MEK inhibition enhances presentation of targetable MHC-I tumor antigens in mutant melanomas
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pnas.2208900119.pdf
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Published version
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1.44 MB
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Author(s) • • • • • • • •
Stopfer, Lauren E
Rettko, Nicholas J
Leddy, Owen
Mesfin, Joshua M
Brown, Eric
Winski, Shannon
Bryson, Bryan
Wells, James A
White, Forest M
Date Issued
December 6, 2022
Journal
Proceedings of the National Academy of Sciences
Publisher
Proceedings of the National Academy of Sciences
Citation
Stopfer, Lauren E, Rettko, Nicholas J, Leddy, Owen, Mesfin, Joshua M, Brown, Eric et al. 2022. "MEK inhibition enhances presentation of targetable MHC-I tumor antigens in mutant melanomas." Proceedings of the National Academy of Sciences, 119 (49).
Version
Final published version
Abstract
Combining multiple therapeutic strategies in NRAS/BRAF mutant melanoma—namely MEK/BRAF kinase inhibitors, immune checkpoint inhibitors (ICIs), and targeted immunotherapies—may offer an improved survival benefit by overcoming limitations associated with any individual therapy. Still, optimal combination, order, and timing of administration remains under investigation. Here, we measure how MEK inhibition (MEKi) alters anti-tumor immunity by utilizing quantitative immunopeptidomics to profile changes in the peptide major histocompatibility molecules (pMHC) repertoire. These data reveal a collection of tumor antigens whose presentation levels are selectively augmented following therapy, including several epitopes present at over 1,000 copies per cell. We leveraged the tunable abundance of MEKi-modulated antigens by targeting four epitopes with pMHC-specific T cell engagers and antibody drug conjugates, enhancing cell killing in tumor cells following MEK inhibition. These results highlight drug treatment as a means to enhance immunotherapy efficacy by targeting specific upregulated pMHCs and provide a methodological framework for identifying, quantifying, and therapeutically targeting additional epitopes of interest.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
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Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1073/pnas.2208900119