Characterizing neoantigens for personalized cancer immunotherapy

- Mutations (neoantigens) are driving protective anti-tumor T cell immunity.
- Neoantigens are promising targets for cancer immunotherapy including vaccines.
- A small fraction of mutations are immunogenic, their identification requires bioinformatics methods.
- Further characterization of neoantigens is needed to improve prediction algorithms.

Somatic mutations can generate neoantigens that are presented on MHC molecules and drive effective T cells responses against cancer. Mutation load in cancer patients predicts response to immune checkpoint blockade therapy. Additionally, vaccination targeting neoantigens controls established tumor growth in preclinical models. These recent findings led to a renewed interest in the field of cancer vaccines and the development of antigen-targeted cancer immunotherapies. However, targeting neoantigens is challenging, as most mutations are unique to each cancer patient. In addition, only a small fraction of the mutations are immunogenic and therefore their accurate prediction is critical. In this review, we discuss the properties of neoantigens that influence their immunogenicity, along with questions that remain to be addressed in order to improve prediction algorithms.