1
|
Zhang M, Cheng Q, Wei Z, Xu J, Wu S, Xu N, Zhao C, Yu L, Feng W. BertTCR: a Bert-based deep learning framework for predicting cancer-related immune status based on T cell receptor repertoire. Brief Bioinform 2024; 25:bbae420. [PMID: 39177262 PMCID: PMC11342255 DOI: 10.1093/bib/bbae420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Revised: 07/24/2024] [Accepted: 08/08/2024] [Indexed: 08/24/2024] Open
Abstract
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.
Collapse
Affiliation(s)
- Min Zhang
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, No. 145 Nantong Street, Nangang District, Harbin, 150001, China
| | - Qi Cheng
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, No. 145 Nantong Street, Nangang District, Harbin, 150001, China
| | - Zhenyu Wei
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, No. 145 Nantong Street, Nangang District, Harbin, 150001, China
| | - Jiayu Xu
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, No. 145 Nantong Street, Nangang District, Harbin, 150001, China
| | - Shiwei Wu
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, No. 145 Nantong Street, Nangang District, Harbin, 150001, China
| | - Nan Xu
- Institute of Biomedical Engineering and Technology, Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, No. 500 Dongchuan Road, Shanghai, 200241, China
- Shanghai Unicar-Therapy Bio-medicine Technology Co., Ltd, No. 1525 Minqiang Road, Shanghai, 201612, China
| | - Chengkui Zhao
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, No. 145 Nantong Street, Nangang District, Harbin, 150001, China
- Shanghai Unicar-Therapy Bio-medicine Technology Co., Ltd, No. 1525 Minqiang Road, Shanghai, 201612, China
| | - Lei Yu
- Institute of Biomedical Engineering and Technology, Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, No. 500 Dongchuan Road, Shanghai, 200241, China
- Shanghai Unicar-Therapy Bio-medicine Technology Co., Ltd, No. 1525 Minqiang Road, Shanghai, 201612, China
| | - Weixing Feng
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, No. 145 Nantong Street, Nangang District, Harbin, 150001, China
| |
Collapse
|
2
|
Vecchio E, Rotundo S, Veneziano C, Abatino A, Aversa I, Gallo R, Giordano C, Serapide F, Fusco P, Viglietto G, Cuda G, Costanzo F, Russo A, Trecarichi EM, Torti C, Palmieri C. The spike-specific TCRβ repertoire shows distinct features in unvaccinated or vaccinated patients with SARS-CoV-2 infection. J Transl Med 2024; 22:33. [PMID: 38185632 PMCID: PMC10771664 DOI: 10.1186/s12967-024-04852-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Accepted: 01/02/2024] [Indexed: 01/09/2024] Open
Abstract
BACKGROUND The evolving variants of SARS-CoV-2 may escape immunity from prior infections or vaccinations. It's vital to understand how immunity adapts to these changes. Both infection and mRNA vaccination induce T cells that target the Spike protein. These T cells can recognize multiple variants, such as Delta and Omicron, even if neutralizing antibodies are weakened. However, the degree of recognition can vary among people, affecting vaccine efficacy. Previous studies demonstrated the capability of T-cell receptor (TCR) repertoire analysis to identify conserved and immunodominant peptides with cross-reactive potential among variant of concerns. However, there is a need to extend the analysis of the TCR repertoire to different clinical scenarios. The aim of this study was to examine the Spike-specific TCR repertoire profiles in natural infections and those with combined natural and vaccine immunity. METHODS A T-cell enrichment approach and bioinformatic tools were used to investigate the Spike-specific TCRβ repertoire in peripheral blood mononuclear cells of previously vaccinated (n = 8) or unvaccinated (n = 6) COVID-19 patients. RESULTS Diversity and clonality of the TCRβ repertoire showed no significant differences between vaccinated and unvaccinated groups. When comparing the TCRβ data to public databases, 692 unique TCRβ sequences linked to S epitopes were found in the vaccinated group and 670 in the unvaccinated group. TCRβ clonotypes related to spike regions S135-177, S264-276, S319-350, and S448-472 appear notably more prevalent in the vaccinated group. In contrast, the S673-699 epitope, believed to have super antigenic properties, is observed more frequently in the unvaccinated group. In-silico analyses suggest that mutations in epitopes, relative to the main SARS-CoV-2 variants of concern, don't hinder their cross-reactive recognition by associated TCRβ clonotypes. CONCLUSIONS Our findings reveal distinct TCRβ signatures in vaccinated and unvaccinated individuals with COVID-19. These differences might be associated with disease severity and could influence clinical outcomes. TRIAL REGISTRATION FESR/FSE 2014-2020 DDRC n. 585, Action 10.5.12, noCOVID19@UMG.
Collapse
Affiliation(s)
- Eleonora Vecchio
- Department of Experimental and Clinical Medicine, University "Magna Graecia", Viale Europa, 88100, Catanzaro, Italy
- Interdepartmental Centre of Services, University "Magna Graecia", 88100, Catanzaro, Italy
| | - Salvatore Rotundo
- Department of Medical and Surgical Sciences, Chair of Infectious and Tropical Diseases, University "Magna Graecia", 88100, Catanzaro, Italy
| | - Claudia Veneziano
- Interdepartmental Centre of Services, University "Magna Graecia", 88100, Catanzaro, Italy
| | - Antonio Abatino
- Department of Experimental and Clinical Medicine, University "Magna Graecia", Viale Europa, 88100, Catanzaro, Italy
| | - Ilenia Aversa
- Department of Experimental and Clinical Medicine, University "Magna Graecia", Viale Europa, 88100, Catanzaro, Italy
| | - Raffaella Gallo
- Department of Experimental and Clinical Medicine, University "Magna Graecia", Viale Europa, 88100, Catanzaro, Italy
| | - Caterina Giordano
- Department of Experimental and Clinical Medicine, University "Magna Graecia", Viale Europa, 88100, Catanzaro, Italy
| | - Francesca Serapide
- Department of Medical and Surgical Sciences, Chair of Infectious and Tropical Diseases, University "Magna Graecia", 88100, Catanzaro, Italy
| | - Paolo Fusco
- Department of Medical and Surgical Sciences, Chair of Infectious and Tropical Diseases, University "Magna Graecia", 88100, Catanzaro, Italy
| | - Giuseppe Viglietto
- Department of Experimental and Clinical Medicine, University "Magna Graecia", Viale Europa, 88100, Catanzaro, Italy
| | - Giovanni Cuda
- Department of Experimental and Clinical Medicine, University "Magna Graecia", Viale Europa, 88100, Catanzaro, Italy
| | - Francesco Costanzo
- Department of Experimental and Clinical Medicine, University "Magna Graecia", Viale Europa, 88100, Catanzaro, Italy
- Interdepartmental Centre of Services, University "Magna Graecia", 88100, Catanzaro, Italy
| | - Alessandro Russo
- Department of Medical and Surgical Sciences, Chair of Infectious and Tropical Diseases, University "Magna Graecia", 88100, Catanzaro, Italy
| | - Enrico Maria Trecarichi
- Department of Medical and Surgical Sciences, Chair of Infectious and Tropical Diseases, University "Magna Graecia", 88100, Catanzaro, Italy
| | - Carlo Torti
- Department of Medical and Surgical Sciences, Chair of Infectious and Tropical Diseases, University "Magna Graecia", 88100, Catanzaro, Italy
| | - Camillo Palmieri
- Department of Experimental and Clinical Medicine, University "Magna Graecia", Viale Europa, 88100, Catanzaro, Italy.
| |
Collapse
|
3
|
Neoantigens: promising targets for cancer therapy. Signal Transduct Target Ther 2023; 8:9. [PMID: 36604431 PMCID: PMC9816309 DOI: 10.1038/s41392-022-01270-x] [Citation(s) in RCA: 205] [Impact Index Per Article: 205.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 11/14/2022] [Accepted: 11/27/2022] [Indexed: 01/07/2023] Open
Abstract
Recent advances in neoantigen research have accelerated the development and regulatory approval of tumor immunotherapies, including cancer vaccines, adoptive cell therapy and antibody-based therapies, especially for solid tumors. Neoantigens are newly formed antigens generated by tumor cells as a result of various tumor-specific alterations, such as genomic mutation, dysregulated RNA splicing, disordered post-translational modification, and integrated viral open reading frames. Neoantigens are recognized as non-self and trigger an immune response that is not subject to central and peripheral tolerance. The quick identification and prediction of tumor-specific neoantigens have been made possible by the advanced development of next-generation sequencing and bioinformatic technologies. Compared to tumor-associated antigens, the highly immunogenic and tumor-specific neoantigens provide emerging targets for personalized cancer immunotherapies, and serve as prospective predictors for tumor survival prognosis and immune checkpoint blockade responses. The development of cancer therapies will be aided by understanding the mechanism underlying neoantigen-induced anti-tumor immune response and by streamlining the process of neoantigen-based immunotherapies. This review provides an overview on the identification and characterization of neoantigens and outlines the clinical applications of prospective immunotherapeutic strategies based on neoantigens. We also explore their current status, inherent challenges, and clinical translation potential.
Collapse
|