抗原
人类白细胞抗原
计算生物学
癌症免疫疗法
免疫疗法
肿瘤抗原
癌症
质谱法
免疫系统
癌症研究
生物
免疫学
化学
遗传学
色谱法
作者
Naomi Hoenisch Gravel,Annika Nelde,Jens Bauer,Lena Mühlenbruch,Sarah M. Schroeder,Marian C. Neidert,Jonas Scheid,Steffen Lemke,Marissa L. Dubbelaar,Marcel Wacker,Anna Dengler,Reinhild Klein,Paul‐Stefan Mauz,Hubert Löwenheim,Mathias Hauri‐Hohl,Roland Martinꝉ,Jörg Hennenlotter,Arnulf Stenzl,Jonas S. Heitmann,Helmut R. Salih,Hans‐Georg Rammensee,Juliane S. Walz
标识
DOI:10.1038/s41467-023-42692-7
摘要
Abstract T cell recognition of human leukocyte antigen (HLA)-presented tumor-associated peptides is central for cancer immune surveillance. Mass spectrometry (MS)-based immunopeptidomics represents the only unbiased method for the direct identification and characterization of naturally presented tumor-associated peptides, a key prerequisite for the development of T cell-based immunotherapies. This study reports on the implementation of ion mobility separation-based time-of-flight (TOF IMS ) MS for next-generation immunopeptidomics, enabling high-speed and sensitive detection of HLA-presented peptides. Applying TOF IMS -based immunopeptidomics, a novel extensive benign TOFIMS dataset was generated from 94 primary benign samples of solid tissue and hematological origin, which enabled the expansion of benign reference immunopeptidome databases with > 150,000 HLA-presented peptides, the refinement of previously described tumor antigens, as well as the identification of frequently presented self antigens and not yet described tumor antigens comprising low abundant mutation-derived neoepitopes that might serve as targets for future cancer immunotherapy development.
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