Neoepitope recognition in cancer mice models

The discovery of immune recognition of cancer implied the existence of a natural defence against malignant cells. This way, aiming to boost the body’s own immune cells to eliminate cancer – so called immunotherapy – is changing the paradigm of cancer treatment. Neoepitopes comprise tumor antigens arising from mutated gene products originated during tumor development. By being uniquely presented by cancer cells in the context of major histocompatibility complex (MHC) molecules, they allow T cells to distinguish between cancer and healthy cells. In addition, owing to their random mutation nature, neoepitopes are highly individual and are paving the way towards the development of fully tumor-specific and personalized immunotherapies. However, they require the use of computational tools to predict them from the tumor’s genomic data. While current algorithms can successfully identify naturally occurring neoepitopes, far from all are recognized by T cells, thus limiting the efficacy of neoepitope-based therapies. This way, prioritization of therapeutically relevant candidates presents a challenge, as the rules governing neoepitopes’ immunogenicity remain to be understood.
The work presented in this thesis explores CD8+ T cell neoepitope recognition in preclinical murine models, aiming to gain knowledge on the characteristics driving neoepitope immunogenicity.
In the first study, we characterized neoepitope-specific CD8+ T cells across the preclinical syngeneic tumor models EMT6, 4T1 and CT26. We employed a high-throughput DNA barcode labeled pH-2 multimer screening in spleens and/or tumors, resulting in experimental detection of 25, 15 and 18 neoepitopes respectively. These syngeneic tumor models are widely used for preclinical evaluation of immunotherapies. In addition, given that they are highly homogeneous in comparison to human tumors, mapping the neoepitope recognition landscape of such models may contribute to defining the determinants of neoepitope immunogenicity.
In the second study, we experimentally examined the influence of key parameters previously hypothesized to influence neoepitope immunogenicity. We immunized Balb/c naïve mice with short CT26 neoepitopes formulated in CAF09b adjuvant. The limited fraction of immunogenic peptides evidenced the need to evaluate larger peptide pools to confirm the observed differences across neoepitopes with distinct MHC-I binding capacity and self-similarity scores. This way, the substantial amount of “real life” data arising from on-going clinical trials of neoepitope-based immunotherapies may prove to be a better source compared to preclinical models, despite the great heterogeneity among cancer patients.
Finally, on the last Chapter I evaluated the antitumor reactivity of adoptively transferred SIINFEKL-specific CD8+ T cells in a B16BL6-OVA tumor model. This study served as a pilot study to evaluate the superior capacity of antigen (Ag)-scaffolds to expand murine OVA-specific CD8+ T cells. By mimicking the immunological synapse between T cells and Ag presenting cells, expansion with Ag-scaffolds rendered higher yields of SIINFEKL-specific CD8+ T cells with superior tumor control capacity. This framework is intended to be used to expand the neoepitope-specific CD8+ T cells detected in the first study and evaluate their tumor killing capacity in the relevant syngeneic tumor model.
Altogether, the research presented in this thesis contributes to the understanding of neoepitope immunogenicity in preclinical syngeneic models, which if translatable, will ultimately support the development of neoepitope-based immunotherapies in the clinic.