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  1. Article ; Online: Molecular mechanism of phosphopeptide neoantigen immunogenicity

    Yury Patskovsky / Aswin Natarajan / Larysa Patskovska / Samantha Nyovanie / Bishnu Joshi / Benjamin Morin / Christine Brittsan / Olivia Huber / Samuel Gordon / Xavier Michelet / Florian Schmitzberger / Robert B. Stein / Mark A. Findeis / Andy Hurwitz / Marc Van Dijk / Jennifer S. Buell / Dennis Underwood / Michelle Krogsgaard

    Nature Communications, Vol 14, Iss 1, Pp 1-

    2023  Volume 18

    Abstract: Abstract Altered protein phosphorylation in cancer cells often leads to surface presentation of phosphopeptide neoantigens. However, their role in cancer immunogenicity remains unclear. Here we describe a mechanism by which an HLA-B*0702-specific acute ... ...

    Abstract Abstract Altered protein phosphorylation in cancer cells often leads to surface presentation of phosphopeptide neoantigens. However, their role in cancer immunogenicity remains unclear. Here we describe a mechanism by which an HLA-B*0702-specific acute myeloid leukemia phosphoneoantigen, pMLL747–755 (EPR(pS)PSHSM), is recognized by a cognate T cell receptor named TCR27, a candidate for cancer immunotherapy. We show that the replacement of phosphoserine P4 with serine or phosphomimetics does not affect pMHC conformation or peptide-MHC affinity but abrogates TCR27-dependent T cell activation and weakens binding between TCR27 and pMHC. Here we describe the crystal structures for TCR27 and cognate pMHC, map of the interface produced by nuclear magnetic resonance, and a ternary complex generated using information-driven protein docking. Our data show that non-covalent interactions between the epitope phosphate group and TCR27 are crucial for TCR specificity. This study supports development of new treatment options for cancer patients through target expansion and TCR optimization.
    Keywords Science ; Q
    Subject code 570
    Language English
    Publishing date 2023-06-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Murine xenograft bioreactors for human immunopeptidome discovery

    James M. Heather / Paisley T. Myers / Feng Shi / Mohammad Ovais Aziz-Zanjani / Keira E. Mahoney / Matthew Perez / Benjamin Morin / Christine Brittsan / Jeffrey Shabanowitz / Donald F. Hunt / Mark Cobbold

    Scientific Reports, Vol 9, Iss 1, Pp 1-

    2019  Volume 15

    Abstract: Abstract The study of peptides presented by MHC class I and class II molecules is limited by the need for relatively large cell numbers, especially when studying post-translationally modified or otherwise rare peptide species. To overcome this problem, ... ...

    Abstract Abstract The study of peptides presented by MHC class I and class II molecules is limited by the need for relatively large cell numbers, especially when studying post-translationally modified or otherwise rare peptide species. To overcome this problem, we pose the hypothesis that human cells grown as xenografts in immunodeficient mice should produce equivalent immunopeptidomes as cultured cells. Comparing human cell lines grown either in vitro or as murine xenografts, we show that the immunopeptidome is substantially preserved. Numerous features are shared across both sample types, including peptides and proteins featured, length distributions, and HLA-binding motifs. Peptides well-represented in both groups were from more abundant proteins, or those with stronger predicted HLA binding affinities. Samples grown in vivo also recapitulated a similar phospho-immunopeptidome, with common sequences being those found at high copy number on the cell surface. These data indicate that xenografts are indeed a viable methodology for the production of cells for immunopeptidomic discovery.
    Keywords Medicine ; R ; Science ; Q
    Subject code 570
    Language English
    Publishing date 2019-12-01T00:00:00Z
    Publisher Nature Publishing Group
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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