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Generation of multiepitope cancer vaccines based on large combinatorial libraries of survivin-derived mutant epitopes.
Immunology. 2020 Jul 03 [Online ahead of print]I

Abstract

Immune tolerance is the main challenge in the field of cancer vaccines, so modified peptide sequences or naturally occurring mutated versions of cancer-related wild-type (WT) antigens represent a promising pathway. However, the low immunogenicity of mutation-induced neoantigens and, particularly, their incapacity to activate CD8+ T cells are generating doubts on the success of neoantigen-based cancer vaccines in clinical trials. We developed a novel vaccine approach based on a new class of vaccine immunogens, called variable epitope libraries (VELs). We used three regions of survivin (SVN), composed of 40, 49 and 51 amino acids, along with the complete SVN protein to generate the VELs as multiepitope vaccines. BALB/c mice, challenged with the aggressive and highly metastatic 4T1 cell line, were vaccinated in a therapeutic setting. We showed significant tumor growth inhibition and, most importantly, strong suppression of lung metastasis after a single immunization using VEL vaccines. We demonstrated vaccine-induced broad cellular immune responses concomitant with extensive tumor infiltration of T cells, the activation of CD107a+ IFN-γ+ T cells in the spleen and a significant increase in the number of CD3+ CD8+ Ly6C+ effector T cells. In addition, we observed the presence of interferon-γ-, granzyme B- and perforin-producing lymphocytes along with modifications in the amount of CD11b+ Ly6Cint/low Ly6G+ granulocytic myeloid-derived suppressor cells and CD4+ CD25+ FoxP3+ regulatory T cells in the lungs and tumors of mice. In summary, we showed that the VELs represent a potent new class of cancer immunotherapy and propose the application of the VEL vaccine concept as a true alternative to currently available vaccine platforms.

Authors+Show Affiliations

Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México (UNAM), México, DF, México.Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México (UNAM), México, DF, México.Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México (UNAM), México, DF, México.Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México (UNAM), México, DF, México.Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México (UNAM), México, DF, México.Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México (UNAM), México, DF, México.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32619293

Citation

Domínguez-Romero, Allan Noé, et al. "Generation of Multiepitope Cancer Vaccines Based On Large Combinatorial Libraries of Survivin-derived Mutant Epitopes." Immunology, 2020.
Domínguez-Romero AN, Martínez-Cortés F, Munguía ME, et al. Generation of multiepitope cancer vaccines based on large combinatorial libraries of survivin-derived mutant epitopes. Immunology. 2020.
Domínguez-Romero, A. N., Martínez-Cortés, F., Munguía, M. E., Odales, J., Gevorkian, G., & Manoutcharian, K. (2020). Generation of multiepitope cancer vaccines based on large combinatorial libraries of survivin-derived mutant epitopes. Immunology. https://doi.org/10.1111/imm.13233
Domínguez-Romero AN, et al. Generation of Multiepitope Cancer Vaccines Based On Large Combinatorial Libraries of Survivin-derived Mutant Epitopes. Immunology. 2020 Jul 3; PubMed PMID: 32619293.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Generation of multiepitope cancer vaccines based on large combinatorial libraries of survivin-derived mutant epitopes. AU - Domínguez-Romero,Allan Noé, AU - Martínez-Cortés,Fernando, AU - Munguía,María Elena, AU - Odales,Josué, AU - Gevorkian,Goar, AU - Manoutcharian,Karen, Y1 - 2020/07/03/ PY - 2020/01/29/received PY - 2020/06/19/revised PY - 2020/06/21/accepted PY - 2020/7/4/pubmed PY - 2020/7/4/medline PY - 2020/7/4/entrez KW - antigenic variability KW - cancer epitope vaccine KW - recombinant M13 phage KW - variable epitope library JF - Immunology JO - Immunology N2 - Immune tolerance is the main challenge in the field of cancer vaccines, so modified peptide sequences or naturally occurring mutated versions of cancer-related wild-type (WT) antigens represent a promising pathway. However, the low immunogenicity of mutation-induced neoantigens and, particularly, their incapacity to activate CD8+ T cells are generating doubts on the success of neoantigen-based cancer vaccines in clinical trials. We developed a novel vaccine approach based on a new class of vaccine immunogens, called variable epitope libraries (VELs). We used three regions of survivin (SVN), composed of 40, 49 and 51 amino acids, along with the complete SVN protein to generate the VELs as multiepitope vaccines. BALB/c mice, challenged with the aggressive and highly metastatic 4T1 cell line, were vaccinated in a therapeutic setting. We showed significant tumor growth inhibition and, most importantly, strong suppression of lung metastasis after a single immunization using VEL vaccines. We demonstrated vaccine-induced broad cellular immune responses concomitant with extensive tumor infiltration of T cells, the activation of CD107a+ IFN-γ+ T cells in the spleen and a significant increase in the number of CD3+ CD8+ Ly6C+ effector T cells. In addition, we observed the presence of interferon-γ-, granzyme B- and perforin-producing lymphocytes along with modifications in the amount of CD11b+ Ly6Cint/low Ly6G+ granulocytic myeloid-derived suppressor cells and CD4+ CD25+ FoxP3+ regulatory T cells in the lungs and tumors of mice. In summary, we showed that the VELs represent a potent new class of cancer immunotherapy and propose the application of the VEL vaccine concept as a true alternative to currently available vaccine platforms. SN - 1365-2567 UR - https://www.unboundmedicine.com/medline/citation/32619293/Generation_of_multiepitope_cancer_vaccines_based_on_large_combinatorial_libraries_of_survivin-derived_mutant_epitopes L2 - https://doi.org/10.1111/imm.13233 DB - PRIME DP - Unbound Medicine ER -
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