Additionally, ENO1 is commonly overexpressed in different tumor types, including melanoma, pancreatic, breast, and lung cancer, thus citrullinated ENO1 peptides are plausible antigens for a wide cancer spectrum [18][30][31]. Furthermore, the combination of citrullinated VIM and ENO1 peptides in a vaccine, designated Modi-1, induced a significant antitumoral response in a mouse model of ovarian cancer. Importantly, a substantial citrulline-specific T cell response was observed in more than half of ovarian cancer patients [32]. Moreover, analysis of the melanoma immunopeptidome led to the identification of MHC-II-bound citrullinated peptides are derived from MMP21, Cp450, and GRI proteins [33]. A combination of these citrullinated peptides did not induce a greater antitumoral response than citrullinated MMP21 and GRI peptides individually, pointing to the potential of a reduced response with multiple peptides with different MHC-II binding specificities [33]. Another source of citrullinated peptides is the NPM protein. Vaccination with a PADI2-mediated-citrullinated NPM peptide induced an antitumoral response which was therapeutic, increasing survival and resulting in protection against a second tumor challenge in melanoma and lung cancer mouse models. Interestingly, PADI4-mediated-citrullination of NPM peptide did not elicit a citrulline-specific Th1 response, in contrast to PADI2-mediated-citrullination [34]. The CD4 responses observed may result from binding of citrullinated peptides primarily by MHC-II [18] in HLA-DP4 and HLA-DR4 transgenic mice. Nevertheless, the vaccine-induced CD4 response was sufficient to inhibit tumor progression, indicating the effectiveness of responses that do not involve CD8+ T cells [10].
Table 1. Summary of the post-translational modified peptides used in immunotherapy.
Post-Translational

Modification		 Protein Cancer Type Immunotherapy MHC Class Reference
Citrullination ENO1 SKCM, PAAD, LUAD, OV Vaccine II [18][30][31][32]
VIM SKCM, LUAD, PAAD, OV Vaccine II [29][32]
MMP21 SKCM Vaccine II [33]
GRI SKCM Vaccine II [33]
Cp450 SKCM Vaccine II [33]
NPM SKCM, LUAD Vaccine II [34]
Phosphorylation ISR2 SKCM Vaccine, ACT I [35][36]
BCAR SKCM Vaccine I [36]
CDC25b SKCM ACT I [35]
Glycosylation MUC1 BRCA, PRAD Vaccine, DCTher I, II [37][38][39][40]
MUC4 NA Vaccine II [41]
PHOX2B Neuroblastoma CAR T cell I [42]
ACT: Adoptive Cell Therapy; DCTher: Dendritic Cell Therapy; ENO1: α-enolase 1; VIM: vimentin; MMP21: Matrix Metalloproteinase-21; GRI: Glutamate Receptor Ionotropic; NPM: Nucleophosmin; ISR2: Insulin Receptor Substrate 2; BCAR: Breast Cancer Antiestrogen Resistance 3; SKCM: Skin Cutaneous Melanoma; PAAD: Pancreatic Adenocarcinoma; PRAD: Prostate Adenocarcinoma; BRCA: Breast Invasive Carcinoma; LUAD: Lung Adenocarcinoma; OV: Ovarian Serous Cystadenocarcinoma; NA; Not Applicable.
There is a more limited number of studies utilizing phosphorylation as a PTM for peptide vaccines, although immunopeptidome analysis has pointed to a substantial number of phosphorylated peptides. Immunopeptidome analysis of melanoma, ovarian carcinoma, B lymphoblastoid, and leukemia resulted in the identification of a large number of phosphopeptides that were cancer specific with CD8 T cell antigen specificity in patients [43][44]. Some of the identified phosphopeptides were derived from ISR2, BCAR, TNS2, SELH, CDC25b, and beta-catenin [35][43][44], concordant with the identification of phosphorylated ISR2, TNS2, and SELH peptides in the colorectal cancer immunopeptidome [45]. 
As for glycopeptide-based cancer vaccines, an initial source was the glycosylated MUC protein displaying the Tn antigen. Immunization of mice with a desialylated ovine MUC with substantial representation of the Tn antigen elicited primarily a CD4+ T cell response specific to the Tn antigen. Conversely, immunization with a deglycosylated MUC did not induce an immune response [46]. The induction of an immune response specifically against the PTM protein suggests that glycosylation may be a useful source of cancer-specific antigens given the findings of aberrant glycosylation in many cancers, notably breast cancer [47][48]. A case in point is a fully synthetic cancer vaccine, a dendrimeric multiple antigenic glycopeptide displaying a trimer of Tn antigens (MAG-Tn3) associated with a promiscuous CD4 epitope, the tetanus toxoid-derived P2 peptide, that has been shown to induce an antitumoral Tn-specific T cell response in monkeys [47]. This MAG-Tn3 vaccine has been used in a phase I clinical trial for high-risk relapsed breast cancer patients (NCT02364492). Another cancer vaccine in clinical trial is based on MUC1 bearing Tn antigens (Tn-MUC1) pulsed with autologous DCs [39]. This phase I/II clinical trial follows the same strategy used in rhesus macaques, which resulted in five out of seven castrate-resistant prostate cancer patients having a CD4 and/or CD8 response (NCT00852007).
 Given the complexity of glycan modifications, there has been a surge of various approaches to identify and develop glycopeptides as vaccines, as reviewed above, including the use of glyco-antigen microarrays to investigate immune responses to cancer vaccines [49][50]. Another development is the use of an antigen delivery system based on gold nanoparticles with Dectin-1 to target DC, conjugated with MHC-II glycopeptides. This gold nanoparticle glycopeptide vaccine elicited a strong humoral and cellular immune response in mice [51]. In all, much progress has been made in the identification of glycopeptides and their structural and other properties to enhance their effectiveness as cancer vaccines [52][53][54][55].

References

  1. Abbott, M.; Ustoyev, Y. Cancer and the Immune System: The History and Background of Immunotherapy. Semin. Oncol. Nurs. 2019, 35, 150923.
  2. Kote, S.; Pirog, A.; Bedran, G.; Alfaro, J.; Dapic, I. Mass Spectrometry-Based Identification of MHC-Associated Peptides. Cancers 2020, 12, 535.
  3. Okada, M.; Shimizu, K.; Fujii, S.I. Identification of Neoantigens in Cancer Cells as Targets for Immunotherapy. Int. J. Mol. Sci. 2022, 23, 2594.
  4. Kotsias, F.; Cebrian, I.; Alloatti, A. Antigen processing and presentation. Int. Rev. Cell Mol. Biol. 2019, 348, 69–121.
  5. Freudenmann, L.K.; Marcu, A.; Stevanovic, S. Mapping the tumour human leukocyte antigen (HLA) ligandome by mass spectrometry. Immunology 2018, 154, 331–345.
  6. Peters, H.L.; Tripathi, S.C.; Kerros, C.; Katayama, H.; Garber, H.R.; St John, L.S.; Federico, L.; Meraz, I.M.; Roth, J.A.; Sepesi, B.; et al. Serine Proteases Enhance Immunogenic Antigen Presentation on Lung Cancer Cells. Cancer Immunol. Res. 2017, 5, 319–329.
  7. Zhang, X.; Qi, Y.; Zhang, Q.; Liu, W. Application of mass spectrometry-based MHC immunopeptidome profiling in neoantigen identification for tumor immunotherapy. Biomed. Pharm. 2019, 120, 109542.
  8. Santambrogio, L. Molecular Determinants Regulating the Plasticity of the MHC Class II Immunopeptidome. Front. Immunol. 2022, 13, 878271.
  9. Olsson, N.; Jiang, W.; Adler, L.N.; Mellins, E.D.; Elias, J.E. Tuning DO:DM Ratios Modulates MHC Class II Immunopeptidomes. Mol. Cell Proteom. 2022, 21, 100204.
  10. Alspach, E.; Lussier, D.M.; Miceli, A.P.; Kizhvatov, I.; DuPage, M.; Luoma, A.M.; Meng, W.; Lichti, C.F.; Esaulova, E.; Vomund, A.N.; et al. MHC-II neoantigens shape tumour immunity and response to immunotherapy. Nature 2019, 574, 696–701.
  11. Hunt, D.F.; Henderson, R.A.; Shabanowitz, J.; Sakaguchi, K.; Michel, H.; Sevilir, N.; Cox, A.L.; Appella, E.; Engelhard, V.H. Characterization of peptides bound to the class I MHC molecule HLA-A2.1 by mass spectrometry. Science 1992, 255, 1261–1263.
  12. Yewdell, J.W. MHC Class I Immunopeptidome: Past, Present & Future. Mol. Cell Proteom. 2022, 100230.
  13. Nielsen, M.; Ternette, N.; Barra, C. The interdependence of machine learning and LC-MS approaches for an unbiased understanding of the cellular immunopeptidome. Expert Rev. Proteom. 2022, 1–12.
  14. Leko, V.; Rosenberg, S.A. Identifying and Targeting Human Tumor Antigens for T Cell-Based Immunotherapy of Solid Tumors. Cancer Cell 2020, 38, 454–472.
  15. Liepe, J.; Sidney, J.; Lorenz, F.K.M.; Sette, A.; Mishto, M. Mapping the MHC Class I-Spliced Immunopeptidome of Cancer Cells. Cancer Immunol. Res. 2019, 7, 62–76.
  16. Mishto, M. Commentary: Are There Indeed Spliced Peptides in the Immunopeptidome? Mol. Cell Proteom. 2021, 20, 100158.
  17. Mishto, M. What We See, What We Do Not See, and What We Do Not Want to See in HLA Class I Immunopeptidomes. Proteomics 2020, 20, e2000112.
  18. Katayama, H.; Kobayashi, M.; Irajizad, E.; Sevillarno, A.; Patel, N.; Mao, X.; Rusling, L.; Vykoukal, J.; Cai, Y.; Hsiao, F.; et al. Protein citrullination as a source of cancer neoantigens. J. Immunother. Cancer 2021, 9.
  19. Wei, J.; Zanker, D.; Di Carluccio, A.R.; Smelkinson, M.G.; Takeda, K.; Seedhom, M.O.; Dersh, D.; Gibbs, J.S.; Yang, N.; Jadhav, A.; et al. Varied Role of Ubiquitylation in Generating MHC Class I Peptide Ligands. J. Immunol. 2017, 198, 3835–3845.
  20. Beresford, G.W.; Boss, J.M. CIITA coordinates multiple histone acetylation modifications at the HLA-DRA promoter. Nat. Immunol. 2001, 2, 652–657.
  21. McGinty, J.W.; Marre, M.L.; Bajzik, V.; Piganelli, J.D.; James, E.A. T cell epitopes and post-translationally modified epitopes in type 1 diabetes. Curr. Diab. Rep. 2015, 15, 90.
  22. Sidney, J.; Vela, J.L.; Friedrich, D.; Kolla, R.; von Herrath, M.; Wesley, J.D.; Sette, A. Low HLA binding of diabetes-associated CD8+ T-cell epitopes is increased by post translational modifications. BMC Immunol. 2018, 19, 12.
  23. Drazic, A.; Myklebust, L.M.; Ree, R.; Arnesen, T. The world of protein acetylation. Biochim. Biophys. Acta 2016, 1864, 1372–1401.
  24. Robert, D.; Schreiber, L.J.O.; Smyth, M.J. Cancer Immunoediting: Integrating Immunity’s Roles in Cancer Suppression and Promotion. Science 2011, 331, 1565–1570.
  25. Chong, C.; Coukos, G.; Bassani-Sternberg, M. Identification of tumor antigens with immunopeptidomics. Nat. Biotechnol. 2022, 40, 175–188.
  26. Sellars, M.C.; Wu, C.J.; Fritsch, E.F. Cancer vaccines: Building a bridge over troubled waters. Cell 2022, 185, 2770–2788.
  27. Gardner, A.; Ruffell, B. Dendritic Cells and Cancer Immunity. Trends Immunol. 2016, 37, 855–865.
  28. Stoitzner, P.; Romani, N.; Rademacher, C.; Probst, H.C.; Mahnke, K. Antigen targeting to dendritic cells: Still a place in future immunotherapy? Eur. J. Immunol. 2022, 1–16.
  29. Brentville, V.A.; Metheringham, R.L.; Gunn, B.; Symonds, P.; Daniels, I.; Gijon, M.; Cook, K.; Xue, W.; Durrant, L.G. Citrullinated Vimentin Presented on MHC-II in Tumor Cells Is a Target for CD4+ T-Cell-Mediated Antitumor Immunity. Cancer Res. 2016, 76, 548–560.
  30. Cook, K.; Daniels, I.; Symonds, P.; Pitt, T.; Gijon, M.; Xue, W.; Metheringham, R.; Durrant, L.; Brentville, V. Citrullinated alpha-enolase is an effective target for anti-cancer immunity. Oncoimmunology 2018, 7, e1390642.
  31. Brentville, V.A.; Vankemmelbeke, M.; Metheringham, R.L.; Durrant, L.G. Post-translational modifications such as citrullination are excellent targets for cancer therapy. Semin. Immunol. 2020, 47, 101393.
  32. Brentville, V.A.; Metheringham, R.L.; Daniels, I.; Atabani, S.; Symonds, P.; Cook, K.W.; Vankemmelbeke, M.; Choudhury, R.; Vaghela, P.; Gijon, M.; et al. Combination vaccine based on citrullinated vimentin and enolase peptides induces potent CD4-mediated anti-tumor responses. J. Immunother. Cancer 2020, 8, e000560.
  33. Symonds, P.; Marcu, A.; Cook, K.W.; Metheringham, R.L.; Durrant, L.G.; Brentville, V.A. Citrullinated Epitopes Identified on Tumour MHC Class II by Peptide Elution Stimulate Both Regulatory and Th1 Responses and Require Careful Selection for Optimal Anti-Tumour Responses. Front. Immunol. 2021, 12, 764462.
  34. Choudhury, R.H.; Symonds, P.; Paston, S.J.; Daniels, I.; Cook, K.W.; Gijon, M.; Metheringham, R.L.; Brentville, V.A.; Durrant, L.G. PAD-2-mediated citrullination of nucleophosmin provides an effective target for tumor immunotherapy. J. Immunother. Cancer 2022, 10, e003526.
  35. Zarling, A.L.; Obeng, R.C.; Desch, A.N.; Pinczewski, J.; Cummings, K.L.; Deacon, D.H.; Conaway, M.; Slingluff, C.L., Jr.; Engelhard, V.H. MHC-restricted phosphopeptides from insulin receptor substrate-2 and CDC25b offer broad-based immunotherapeutic agents for cancer. Cancer Res. 2014, 74, 6784–6795.
  36. Engelhard, V.H.; Obeng, R.C.; Cummings, K.L.; Petroni, G.R.; Ambakhutwala, A.L.; Chianese-Bullock, K.A.; Smith, K.T.; Lulu, A.; Varhegyi, N.; Smolkin, M.E.; et al. MHC-restricted phosphopeptide antigens: Preclinical validation and first-in-humans clinical trial in participants with high-risk melanoma. J. Immunother. Cancer 2020, 8, e000262.
  37. Merikhian, P.; Darvishi, B.; Jalili, N.; Esmailinejad, M.R.; Khatibi, A.S.; Kalbolandi, S.M.; Salehi, M.; Mosayebzadeh, M.; Barough, M.S.; Majidzadeh, A.K.; et al. Recombinant nanobody against MUC1 tandem repeats inhibits growth, invasion, metastasis, and vascularization of spontaneous mouse mammary tumors. Mol. Oncol. 2022, 16, 485–507.
  38. Palitzsch, B.; Gaidzik, N.; Stergiou, N.; Stahn, S.; Hartmann, S.; Gerlitzki, B.; Teusch, N.; Flemming, P.; Schmitt, E.; Kunz, H. A Synthetic Glycopeptide Vaccine for the Induction of a Monoclonal Antibody that Differentiates between Normal and Tumor Mammary Cells and Enables the Diagnosis of Human Pancreatic Cancer. Angew. Chem. Int. Ed. Engl. 2016, 55, 2894–2898.
  39. Scheid, E.; Major, P.; Bergeron, A.; Finn, O.J.; Salter, R.D.; Eady, R.; Yassine-Diab, B.; Favre, D.; Peretz, Y.; Landry, C.; et al. Tn-MUC1 DC Vaccination of Rhesus Macaques and a Phase I/II Trial in Patients with Nonmetastatic Castrate-Resistant Prostate Cancer. Cancer Immunol. Res. 2016, 4, 881–892.
  40. Glaffig, M.; Stergiou, N.; Schmitt, E.; Kunz, H. Immunogenicity of a Fully Synthetic MUC1 Glycopeptide Antitumor Vaccine Enhanced by Poly(I:C) as a TLR3-Activating Adjuvant. ChemMedChem 2017, 12, 722–727.
  41. Trabbic, K.R.; Whalen, K.; Abarca-Heideman, K.; Xia, L.; Temme, J.S.; Edmondson, E.F.; Gildersleeve, J.C.; Barchi, J.J., Jr. A Tumor-Selective Monoclonal Antibody from Immunization with a Tumor-Associated Mucin Glycopeptide. Sci. Rep. 2019, 9, 5662.
  42. Yarmarkovich, M.; Marshall, Q.F.; Warrington, J.M.; Premaratne, R.; Farrel, A.; Groff, D.; Li, W.; di Marco, M.; Runbeck, E.; Truong, H.; et al. Cross-HLA targeting of intracellular oncoproteins with peptide-centric CARs. Nature 2021, 599, 477–484.
  43. Zarling, A.L.; Polefrone, J.M.; Evans, A.M.; Mikesh, L.M.; Shabanowitz, J.; Lewis, S.T.; Engelhardt, V.H.; Hunt, D.F. Identification of class I MHC-associated phosphopeptides as targets for cancer immunotherapy. Proc. Natl. Acad. Sci. USA 2006, 103, 14889–14894.
  44. Cobbold, M.; De La Pena, H.; Norris, A.; Polefrone, J.M.; Qian, J.; English, A.M.; Cummings, K.L.; Penny, S.; Turner, J.E.; Cottine, J.; et al. MHC Class I-Associated Phosphopeptides Are the Targets of Memory-like Immunity in Leukemia. Sci. Transl. Med. 2013, 5, 203ra125.
  45. Penny, S.A.; Abelin, J.G.; Malaker, S.A.; Myers, P.T.; Saeed, A.Z.; Steadman, L.G.; Bai, D.L.; Ward, S.T.; Shabanowitz, J.; Hunt, D.F.; et al. Tumor Infiltrating Lymphocytes Target HLA-I Phosphopeptides Derived From Cancer Signaling in Colorectal Cancer. Front. Immunol. 2021, 12, 723566.
  46. Singhal, A.; Fohn, M.; Hakomori, S. Induction of alpha-N-acetylgalactosamine-O-serine/threonine (Tn) antigen-mediated cellular immune response for active immunotherapy in mice. Cancer Res. 1991, 51, 1406–1411.
  47. Laubreton, D.; Bay, S.; Sedlik, C.; Artaud, C.; Ganneau, C.; Deriaud, E.; Viel, S.; Puaux, A.L.; Amigorena, S.; Gerard, C.; et al. The fully synthetic MAG-Tn3 therapeutic vaccine containing the tetanus toxoid-derived TT830-844 universal epitope provides anti-tumor immunity. Cancer Immunol. Immunother. 2016, 65, 315–325.
  48. Vlad, A.M.; Finn, O.J. Glycoprotein tumor antigens for immunotherapy of breast cancer. Breast. Dis. 2004, 20, 73–79.
  49. Padler-Karavani, V. Glycan Microarray Reveal the Sweet Side of Cancer Vaccines. Cell Chem. Biol. 2016, 23, 1446–1447.
  50. Marchiori, M.F.; Bortot, L.O.; Carvalho, I.; Campo, V.L. Synthesis of MUC1-derived glycopeptide bearing a novel triazole STn analog. Carbohydr. Res. 2020, 498, 108155.
  51. Trabbic, K.R.; Kleski, K.A.; Barchi, J.J., Jr. A Stable Gold Nanoparticle-Based Vaccine for the Targeted Delivery of Tumor-Associated Glycopeptide Antigens. ACS Biol. Med. Chem. Au. 2021, 1, 31–43.
  52. Stergiou, N.; Urschbach, M.; Gabba, A.; Schmitt, E.; Kunz, H.; Besenius, P. The Development of Vaccines from Synthetic Tumor-Associated Mucin Glycopeptides and their Glycosylation-Dependent Immune Response. Chem. Rec. 2021, 21, 3313–3331.
  53. Asín, A.; García-Martín, F.; Busto, J.H.; Avenoza, A.; Peregrina, J.M.; Corzana, F. Structure-based Design of Anti-cancer Vaccines: The Significance of Antigen Presentation to Boost the Immune Response. Curr. Med. Chem. 2022, 29, 1258–1270.
  54. Toraskar, S.; Madhukar Chaudhary, P.; Kikkeri, R. The Shape of Nanostructures Encodes Immunomodulation of Carbohydrate Antigen and Vaccine Development. ACS Chem. Biol. 2022, 17, 1122–1130.
  55. Ferreira, J.A.; Relvas-Santos, M.; Peixoto, A.; Silva, A.M.N.; Lara Santos, L. Glycoproteogenomics: Setting the Course for Next-generation Cancer Neoantigen Discovery for Cancer Vaccines. Genom. Proteom. Bioinform. 2021, 19, 25–43.
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