About this Research Topic
High quality anti-tumor T cell responses are highly dependent on neoepitope presentation. Tumors with high mutational loads, thus presenting diverse neoepitope repertoires, elicit the greatest T cell responses and correlate with good patient prognosis in response to immunotherapies. Prediction and characterisation of the neoepitope repertoire of various cancers is an important step in identifying tumor specific targets for immunotherapies, particularly given the unique nature of the neoepitope repertoire between individuals and tumors. Currently, the predicted neoepitope landscape is very large, while T cell reactivity studies demonstrate only a few neoepitopes to be immunogenic. This disparity between neoepitope immunogenicity and neoepitope discovery necessitates the identification of better neopeitope prediction algorithms that can encompass immunogenicity together with proteomic identification and validation of neoepitopes presented by individual cancers. Understanding the properties of immunogenic neoepitopes through the characterisation of T cell responses to tumors and their antigens is essential for translating neoepitope predictions into efficacious immunotherapies in the clinic.
This Research Topic will give a comprehensive overview of current methods used to predict and identify neoepitopes and the validation of neoepitope identification through the characterization of TCRs and T cell responses to neoantigens, including but not limited to:
1. Computational methods for neoepitope prediction.
2. Structural biology of neoepitope presentation and TCR recognition by MHC I and MHC II systems.
3. Characterization of T cell responses to neoepitopes.
4. Proteomic approaches to neoepitope discovery.
5. Identification of neoepitope specific TCRs and characterisation of anti-tumor TCR repertoires.
6. Characterization of tumor neoepitope landscapes.
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