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Review
. 2020 Aug;8(2):e001111.
doi: 10.1136/jitc-2020-001111.

Antigen processing and presentation in cancer immunotherapy

Affiliations
Review

Antigen processing and presentation in cancer immunotherapy

Maxwell Y Lee et al. J Immunother Cancer. 2020 Aug.

Abstract

Background: Knowledge about and identification of T cell tumor antigens may inform the development of T cell receptor-engineered adoptive cell transfer or personalized cancer vaccine immunotherapy. Here, we review antigen processing and presentation and discuss limitations in tumor antigen prediction approaches.

Methods: Original articles covering antigen processing and presentation, epitope discovery, and in silico T cell epitope prediction were reviewed.

Results: Natural processing and presentation of antigens is a complex process that involves proteasomal proteolysis of parental proteins, transportation of digested peptides into the endoplasmic reticulum, loading of peptides onto major histocompatibility complex (MHC) class I molecules, and shuttling of peptide:MHC complexes to the cell surface. A number of T cell tumor antigens have been experimentally validated in patients with cancer. Assessment of predicted MHC class I binding and total score for these validated T cell antigens demonstrated a wide range of values, with nearly one-third of validated antigens carrying an IC50 of greater than 500 nM.

Conclusions: Antigen processing and presentation is a complex, multistep process. In silico epitope prediction techniques can be a useful tool, but comprehensive experimental testing and validation on a patient-by-patient basis may be required to reliably identify T cell tumor antigens.

Keywords: T-lymphocytes; antigen presentation; antigens; immunotherapy; neoplasm.

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Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1
Performance of in silico predictions in validated T cell antigens. (A) Dot plots of predicted MHC IC50 for a panel of validated T cell antigens. A reference level of IC50 500 nM is provided to delineate a common cut-off score used by researchers. (B) Scatterplot of MHC IC50 and total prediction score showing a linear correlation (Pearson correlation, p<0.001). (C) Scatterplots of predicted MHC IC50 and total score between wild-type and mutant peptides for validated neoepitopes. MHC, major histocompatibility complex.

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