in-silico identification of immunogenic peptide epitopes for the design of a multi-epitope therapeutic vaccine against triple-negative breast cancer

Introduction: triple-negative breast cancer (tnbc) is an aggressive subtype of breast cancer characterized by the absence of estrogen receptors (er), progesterone receptors (pr), and her2 expression, which limits the efficacy of conventional targeted therapies. immunotherapy, particularly peptide-based therapeutic vaccines, offers a promising alternative strategy by harnessing the body's cytotoxic t lymphocyte (ctl) responses against tumor-specific antigens (tsas). this study aimed to identify and validate immunogenic peptide epitopes derived from highly tumor-specific antigens for the design of a multi-epitope vaccine targeting tnbc.materials and method: using a comprehensive immunoinformatics workflow, tumor-associated antigens with high immunogenic potential—survivin (birc5), mage-a3, and ny-eso-1—were selected based on expression profiles and previous evidence of immunoreactivity. candidate epitopes were predicted through netctl, syfpeithi, and mhcflurry servers, with selection criteria including strong binding affinity to hla-a*02:01, favorable proteasomal cleavage patterns, tap transport efficiency, and minimal cross-reactivity.results: three high-scoring cd8⁺ t-cell epitopes were identified—lmlgeflkl from survivin (birc5), flwgprala from mage-a3, and sllmwitqc from ny-eso-1. all epitopes exhibited ic50 values below 50 nm and high immunogenicity scores, supporting their suitability for incorporation into a multi-epitope vaccine construct targeting tnbc.conclusion: our results support the rational design of a peptide-based therapeutic vaccine for tnbc by integrating three validated epitopes derived from the tumor antigens survivin, mage-a3, and ny-eso-1. this study contributes to the growing field of cancer immunotherapy by offering a novel, computationally driven approach for vaccine development against refractory breast cancers.