Integrated approaches for design of precision cancer immunotherapies: Selection of Class I and Class II T cell neo-epitopes and removal of Treg epitopes

Next-generation sequencing has opened the door to precision cancer therapies targeting mutations expressed by tumor cells. However, most neo-epitopes selected by traditional T cell epitope prediction algorithms prove to be non-immunogenic. Poor predictive performance may partially be due to inclusion of mutated epitopes cross-conserved with self-epitopes recognized by the T cell receptor of regulatory (Treg), anergic or deleted T cells. Vaccination with self-epitopes can lead to weak effector responses, active immune suppression, and toxicity due to immune-mediated adverse effects. We have developed Ancer, an advanced cancer T cell epitope identification and characterization tool, that streamlines the selection of Class I and Class II T cell neo-epitopes. Ancer leverages EpiMatrix and JanusMatrix, state-of-the-art predictive algorithms that have been extensively validated in prospective vaccine studies for infectious diseases [Moise et al., Hum. Vaccines Immunother 2015; Wada et al., Sci. Rep. 2017]. Distinctive features of Ancer are its ability to accurately predict Class II HLA ligands with EpiMatrix and its 82% positive predictive value, as estimated in previous prospective studies. Additionally, the application of JanusMatrix allows for the prioritization of neo-epitopes with reduced potential for Treg induction, that is responsible for diminished efficacy of current cancer therapies. We validated Ancer9s predictive accuracy using datasets of HLA-bound peptides detected by mass spectrometry, which are independent of training sequence data used in model development. Analysis of sequences from Abelin et al., Immunity 2017 shows a 96% agreement between Ancer predictions and peptides eluted from common Class I HLAs, while only 86% of these sequences are accurately predicted by NetMHC or NetMHCpan. An additional retrospective analysis of a cancer immunogenicity study [Stronen et al., Science 2016] demonstrates that Ancer selects immunogenic neo-epitopes with 72% accuracy, as compared to 21% accuracy when using public prediction tools. These results demonstrate that Ancer may focus epitope candidate selection on higher value sequences than conventional algorithms. Class I and Class II neo-epitopes with low Treg activation potential may then be used to support the development of safer and more effective vaccines. Citation Format: Guilhem Richard, Lenny Moise, Matthew Ardito, Frances Terry, Gad Berdugo, William Martin, Anne De Groot. Integrated approaches for design of precision cancer immunotherapies: Selection of Class I and Class II T cell neo-epitopes and removal of Treg epitopes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5311.