Molecular mimicry as a key parameter shaping T cell immunity

Scientific Challenge

Immunotherapy has revolutionized cancer treatment, yet only a minor fraction of patients respond to frequently used immunotherapeutic treatments. T cell recognition of peptide-major histocompatibility (pMHC) class I complexes is essential to maintain immune surveillance and eliminate cancerous cells. Numerous products of genetic and epigenetic alterations can serve as targets for T cell recognition of cancer.

However, our capacity to predict what MHC-embedded targets T cells can recognize on the surface of cancer cells is still poor, with a less than 5% hit rate. While we have robust tools for the prediction of antigen presentation, we still have very limited understanding of the factors driving immunogenicity, i.e., which of the presented targets will give rise to T cell recognition.

Molecular Mimicry

A fundamental mechanism influencing T cell recognition is molecular mimicry. It has long been proposed that the ability of a given T-cell receptor (TCR) to recognize multiple different pMHC complexes is essential to provide immunological coverage of all potential pathogens that we may encounter.

T cell epitopes that, at first glance, appear very different may have structural similarities once embedded in the MHC I binding groove, and hence appear similar to the given TCR (molecular mimicry).

Objective

In MIMIC, I will determine the role of molecular mimicry in T cell recognition and demonstrate how pre-existing immunity may shape the T cell recognition of cancer antigens. I will use the SARS-CoV2 infection as a model system to understand molecular mimicry and apply the learnings from this to cancer immunogenicity.

Expected Outcome

I predict that by understanding the influence of molecular mimicry, the rules governing the immunogenicity of T cell epitopes can be determined, and the selection of antigens optimized. This will be essential to develop precision T cell therapies targeting tumor antigens of relevance for the individual patient.