{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T12:59:07Z","timestamp":1769086747998,"version":"3.49.0"},"reference-count":55,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2026,1,11]],"date-time":"2026-01-11T00:00:00Z","timestamp":1768089600000},"content-version":"vor","delay-in-days":10,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31870829"],"award-info":[{"award-number":["31870829"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"The 2024 STCSM \u2018Science and Technology Innovation Action Plan\u2019 Computational Biology Program in Shanghai","award":["24JS2840300"],"award-info":[{"award-number":["24JS2840300"]}]},{"name":"National Center of Technology Innovation for Biopharmaceuticals in China","award":["NCTIB2022HS02007"],"award-info":[{"award-number":["NCTIB2022HS02007"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The ability of T-cell receptors (TCRs) to recognize neoantigens is fundamental to the initiation and maintenance of adaptive immune responses. In TCR-based immunotherapies, elucidating the recognition patterns of TCRs for peptides and accurately identifying therapeutically relevant TCR-peptide pairs remain critical challenges. Here, we present a novel dual-pathway network model, ProTCR, which integrates the protein language model ProtT5 with deep learning methods. By incorporating both global and local feature extraction mechanisms, ProTCR enables efficient representation of amino acid sequences, thereby enhancing the model\u2019s generalizability across diverse data distributions and improving its biological interpretability. ProTCR demonstrates robust performance and broad applicability across various datasets, including neoantigens, previously unseen peptides, and MHC class II-restricted epitopes, overcoming the reliance on known peptide-TCR pairs observed in previous studies. It also offers new insights for predicting diverse classes of antigenic peptides. We applied ProTCR to several clinically relevant scenarios, including immunotherapeutic target identification in acute myeloid leukemia, neoantigen-targeted immunotherapy in solid tumours, and antigen-specific T cell recognition against pathogens such as influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Across these complex settings, ProTCR consistently maintained high accuracy and stability, demonstrating strong cross-task adaptability and broad potential for clinical application. This work not only provides a powerful tool for elucidating immune response mechanisms but also offers a solid computational foundation for the design of neoantigen or TCR based precision immunotherapy strategies.<\/jats:p>","DOI":"10.1093\/bib\/bbaf716","type":"journal-article","created":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T12:34:40Z","timestamp":1766406880000},"source":"Crossref","is-referenced-by-count":0,"title":["ProTCR: a protein language model-driven framework for decoding TCR-antigen recognition toward precision immunotherapies"],"prefix":"10.1093","volume":"27","author":[{"given":"Minrui","family":"Xu","sequence":"first","affiliation":[{"name":"Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies , Shanghai 200237 ,","place":["China"]},{"name":"School of Health Science and Engineering, University of Shanghai for Science and Technology , Shanghai 200093 ,","place":["China"]}]},{"given":"Manman","family":"Lu","sequence":"additional","affiliation":[{"name":"Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies , Shanghai 200237 ,","place":["China"]},{"name":"College of Food Science and Technology, Shanghai Ocean University , Shanghai 201306 ,","place":["China"]}]},{"given":"Peng","family":"Liu","sequence":"additional","affiliation":[{"name":"Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies , Shanghai 200237 ,","place":["China"]}]},{"given":"Siwen","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies , Shanghai 200237 ,","place":["China"]},{"name":"Shanghai Institute for Biomedical and Pharmaceutical Technologies, School of Public Health, Fudan University , Shanghai 200237 ,","place":["China"]}]},{"given":"Lanming","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Food Science and Technology, Shanghai Ocean University , Shanghai 201306 ,","place":["China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2578-1221","authenticated-orcid":false,"given":"Qi","family":"Liu","sequence":"additional","affiliation":[{"name":"Bioinformatics Department, School of Life Sciences and Technology, Tongji University , Shanghai 200092 ,","place":["China"]}]},{"given":"Yong","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Health Science and Engineering, University of Shanghai for Science and Technology , Shanghai 200093 ,","place":["China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7541-2243","authenticated-orcid":false,"given":"Lu","family":"Xie","sequence":"additional","affiliation":[{"name":"Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies , Shanghai 200237 ,","place":["China"]},{"name":"Shanghai Institute for Biomedical and Pharmaceutical Technologies, School of Public Health, Fudan University , Shanghai 200237 ,","place":["China"]}]}],"member":"286","published-online":{"date-parts":[[2026,1,11]]},"reference":[{"key":"2026011104411002000_ref1","doi-asserted-by":"publisher","first-page":"623","DOI":"10.1038\/s41587-024-02248-6","article-title":"High-throughput discovery of MHC class I- and II-restricted T cell epitopes using synthetic cellular circuits","volume":"43","author":"Kohlgruber","year":"2025","journal-title":"Nat Biotechnol."},{"key":"2026011104411002000_ref2","doi-asserted-by":"publisher","first-page":"1345","DOI":"10.1038\/s41590-023-01543-9","article-title":"Neoantigen-specific stem cell memory-like CD4(+) T cells mediate CD8(+) T cell-dependent immunotherapy of MHC class II-negative solid tumors","volume":"24","author":"Brightman","year":"2023","journal-title":"Nat 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