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3348 Structural Determinants of Neoantigen Immunogenicity for Cancer Therapy

Published online by Cambridge University Press:  26 March 2019

Jason Devlin
Affiliation:
University of Notre Dame
Sara Bobisse
Affiliation:
University of Lausanne, Lausanne, Switzerland
Alexandre Harari
Affiliation:
University of Lausanne, Lausanne, Switzerland
Brian Baker
Affiliation:
University of Notre Dame
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Abstract

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OBJECTIVES/SPECIFIC AIMS: We are exploring the structure of the interaction between an immunogenic neoantigen and a T cell receptor (TCR) that recognizes the neoantigen while tolerating the counterpart self antigen. No structural example exists to date of how a TCR can discriminate between a neoantigen and the self antigen. We aim to determine the structural and biophysical features that underlie the immunogenicity for this neoantigen, and the features we determine are likely to be present in other immunogenic neoantigens. Algorithms to predict the immunogenicity of neoantigens are available, but do not incorporate structural or biophysical factors. We aim to improve these methods for immunogenic neoantigen prediction by determining structural and biophysical factors that result in recognition by the immune system. METHODS/STUDY POPULATION: Recombinant protein expression, production, and purification. Protein x-ray crystallography. Biophysical protein-protein binding experiments RESULTS/ANTICIPATED RESULTS: The T cell receptor (TCR) bound to the neoantigen with an affinity 15-fold higher than the self antigen. The leucine to phenylalanine mutation occurs at position 8 of a 9-amino acid long peptide antigen. This position is typically in the interface bound by the T cell receptor. The structures of the unbound neoantigen and self antigen showed that the mutated residue was in the TCR interface. Additionally we noted a change in the side chain position of a proximal tryptophan, potentially due to clashes with the larger phenylalanine residue. The structure of the TCR bound to the neoantigen showed that the TCR interacted with the tryptophan in the mutation-induced conformation and with the phenylalanine residue. Thus the mutation may be altering TCR binding affinity by interactions of the residue itself with the TCR, and by locking the proximal tryptophan residue in an optimal position to interact with the TCR. We are testing the contributions of each of these factors to the overall affinity change. Hydrophobicity has been linked to immunogenicity, so mutations that increase hydrophobicity compared to the self antigen are likely to be immunogenic. However, leucine and phenylalanine are similar on hydrophobicity scales. On the other hand, a side chain rotation is unlikely to represent a large energy barrier. Therefore, we hypothesize that another property of the phenylalanine, such as size or aromaticity, is driving the affinity difference. DISCUSSION/SIGNIFICANCE OF IMPACT: Traditional forms of cancer therapy do not specifically target cancer cells, and their toxicity to healthy cells limits their effectiveness. Immunotherapy, which involves orchestrating a specific anti-cancer immune response, is now an established cancer therapy. Several forms of immunotherapy target “neoantigens,” which are derived from mutated proteins in cancer, and are therefore are cancer-specific. Neoantigens represent a foothold that can allow the immune system to distinguish between cancer cells and healthy cells, and thus specifically target cancer cells for destruction while imparting no activity toward healthy cells that lack the neoantigen. Most cancer mutations that result in neoantigens arise from random passenger mutations in cancer and will be different among patients. Neoantigen-based cancer therapies are thus a precision medicine technique. The quality of neoantigens to induce an immune response (immunogenicity), which relates to how likely they are to be presented to the immune system and recognized as foreign, has been shown to be a critical factor in predicting the outcome of immunotherapy treatment. We are investigating, on a structural and biophysical level, features that may increase the likelihood of a neoantigen being recognized as foreign by the immune system. The structural insight we gain can be incorporated into algorithms that predict neoantigens from cancer exome sequencing for patient-specific identification of immunogenic neoantigens for immunotherapeutic intervention.

Type
Basic/Translational Science/Team Science
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-ncnd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Association for Clinical and Translational Science 2019