Single amino acid residue substitution to improve immunogenicity of HLA peptides targeting p53 neoantigen

Background and objective: p53 tumor suppressor gene is frequently mutated in human cancer, which is highly associated with advance malignancy development and poor prognosis. However, there are no effective treatments targeting p53 expressed by mutant p53. Aiming at developing therapeutic vaccines targeting mutant p53, we coupled amino acid residue substitution and HLA peptide prediction using an AI model that we developed. Previously, we reported that modified HLA-A*02:01-specific peptides designed using our approach demonstrated significant immunogenicity in a HLA-A*02:01-humanized mouse model. Here, we further designed modified p53 neo-epitopes specific to HLA-A*03:01 and HLA-A*11:01 using this approach and studied their immunogenicity in HLA-humanized mice. Methods: The AI model was used to analyze common p53 neoantigens and predict epitopes for HLA-A*03:01 and HLA-A*11:01. The epitopes underwent computer-assisted saturation mutagenesis that simulated single amino acid substitution to obtain the associated presentation score changes. Peptide sequences with improved presentation scores were synthesized. The binding affinity with HLA was determined using surface plasmon resonance (SPR). The immunogenicity was determined by IFNgamma ELISpot assay and intracellular cytokine staining (ICS) using splenocytes collected from mice vaccinated with the peptides. Results: Modified p53 neo-epitopes were analyzed by our AI model after saturation mutagenesis, and twelve of the modified neo-epitopes with at least 5% increase of presentation probability were selected for experimental analyses. Most of these peptides demonstrated high binding affinity with HLA-A*03:01 or HLA-A*11:01 and beta2-microglobulin heterodimer as characterized by SPR. Using splenocytes collected from HLA-A*03:01 or HLA-A*11:01-humanized mice vaccinated with pools of these peptides, IFNgamma ELISpot assay and IFNgamma ICS revealed that all HLA-A*03:01 peptides and 9 out of 10 HLA-A*11:01 peptides effectively induced CD8 + T-cell response. Remarkably, challenging the splenocytes with the respective native neoantigen peptides reactivated the cellular immunity induced by most of AI-designed modified peptides, suggesting that immunization of the AI-designed modified peptides induced CD8 + T-cell response against the native p53 neoantigens. Conclusion: We have designed multiple peptides derived from common p53 neoantigens and demonstrated that they are strongly immunogenic in HLA-A*02:01, HLA-A*03:01 and HLA-A*11:01 background. These findings further support that the coupling of MHC-I presentation prediction AI model and computer assisted saturation mutagenesis is promising in modifying neo-epitopes to improve anti-tumor immunity via the CD8 + T-cell response.