Pub Date : 2026-01-02DOI: 10.1038/s41551-025-01563-w
Jose Cabezas-Caballero, Anna Huhn, Mikhail A Kutuzov, Violaine Andre, Alina Shomuradova, Bas W A Peeters, Geraldine M Gillespie, P Anton van der Merwe, Omer Dushek
Adoptive T cell therapy using T cells engineered with novel T cell receptors (TCRs) targeting tumour-specific peptides is a promising immunotherapy. However, these TCR-T cells can cross-react with off-target peptides, leading to severe autoimmune toxicities. Current efforts focus on identifying TCRs with reduced cross-reactivity. Here we show that T cell cross-reactivity can be controlled by the co-signalling molecules CD5, CD8 and CD4, without modifying the TCR. We find the largest reduction in cytotoxic T cell cross-reactivity by knocking out CD8 and expressing CD4. Cytotoxic T cells engineered with a CD8→CD4 co-receptor switch show reduced cross-reactivity to random and positional scanning peptide libraries, as well as to self-peptides, while maintaining their on-target potency. Therefore, co-receptor switching generates super selective T cells that reduce the risk of lethal off-target cross-reactivity and offers a universal method to enhance the safety of T cell immunotherapies for potentially any TCR.
{"title":"Generation of T cells with reduced off-target cross-reactivities by engineering co-signalling receptors.","authors":"Jose Cabezas-Caballero, Anna Huhn, Mikhail A Kutuzov, Violaine Andre, Alina Shomuradova, Bas W A Peeters, Geraldine M Gillespie, P Anton van der Merwe, Omer Dushek","doi":"10.1038/s41551-025-01563-w","DOIUrl":"10.1038/s41551-025-01563-w","url":null,"abstract":"<p><p>Adoptive T cell therapy using T cells engineered with novel T cell receptors (TCRs) targeting tumour-specific peptides is a promising immunotherapy. However, these TCR-T cells can cross-react with off-target peptides, leading to severe autoimmune toxicities. Current efforts focus on identifying TCRs with reduced cross-reactivity. Here we show that T cell cross-reactivity can be controlled by the co-signalling molecules CD5, CD8 and CD4, without modifying the TCR. We find the largest reduction in cytotoxic T cell cross-reactivity by knocking out CD8 and expressing CD4. Cytotoxic T cells engineered with a CD8→CD4 co-receptor switch show reduced cross-reactivity to random and positional scanning peptide libraries, as well as to self-peptides, while maintaining their on-target potency. Therefore, co-receptor switching generates super selective T cells that reduce the risk of lethal off-target cross-reactivity and offers a universal method to enhance the safety of T cell immunotherapies for potentially any TCR.</p>","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":26.8,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7618719/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145892747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-02DOI: 10.1038/s41551-025-01564-9
Xuehao Xiu, Yi Wu, Jiangxue Li, Dongfa Lin, Xiao Sun, Xinglei Su, Zhi Weng, Xiaolei Zuo, Xiurong Yang, Chunhai Fan, Yudong Wang, David Yu Zhang, Ping Song
Identifying novel gene fusions is critical for cancer diagnosis and drug development. While a few advanced methods have shown the capability to detect gene fusions involving unknown partners, comprehensive detection of gene fusions, especially of those with low copy numbers, remains a challenge. Indeed, most current panel-based sequencing methods fall short in reliability and cost efficiency. Here we present a method for detecting potentially novel gene fusions using anchored random reverse primers (ARRP) during PCR-based library construction, allowing the simultaneous capture of mutations and RNA splicing variants. Furthermore, the combination with blocker displacement amplification technology enables a median of 22-fold allele enrichment for gene fusions, achieving a limit of detection ~10-fold lower than that of current technologies and resulting in an 8-fold cost reduction. Using ARRP-seq, we identify numerous novel fusions in 98 clinical tissue samples, showcasing its diagnostic potential in prostate cancer and capacity for personalized diagnostics in cervical cancer.
{"title":"Anchored random reverse primer sequencing for quantitative detection of novel gene fusions.","authors":"Xuehao Xiu, Yi Wu, Jiangxue Li, Dongfa Lin, Xiao Sun, Xinglei Su, Zhi Weng, Xiaolei Zuo, Xiurong Yang, Chunhai Fan, Yudong Wang, David Yu Zhang, Ping Song","doi":"10.1038/s41551-025-01564-9","DOIUrl":"https://doi.org/10.1038/s41551-025-01564-9","url":null,"abstract":"<p><p>Identifying novel gene fusions is critical for cancer diagnosis and drug development. While a few advanced methods have shown the capability to detect gene fusions involving unknown partners, comprehensive detection of gene fusions, especially of those with low copy numbers, remains a challenge. Indeed, most current panel-based sequencing methods fall short in reliability and cost efficiency. Here we present a method for detecting potentially novel gene fusions using anchored random reverse primers (ARRP) during PCR-based library construction, allowing the simultaneous capture of mutations and RNA splicing variants. Furthermore, the combination with blocker displacement amplification technology enables a median of 22-fold allele enrichment for gene fusions, achieving a limit of detection ~10-fold lower than that of current technologies and resulting in an 8-fold cost reduction. Using ARRP-seq, we identify numerous novel fusions in 98 clinical tissue samples, showcasing its diagnostic potential in prostate cancer and capacity for personalized diagnostics in cervical cancer.</p>","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":26.8,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145892782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-16DOI: 10.1038/s41551-025-01595-2
In this editorial, we feature several standout papers across disciplines published in Nature Biomedical Engineering in 2025.
在这篇社论中，我们将介绍2025年发表在《自然生物医学工程》上的几篇跨学科的杰出论文。
{"title":"2025 in review","authors":"","doi":"10.1038/s41551-025-01595-2","DOIUrl":"10.1038/s41551-025-01595-2","url":null,"abstract":"In this editorial, we feature several standout papers across disciplines published in Nature Biomedical Engineering in 2025.","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"9 12","pages":"2013-2014"},"PeriodicalIF":26.8,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41551-025-01595-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145761521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-10DOI: 10.1038/s41551-025-01569-4
Changrui Yang, Shanni Guo, Kaiyan Ye, Yizong Ding, Xingzhong Zhao, Yucheng T. Yang, Bowen Sun, Shuyi Qian, Mei-Chun Cai, Luyan Liu, Libing Xiang, Xia Yin, Xing-Ming Zhao, Jieyi Wang, Jiwei Zhang, Wen Di, Guanglei Zhuang, Fan Yang
Immunologically unresponsive tumours often resist immune checkpoint inhibitors due to the low abundance of tumour-specific T cells and an immunosuppressive microenvironment, despite pronounced infiltration of non-tumour-specific (bystander) T cells. Here we analysed single-cell RNA sequencing data from 300 patients across 17 tumour types, identifying abundant but functionally restrained bystander T cells in multiple malignancies, including ovarian and colorectal cancer. To enhance antitumour immunity in such contexts, we engineered B7H3xCD3xPDL1, a trispecific immunoglobulin-based T cell engager targeting B7H3, CD3 and PDL1, to redirect T cells while mitigating immunosuppression. Functional validation in co-culture systems, patient-derived tumour suspensions and fragments, and humanized mouse models showed T cell activation and tumour killing. Imaging cytometry and single-cell transcriptomics revealed IFNγ-dependent macrophage reprogramming and IL-15 secretion, establishing a feed-forward loop that augments T cell functionality. A machine learning model trained on ex vivo cytotoxicity and transcriptomic data predicted patient responsiveness, supporting data-driven clinical stratification for solid tumour immunotherapy.
{"title":"A trispecific antibody engaging T cells with tumour and myeloid cells augments antitumour immunity","authors":"Changrui Yang, Shanni Guo, Kaiyan Ye, Yizong Ding, Xingzhong Zhao, Yucheng T. Yang, Bowen Sun, Shuyi Qian, Mei-Chun Cai, Luyan Liu, Libing Xiang, Xia Yin, Xing-Ming Zhao, Jieyi Wang, Jiwei Zhang, Wen Di, Guanglei Zhuang, Fan Yang","doi":"10.1038/s41551-025-01569-4","DOIUrl":"https://doi.org/10.1038/s41551-025-01569-4","url":null,"abstract":"Immunologically unresponsive tumours often resist immune checkpoint inhibitors due to the low abundance of tumour-specific T cells and an immunosuppressive microenvironment, despite pronounced infiltration of non-tumour-specific (bystander) T cells. Here we analysed single-cell RNA sequencing data from 300 patients across 17 tumour types, identifying abundant but functionally restrained bystander T cells in multiple malignancies, including ovarian and colorectal cancer. To enhance antitumour immunity in such contexts, we engineered B7H3xCD3xPDL1, a trispecific immunoglobulin-based T cell engager targeting B7H3, CD3 and PDL1, to redirect T cells while mitigating immunosuppression. Functional validation in co-culture systems, patient-derived tumour suspensions and fragments, and humanized mouse models showed T cell activation and tumour killing. Imaging cytometry and single-cell transcriptomics revealed IFNγ-dependent macrophage reprogramming and IL-15 secretion, establishing a feed-forward loop that augments T cell functionality. A machine learning model trained on ex vivo cytotoxicity and transcriptomic data predicted patient responsiveness, supporting data-driven clinical stratification for solid tumour immunotherapy.","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"144 1","pages":""},"PeriodicalIF":28.1,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145711553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-08DOI: 10.1038/s41551-025-01536-z
Guy H Wilson,Elias A Stein,Foram Kamdar,Donald T Avansino,Tsam Kiu Pun,Ronnie Gross,Tommy Hosman,Tyler Singer-Clark,Anastasia Kapitonava,Leigh R Hochberg,John D Simeral,Krishna V Shenoy,Shaul Druckmann,Jaimie M Henderson,Francis R Willett
Intracortical brain-computer interfaces (iBCIs) require frequent recalibration to maintain robust performance due to changes in neural activity that accumulate over time, which result in periods when users cannot use their device. Here we introduce a hidden Markov model to infer which targets users are moving towards during iBCI use and we retrain the system using these inferred targets, enabling unsupervised adaptation to changing neural activity. Our approach outperforms distribution alignment methods in large-scale, closed-loop simulations over two months, as well as in a closed loop with a human iBCI user over one month. Leveraging an offline dataset spanning five years of iBCI recordings, we show how target inference recalibration methods appear capable of long-term unsupervised recalibration, whereas recently proposed data-distribution-matching approaches appear to accumulate compounding errors over time. We show offline that our approach performs well on freeform datasets of a person using a home computer with an iBCI. Our results demonstrate the use of task structure to bootstrap a noisy decoder into a highly performant one, thereby overcoming one of the major barriers to clinically translating BCIs.
{"title":"Long-term unsupervised recalibration of cursor-based intracortical brain-computer interfaces using a hidden Markov model.","authors":"Guy H Wilson,Elias A Stein,Foram Kamdar,Donald T Avansino,Tsam Kiu Pun,Ronnie Gross,Tommy Hosman,Tyler Singer-Clark,Anastasia Kapitonava,Leigh R Hochberg,John D Simeral,Krishna V Shenoy,Shaul Druckmann,Jaimie M Henderson,Francis R Willett","doi":"10.1038/s41551-025-01536-z","DOIUrl":"https://doi.org/10.1038/s41551-025-01536-z","url":null,"abstract":"Intracortical brain-computer interfaces (iBCIs) require frequent recalibration to maintain robust performance due to changes in neural activity that accumulate over time, which result in periods when users cannot use their device. Here we introduce a hidden Markov model to infer which targets users are moving towards during iBCI use and we retrain the system using these inferred targets, enabling unsupervised adaptation to changing neural activity. Our approach outperforms distribution alignment methods in large-scale, closed-loop simulations over two months, as well as in a closed loop with a human iBCI user over one month. Leveraging an offline dataset spanning five years of iBCI recordings, we show how target inference recalibration methods appear capable of long-term unsupervised recalibration, whereas recently proposed data-distribution-matching approaches appear to accumulate compounding errors over time. We show offline that our approach performs well on freeform datasets of a person using a home computer with an iBCI. Our results demonstrate the use of task structure to bootstrap a noisy decoder into a highly performant one, thereby overcoming one of the major barriers to clinically translating BCIs.","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"79 1","pages":""},"PeriodicalIF":28.1,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145704661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-04DOI: 10.1038/s41551-025-01567-6
{"title":"A bioorthogonal ligation system induces controlled proximity for cancer therapy.","authors":"","doi":"10.1038/s41551-025-01567-6","DOIUrl":"https://doi.org/10.1038/s41551-025-01567-6","url":null,"abstract":"","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"10 1","pages":""},"PeriodicalIF":28.1,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145674447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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