Effects of thymic selection on T cell recognition of foreign and tumor antigenic peptides

Jason T. George, David A. Kessler, Herbert Levine

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

The advent of cancer immunotherapy has generated renewed hope for the treatment of many malignancies by introducing a number of novel strategies that exploit various properties of the immune system. These therapies are based on the idea that cytotoxic T lymphocytes (CTLs) directly recognize and respond to tumor-associated neoantigens (TANs) in much the same way as they would to foreign peptides presented on cell surfaces. To date, however, nearly all attempts to optimize immunotherapeutic strategies have been empirical. Here, we develop a model of T cell selection based on the assumption of random interaction strengths between a self-peptide and the various T cell receptors. The model enables the analytical study of the effects of selection on the CTL recognition of TANs and completely foreign peptides and can estimate the number of CTLs that can detect donor-matched transplants. We show that negative selection thresholds chosen to reflect experimentally observed thymic survival rates result in near-optimal production of T cells that are capable of surviving selection and recognizing foreign antigen. These analytical results are confirmed by simulation.

Original languageEnglish
Pages (from-to)E7875-E7881
JournalProceedings of the National Academy of Sciences of the United States of America
Volume114
Issue number38
DOIs
StatePublished - 19 Sep 2017

Bibliographical note

Publisher Copyright:
© 2017, National Academy of Sciences. All rights reserved.

Funding

ACKNOWLEDGMENTS. We thank Philip A. Ernst for critical reading of the manuscript and Haven R. Garber and Jeffrey J. Molldrem for helpful discussions. J.T.G. is supported by National Cancer Institute of the NIH Grant F30CA213878. D.A.K. is supported by United States–Israel Binational Science Foundation Grant 2015619. H.L. is supported by Cancer Prevention and Research Institute of Texas Scholars Program R1111.

FundersFunder number
Cancer Prevention and Research Institute of Texas Scholars ProgramR1111
National Institutes of Health
National Cancer InstituteF30CA213878
United States-Israel Binational Science Foundation2015619

    Keywords

    • Applied probability
    • Immunotherapy
    • Neoantigen
    • T cell

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