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The ability to selectively bind to antigenic peptides and secrete effector molecules can define rare and low-affinity populations of cells with therapeutic potential in emerging T cell receptor (TCR) immunotherapies. We leverage cavity-containing hydrogel microparticles, called nanovials, each coated with peptide-major histocompatibility complex (pMHC) monomers to isolate antigen-reactive T cells. T cells are captured and activated by pMHCs inducing the secretion of effector molecules including IFN-γ and granzyme B that are accumulated on nanovials, allowing sorting based on both binding and function. The TCRs of sorted cells on nanovials are sequenced, recovering paired αβ-chains using microfluidic emulsion-based single-cell sequencing. By labeling nanovials having different pMHCs with unique oligonucleotide-barcodes and secretions with oligo-barcoded detection antibodies, we could accurately link TCR sequences to specific targets and rank each TCR based on the corresponding cells secretion level. Using the technique, we identified an expanded repertoire of functional TCRs targeting viral antigens with high specificity and found rare TCRs with activity against cancer-specific splicing-enhanced epitopes.

Background: Mycosis fungoides (MF) is the most common subtype of cutaneous T-cell lymphoma (CTCL). Comprehensive analysis of MF cells in situ and ex vivo is complicated by the fact that is challenging to distinguish malignant from reactive T cells with certainty. Methods: To overcome this limitation, we performed combined single-cell RNA (scRNAseq) and T-cell receptor TCR sequencing (scTCRseq) of skin lesions of cutaneous MF lesions from 12 patients. A sufficient quantity of living T cells was obtained from 9 patients, but 2 had to be excluded due to unclear diagnoses (coexisting CLL or revision to a fixed toxic drug eruption). Results: From the remaining patients we established single-cell mRNA expression profiles and the corresponding TCR repertoire of 18,630 T cells. TCR clonality unequivocally identified 13,592 malignant T cells. Reactive T cells of all patients clustered together, while malignant cells of each patient formed a unique cluster expressing genes typical of naive/memory, such as CD27, CCR7 and IL7R, or cytotoxic T cells, e.g., GZMA, NKG7 and GNLY. Genes encoding classic CTCL markers were not detected in all clusters, consistent with the fact that mRNA expression does not correlate linearly with protein expression. Nevertheless, we successfully pinpointed distinctive gene signatures differentiating reactive malignant from malignant T cells: keratins (KRT81, KRT86), galectins (LGALS1, LGALS3) and S100 genes (S100A4, S100A6) being overexpressed in malignant cells. Conclusions: Combined scRNAseq and scTCRseq not only allows unambiguous identification of MF cells, but also revealed marked heterogeneity between and within patients with unexpected functional phenotypes. While the correlation between mRNA and protein abundance was limited with respect to established MF markers, we were able to identify a single-cell gene expression signature that distinguishes malignant from reactive T cells. [ABSTRACT FROM AUTHOR]

In the realm of cancer immunotherapy, the meticulous selection of neoantigens plays a fundamental role in enhancing personalized treatments. Traditionally, this selection process has heavily relied on predicting the binding of peptides to human leukocyte antigens (pHLA). Nevertheless, this approach often overlooks the dynamic interaction between tumor cells and the immune system. In response to this limitation, we have developed an innovative prediction algorithm rooted in machine learning, integrating T cell receptor β chain (TCRβ) profiling data from colorectal cancer (CRC) patients for a more precise neoantigen prioritization. TCRβ sequencing was conducted to profile the TCR repertoire of tumor-infiltrating lymphocytes (TILs) from 28 CRC patients. The data unveiled both intra-tumor and inter-patient heterogeneity in the TCRβ repertoires of CRC patients, likely resulting from the stochastic utilization of V and J segments in response to neoantigens. Our novel combined model integrates pHLA binding information with pHLA-TCR binding to prioritize neoantigens, resulting in heightened specificity and sensitivity compared to models using individual features alone. The efficacy of our proposed model was corroborated through ELISpot assays on long peptides, performed on four CRC patients. These assays demonstrated that neoantigen candidates prioritized by our combined model outperformed predictions made by the established tool NetMHCpan. This comprehensive assessment underscores the significance of integrating pHLA binding with pHLA-TCR binding analysis for more effective immunotherapeutic strategies.

An individual's T-cell repertoire constantly changes under the influence of external and internal factors. Cells that do not receive a stimulatory signal die, while those that encounter and recognize a pathogen or receive a costimulatory signal divide, resulting in clonal expansions. T-cell clones can be traced by monitoring the presence of their unique T-cell receptor (TCR) sequence, which is assembled de novo through a process known as V(D)J rearrangement. Tracking T cells can provide valuable insights into the survival of cells after hematopoietic stem cell transplantation (HSCT) or cancer treatment response and can indicate the induction of protective immunity by vaccination. In this study, we report a bioinformatic method for quantifying the T-cell repertoire dynamics from TCR sequencing data. We demonstrate its utility by measuring the T-cell repertoire stability in healthy donors, by quantifying the effect of donor lymphocyte infusion (DLI), and by tracking the fate of the different T-cell subsets in HSCT patients and the expansion of pathogen-specific clones in vaccinated individuals. [ABSTRACT FROM AUTHOR]

Adenovirus vaccines, particularly the COVID-19 Ad5-nCoV adenovirus vaccine, have emerged as promising tools in the fight against infectious diseases. In this study, we investigated the structure of the T cell response to the Spike protein of the SARS-CoV-2 virus used in the COVID-19 Ad5-nCoV adenoviral vaccine in a phase 3 clinical trial (NCT04540419). In 69 participants, we collected peripheral blood samples at four time points after vaccination or placebo injection. Sequencing of T cell receptor repertoires from Spike-stimulated T cell cultures at day 14 from 17 vaccinated revealed a more diverse CD4+ T cell repertoire compared to CD8+. Nevertheless, CD8+ clonotypes accounted for more than half of the Spike-specific repertoire. Our longitudinal analysis showed a peak T cell response at day 14, followed by a decline untilmonth 6. Remarkably, multiple T cell clonotypes persisted for at least 6 months after vaccination, as demonstrated by ex vivo stimulation. Examination of CDR3 regions revealed homologous sequences in both CD4+ and CD8+ clonotypes, with major CD8+ clonotypes sharing high similarity with annotated sequences specific for the NYNYLYRLF peptide, suggesting potential immunodominance. In conclusion, our study demonstrates the immunogenicity of the Ad5-nCoV adenoviral vaccine and highlights its ability to induce robust and durable T cell responses. These findings provide valuable insight into the efficacy of the vaccine against COVID-19 and provide critical information for ongoing efforts to control infectious diseases. [ABSTRACT FROM AUTHOR]

The ability to selectively bind to antigenic peptides and secrete effector molecules can define rare and low-affinity populations of cells with therapeutic potential in emerging T cell receptor (TCR) immunotherapies. We leverage cavity-containing hydrogel microparticles, called nanovials, each coated with peptide-major histocompatibility complex (pMHC) monomers to isolate antigen-reactive T cells. T cells are captured and activated by pMHCs inducing the secretion of effector molecules including IFN-γ and granzyme B that are accumulated on nanovials, allowing sorting based on both binding and function. The TCRs of sorted cells on nanovials are sequenced, recovering paired αβ-chains using microfluidic emulsion-based single-cell sequencing. By labeling nanovials having different pMHCs with unique oligonucleotide-barcodes and secretions with oligo-barcoded detection antibodies, we could accurately link TCR sequences to specific targets and rank each TCR based on the corresponding cell's secretion level. Using the technique, we identified an expanded repertoire of functional TCRs targeting viral antigens with high specificity and found rare TCRs with activity against cancer-specific splicing-enhanced epitopes. [ABSTRACT FROM AUTHOR]

Background: Accumulating evidence supports the involvement of adaptive immunity in the development of radiation‐induced brain injury (RIBI). Our previous work has emphasized the cytotoxic function of CD8+ T cells in RIBI. In this study, we aimed to investigate the presence and potential roles of cytotoxic CD4+ T cells (CD4+ CTLs) in RIBI to gain a more comprehensive understanding of adaptive immunity in this context. Main Text: Utilizing single‐cell RNA sequencing (scRNA‐seq), we analyzed 3934 CD4+ T cells from the brain lesions of four RIBI patients and identified six subclusters within this population. A notable subset, the cytotoxic CD4+ T cells (CD4+ CTLs), was marked with high expression of cytotoxicity‐related genes (NKG7, GZMH, GNLY, FGFBP2, and GZMB) and several chemokine and chemokine receptors (CCL5, CX3CR1, and CCL4L2). Through in‐depth pseudotime analysis, which simulates the development of CD4+ T cells, we observed that the CD4+ CTLs exhibited signatures of terminal differentiation. Their functions were enriched in protein serine/threonine kinase activity, GTPase regulator activity, phosphoprotein phosphatase activity, and cysteine‐type endopeptidase activity involved in the apoptotic signaling pathway. Correspondingly, mice subjected to gamma knife irradiation on the brain showed a time‐dependent infiltration of CD4+ T cells, an increase of MHCII+ cells, and the existence of CD4+ CTLs in lesions, along with an elevation of apoptotic‐related proteins. Finally, and most crucially, single‐cell T‐cell receptor sequencing (scTCR‐seq) analysis at the patient level determined a large clonal expansion of CD4+ CTLs in lesion tissues of RIBI. Transcriptional factor‐encoding genes TBX21, RORB, and EOMES showed positive correlations with the cytotoxic functions of CD4+ T cells, suggesting their potential to distinguish RIBI‐related CD4+ CTLs from other subsets. Conclusion: The present study enriches the understanding of the transcriptional landscape of adaptive immune cells in RIBI patients. It provides the first description of a clonally expanded CD4+ CTL subset in RIBI lesions, which may illuminate new mechanisms in the development of RIBI and offer potential biomarkers or therapeutic targets for the disease. [ABSTRACT FROM AUTHOR]

BackgroundMycosis fungoides (MF) is the most common subtype of cutaneous T-cell lymphoma (CTCL). Comprehensive analysis of MF cells in situ and ex vivo is complicated by the fact that is challenging to distinguish malignant from reactive T cells with certainty.MethodsTo overcome this limitation, we performed combined single-cell RNA (scRNAseq) and T-cell receptor TCR sequencing (scTCRseq) of skin lesions of cutaneous MF lesions from 12 patients. A sufficient quantity of living T cells was obtained from 9 patients, but 2 had to be excluded due to unclear diagnoses (coexisting CLL or revision to a fixed toxic drug eruption).ResultsFrom the remaining patients we established single-cell mRNA expression profiles and the corresponding TCR repertoire of 18,630 T cells. TCR clonality unequivocally identified 13,592 malignant T cells. Reactive T cells of all patients clustered together, while malignant cells of each patient formed a unique cluster expressing genes typical of naive/memory, such as CD27, CCR7 and IL7R, or cytotoxic T cells, e.g., GZMA, NKG7 and GNLY. Genes encoding classic CTCL markers were not detected in all clusters, consistent with the fact that mRNA expression does not correlate linearly with protein expression. Nevertheless, we successfully pinpointed distinctive gene signatures differentiating reactive malignant from malignant T cells: keratins (KRT81, KRT86), galectins (LGALS1, LGALS3) and S100 genes (S100A4, S100A6) being overexpressed in malignant cells.ConclusionsCombined scRNAseq and scTCRseq not only allows unambiguous identification of MF cells, but also revealed marked heterogeneity between and within patients with unexpected functional phenotypes. While the correlation between mRNA and protein abundance was limited with respect to established MF markers, we were able to identify a single-cell gene expression signature that distinguishes malignant from reactive T cells.

Abstract Immunoglobulin A nephropathy (IgAN) is an autoimmune disease characterized by abnormal IgA deposition in glomerulus. Current diagnosis of IgAN still depends on renal biopsy, an invasive method that might increase the risk of clinical outcomes. Therefore, we aimed to explore the characteristics of T cell repertoire in IgAN from peripheral blood samples for identifying innovative diagnostic biomarkers. Herein, we included 8 IgAN patients, 25 non-IgAN patients, and 10 healthy controls in the study. A high-throughput immune repertoire sequencing was conducted to investigate the T-cell receptor beta-chain (TCRβ) repertoire of peripheral blood. Characteristics of TCRβ repertoire were assessed for these three distinct groups. A reduced TCRβ repertoire diversity was observed in IgAN patients compared to non-IgAN and healthy individuals. A skewed distribution toward shorter TCRβ complementarity determining region (CDR3) length was found in non-IgAN relative to IgAN patients. In addition, the differences in usages of five TRBV genes (TRBV5-4, TRBV6-4, TRBV12-1, TRBV16, and TRBV21-1) were identified between IgAN, non-IgAN, and healthy subjects. Of note, the TRBV6-4 gene, which is associated with mucosal-associated invariant T (MAIT) cells, exhibited higher usage in IgAN patients, suggesting potential importance of MAIT cells in IgAN. In short, our findings supported TCR repertoire characteristics as potential biomarkers for IgAN diagnosis.

T-cell–based diagnostic tools identify pathogen exposure but lack differentiation between recent and historical exposures in acute infectious diseases. Here, T-cell receptor (TCR) RNA sequencing was performed on HLA-DR+/CD38+CD8+ T-cell subsets of hospitalized coronavirus disease 2019 (COVID-19) patients (n = 30) and healthy controls (n = 30; 10 of whom had previously been exposed to severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]). CDR3α and CDR3β TCR regions were clustered separately before epitope specificity annotation using a database of SARS-CoV-2–associated CDR3α and CDR3β sequences corresponding to >1000 SARS-CoV-2 epitopes. The depth of the SARS-CoV-2–associated CDR3α/β sequences differentiated COVID-19 patients from the healthy controls with a receiver operating characteristic area under the curve of 0.84 ± 0.10. Hence, annotating TCR sequences of activated CD8+ T cells can be used to diagnose an acute viral infection and discriminate it from historical exposure. In essence, this work presents a new paradigm for applying the T-cell repertoire to accomplish TCR-based diagnostics. [ABSTRACT FROM AUTHOR]

Immunoglobulin A nephropathy (IgAN) is an autoimmune disease characterized by abnormal IgA deposition in glomerulus. Current diagnosis of IgAN still depends on renal biopsy, an invasive method that might increase the risk of clinical outcomes. Therefore, we aimed to explore the characteristics of T cell repertoire in IgAN from peripheral blood samples for identifying innovative diagnostic biomarkers. Herein, we included 8 IgAN patients, 25 non-IgAN patients, and 10 healthy controls in the study. A high-throughput immune repertoire sequencing was conducted to investigate the T-cell receptor beta-chain (TCRβ) repertoire of peripheral blood. Characteristics of TCRβ repertoire were assessed for these three distinct groups. A reduced TCRβ repertoire diversity was observed in IgAN patients compared to non-IgAN and healthy individuals. A skewed distribution toward shorter TCRβ complementarity determining region (CDR3) length was found in non-IgAN relative to IgAN patients. In addition, the differences in usages of five TRBV genes (TRBV5-4, TRBV6-4, TRBV12-1, TRBV16, and TRBV21-1) were identified between IgAN, non-IgAN, and healthy subjects. Of note, the TRBV6-4 gene, which is associated with mucosal-associated invariant T (MAIT) cells, exhibited higher usage in IgAN patients, suggesting potential importance of MAIT cells in IgAN. In short, our findings supported TCR repertoire characteristics as potential biomarkers for IgAN diagnosis. [ABSTRACT FROM AUTHOR]

Objectives: Infection with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) causes coronavirus disease 2019 (COVID‐19). Although an acute SARS‐CoV‐2 infection mainly presents with respiratory illness, neurologic symptoms and sequelae are increasingly recognised in the long‐term treatment of COVID‐19 patients. The pathophysiology and the neuropathogenesis behind neurologic complications of COVID‐19 remain poorly understood, but mounting evidence points to endothelial dysfunction either directly caused by viral infection or indirectly by inflammatory cytokines, followed by a local immune response that may include virus‐specific T cells. However, the type and role of central nervous system‐infiltrating T cells in COVID‐19 are complex and not fully understood. Methods: We analysed distinct anatomical brain regions of patients who had deceased as a result of COVID‐19‐associated pneumonia or complications thereof and performed T cell receptor Vβ repertoire sequencing. Clonotypes were analysed for SARS‐CoV‐2 association using public TCR repertoire data. Results: Our descriptive study demonstrates that SARS‐CoV‐2‐associated T cells are found in almost all brain areas of patients with fatal COVID‐19 courses. The olfactory bulb, medulla and cerebellum were brain regions showing the most SARS‐CoV‐2 specific sequence patterns. Neuropathological workup demonstrated primary CD8+ T‐cell infiltration with a perivascular infiltration pattern. Conclusion: Future research is needed to better define the relationship between T‐cell infiltration and neurological symptoms and its long‐term impact on patients' cognitive and mental health. [ABSTRACT FROM AUTHOR]

Analysis of T‐cell receptor (TCR) repertoires in different stages of hepatocellular carcinoma (HCC) might help to elucidate its pathogenesis and progression. This study aimed to investigate TCR profiles in liver biopsies and peripheral blood mononuclear cells (PBMCs) in different Barcelona Clinic liver cancer (BCLC) stages of HCC. Ten patients in early stage (BCLC_A), 10 patients in middle stage (BCLC_B), and 10 patients in late stage (BCLC_C) cancer were prospectively enrolled. The liver tumor tissues, adjacent tissues, and PBMCs of each patient were collected and examined by TCR β sequencing. Based on the ImMunoGeneTics (IMGT) database, we aligned the V, D, J, and C gene segments and identified the frequency of CDR3 sequences and amino acids sequence. Diversity of TCR in PBMCs was higher than in both tumor tissues and adjacent tissues, regardless of BCLC stage and postoperative recurrence. TCR clonality was increased in T cells from peripheral blood in advanced HCC, compared with the early and middle stages. No statistical differences were observed between different BCLC stages, either in tumors or adjacent tissues. TCR clonality revealed no significant difference between recurrent tumor and non‐recurrent tumor, therefore PBMCs was better to be representative of TCR characteristics in different stages of HCC compared to tumor tissues. Clonal expansion of T cells was associated with low risk of recurrence in HCC patients. [ABSTRACT FROM AUTHOR]

Abstract Objectives Infection with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) causes coronavirus disease 2019 (COVID‐19). Although an acute SARS‐CoV‐2 infection mainly presents with respiratory illness, neurologic symptoms and sequelae are increasingly recognised in the long‐term treatment of COVID‐19 patients. The pathophysiology and the neuropathogenesis behind neurologic complications of COVID‐19 remain poorly understood, but mounting evidence points to endothelial dysfunction either directly caused by viral infection or indirectly by inflammatory cytokines, followed by a local immune response that may include virus‐specific T cells. However, the type and role of central nervous system‐infiltrating T cells in COVID‐19 are complex and not fully understood. Methods We analysed distinct anatomical brain regions of patients who had deceased as a result of COVID‐19‐associated pneumonia or complications thereof and performed T cell receptor Vβ repertoire sequencing. Clonotypes were analysed for SARS‐CoV‐2 association using public TCR repertoire data. Results Our descriptive study demonstrates that SARS‐CoV‐2‐associated T cells are found in almost all brain areas of patients with fatal COVID‐19 courses. The olfactory bulb, medulla and cerebellum were brain regions showing the most SARS‐CoV‐2 specific sequence patterns. Neuropathological workup demonstrated primary CD8+ T‐cell infiltration with a perivascular infiltration pattern. Conclusion Future research is needed to better define the relationship between T‐cell infiltration and neurological symptoms and its long‐term impact on patients' cognitive and mental health.

This document is an editorial published in the journal Frontiers in Immunology. It discusses the role of adaptive immunity in atherosclerosis, a condition that contributes to acute cardiovascular events. The editorial highlights the importance of chronic inflammation in atherosclerosis and the potential for new intervention strategies. It also explores the use of new immunological techniques to study the role of the adaptive immune system in the development, progression, and regression of atherosclerosis. The document includes summaries of several research papers that investigate different aspects of adaptive immunity in atherosclerosis, including T cell and B cell responses. Overall, the editorial provides an overview of the latest findings in this field and serves as a valuable resource for researchers interested in studying adaptive immunity in atherosclerosis. [Extracted from the article]

In the realm of cancer immunotherapy, the meticulous selection of neoantigens plays a fundamental role in enhancing personalized treatments. Traditionally, this selection process has heavily relied on predicting the binding of peptides to human leukocyte antigens (pHLA). Nevertheless, this approach often overlooks the dynamic interaction between tumor cells and the immune system. In response to this limitation, we have developed an innovative prediction algorithm rooted in machine learning, integrating T cell receptor β chain (TCRβ) profiling data from colorectal cancer (CRC) patients for a more precise neoantigen prioritization. TCRβ sequencing was conducted to profile the TCR repertoire of tumor-infiltrating lymphocytes (TILs) from 28 CRC patients. The data unveiled both intra-tumor and inter-patient heterogeneity in the TCRβ repertoires of CRC patients, likely resulting from the stochastic utilization of V and J segments in response to neoantigens. Our novel combined model integrates pHLA binding information with pHLA-TCR binding to prioritize neoantigens, resulting in heightened specificity and sensitivity compared to models using individual features alone. The efficacy of our proposed model was corroborated through ELISpot assays on long peptides, performed on four CRC patients. These assays demonstrated that neoantigen candidates prioritized by our combined model outperformed predictions made by the established tool NetMHCpan. This comprehensive assessment underscores the significance of integrating pHLA binding with pHLA-TCR binding analysis for more effective immunotherapeutic strategies., Competing Interests: TP, TN, BT, TD, ND, HP, TC, DL, HN, DT, TT, TP, ML, TV, MP, HG, HN, LT No competing interests declared, (© 2024, Pham et al.)

This article is an editorial published in Frontiers in Pharmacology titled "Synthetic peptide vaccine platforms targeting tumor-specific antigens: advances and challenges." The authors discuss the discovery and therapeutic aspects of peptide vaccine platforms, specifically in relation to identifying potential antigen targets on tumors and strategies to enhance their immunogenicity. The article highlights advancements in computational techniques for identifying immunogenic peptide antigens, as well as the use of toll-like receptor agonists to improve the immunogenicity of vaccines. The authors emphasize the importance of confirming peptide binding characteristics through in-vivo or in-vitro determination. The article concludes by discussing the potential advantages of synthetic peptide vaccine platforms and the increasing tools available for designing peptide vaccines for oncology applications. [Extracted from the article]

• TCR diversity increased in biologic-treated AS patients with better improvement. • Higher difference of contracted minus expanded TCRs related to better improvement. • IL-23 level positively correlated with TCR diversity in AS patients. • AS-associated TCRs contracted in biologic-treated patients with better improvement. Ankylosing spondylitis (AS) is a chronic inflammatory autoimmune disease in which T-cell immune responses play important roles. AS has been characterized by altered T-cell receptor (TCR) repertoire profiles, which are thought to be caused by expansion of disease-related TCR clonotypes. However, how biological agents affect the TCR repertoire status and whether their therapeutic outcomes are associated with certain features or dynamic patterns of the TCR repertoire are still elusive. We collected clinical samples from AS patients pre- and post-treatment with biologics. TCR repertoire sequencing was conducted to investigate associations of TCRα and TCRβ repertoire characteristics with disease activity and inflammatory indicators/cytokines. Our results showed that good responders were associated with an increase in the TCR repertoire diversity with higher proportions of contracted TCR clonotypes. Additionally, we further identified a positive correlation between TCR repertoire diversity and interleukin (IL)–23 levels in AS patients. A network analysis revealed that contracted AS-associated TCR clonotypes with the same complementary-determining region 3 (CDR3) motifs, which represented high probabilities of sharing TCR specificities to AS-related antigens, were dominant in good responders of AS after treatment with biologic therapies. Our findings suggested an important connection between TCR repertoire changes and therapeutic outcomes in biologic-treated AS patients. The status and dynamics of TCR repertoire profiles are useful for assessing the prognosis of biologic treatments in AS patients. [ABSTRACT FROM AUTHOR]

Merkel cell carcinoma is a skin cancer often driven by Merkel cell polyomavirus (MCPyV) with high rates of response to anti-PD-1 therapy despite low mutational burden. MCPyV-specific CD8 T cells are implicated in anti-PD-1-associated immune responses and provide a means to directly study tumor-specific T cell responses to treatment. Using mass cytometry and combinatorial tetramer staining, we find that baseline frequencies of blood MCPyV-specific cells correlated with response and survival. Frequencies of these cells decrease markedly during response to therapy. Phenotypes of MCPyV-specific CD8 T cells have distinct expression patterns of CD39, cutaneous lymphocyte-associated antigen (CLA), and CD103. Correspondingly, overall bulk CD39 + CLA + CD8 T cell frequencies in blood correlate with MCPyV-specific cell frequencies and similarly predicted favorable clinical outcomes. Conversely, frequencies of CD39 + CD103 + CD8 T cells are associated with tumor burden and worse outcomes. These cell subsets can be useful as biomarkers and to isolate blood-derived tumor-specific T cells., Competing Interests: Declaration of interests E.W.N. is a co-founder, advisor, and shareholder for ImmunoScape Pte. Ltd., a scientific advisory board member and shareholder for Neogene Therapeutics, and a scientific advisory board member for Nanostring Biotechnologies and Trojan Biotechnologies. D.M.K. and P.N. are co-inventors on an institutionally owned patent concerning MCPyV-specific TCRs., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

T-cell-based diagnostic tools identify pathogen exposure but lack differentiation between recent and historical exposures in acute infectious diseases. Here, T-cell receptor (TCR) RNA sequencing was performed on HLA-DR+/CD38+CD8+ T-cell subsets of hospitalized coronavirus disease 2019 (COVID-19) patients (n = 30) and healthy controls (n = 30; 10 of whom had previously been exposed to severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]). CDR3α and CDR3β TCR regions were clustered separately before epitope specificity annotation using a database of SARS-CoV-2-associated CDR3α and CDR3β sequences corresponding to >1000 SARS-CoV-2 epitopes. The depth of the SARS-CoV-2-associated CDR3α/β sequences differentiated COVID-19 patients from the healthy controls with a receiver operating characteristic area under the curve of 0.84 ± 0.10. Hence, annotating TCR sequences of activated CD8+ T cells can be used to diagnose an acute viral infection and discriminate it from historical exposure. In essence, this work presents a new paradigm for applying the T-cell repertoire to accomplish TCR-based diagnostics., Competing Interests: Potential conflicts of interest . B. O., K. L., and P. M. are cofounders, board directors, and shareholders of ImmuneWatch. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)