An immunoinformatic approach for a therapeutic epitope-based peptide vaccine design by targeting HPV16-E6: in silico study

Cervical cancer is one of the leading causes of death worldwide, causing approximately 500,000 new cases and 250,000 cancer deaths each year. Persistent infection with high-risk human papillomaviruses (HPVs), particularly type 16, is the primary cause of cervical cancer development and maintenance among women worldwide. The E6 therapeutic vaccines can induce strong anti-tumor T cell-mediated immune responses, such as cytotoxic T lymphocytes, that play vital roles in current therapeutic vaccine development. In our study, bioinformatics approaches and in silico analyzes, such as protein sequence retrieval, identification of conserved regions, drawing of pedigrees, prediction of T-cell epitopes, calculation of population coverage of predicted epitopes, and molecular docking, were used to predict the major histocompatibility complex (MHC) Class I and Class II T cell epitopes of HPV16 E6. Taking into account the scores from different steps, six CD8+ T cells and three CD4+ epitopes were selected. The fusion of the selected epitopes created a universal potential vaccine with a population coverage of 86.41%. The population coverage was obtained by evaluating the potential of these epitopes to elicit innate and acquired immunity. These theoretically confirmed peptides could be employed in a poly-epitope construct as a candidate vaccine for further analyses. Also, these results provide new insights into therapeutic vaccine development.