MMP-7 derived peptides with MHC class-I binding motifs from canine mammary tumor tissue elicit strong antigen-specific T-cell responses in BALB/c mice

Abstract

Matrix Metalloproteinases (MMPs)-induced altered proteolysis of extracellular matrix proteins and basement membrane holds the key for tumor progression and metastasis. Matrix metalloproteinases-7 (Matrilysin), the smallest member of the MMP family also performs quite alike; thus serves as a potential candidate for anti-tumor immunotherapy. Conversely, being an endogenous tumor-associated antigen (TAA), targeting MMP-7 for immunization is challenging. But MMP-7-based xenovaccine can surmount the obstacle of poor immunogenicity and immunological tolerance, often encountered in TAA-based conventional vaccine for anti-tumor immunotherapy. This paves the way for investigating the potential of MMP-7-derived major histocompatibility complex (MHC)-binding peptides to elicit precise epitope-specific T-cell responses towards their possible inclusion in anti-tumor vaccine formulations. Perhaps it also ushers the path of achieving multiple epitope-based broad and universal cellular immunity. In current experiment, an immunoinformatics approach has been employed to identify the putative canine matrix matelloproteinases-7 (cMMP-7)-derived peptides with MHC class-I-binding motifs which can elicit potent antigen-specific immune responses in BALB/c mice. Immunization with the cMMP-7 DNA vaccine induced a strong CD8+ cytotoxic T lymphocytes (CTLs) and Th1- type response, with high level of gamma interferon (IFN-γ) production in BALB/c mice. The two identified putative MHC-I-binding nonameric peptides (Peptide32-40 and Peptide175-183) from cMMP-7 induced significant lymphocyte proliferation along with the production of IFN-γ from CD8+ T-cells in mice immunized with cMMP-7 DNA vaccine. The current observation has depicted the immunogenic potential of the two cMMP-7-derived nonapeptides for their possible exploitation in xenovaccine-mediated anti-tumor immunotherapy in mouse model. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.