T Cell Receptor Clustering Research Articles

Interpretable GWAS by linking clinical phenotypes to quantifiable immune repertoire components

Bridging the gap between genotype and phenotype in GWAS studies is challenging. A multitude of genetic variants have been associated with immune-related diseases, including cancer, yet the interpretability of most variants remains low. Here, we investigate the quantitative components in the T cell receptor (TCR) repertoire, the frequency of clusters of TCR sequences predicted to have common antigen specificity, to interpret the genetic associations of diverse human diseases. We first developed a statistical model to predict the TCR components using variants in the TRB and HLA loci. Applying this model to over 300,000 individuals in the UK Biobank data, we identified 2309 associations between TCR abundances and various immune diseases. TCR clusters predicted to be pathogenic for autoimmune diseases were significantly enriched for predicted autoantigen-specificity. Moreover, four TCR clusters were associated with better outcomes in distinct cancers, where conventional GWAS cannot identify any significant locus. Collectively, our results highlight the integral role of adaptive immune responses in explaining the associations between genotype and phenotype.

TCR clustering by contrastive learning on antigen specificity.

Effective clustering of T-cell receptor (TCR) sequences could be used to predict their antigen-specificities. TCRs with highly dissimilar sequences can bind to the same antigen, thus making their clustering into a common antigen group a central challenge. Here, we develop TouCAN, a method that relies on contrastive learning and pretrained protein language models to perform TCR sequence clustering and antigen-specificity predictions. Following training, TouCAN demonstrates the ability to cluster highly dissimilar TCRs into common antigen groups. Additionally, TouCAN demonstrates TCR clustering performance and antigen-specificity predictions comparable to other leading methods in the field.

Engineering Mesoscale T Cell Receptor Clustering by Plug-and-Play Nanotools.

Tcell receptor (TCR) clustering and formation of an immune synapse are crucial for TCR signaling. However, limited information is available about these dynamic assemblies and their connection to transmembrane signaling. Here, we controlled TCR clustering via plug-and-play nanotools based on an engineered irreversible conjugation pair and a peptide-loaded major histocompatibility complex (pMHC) molecule to compare receptor assembly in a ligand (pMHC)-induced or ligand-independent manner. A streptavidin-binding peptide displayed in both tools enabled their anchoring in streptavidin-pre-structured matrices. Strikingly, pMHC-induced clustering in the confined regions exhibited higher density and dynamics than the ligand-free approach, indicating that the size and architecture of the pMHC ligand influences TCR assembly. Our approach enables the control of membrane receptor clustering with high specificity and provide the possibility to explore different modalities of receptor activation. This article is protected by copyright. All rights reserved.

Designing meaningful continuous representations of T cell receptor sequences with deep generative models

T Cell Receptor (TCR) antigen binding underlies a key mechanism of the adaptive immune response yet the vast diversity of TCRs and the complexity of protein interactions limits our ability to build useful low dimensional representations of TCRs. To address the current limitations in TCR analysis we develop a capacity-controlled disentangling variational autoencoder trained using a dataset of approximately 100 million TCR sequences, that we name TCR-VALID. We design TCR-VALID such that the model representations are low-dimensional, continuous, disentangled, and sufficiently informative to provide high-quality TCR sequence de novo generation. We thoroughly quantify these properties of the representations, providing a framework for future protein representation learning in low dimensions. The continuity of TCR-VALID representations allows fast and accurate TCR clustering and is benchmarked against other state-of-the-art TCR clustering tools and pre-trained language models.

Single-cell analysis of bronchoalveolar cells in inflammatory and fibrotic post-COVID lung disease.

Persistent radiological lung abnormalities are evident in many survivors of acute coronavirus disease 2019 (COVID-19). Consolidation and ground glass opacities are interpreted to indicate subacute inflammation whereas reticulation is thought to reflect fibrosis. We sought to identify differences at molecular and cellular level, in the local immunopathology of post-COVID inflammation and fibrosis. We compared single-cell transcriptomic profiles and T cell receptor (TCR) repertoires of bronchoalveolar cells obtained from convalescent individuals with each radiological pattern, targeting lung segments affected by the predominant abnormality. CD4 central memory T cells and CD8 effector memory T cells were significantly more abundant in those with inflammatory radiology. Clustering of similar TCRs from multiple donors was a striking feature of both phenotypes, consistent with tissue localised antigen-specific immune responses. There was no enrichment for known SARS-CoV-2-reactive TCRs, raising the possibility of T cell-mediated immunopathology driven by failure in immune self-tolerance. Post-COVID radiological inflammation and fibrosis show evidence of shared antigen-specific T cell responses, suggesting a role for therapies targeting T cells in limiting post-COVID lung damage.

Increase in HIV reservoir and T cell immune response after CoronaVac vaccination in people living with HIV

IntroductionCoronaVac, an inactivated vaccine developed by Sinovac Life Sciences, has been widely used for protection against Coronavirus Disease 2019 (COVID-19). This study investigates its effect on the HIV reservoir and T cell repertoires in people living with HIV (PLWHs). MethodsBlood samples were collected from fifteen PLWHs who were administered at least two doses of CoronaVac between April 2021 and February 2022. The levels of cell-associated HIV RNA (CA HIV RNA) and HIV DNA, as well as the T cell receptor (TCR) repertoire profiles, TCR clustering and TCRβ annotation, were studied. ResultsA significant increase was observed in CA HIV RNA at 2 weeks (431.5 ± 164.2 copies/106 cells, P = 0.039) and 12 weeks (330.2 ± 105.9 copies/106 cells, P = 0.019) after the second dose, when compared to the baseline (0 weeks) (73.6 ± 23.7 copies/106 cells). Various diversity indices of the TCRβ repertoire, including Shannon index, Pielou's evenness index, and Hvj Index, revealed a slight increase (P < 0.05) following CoronaVac vaccination. The proportion of overlapping TCRβ clonotypes increased from baseline (31.9 %) to 2 weeks (32.5 %) and 12 weeks (40.4 %) after the second dose. We also found that the breadth and depth of COVID-19-specific T cells increased from baseline (0.003 and 0.0035) to 12 weeks (0.0066 and 0.0058) post the second dose. ConclusionsOur study demonstrated an initial increase in HIV reservoir and TCR repertoire diversity, as well as an expansion in the depth and breadth of COVID-19-specific T-cell clones among CoronaVac-vaccinated PLWHs. These findings provide important insights into the effects of COVID-19 vaccination in PLWHs.

Abstract 7473: Flotillin-2 ablation in T cells enhances antigen sensitivity and functionality

Abstract The membrane scaffolding protein flotillin-2 (Flot2) has been proposed to support receptor signaling, but its involvement in T cell receptor (TCR) signaling and T cell responses remains unclear. Here, we show that the deletion of Flot2 increases antigen sensitivity along with changes in surface TCR clustering, resulting in enhanced TCR signaling and effector function to weak TCR stimulation. T cell-specific Flot2-deficient mice showed enhanced proliferation and effector cytokine production in both CD4+ and CD8+ T cells, resulting in better control of tumor growth and infection. However, in vitro TCR stimulation with plate-bound anti-CD3 and soluble anti-CD28 showed increased TCR signaling and early activation of CD4+, but not CD8+ Flot2-deficient T cells upon weak stimulation. In addition, Flot2-deficient CD4+ T cells showed better in vitro polarization toward T helper 1 cells upon weak TCR stimulation, likely due to increased sensitivity of the TCR-triggering threshold. Changes in TCR clustering on the membrane have been suggested to influence the early detection of foreign stimuli and the formation of immune synapses. Flot2 ablation indeed increased the number of membrane TCR nanoclusters on naïve CD4+ T cells. Collectively, this study suggests a mechanism for increasing T cell functionality to weak TCR stimulation by modulating the membrane protein Flot2, which affects surface TCR clustering. These results may have important implications for improving T cell reactivity in diseases with poor antigenicity, such as anti-tumor immune responses. Citation Format: Sookjin Moon, Peer W. Karmaus, Michael B. Fessler. Flotillin-2 ablation in T cells enhances antigen sensitivity and functionality [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7473.

Abstract 4093: Modeling tumor immunoediting under immune selective pressure to inform neoantigen landscape dynamics for effective cancer vaccines

Abstract Tumor specific neoantigens, encoded by somatic mutations, are recognized by T cells, inducing anti-tumor immune responses. This renders neoantigens viable targets for personalized cancer vaccines. However, the identification of immunogenic neoantigens remains suboptimal. Understanding how immune selective pressure-mediated tumor evolution and neoantigen editing contribute to emergence of immunogenic neoantigens may improve prediction accuracy. In this study, we aimed to model tumor evolution and heterogeneity under immune pressure using three preclinical models of lung cancer with common driver mutations, Kras G12D/+ and p53 -/-, namely KPA, KPC, and HKP1, subcutaneously implanted in immunocompetent C57BL/6 (B6) and immune-deficient Rag1-/- mice. Our data suggest that despite shared driver mutations identified by whole exome and RNA-seq, tumor growth in vivo varied between tumor models. KPA tumors were immunogenic, as they were controlled in B6 mice but rapidly progressed in Rag1-/- mice, suggesting immunoediting of KPA-specific neoantigens. In contrast, HKP1 was non-immunogenic, with tumors progressing regardless of immune competency. KPC showed moderate tumor control in B6 mice, which was lost in Rag1-/- mice. We then estimated the cancer cell fraction on every mutation based on phylogenetic reconstruction. Immunogenic KPA tumors had significantly lower mutation burden in B6 than in Rag1-/- mice and the fraction of cell line mutations edited in vivo was significantly higher, suggesting active immunoediting in the former. Non-immunogenic HKP1 tumors did not show significant differences in mutation burden nor fraction of mutations edited between B6 and Rag1-/- mice. The immunogenicity was reflected in the immune infiltrate levels within tumors, with KPA being highly infiltrated by activated CD4 and CD8 T cells compared to KPC. HKP1 tumors showed increased infiltration of suppressive regulatory T cells. T cell receptor (TCR) sequencing on lung tumors showed that clonal expansion is strongly associated with immunogenicity. KPA tumors showed significantly higher TCR clustering with less diversity compared to KPC and more than HKP1. Following a simple approach to study the immunogenicity of shared neoantigens to elicit cross-protective anti-tumor responses, mice were immunized with whole irradiated (IR) tumor cell lines and implanted with live tumor cells (matched and unmatched). While immunization with IR-KPA protected against corresponding tumor implant and moderately against KPC, it did not protect against HKP1, indicating lack of immunogenicity of mutations shared between KPA and HKP1. Further studies testing the anti-tumor responses and characteristics of neoantigens shared between these three related tumor cell lines will inform the conditions under which tumors may escape or regress and help improve neoantigen identifying algorithms. Citation Format: Mariam Mathew George, Jayon Lihm, Hyejin Choi, Yuval Elhanati, Stephen Martis, Marta Luksza, Benjamin Greenbaum, Jedd D. Wolchok, Taha Merghoub. Modeling tumor immunoediting under immune selective pressure to inform neoantigen landscape dynamics for effective cancer vaccines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4093.

Abstract 3559: A validated bioinformatics tool-set for predicting TCR specificity

Abstract Background: The T-cell receptor (TCR) is a transmembrane receptor on T cells, which is responsible for recognizing any foreign antigen derived peptide, presented on infected or abnormal cells by the MHC-I complex. Predicting TCR specificity computationally is a long-standing problem. Many methods leverage large libraries of TCR sequences and cognate epitopes as input for machine learning and predict specificity from sequence alone. Most methods generally do not perform very well, especially in the case of unseen peptides, i.e. for cases where peptides were not part of the input library. Methods: Here we describe three independent but interacting in-silico modules for TCR discovery. 1) The first module predicts specificity from deep phenotypic T cell profiles. We produce these profiles using a high-throughput pipeline, which combines multiplexed CyTOF with subsequent VDJ CITE-Seq. The generated multiomics data is aggregated into a database called TCAPS, which is the basis for machine learning models. These models can predict T cell specificity from the deep phenotype alone, i.e. without TCR sequence information. The resolution however is limited to the target class and hence the actual epitope has to be determined through subsequent deorphanization. This deorphanization step is augmented by the other two modules also described here. 2) The second module enables ultrafast sequence similarity search, which is used to find similar TCRs with known epitope specificity 3) The third module ranks TCR candidates for prioritisation for in-vitro validation. This is achieved by running the Alphafold-based structure prediction program TCRDock. Results: 1) We demonstrate how TCR specificity can be correctly predicted from multiomics deep T-cell profiles and specifically highlight two in-vitro validated predictions, for which the corresponding epitope/antigen were not part of the input panel. 2) Using a recently published TCR clustering benchmark TCRScapes, we demonstrate the superior performance of our ultrafast sequence similarity search. 3) We furthermore showcase TCRdock-directed experiments on TCRs specific for SF3B1mut-induced splice variants. TCRdock correctly ranked TCR candidates, including artificial combinations, whose functionality we prove through in-vitro validation. Conclusions: We describe three modules for TCR discovery and demonstrate their utility by benchmarking and in-vitro validation of multiple predictions, including two examples against unseen epitopes/antigens. Citation Format: Andreas Wilm, Florian Schmidt, Melissa Wirawan, Manisha Cooray, Kan Xing Wu, Katja Fink, Dan MacLeod. A validated bioinformatics tool-set for predicting TCR specificity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3559.

Tumor cell–derived spermidine is an oncometabolite that suppresses TCR clustering for intratumoral CD8+ T cell activation

The activation and expansion of T cells that recognize cancer cells is an essential aspect to antitumor immunity. Tumors may escape destruction by the immune system through ectopic expression of inhibitory immune ligands typically exemplified by the PD-L1/PD-1 pathway. Here, we reveal another facet of tumor evasion from T cell surveillance. By secretome profiling of necrotic tumor cells, we identified an oncometabolite spermidine as a unique inhibitor of T cell receptor (TCR) signaling. Mechanistically, spermidine causes the downregulation of the plasma membrane cholesterol levels, resulting in the suppression of TCR clustering. Using syngeneic mouse models, we show that spermidine is abundantly detected in the tumor immune microenvironment (TIME) and that administration of the polyamine synthesis inhibitor effectively enhanced CD8+ T cell-dependent antitumor responses. Further, the combination of the polyamine synthesis inhibitor with anti-PD-1 immune checkpoint antibody resulted in a much stronger antitumor immune response. This study reveals an aspect of immunosuppressive TIME, wherein spermidine functions as a metabolic T cell checkpoint that may offer a unique approach for promoting tumor immunotherapy.

Dynamics and survival associations of T cell receptor clusters in patients with pleural mesothelioma treated with immunotherapy

BackgroundImmune checkpoint inhibitors (ICIs) are now a first-line treatment option for patients with pleural mesothelioma with the recent approval of ipilimumab and nivolumab. Mesothelioma has a low tumor mutation burden...

Abstract 1198: T cell receptor (TCR) landscape of childhood brain tumors

Abstract T lymphocytes have a unique ability to recognize a vast array of antigens prompt by an enormous T cell receptor (TCR) repertoire. Characterization of tumor-infiltrating T cells (TILs) is key to understand MHC-restricted anti-tumor immunity and for developing T cell-centered immunotherapies such as adoptive cell therapy and tumor vaccines. In the current work, we investigated RNA-Seq data from 997 pediatric brain tumor patients and performed a large-scale comprehensive examination of the immunogenomic and TCR landscape of TILs across the entire spectrum of pediatric brain tumors. We show that the relative ratio between T cell clonal diversity and T cell abundance within each sample, represented by the clonal expansion index (CEI), is a strong predictor of prognosis both within and between tumor types. Interestingly, we show that CEI is strongly associated with molecular subgroups of medulloblastoma but not with known genomic features of these subgroups. Investigation of TCR clonotypes recognizing a common recurrent tumor-antigen across patients based on CDR3 homology and characteristics, reveals 9 TCR clusters which are tumor-type restricted with defined prognoses and HLA dominance. Using computational immunogenomics and machine learning-based investigations of these clusters we identified novel putative HLA-restricted tumor antigens which could bind and activate the clusters’ specific TCRs. Importantly, our framework grounded the foundations for developing a precision medicine approach of T cell-centered immunotherapies. These findings have major implications for understanding the interplay between T cell and tumor genomics, and for developing new immunotherapies for children with brain tumors and other cancers. Citation Format: Itay Raphael, Michal Nisnboym, Rebecca A. Raphael, Shikhar Uttam, Ian F. Pollack, Maria Chikina, Dhivyaa Rajasundaram, Gary Kohanbash. T cell receptor (TCR) landscape of childhood brain tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1198.

Abstract 610: Modeling tumor immunoediting coupled with T-cell repertoire dynamic

Abstract As tumors evolve, cancer cells acquire somatic mutations and these mutations generate tumor specific neoantigens that are different from self and can be recognized by T-cells, inducing anti-tumor immune responses. Such immunogenic antigens can be effective targets for neoantigen-based cancer vaccines. However, the identification of immunogenic neoantigens remains limited with the current prediction models. Here we designed mouse experiments to model tumor evolution under immune pressure and its association with T-cell clones to identify these antigens agnostically and improve current prediction models. We injected three lung cancer cell lines (KPA, KPC, and HKP1) in wildtype immune-competent C57BL/6 mice and immune-deficient Rag1 defective (Rag1 KO) mice, respectively. The three tumor cell lines have common driver mutations, Kras G12D/+ and p53 flox/flox. Two weeks post tumor implantation, whole exome sequencing and RNA-seq was performed on tumor samples. We also performed T cell receptor (TCR) sequencing to profile tumor infiltrated TCR clones. Despite the shared driver mutations, tumor growth patterns in vivo over time are very distinct for each cell line. Interestingly, KPA tumors show differential evolutionary patterns in wild type mice versus Rag1 KO mice, regressing in the former but rapidly progressing in the latter, suggesting that the difference can be attributed to immunoediting of KPA specific neoantigens. HKP1 tumors do not show substantial differences in that aggressive tumor progression is observed in both types of mice. Using WES data, we estimated the cancer cell fraction of each mutation based on phylogeny re-construction. We found that evolved KPA tumors (immunogenic) had significantly lower mutation burden in wild type mice compared to Rag1 KO mice (3410 vs 4199 on average), and the fraction of cell line mutations edited in vivo is significantly higher in wild type than in Rag1 KO (26% vs 14% on average), suggesting again the active on-going immunosurveillance in immune competent mice. In contrast, HKP1 tumors (non-immunogenic) do not show significant differences in mutation burden nor fraction of mutations edited between wild type and Rag1 KO mice. Furthermore, TCR-seq data show that the clonal expansion of T-cells is strongly associated with tumor immunogenicity. KPA tumor samples show significantly higher TCR clustering but with less diversity, quantified by modified Simpson’s Index, that is strongly correlated with the suppression of mutational burden (r=0.74). In summary, we found that tumor evolution in immune competent mice is dependent on mutational context of the tumor. By analyzing longitudinal tumor and TCR sequencing data, we showed that the immunogenicity of tumors is associated with significant decrease in mutational burden and higher T-cell clustering that is indicative of tumor mutation and TCR clone expansion co-evolution in immune competent mice. Citation Format: Jayon Lihm, Hyejin Choi, Mariam M. George, Yuval Elhanati, David Hoyos, Marta Luksza, Taha Merghoub, Benjamin D. Greenbaum. Modeling tumor immunoediting coupled with T-cell repertoire dynamic [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 610.

The impact of lipids on the cancer-immunity cycle and strategies for modulating lipid metabolism to improve cancer immunotherapy.

Lipids have been found to modulate tumor biology, including proliferation, survival, and metastasis. With the new understanding of tumor immune escape that has developed in recent years, the influence of lipids on the cancer-immunity cycle has also been gradually discovered. First, regarding antigen presentation, cholesterol prevents tumor antigens from being identified by antigen presenting cells. Fatty acids reduce the expression of major histocompatibility complex class I and costimulatory factors in dendritic cells, impairing antigen presentation to T cells. Prostaglandin E2 (PGE2) reduce the accumulation of tumor-infiltrating dendritic cells. Regarding T-cell priming and activation, cholesterol destroys the structure of the T-cell receptor and reduces immunodetection. In contrast, cholesterol also promotes T-cell receptor clustering and relative signal transduction. PGE2 represses T-cell proliferation. Finally, regarding T-cell killing of cancer cells, PGE2 and cholesterol weaken granule-dependent cytotoxicity. Moreover, fatty acids, cholesterol, and PGE2 can improve the activity of immunosuppressive cells, increase the expression of immune checkpoints and promote the secretion of immunosuppressive cytokines. Given the regulatory role of lipids in the cancer-immunity cycle, drugs that modulate fatty acids, cholesterol and PGE2 have been envisioned as effective way in restoring antitumor immunity and synergizing with immunotherapy. These strategies have been studied in both preclinical and clinical studies.

Compartmentalization and persistence of dominant (regulatory) T cell clones indicates antigen skewing in juvenile idiopathic arthritis.

Autoimmune inflammation is characterized by tissue infiltration and expansion of antigen-specific T cells. Although this inflammation is often limited to specific target tissues, it remains yet to be explored whether distinct affected sites are infiltrated with the same, persistent T cell clones. Here, we performed CyTOF analysis and T cell receptor (TCR) sequencing to study immune cell composition and (hyper-)expansion of circulating and joint-derived Tregs and non-Tregs in juvenile idiopathic arthritis (JIA). We studied different joints affected at the same time, as well as over the course of relapsing-remitting disease. We found that the composition and functional characteristics of immune infiltrates are strikingly similar between joints within one patient, and observed a strong overlap between dominant T cell clones, especially Treg, of which some could also be detected in circulation and persisted over the course of relapsing-remitting disease. Moreover, these T cell clones were characterized by a high degree of sequence similarity, indicating the presence of TCR clusters responding to the same antigens. These data suggest that in localized autoimmune disease, there is autoantigen-driven expansion of both Teffector and Treg clones that are highly persistent and are (re)circulating. These dominant clones might represent interesting therapeutic targets.

Immune environment and antigen specificity of the T cell receptor repertoire of malignant ascites in ovarian cancer.

We evaluated the association of disease outcome with T cell immune-related characteristics and T cell receptor (TCR) repertoire in malignant ascites from patients with high-grade epithelial ovarian cancer. Ascitic fluid samples were collected from 47 high-grade epithelial ovarian cancer patients and analyzed using flow cytometry and TCR sequencing to characterize the complementarity determining region 3 TCR β-chain. TCR functions were analyzed using the McPAS-TCR and VDJ databases. TCR clustering was implemented using Grouping of Lymphocyte Interactions by Paratope Hotspots software. Patients with poor prognosis had ascites characterized by an increased ratio of CD8+ T cells to regulatory T cells, which correlated with an increased productive frequency of the top 100 clones and decreased productive entropy. TCRs enriched in patients with an excellent or good prognosis were more likely to recognize cancer antigens and contained more TCR reads predicted to recognize epithelial ovarian cancer antigens. In addition, a TCR motif that is predicted to bind the TP53 neoantigen was identified, and this motif was enriched in patients with an excellent or good prognosis. Ascitic fluid in high-grade epithelial ovarian cancer patients with an excellent or good prognosis is enriched with TCRs that may recognize ovarian cancer-specific neoantigens, including mutated TP53 and TEAD1. These results suggest that an effective antigen-specific immune response in ascites is vital for a good outcome in high-grade epithelial ovarian cancer.

Discovery of Aptamers Against Cell Surface Markers Using Ligand-Guided Selection.

Oligonucleotide ligands (DNA, RNA, or XNA), also known as aptamers, are selected against various target molecules using an iterative, evolutionary process called systematic evolution of ligands by exponential enrichment (SELEX). To select aptamers against complex cell surface proteins in their native state, a variant of SELEX termed ligand-guided selection (LIGS) was recently introduced. The significance of LIGS is rooted in its strategy of exploiting the selection step in SELEX to identify highly specific aptamers against known cell surface markers. Thus, in LIGS, a higher-affinity secondary ligand, such as a monoclonal antibody (mAb) to a whole-cell bound to an evolved SELEX library, is introduced to outcompete sequences against the mAb targeting cell surface protein or induce a conformational switch to destabilize the aptamer-surface cell surface protein resulting in elution of the sequences. Here, we describe the detailed method of LIGS utilized in identifying aptamers against T-cell receptor cluster of differentiation three complex (TCR-CD3) expressed in human T-cells and T-cell leukemia.

IFN-α with dasatinib broadens the immune repertoire in patients with chronic-phase chronic myeloid leukemia.

In chronic myeloid leukemia (CML), combination therapies with tyrosine kinase inhibitors (TKIs) aim to improve the achievement of deep molecular remission that would allow therapy discontinuation. IFN-α is one promising candidate, as it has long-lasting effects on both malignant and immune cells. In connection with a multicenter clinical trial combining dasatinib with IFN-α in 40 patients with chronic-phase CML (NordCML007, NCT01725204), we performed immune monitoring with single-cell RNA and T cell receptor (TCR) sequencing (n = 4, 12 samples), bulk TCRβ sequencing (n = 13, 26 samples), flow cytometry (n = 40, 106 samples), cytokine analyses (n = 17, 80 samples), and ex vivo functional studies (n = 39, 80 samples). Dasatinib drove the immune repertoire toward terminally differentiated NK and CD8+ T cells with dampened functional capabilities. Patients with dasatinib-associated pleural effusions had increased numbers of CD8+ recently activated effector memory T (Temra) cells. In vitro, dasatinib prevented CD3-induced cell death by blocking TCR signaling. The addition of IFN-α reversed the terminally differentiated phenotypes and increased the number of costimulatory intercellular interactions and the number of unique putative epitope-specific TCR clusters. In vitro IFN-α had costimulatory effects on TCR signaling. Our work supports the combination of IFN-α with TKI therapy, as IFN-α broadens the immune repertoire and restores immunological function.

Characterization of T cell receptors reactive to HCRTNH2, pHA273-287, and NP17-31 in control and narcolepsy patients

Narcolepsy type 1 (NT1), a disorder caused by hypocretin/orexin (HCRT) cell loss, is associated with human leukocyte antigen (HLA)-DQ0602 (98%) and T cell receptor (TCR) polymorphisms. Increased CD4+ T cell reactivity to HCRT, especially DQ0602-presented amidated C-terminal HCRT (HCRTNH2), has been reported, and homology with pHA273-287 flu antigens from pandemic 2009 H1N1, an established trigger of the disease, suggests molecular mimicry. In this work, we extended DQ0602 tetramer and dextramer data to 77 cases and 44 controls, replicating our prior finding and testing 709 TCRs in Jurkat 76 T cells for functional activation. We found that fewer TCRs isolated with HCRTNH2 (∼11%) versus pHA273-287 or NP17-31 antigens (∼50%) were activated by their ligand. Single-cell characterization did not reveal phenotype differences in influenza versus HCRTNH2-reactive T cells, and analysis of TCR CDR3αβ sequences showed TCR clustering by responses to antigens but no cross-peptide class reactivity. Our results do not support the existence of molecular mimicry between HCRT and pHA273-287 or NP17-31.

The importance of taking ART appropriately in children and adolescents with HIV-1 to reach the highest capacity of immune function later in life.

Current antiretroviral therapy (ART) guidelines recommend treating all children with HIV-1 infection. This has changed from the broader use of ART to treat children to improve morbidity and minimise mortality. However, prior to current recommendations, not everyone with HIV-1 received timely treatment. What happens to the paediatric immune system when HIV-1 replication is not appropriately supressed remains unclear. 11 samples from adolescents with HIV-1 on ART and uninfected controls in the UK, aged 12–25 years, were examined; overall, adolescents with CD4+ counts > 500/μl and a viral load < 50 copies/ml were compared with adolescents with CD4+ counts < 500/μl and a viral load > 50 copies/ml at time of sampling. Measurements of thymic output were combined with high throughput next generation sequencing and bioinformatics to systematically organize CD4+ and CD8+ T cell receptor (TCR) repertoires. TCR repertoire diversity, clonal expansions, TCR sequence sharing, and formation of TCR clusters in HIV-1 infected adolescents with successful HIV-1 suppression were compared to adolescents with ineffective HIV-1 suppression. Thymic output and CD4+ T cell numbers were decreased in HIV-1 infected adolescents with poor HIV-1 suppression. A strong homeostatic TCR response, driven by the decreased CD4+ T cell compartment and reduced thymic output was observed in the virally uncontrolled HIV-1-infected adolescents. Formation of abundant robust TCR clusters and structurally related TCRs were found in the adolescents with effective HIV-1 suppression. Numerous CD4+ T cell numbers in the virally controlled adolescents emphasize the importance of high thymic output and formation of robust TCR clusters in the maintenance of HIV-1 suppression. While the profound capacity for immune recovery in children may allow better opportunity to deal with immunological stress, when ART is taken appropriately, this study demonstrates new insights into the unique paediatric immune system and the immunological changes when HIV-1 replication is ongoing.