{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T17:46:29Z","timestamp":1793295989962,"version":"4.5.0"},"reference-count":73,"publisher":"BMJ","issue":"4","license":[{"start":{"date-parts":[[2025,4,15]],"date-time":"2025-04-15T00:00:00Z","timestamp":1744675200000},"content-version":"unspecified","delay-in-days":14,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Applied Clinical Research program"},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"crossref","award":["DFG Grant WA4608\/1-2"],"award-info":[{"award-number":["DFG Grant WA4608\/1-2"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Deutsche Forschungsgemeinschaft under Germany\u2018s Excellence Strategy","award":["EXC2180"],"award-info":[{"award-number":["EXC2180"]}]},{"name":"Deutsche Forschungsgemeinschaft under Germany\u2018s Excellence Strategy","award":["EXC2180-390900677"],"award-info":[{"award-number":["EXC2180-390900677"]}]},{"DOI":"10.13039\/501100005972","name":"Deutsche Krebshilfe","doi-asserted-by":"crossref","award":["70114948"],"award-info":[{"award-number":["70114948"]}],"id":[{"id":"10.13039\/501100005972","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100005677","name":"Jos\u00e9 Carreras Leuk\u00e4mie-Stiftung","doi-asserted-by":"publisher","award":["Grant DJCLS 05 R\/2017"],"award-info":[{"award-number":["Grant DJCLS 05 R\/2017"]}],"id":[{"id":"10.13039\/501100005677","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Zentrum f\u00fcr Personalisierte Medizin"},{"DOI":"10.13039\/501100012353","name":"German Cancer Consortium","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100012353","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Wilhelm Sander Stiftung","award":["Grant 2016.177.3"],"award-info":[{"award-number":["Grant 2016.177.3"]}]},{"name":"Ernst Jung Prize for Medicine"},{"name":"Landesforschungspreis of Baden-W\u00fcrttemberg"},{"name":"ForTra gGmbH of the Else Kr\u00f6ner Fresenius Stiftung, Translatorik Programm","award":["Grant 2022_EKTP03"],"award-info":[{"award-number":["Grant 2022_EKTP03"]}]}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["J Immunother Cancer"],"accepted":{"date-parts":[[2025,3,20]]},"published-print":{"date-parts":[[2025,4]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Various cancer immunotherapies rely on the T cell-mediated recognition of peptide antigens presented on human leukocyte antigens (HLA). However, the identification and selection of naturally presented peptide targets for the development of personalized as well as off-the-shelf immunotherapy approaches remain challenging.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Over 10,000 raw mass spectrometry (MS) files from over 3,000 tissue samples were analyzed, summing to approximately seven terabytes of data. The raw MS data were processed using the standardized and open-source nf-core pipelines MHCquant2 and epitopeprediction, providing a uniform procedure for data handling. A global false discovery rate was applied to minimize false-positive identifications.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Here, we introduce the open-access Peptides for Cancer Immunotherapy Database (PCI-DB,\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/pci-db.org\/\">https:\/\/pci-db.org\/<\/jats:ext-link>\n                      ), a comprehensive resource of immunopeptidome data originating from various malignant and benign primary tissues that provides the research community with a convenient tool to facilitate the identification of peptide targets for immunotherapy development. The PCI-DB includes &gt;6.6\u2009million HLA class I and &gt;3.4\u2009million HLA class II peptides from over 40 tissue types and cancer entities. First application of the database provided insights into the representation of cancer-testis antigens across malignant and benign tissues, enabling the identification and characterization of cross-tumor entity and entity-specific tumor-associated antigens (TAAs) as well as naturally presented neoepitopes from frequent cancer mutations. Further, we used the PCI-DB to design personalized peptide vaccines for two patients suffering from metastatic cancer. In a retrospective analysis, PCI-DB enabled the composition of both a multi-peptide vaccine comprising non-mutated, highly frequent TAAs matching the immunopeptidome of the individual patient\u2019s tumor and a neoepitope-based vaccine matching the mutational profile of a patient with cancer. Both vaccine approaches induced potent and long-lasting T-cell responses, accompanied by long-term survival of these patients with advanced cancer.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The PCI-DB provides a highly versatile tool to broaden the understanding of cancer-related antigen presentation and, ultimately, supports the development of novel immunotherapies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/jitc-2024-011366","type":"journal-article","created":{"date-parts":[[2025,4,15]],"date-time":"2025-04-15T21:05:17Z","timestamp":1744751117000},"page":"e011366","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":15,"title":["PCI-DB: a novel primary tissue immunopeptidome database to guide next-generation peptide-based immunotherapy development"],"prefix":"10.1136","volume":"13","clinical-trial-number":[{"clinical-trial-number":"nct05014607","registry":"10.18810\/clinical-trials-gov"}],"author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-8121-082X","authenticated-orcid":false,"given":"Steffen","family":"Lemke","sequence":"first","affiliation":[{"name":"Department of Peptide-based Immunotherapy, Institute of Immunology, University and University Hospital T\u00fcbingen, T\u00fcbingen, BW, Germany"},{"name":"Cluster of Excellence iFIT (EXC2180) \u201cImage-Guided and Functionally Instructed Tumor Therapies\u201d, University of T\u00fcbingen, T\u00fcbingen, BW, Germany"},{"name":"Quantitative Biology Center (QBiC), University of T\u00fcbingen, T\u00fcbingen, BW, Germany"},{"name":"Department of Computer Science, University of T\u00fcbingen, T\u00fcbingen, BW, Germany"},{"name":"Institute for Bioinformatics and Medical Informatics (IBMI), University of T\u00fcbingen, T\u00fcbingen, BW, 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\u201cImage-Guided and Functionally Instructed Tumor Therapies\u201d, University of T\u00fcbingen, T\u00fcbingen, BW, Germany"},{"name":"German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), partner site T\u00fcbingen, T\u00fcbingen, BW, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jens","family":"Bauer","sequence":"additional","affiliation":[{"name":"Department of Peptide-based Immunotherapy, Institute of Immunology, University and University Hospital T\u00fcbingen, T\u00fcbingen, BW, Germany"},{"name":"Cluster of Excellence iFIT (EXC2180) \u201cImage-Guided and Functionally Instructed Tumor Therapies\u201d, University of T\u00fcbingen, T\u00fcbingen, BW, Germany"},{"name":"German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), partner site T\u00fcbingen, T\u00fcbingen, BW, 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