Breast cancer is one of the most diagnosed cancers in women; the number of cases continues to rise. The high prevalence and increased incidence need more attention in developing effective therapy. Current passive therapy has several drawbacks that have not yet been resolved. Thus, an alternative and preventive therapy for cancer is needed by utilizing vaccines. Immunoinformatics approach is one of the promising methods predicting epitopes in vaccine research. This approach could accelerate the initial study process of vaccine development and reduce research costs. Epitope conservancy and vaccine coverage are important parameters in vaccine research due to addressing the variability and diversity of cancer genomics. This study will be carried out on the multiepitope characterization of potential T cells against the protein mechanism in breast cancer. Proteins used in this study are Mucin-4, Phosphatase And Tensin Homolog, and Receptor tyrosine-protein kinase erbB-2. CTL epitopes, antigenicity, immunogenicity, allergenicity, and toxicity were predicted for the peptide vaccine. Immunoinformatics analysis generates a multiepitope sequence consisting of seven epitopes: DPVALVAPF, SVAYRLGTL, SQINTLNTL, RFRELVSEF, VTSANIQEF, RPRFRELVS, and MYFEFPQPL by AAY linker. The docking and molecular dynamics analyses were conducted to confirm the interactions between the multiepitope vaccine molecule and TLR-4-MD. The multiepitope vaccine construct can be an appropriate choice for further experiments.
- Breast cancer
- peptide vaccine design