Post-translational modification (PTM) of antigens provides an additional source of specificities targeted by immune responses to tumors or pathogens, but identifying antigen PTMs and assessing their role in shaping the immunopeptidome is challenging. Here we describe the Protein Modification Integrated Search Engine (PROMISE), an antigen discovery pipeline that enables the analysis of 29 different PTM combinations from multiple clinical cohorts and cell lines. We expanded the antigen landscape, uncovering human leukocyte antigen class I binding motifs defined by specific PTMs with haplotype-specific binding preferences and revealing disease-specific modified targets, including thousands of new cancer-specific antigens that can be shared between patients and across cancer types. Furthermore, we uncovered a subset of modified peptides that are specific to cancer tissue and driven by post-translational changes that occurred in the tumor proteome. Our findings highlight principles of PTM-driven antigenicity, which may have broad implications for T cell-mediated therapies in cancer and beyond.
Bibliographical noteFunding Information:
We thank the members of the Merbl lab, as well as A. Solomon, O. Bartok, G. Cafri, C. Cohen and M. Besser for scientific discussion and I. Cohen, A. Eisenberg-Lerner, J. DeMartino, C. Putterman, E. Zisman and A. Erez for critical reading of the manuscript. We would like to thank S. Meril for technical help and A. Erez for MC38 cells. Y.M. is supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 677748), the I-CORE Program of the Planning and Budgeting Committee, the Israel Science Foundation (grant nos. 1775/12 and 2109/18), the University of Michigan: UM/Israel Research Partnership Weizmann and the Moross Integrated Cancer Center (MICC). This research was partially supported by the Israeli Council for Higher Education (CHE) via the Weizmann Data Science Research Center and by a research grant from Madame Olga Klein—Astrachan. A.I.N. was supported by the US National Institutes of Health grants R01-GM-094231 and U24-CA210967. Y.M. is the incumbent of the Leonard and C. Berall Career Development Chair. A.K. was partially supported by the Israeli Council for Higher Education(CHE) via Weizmann Data Science Research Center and by the research grant from Madam Olga Klein Astrachan.
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