Predicted peptide-based MHC-I, MHC-II, CTL and B-cell epitopes of MUC-1 by immunoinformatics methods: a clue for novel multi-epitope vaccine development against breast cancer

Abstract

BACKGROUND: Breast cancer (BC) is one of the most common types of women malignancy. Multi-epitope vaccines are new hopes for treatment of this cancer. MUC-1 is a tumor associated antigen that focused for multi-epitope vaccine development in case of BC. METHODS: Here, primary data from a computation analysis of this glycoprotein to find potential MHC-I, MHC-II, CTL and B-cell epitopes are described using immunoinformatics tools. RESULTS: According to the results, 1156VPGWGIALL984 corresponding to HLA-B0702 and HLA-A0101 alleles for MHC-I epitopes, 1209YPTYHTHGR1118 corresponding to DRB1*13 and DQB1*06 alleles for MHC-II epitops, 1122NQYKTEAAS45 for CTL epitopes and 1204HPMSEYPTYHTHGRYV896 for B-cell epitopes are the peptides with the best binding affinity. CONCLUSIONS: These data may be useful for further multi-epitope vaccine development. KEY WORDS: Breast neoplasms; Epitopes; Vaccines, synthetic; Mucin-1