{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T14:14:13Z","timestamp":1778595253129,"version":"3.51.4"},"reference-count":64,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T00:00:00Z","timestamp":1724371200000},"content-version":"vor","delay-in-days":29,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005046","name":"Natural Science Foundation of Heilongjiang Province of China","doi-asserted-by":"crossref","award":["LH2022F012"],"award-info":[{"award-number":["LH2022F012"]}],"id":[{"id":"10.13039\/501100005046","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"China National Natural Science Foundation","doi-asserted-by":"crossref","award":["82073800"],"award-info":[{"award-number":["82073800"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"China National Natural Science Foundation","doi-asserted-by":"crossref","award":["62172121"],"award-info":[{"award-number":["62172121"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,25]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The T cell receptor (TCR) repertoire is pivotal to the human immune system, and understanding its nuances can significantly enhance our ability to forecast cancer-related immune responses. However, existing methods often overlook the intra- and inter-sequence interactions of T cell receptors (TCRs), limiting the development of sequence-based cancer-related immune status predictions. To address this challenge, we propose BertTCR, an innovative deep learning framework designed to predict cancer-related immune status using TCRs. BertTCR combines a pre-trained protein large language model with deep learning architectures, enabling it to extract deeper contextual information from TCRs. Compared to three state-of-the-art sequence-based methods, BertTCR improves the AUC on an external validation set for thyroid cancer detection by 21 percentage points. Additionally, this model was trained on over 2000 publicly available TCR libraries covering 17 types of cancer and healthy samples, and it has been validated on multiple public external datasets for its ability to distinguish cancer patients from healthy individuals. Furthermore, BertTCR can accurately classify various cancer types and healthy individuals. Overall, BertTCR is the advancing method for cancer-related immune status forecasting based on TCRs, offering promising potential for a wide range of immune status prediction tasks.<\/jats:p>","DOI":"10.1093\/bib\/bbae420","type":"journal-article","created":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T23:30:13Z","timestamp":1724455813000},"source":"Crossref","is-referenced-by-count":18,"title":["BertTCR: a Bert-based deep learning framework for predicting cancer-related immune status based on T cell receptor repertoire"],"prefix":"10.1093","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9928-5189","authenticated-orcid":false,"given":"Min","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Intelligent Systems Science and Engineering , , No. 145 Nantong Street, Nangang District, Harbin, 150001 , China"},{"name":"Harbin Engineering University , , No. 145 Nantong Street, Nangang District, Harbin, 150001 , China"}]},{"given":"Qi","family":"Cheng","sequence":"additional","affiliation":[{"name":"College of Intelligent Systems Science and Engineering , , No. 145 Nantong Street, Nangang District, Harbin, 150001 , China"},{"name":"Harbin Engineering University , , No. 145 Nantong Street, Nangang District, Harbin, 150001 , China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-2950-2560","authenticated-orcid":false,"given":"Zhenyu","family":"Wei","sequence":"additional","affiliation":[{"name":"College of Intelligent Systems Science and Engineering , , No. 145 Nantong Street, Nangang District, Harbin, 150001 , China"},{"name":"Harbin Engineering University , , No. 145 Nantong Street, Nangang District, Harbin, 150001 , China"}]},{"given":"Jiayu","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Intelligent Systems Science and Engineering , , No. 145 Nantong Street, Nangang District, Harbin, 150001 , China"},{"name":"Harbin Engineering University , , No. 145 Nantong Street, Nangang District, Harbin, 150001 , China"}]},{"given":"Shiwei","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Intelligent Systems Science and Engineering , , No. 145 Nantong Street, Nangang District, Harbin, 150001 , China"},{"name":"Harbin Engineering University , , No. 145 Nantong Street, Nangang District, Harbin, 150001 , China"}]},{"given":"Nan","family":"Xu","sequence":"additional","affiliation":[{"name":"Institute of Biomedical Engineering and Technology , Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, , No. 500 Dongchuan Road, Shanghai, 200241 , China"},{"name":"East China Normal University , Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, , No. 500 Dongchuan Road, Shanghai, 200241 , China"},{"name":"Shanghai Unicar-Therapy Bio-medicine Technology Co., Ltd , No. 1525 Minqiang Road, Shanghai, 201612 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4328-466X","authenticated-orcid":false,"given":"Chengkui","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Intelligent Systems Science and Engineering , , No. 145 Nantong Street, Nangang District, Harbin, 150001 , China"},{"name":"Harbin Engineering University , , No. 145 Nantong Street, Nangang District, Harbin, 150001 , China"},{"name":"Shanghai Unicar-Therapy Bio-medicine Technology Co., Ltd , No. 1525 Minqiang Road, Shanghai, 201612 , China"}]},{"given":"Lei","family":"Yu","sequence":"additional","affiliation":[{"name":"Institute of Biomedical Engineering and Technology , Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, , No. 500 Dongchuan Road, Shanghai, 200241 , China"},{"name":"East China Normal University , Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, , No. 500 Dongchuan Road, Shanghai, 200241 , China"},{"name":"Shanghai Unicar-Therapy Bio-medicine Technology Co., Ltd , No. 1525 Minqiang Road, Shanghai, 201612 , China"}]},{"given":"Weixing","family":"Feng","sequence":"additional","affiliation":[{"name":"College of Intelligent Systems Science and Engineering , , No. 145 Nantong Street, Nangang District, Harbin, 150001 , China"},{"name":"Harbin Engineering University , , No. 145 Nantong Street, Nangang District, Harbin, 150001 , China"}]}],"member":"286","published-online":{"date-parts":[[2024,8,23]]},"reference":[{"key":"2024082311182225400_ref1","doi-asserted-by":"crossref","DOI":"10.3390\/cancers11091235","article-title":"Cancer diagnosis using deep learning: a bibliographic review","volume":"11","author":"Munir","year":"2019","journal-title":"Cancers (Basel)"},{"key":"2024082311182225400_ref2","article-title":"Characteristics and clinical significance of T-cell receptor 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