Skip to main content

Analyzing the Immune Response of Neoepitopes for Personalized Vaccine Design

  • Conference paper
  • First Online:
Bioinformatics and Biomedical Engineering (IWBBIO 2020)

Abstract

In the last few years, the importance of neoepitopes for the development of personalized antitumor vaccines has increased remarkably. This kind of epitopes are considered to generate a strong immune reaction, while their non-mutated version, which sometimes differs only in a single amino-acid, does not generate a response at all. In order to study if, regardless the immune tolerance, neoepitopes are quantitatively more immunogenic than the original strings, we have obtained samples of mutated and non-mutated epitopes of six patients with cutaneous melanoma in different stages, and then we have compared them. More precisely, we have used several bioinformatic tools to study certain properties of the epitopes such as the HLA binding affinity of classes I and II, and found that some of them are in fact increased in their mutated versions, which supports the hypothesis, and also reinforces the use of neoepitopes for cancer vaccine design.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Vormehr, M., Diken, M., TĂŒreci, Ö., Sahin, U., Kreiter, S.: Personalized neo-epitope vaccines for cancer treatment. In: Theobald, M. (ed.) Current Immunotherapeutic Strategies in Cancer. RRCR, vol. 214, pp. 153–167. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-23765-3_5

    Chapter  Google Scholar 

  2. Vermaelen, K.: Vaccine strategies to improve anti-cancer cellular immune responses. Front. Immunol. 10, 8 (2019). https://doi.org/10.3389/fimmu.2019.00008

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Sahin, U., et al.: Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer. Nature 547, 7662 (2017)

    Article  Google Scholar 

  4. Kakimi, K., Karasaki, T., Matsushita, H., Sugie, T.: Advances in personalized cancer immunotherapy. Breast Cancer 24, 16–24 (2017)

    Article  Google Scholar 

  5. Stratton, M.R.: Exploring the genomes of cancer cells: progress and promise. Science 331, 1553–1558 (2011)

    Article  CAS  Google Scholar 

  6. Kreiter, S., Castle, J.C., TĂŒreci, Ö., Sahin, U.: Targeting the tumor mutanome for personalized vaccination therapy. Oncoimmunology 1, 768–769 (2012)

    Article  Google Scholar 

  7. Leclerc, M., et al.: Recent advances in lung cancer immunotherapy: input of T-cell epitopes associated with impaired peptide processing. Front. Immunol. 10, 1505 (2019)

    Article  CAS  Google Scholar 

  8. Vormehr, M., TĂŒreci, Ö., Sahin, U.: Harnessing tumor mutations for truly individualized cancer vaccines. Annu. Rev. Med. 70, 395–407 (2019)

    Article  CAS  Google Scholar 

  9. Tanyi, J.L., et al.: Personalized cancer vaccine effectively mobilizes antitumor T cell immunity in ovarian cancer. Sci. Transl. Med. 10, eaao5931 (2018)

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

  11. Fritsch, E.F., Rajasagi, M., Ott, P.A., Brusic, V., Hacohen, N., Wu, C.J.: HLA-binding properties of tumor neoepitopes in humans. Cancer Immunol. Res. 2, 522–529 (2014)

    Article  CAS  Google Scholar 

  12. Lundegaard, C., Lund, O., Nielsen, M.: Prediction of epitopes using neural network-based methods. J. Immunol. Methods 374, 26–34 (2011)

    Article  CAS  Google Scholar 

  13. Zhang, Q., et al.: Immune epitope database analysis resource (IEDB-AR). Nucl. Acids Res. 36, 513–518 (2008)

    Article  Google Scholar 

  14. Soria-Guerra, R.E., Nieto-Gomez, R., Govea-Alonso, D.O., Rosales-Mendoza, S.: An overview of bioinformatics tools for epitope prediction: implications on vaccine development. J. Biomed. Inform. 53, 405–414 (2015)

    Article  Google Scholar 

  15. MartĂ­nez, L., Milanič, M., Malaina, I., Álvarez, C., PĂ©rez, M.B., Ildefonso, M.: Weighted lambda superstrings applied to vaccine design. PLoS ONE 14, e0211714 (2019)

    Article  Google Scholar 

  16. Malaina, I., et al.: Metastasis of cutaneous melanoma: risk factors, detection and forecasting. In: Rojas, I., Ortuño, F. (eds.) IWBBIO 2018. LNCS, vol. 10813, pp. 511–519. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-78723-7_44

    Chapter  Google Scholar 

  17. Miller, A.J., Mihm, M.C.: Melanoma. N. Engl. J. Med. 355, 51–65 (2006)

    Article  CAS  Google Scholar 

  18. Thompson, J.A.: The revised american joint committee on cancer staging system for melanoma. In: Seminars in Oncology, vol. 29, pp. 361–369. WB Saunders (2002)

    Google Scholar 

  19. Edlundh-Rose, E., et al.: NRAS and BRAF mutations in melanoma tumours in relation to clinical characteristics: a study based on mutation screening by pyrosequencing. Melanoma Res. 16, 471–478 (2006)

    Article  CAS  Google Scholar 

  20. Nikolaev, S.I., et al.: Exome sequencing identifies recurrent somatic MAP2K1 and MAP2K2 mutations in melanoma. Nat. Genet. 44, 133 (2012)

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  22. Mann, E.R., Li, X.: Intestinal antigen-presenting cells in mucosal immune homeostasis: crosstalk between dendritic cells, macrophages and B-cells. World J. Gastroenterol. WJG 20, 9653 (2014)

    Article  Google Scholar 

  23. Trolle, T., et al.: The length distribution of class I–restricted T cell epitopes is determined by both peptide supply and MHC allele–specific binding preference. J. Immunol. 196, 1480–1487 (2016)

    Article  CAS  Google Scholar 

  24. LĂłpez-MartĂ­nez, A., ChĂĄvez-Muñoz, C., Granados, J.: FunciĂłn biolĂłgica del complejo principal de histocompatibilidad. Revista de investigaciĂłn clĂ­nica 57, 132–141 (2005)

    PubMed  Google Scholar 

  25. Sette, A., et al.: The relationship between class I binding affinity and immunogenicity of potential cytotoxic T cell epitopes. J. Immunol. 153, 5586–5592 (1994)

    CAS  PubMed  Google Scholar 

  26. 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 (2006)

    Article  CAS  Google Scholar 

  27. Kotturi, M.F., et al.: The CD8+ T-cell response to lymphocytic choriomeningitis virus involves the L antigen: uncovering new tricks for an old virus. J. Virol. 81, 4928–4940 (2007)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This work was supported by Basque Government funding (IT1974-16, KK-2018/00090), and by the UPV/EHU and Basque Center of Applied Mathematics (US18/21)

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Iker Malaina .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Malaina, I., Legarreta, L., Boyano, M.D., Alonso, S., De la Fuente, I.M., Martinez, L. (2020). Analyzing the Immune Response of Neoepitopes for Personalized Vaccine Design. In: Rojas, I., Valenzuela, O., Rojas, F., Herrera, L., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2020. Lecture Notes in Computer Science(), vol 12108. Springer, Cham. https://doi.org/10.1007/978-3-030-45385-5_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-45385-5_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-45384-8

  • Online ISBN: 978-3-030-45385-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics