TRBV Gene Research Articles

HTS and scRNA-seq revealed that the location and RSS quality of the mammalian TRBV and TRBJ genes impact biased rearrangement

The quality of Recombination signal sequences (RSSs), location, and genetics of mammalian V, D, and J genes synergistically affect the recombination frequency of genes; however, the specific regulatory mechanism and efficiency have not been elucidated. By taking advantage of single-cell RNA-sequencing (scRNA-seq) and high-throughput sequencing (HTS) to investigate V(D)J rearrangement characteristics in the CDR3 repertoire, we found that the distal and proximal V genes (or J genes) “to D” gene were involved in rearrangement significantly more frequently than the middle V genes (or J genes) in the TRB locus among various species, including Primates (human and rhesus monkey), Rodentia (BALB/c, C57BL/6, and Kunming mice), Artiodactyla (buffalo), and Chiroptera (Rhinolophus affinis). The RSS quality of the V and J genes affected their frequency in rearrangement to varying degrees, especially when the V-RSSs with recombination signal information content (RIC) score < -45 significantly reduced the recombination frequency of the V gene. The V and J genes that were “away from D” had the dual advantages of recombinant structural accessibility and relatively high-quality RSSs, which promoted their preferential utilization in rearrangement. The quality of J-RSSs formed during mammalian evolution was apparently greater than that of V-RSSs, and the D-J distance was obviously shorter than that of V-D, which may be one of the reasons for guaranteeing that the “D-to-J preceding V-to-DJ rule” occurred when rearranged. This study provides a novel perspective on the mechanism and efficiency of V-D-J rearrangement in the mammalian TRB locus, as well as the biased utilization characteristics and application of V and J genes in the initial CDR3 repertoire.

A Comprehensive Analysis of the Genomic and Expressed Repertoire of the T-Cell Receptor Beta Chain in Equus caballus

In this paper, we report a comprehensive and consistent annotation of the locus encoding the β-chain of the equine T-cell receptor (TRB), as inferred from recent genome assembly using bioinformatics tools. The horse TRB locus spans approximately 1 Mb, making it the largest locus among the mammalian species studied to date, with a significantly higher number of genes related to extensive duplicative events. In the region, 136 TRBV (belonging to 29 subgroups), 2 TRBD, 13 TRBJ, and 2 TRBC genes, were identified. The general genomic organization resembles that of other mammals, with a V cluster of 135 TRBV genes located upstream of two in-tandem aligned TRBD-J-C clusters and an inverted TRBV gene at the 3′ end of the last TRBC gene. However, the horse b-chain repertoire would be affected by a high number of non-functional TRBV genes. Thus, we queried a transcriptomic dataset derived from splenic tissue of a healthy adult horse, using each TRBJ gene as a probe to analyze clonotypes encompassing the V(D)J junction. This analysis provided insights into the usage of the TRBV, TRBD, and TRBJ genes and the variability of the non-germline-encoded CDR3. Our results clearly demonstrated that the horse β-chain constitutes a complex level of variability, broadly like that described in other mammalian species.

Single-cell T-cell receptor repertoire profiling in dogs

Spontaneous cancers in companion dogs are robust models of human disease. Tracking tumor-specific immune responses in these models requires reagents to perform species-specific single cell T cell receptor sequencing (scTCRseq). scTCRseq and integration with scRNA data have not been demonstrated on companion dogs with cancer. Here, five healthy dogs, two dogs with T cell lymphoma and four dogs with melanoma are selected to demonstrate applicability of scTCRseq in a cancer immunotherapy setting. Single-cell suspensions of PBMCs or lymph node aspirates are profiled using scRNA and dog-specific scTCRseq primers. In total, 77,809 V(D)J-expressing cells are detected, with an average of 3498 (348 - 5,971) unique clonotypes identified per sample. In total, 29/34, 40/40, 22/22 and 9/9 known functional TRAV, TRAJ, TRBV and TRBJ gene segments are observed respectively. Pseudogene or otherwise defective gene segments are also detected supporting re-annotation of several as functional. Healthy dogs exhibit highly diverse repertoires, T cell lymphomas exhibit clonal repertoires, and vaccine-treated melanoma dogs are dominated by a small number of highly abundant clonotypes. scRNA libraries define large clusters of V(D)J-expressing CD8+ and CD4 + T cells. Dominant clonotypes observed in melanoma PBMCs are predominantly CD8 + T cells, with activated phenotypes, suggesting possible anti-tumor T cell populations.

Abstract 7011: The DNA methylation landscape across the TCR loci genes in patients with acute myeloid leukemia

Abstract The T-cell receptor (TCR) repertoire is partly shaped by epigenetic modifications, including DNA methylation. Hypomethylating agents like decitabine are used to treat patients with acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). The precise DNA methylation patterns within the TCR loci and their dynamics associated with HMAs treatments remain underexplored. Here, we analyzed methylation patterns across TCR alpha and beta gene loci in T cells from GSE175758 and GSE67170 datasets, comparing patterns between patients with AML and healthy controls. We also investigated the impact of decitabine on the methylation patterns of TCR gene loci in patients with AML and MDS (GSE175758 and GSE80762).The overall levels of methylation between T cells from healthy donors and patients with AML were significantly different within the TRAV (0.55 vs 0.42, P &amp;lt; 0.001) and TRBV regions (0.70 vs 0.59, P &amp;lt; 0.001) with 46 TRAV and 33 TRBV sites differentially methylated positions, respectively. However, methylation patterns in HSCs (GSE63409), T cells from healthy donors and patients with AML and those in AML cells were strongly correlated (R &amp;gt; 0.67, range 0.67-0.99, P &amp;lt; 0.001).Because decitabine preferentially acts on leukemic cells and given the high correlation levels between AML cells and T cells across datasets we analyzed the effects of decitabine on TCR DNA methylation patterns in AML cells. In the leukemic cells decitabine treatment led to significant demethylation across 33 and 30 CpG sites within the TRAV and TRBV genes, respectively. In the pre-treatment AML samples higher methylation beta values were observed in differentially methylated positions (DMPs) compared with non-DMPs (TRAV: 0.847 vs 0.407; P &amp;lt; 0.001; TRBV: 0.771 vs 0.538; P = 0.049). In samples largely enriched of myeloid leukemic blasts, we found that TRAV and TRBV loci methylation patterns differ significantly between AML patients with good, moderate, and poor risk patients (P &amp;lt; 0.001). We found TRBV6-1 position 1 and 2 methylation was lower in patients with good risk, compared with intermediate risk (pos1: 0.07 vs 0.13, P=0.04; pos2: 0.1 vs 0.2, P = 0.002) and poor risk (pos 1: 0.07 vs 0.21, P &amp;lt; 0.001; pos 2: 0.1 vs 0.32, P &amp;lt; 0.001) and was lower in patients with intermediate risk compared with poor risk (pos1: 0.13 vs 0.21, p=0.007; pos 2: 0.21 vs 0.32, P = 0.001). The high correlation of TCR DNA methylation patterns between the T cells and the myeloid cells, suggests the need for similar analyses in the context of AML T cells. The study highlights the presence of a conserved TCR loci methylated signatures which is highly correlated between myeloid leukemic cells and T cells and is associated with clinical outcomes, offering a potential avenue for therapeutic intervention. Hypomethylating agents, such as decitabine, can modulate TCR loci methylation patterns. Citation Format: Mateusz Pospiech, John Beckford, Advaith M. Kumar, Mukund Tamizharasan, Jaqueline Brito, Gangning Liang, Serghei Mangul, Houda Alachkar. The DNA methylation landscape across the TCR loci genes in patients with acute myeloid leukemia [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 7011.

The self-reactive FVIII T cell repertoire in healthy individuals relies on a short set of epitopes and public clonotypes.

Non-mutated FVIII-specific CD4 T cell epitopes have been recently found to contribute to the development of inhibitors in patients with hemophilia A (HA), while auto-reactive CD4 T cells specific to FVIII circulate in the blood of healthy individuals at a frequency close to the foreign protein ovalbumin. Thus, although FVIII is a self-protein, the central tolerance raised against FVIII appears to be low. In this study, we conducted a comprehensive analysis of the FVIII CD4 T cell repertoire in 29 healthy donors. Sequencing of the CDR3β TCR region from isolated FVIII-specific CD4 T cells revealed a limited usage and pairing of TRBV and TRBJ genes as well as a mostly hydrophobic composition of the CDR3β region according to their auto-reactivity. The FVIII repertoire is dominated by a few clonotypes, with only 13 clonotypes accounting for half of the FVIII response. Through a large-scale epitope mapping of the full-length FVIII sequence, we identified 18 immunodominant epitopes located in the A1, A3, C1, and C2 domains and covering half of the T cell response. These epitopes exhibited a broad specificity for HLA-DR or DP molecules or both. T cell priming with this reduced set of peptides revealed that highly expanded clonotypes specific to these epitopes were responsible individually for up to 32% of the total FVIII repertoire. These FVIII T cell epitopes and clonotypes were shared among HLA-unrelated donors tested and previously reported HA patients. Our study highlights the role of the auto-reactive T cell response against FVIII in HA and its similarity to the response observed in healthy individuals. Thus, it provides valuable insights for the development of new tolerance induction and deimmunization strategies.

Distinct T Cell Receptor Gene Repertoires and T Cell Subset Distribution in Peripheral Blood and Bone Marrow of Patients with Multiple Myeloma

Mounting evidence suggests that the T cell repertoire in multiple myeloma (MM) is actively shaped by antigen selection. However, the molecular underpinnings of this observation are not fully understood, while relevant studies have been mostly based on immunophenotypic characterization of T cell subsets, with considerably less information regarding T cell receptor (TR) gene repertoire profiles. Moreover, most available information derives from the analysis of a single tissue compartment [i.e. peripheral blood (PB) or bone marrow (BM)], thus hindering addressing the potential impact of local T cell responses. Here we sought to overcome these limitations through paired analysis of PB and BM aspirates of 20 newly diagnosed patients with MM before the administration of any treatment, from whom we isolated the PB and BM mononuclear cell (PBMC/BMMC) fraction, as well as CD4 + and CD8 + T cells. TR beta (TRB) chain gene rearrangements were RT-PCR amplified on RNA extracted from CD4 + and CD8 + T cells and then subjected to paired-end next generation sequencing (NGS). Raw reads (n=14,369,410 | median 179,618/sample) were processed through a purpose-built bioinformatics pipeline. Productive TRBV-TRBD-TRBJ gene rearrangements were taken into consideration (n=9,212,507 | median 115,156/sample) for the computation of clonotypes (i.e. TRB rearrangements with identical TRBV gene usage and amino acid complementarity-determining region 3 sequence). Overall, 1,005,150 TRΒ distinct clonotypes were assessed (median=12,565/sample). Both CD4 + and CD8 + T cell populations displayed skewed TRBV repertoires (7 TRBV genes and 3 TRBJ genes accounting for about ~40% and ~60% of the repertoire) in both BM and PB. All patients displayed oligoclonal T cell expansions in both CD4 + and CD8 + T cells, albeit these were significantly (p&amp;lt;0.001) more pronounced in CD8 + T cells for both BM and PB samples. That said, oligoclonality was more pronounced in BM vs. PB for both CD4 and CD8 T cells, reaching statistical significance in the former: in particular, the median cumulative frequency of the most expanded clonotypes/sample was ~40% higher in CD4 + BM T cells vs. CD4 + PB T cells (p&amp;lt;0.001). Additionally, a significant shift was noticed in the major clonotype repertoire of CD4 + and CD8 + T cells in both PB and BM. In more detail, the 10 most expanded clonotypes/sample in PB had significantly lower frequency in BM, and, vice versa, the 10 most expanded clonotypes in BM were represented at diminished frequency or were absent in the PB in 12/20 patients. Flow cytometry analysis revealed distinct T cell subset composition in CD4 + or CD8 + T cells, also in different tissue compartments (BM vs. PB). Significant (p&amp;lt;0.001) differences concerned the over-representation of: (i) effector T cells (CD45RA +/CCR7 -, Temra) in CD8 + vs. CD4 + T cells in both BM and PB (median frequencies in BM and PB: 22.5% and 7% for CD8 + T cells; 6% and 1.6% for CD4 + T cells); (ii) CD8 + Temra cells in BM vs. PB (median frequencies of 22.5% vs. 7% in BM and PB, respectively; p&amp;lt;0.001); (iii) CD4 + vs. CD8 + central memory T cells (CD45RO +/CCR7 +, Tcm) in both PB and BM (median frequencies in PB and BM: 42.7% and 49.1% for CD4 + Tcm and 14% and 18.8% for CD8 + Tcm); (iv) CD8 + effector memory T cells (CD45RO +/CCR7 -, Tem) in BM vs. PB (median frequencies of 21.8% vs. 2.7% in BM and PB, respectively); (v) CD8 + naïve T cells (CD45RA +/CCR7 +, Tn) in PB vs. BM (median frequencies of 67.7% vs. 24.2% in PB and BM, respectively). In conclusion, oligoclonal expansions of CD4 + and, particularly, CD8 + T cells in MM that are more pronounced in the BM (at least for CD4 + cells) argue for selection by BM-biased antigens, a claim also supported by the significant differences in the relative frequency of dominant clonotypes in BM vs. PB. The distinctive T cell subset distribution in the BM, characterized by a significant increase of effector at the expense of memory T cells, likely reflects an antigen-driven albeit ineffective immune response.

Novel bimodal TRBD1-TRBD2 rearrangements with dual or absent D-region contribute to TRB V-(D)-J combinatorial diversity.

T-cell receptor (TR) diversity of the variable domains is generated by recombination of both the alpha (TRA) and beta (TRB) chains. The textbook process of TRB chain production starts with TRBD and TRBJ gene rearrangement, followed by the rearrangement of a TRBV gene to the partially rearranged D-J gene. Unsuccessful V-D-J TRB rearrangements lead to apoptosis of the cell. Here, we performed deep sequencing of the poorly explored pool of partial TRBD1-TRBD2 rearrangements in T-cell genomic DNA. We reconstructed full repertoires of human partial TRBD1-TRBD2 rearrangements using novel sequencing and validated them by detecting V-D-J recombination-specific byproducts: excision circles containing the recombination signal (RS) joint 5'D2-RS - 3'D1-RS. Identified rearrangements were in compliance with the classical 12/23 rule, common for humans, rats, and mice and contained typical V-D-J recombination footprints. Interestingly, we detected a bimodal distribution of D-D junctions indicating two active recombination sites producing long and short D-D rearrangements. Long TRB D-D rearrangements with two D-regions are coding joints D1-D2 remaining classically on the chromosome. The short TRB D-D rearrangements with no D-region are signal joints, the coding joint D1-D2 being excised from the chromosome. They both contribute to the TRB V-(D)-J combinatorial diversity. Indeed, short D-D rearrangements may be followed by direct V-J2 recombination. Long D-D rearrangements may recombine further with J2 and V genes forming partial D1-D2-J2 and then complete V-D1-D2-J2 rearrangement. Productive TRB V-D1-D2-J2 chains are present and expressed in thousands of clones of human antigen-experienced memory T cells proving their capacity for antigen recognition and actual participation in the immune response.

New insights into the germline genes and CDR3 repertoire of the TCRβ chain in Chiroptera.

Bats are recognized as natural reservoirs for many viruses, and their unique immune system enables them to coexist with these viruses without frequently exhibiting disease symptoms. However, the current understanding of the bat adaptive immune system is limited due to the lack of a database or tool capable of processing T-cell receptor (TCR) sequences for bats. We performed germline gene annotation in three bat species using homologous genes and RSSs (Recombinational Signal Sequences) scanning method. Then we used the conserved C gene to construct the TCRβ chain receptor library of the Intermediate Horseshoe Bat. Bats' TCRβ data will be analyzed using MiXCR and constructed reference library. Regarding the annotation results, we found that the Pale Spear-nosed Bat has 37 members in the TRBV12 family, which is more than the total number of TRBV genes in the Greater Horseshoe Bat. The average number of unique TCRβ chain receptor sequences in each Intermediate Horseshoe Bat sample reached 24,904. The distinct variations in the distribution of TRBV genes among the three types of bats could have a direct impact on the diversity of the TCR repertoire, as evidenced by the presence of conserved amino acids that indicate the T-cell recognition of antigens in bats is MHC-restricted. The bats' TCRβ repertoire is formed through the rearrangement of the V-D-J-C genes, with D-J/V-D deletions and insertions resulting in high diversity.

T Cell Epitope Prediction within the Clonotypic Immunoglobulin Heavy and Light Chains in Patients with Multiple Myeloma

Despite remarkable therapeutic advances in recent years, multiple myeloma (MM) remains incurable, hence representing an unmet clinical need. Therapeutic approaches based on induced T cell anti-tumor immunity towards cancer eradication show promising results in many hematologic malignancies, including multiple myeloma (MM), highlighting the need for comprehensive understanding of the implicated mechanisms. Similar to other mature B cell malignancies, immunoglobulin (IG) gene rearrangements in MM lead to the expression of unique, novel peptide sequences that can be used as neoantigens, conceivably representing a potential attractive target for cancer-specific immune responses. Here we sought to explore this possibility by performing ad hoc prediction of putative T-cell class I/II neoepitopes contained within the MM clonotypic IG gene rearrangements. To that end, we investigated 16 newly diagnosed patients with MM from whom we isolated the peripheral blood and/or bone marrow mononuclear cell (PBMC/BMMC) fraction as well as CD138+ myeloma cells, CD4+ and CD8+ T cells. Clonotypic IG heavy and light chain gene rearrangements were RT-PCR amplified on RNA extracted from the PBMC/BMMC fraction using subgroup-specific leader primers for the IGHV/IGK/LV gene and universal primers annealing to the constant domain (IGHG, IGHM, IGKC, IGLC), in order to produce the full-length V-(D)-J gene rearrangement sequence, plus the start of the constant domain. The corresponding sequences were determined by bidirectional Sanger sequencing. Moreover, T cell receptor beta (TRB) chain gene rearrangements were RT-PCR amplified on RNA extracted from CD4+ and CD8+ T cells and then subjected to paired-end next generation sequencing (NGS). The deduced amino acid sequences of the IG heavy and light chain variable/constant domains were subsequently parsed in peptides and subjected to bioinformatics analysis for the identification of putative T-cell class I/II neoepitopes using the NetMHCpan and NetMHIICpan softwares. The rank score was calculated, considering the 4-digit HLA-A, -B, -C and DRB1 typing for each individual patient. High- and medium-binding peptides (rank score <2%) were selected. Prediction of the binding specificity of T Cell Receptors (TR) to MHC-peptide complexes (pMHCs) was performed by the ERGO-II tool. The rank score was calculated, considering the peptides resulted by NetMHCpan/ NetMHIICpan, the HLA, and the clonotypes for each patient (AUC>0.8). Exact matches to germline and/or proteome databases were excluded. Overall, 757,263 TRΒ distinct clonotypes were assessed (median= 18,244 /sample). All patients displayed oligoclonal T cell expansions in both CD4+ and CD8+ T cells, albeit these were significantly (p<0.001) more pronounced in the latter. Both T cell subpopulations displayed skewed TRBV and TRBJ gene repertoires (7 TRBV genes and 3 TRBJ genes accounting for about 40% and 59% of the repertoire, respectively). Overall, 1,219 predicted neoepitopes were identified. All patients had predicted CD4+ and CD8 + T-cell epitopes within the MM clonotypic IG, either in the heavy chain (16/16 pts, n=459 epitopes) or the light chain (16/16 pts, n=760 epitopes). There was no statistically significant difference in the rank score of peptides involving the complementarity determining region 3 (CDR3) vs. all other IG regions. Interestingly, 998/1,219 (82%) peptides with strong binding affinity resulted from IG gene sequence motifs outside the CDR3. Most of these peptides (853/1,219, 75%) resulted from somatic hypermutations (SHM) across the IG variable domain. Overall, 51,574 clonotypes of CD4+ T cells and 35,751 clonotypes of CD8+ T cells were in silico predicted by ERGO to have strong binding affinity. Relevant to mention, 528 clonotypes with high binding score were found to be shared between CD4+ T cells of all patients and 209 clonotypes between CD8+ T cells of all patients and, thus, were deemed as public. In conclusion, in silico prediction identified a significant number of putative T-cell class I/II neoepitopes contained within the clonotypic IG of MM patients. Many of the identified peptides derive from SHM, implying that the SHM which shapes the MM BcR IG repertoire may produce immunogenic CD4+/CD8+ T cell epitopes. Their actual immunogenicity has to be tested in ex vivo studies, currently underway by our group.

Longitudinal Profiling of the T Cell Compartment in Patients with Chronic Lymphocytic Leukemia Treated with Venetoclax

Venetoclax (ven), an inhibitor of the BCL2 anti-apoptotic protein, has been proven remarkably effective in the treatment of patients with chronic lymphocytic leukemia (CLL), where the malignant B cells typically overexpress BCL2. BCL2 is also expressed by various bystander cells in the CLL microenvironment, including T cells. Hence, investigating the effects of ven treatment on T cells is highly relevant, especially considering that distinct T cell subpopulations exhibit different sensitivity to anti-apoptotic signaling blockade. Herein we interrogated the molecular and phenotypic profiles of the T cell compartment in 1 treatment-naïve and 15 relapsed/refractory CLL patients who received ven either as monotherapy (n=12) or in combination with an anti-CD20 antibody (obinutuzumab, n=1; rituximab, n=3). We studied peripheral blood samples collected prior to ven initiation and after 5 months of treatment, from which we isolated T cell subpopulations (CD3+ T cells n=8; CD4+ and CD8+ T cells, n=8). Longitudinal analysis of pre/post-treatment samples by flow cytometry (n=7) revealed a significant (p=0.01) decrease in the numbers of central memory (CD45RO+/CCR7+) CD4+ (21.8% vs 8.8%) and CD8+ cells (21.4% vs 9.7%) under ven; in contrast, a significant (p=0.01) increase of CD8+ effector memory cells (CD45RO+/CCR7-) was observed (27.8% vs 32.9%). Profiling of the T cell receptor beta (TRB) chain gene repertoire overtime (n=15) was performed by next generation sequencing (NGS). Clonotypes (i.e. TRBV-TRBD-TRBJ gene rearrangements with unique pairs of TRBV genes and identical CDR3 amino acid sequences) were calculated and clonality was estimated as the average cumulative frequency of the 10 most frequent clonotypes per sample (ACF-10). A significantly (p=0.01) more diverse repertoire was identified in CD4+ vs CD8+ cells at both pre- and post-treatment timepoints (average numbers of clonotypes pre-/post-treatment: CD4+ cells, 16,908/13,768; CD8+ cells, 4,437/3,633). Expanded clonotypes corresponding to oligoclonal expansions were documented in all examined subpopulations at both timepoints. However, significantly (p=0.01) more pronounced skewing was observed in CD8+ vs CD4+ cells (pre-/post-treatment ACF-10 values: 64.4%/70.6% vs 31.4%/42.2%, respectively). Repertoire comparisons overtime highlighted a fraction of T clonotypes that were retained after treatment in all examined subpopulations. Of note, repertoire conservation was significantly (p=0.01) greater in CD8+ vs CD4+ T cells [retained pre-treatment clonotypes: 7,102/31,063 (28%) vs 11,525/118,359 (12%), respectively]. Transcriptome profiling of CD4+ and CD8+ cells pre-/post-treatment was performed using the Oncomine Immune Response Research Assay (395 genes) in 5 cases attaining a complete response after treatment. While the transcriptomes of CD4+ cells remained essentially unaltered, significant differences were identified in CD8+ cells, where 19 genes were found to be downregulated (adj.p<0.05, fold change>2). These genes are implicated in functions such as immune response (e.g. TLR7, TLR9, CD40), regulation of immune system (e.g. HLA genes, CIITA, TNFAIP8) and lymphocyte activation pathways (e.g. ICOSLG, CEACAM1, CXCR5), with at least some of these having immunosuppressive functions (e.g. BTLA and CTLA4 encoding inhibitory receptors associated with T cell exhaustion). In conclusion, ven treatment led to increased numbers of CD8+ effector subpopulations along with prominent clonal expansions and transcriptional rewiring that could conceivably contribute to clinical response. Downregulation of immune-related genes implicated in core regulatory/activation pathways supports immune recovery by ven, offering a rationale for future combination strategies aiming to increase the depth of clinical response.

Comprehensive analysis of B and T cell receptor repertoire in patients after kidney transplantation by high-throughput sequencing

PurposeThe dynamic immunity of kidney transplant patients has not been fully elucidated. In this study, we explored the repertoire features of B/T cell receptor (BCR/TCR) of kidney transplant patients. MethodsUsing combined multiplex PCR amplification and high-throughput sequencing technique, we analyzed the uremic patients' BCR H chain and TCR beta chain repertoire which obtained 1 day before kidney transplantation (PRE-1), 1 day and 7 day after kidney transplantation (POST-1 and POST-7). ResultsOur analysis results showed the diversity of TCRβ CDR3 in POST-7 group was highest. In addition, there were specific skewed usage of TRBV gene subfamilies, and V-J combinations in different time points during kidney transplantation. Moreover, the overlap degrees of BCR-H (TCR-β) CDR3 repertoire among each group were identified. Notably, the abundance of some TCR-β CDR3 sequences changed regularly in the time point of kidney transplantation. ConclusionsThe BCR-H (TCR-β) CDR3 repertoire of kidney transplant patients changed dynamically.

Control of naive and effector CD4 T cell receptor repertoires by rheumatoid-arthritis-risk HLA alleles

ObjectiveHuman Leukocyte Antigen (HLA) alleles regulate susceptibility to rheumatoid arthritis (RA) and immune-mediated diseases. This study aims to elucidate the impact of HLA alleles to T cell subsets. MethodsWe performed genome-wide and HLA allele association analysis for T cell receptor (TCR) beta chain repertoire in 13 purified T cell subsets from the ImmuNexUT database, consisting of 407 donors with ten immune-mediated diseases and healthy controls. ResultsHLA class II alleles were associated with TRBV gene usage and the public clones of CD4 T cells, while HLA class I alleles were associated with CD8 T cells. RA-risk and immune-mediated diseases-risk HLA alleles were associated with TRBV gene usage of naive and effector CD4 T cell subsets and public clones accumulating in Th17. Clonal diversity was independent of HLA alleles and was correlated with transcriptome changes that reflect TCR signaling. ConclusionThis study revealed in vivo evidence that both HLA alleles and environmental factors shape naive and effector TCR repertoires in RA and immune-mediated diseases patients.

Human T cells in barrier sites exhibit site-specific characteristics and clonal compartmentalization

Abstract The skin, gut, and lung are critical physical and immune barriers that protect from pathogen entry. Within these sites, T cell memory is largely maintained by populations of tissue resident memory T cells (TRMs), capable of rapid protective responses. The degree of interconnection between these TRMs from various sites of residence is poorly understood, particularly in humans. Here, we analyze how tissue specificity affects transcriptional heterogeneity and the T cell receptor (TCR) repertoire across 9 tissue sites within individual donors, including barrier sites (skin, gut, and lung) and associated lymph nodes, as well as blood and lymphoid organs (blood, bone marrow, spleen). Cytometry by time-of-flight (CyTOF) and single cell RNA sequencing reveal phenotypic and transcriptomic features unique to skin or gut T cells, which are distinct from T cells in lymphoid sites or blood. These results were reflected in both bulk sequencing of TRBV gene rearrangement and single cell TCR sequencing, where skin and gut T cells exhibited site-specific clonal expansions that were not present in other sites. Conversely, lung T cells showed clonal overlap and transcriptional similarity to T cells in lymphoid and blood rich sites. Site-specific expansions were mediated by TRMs, while clones disseminated across tissues exhibit large clonal expansions and a CD8 terminal effector (TEMRA) phenotype. Together, these results reveal that TRMs in barrier sites are maintained in situ, while memory T cells in the lung, blood-rich and lymphoid sites are more interconnected. Blood T cells are not representative of barrier T cell clonal space. These results have important implications for monitoring and promoting barrier immunity through site-specific targeting. Supported by grants from NIH (P01 AI106697)

High-throughput T cell receptor sequencing reveals differential immune repertoires in autoimmune thyroid diseases

BackgroundAutoimmune thyroid diseases (AITDs) are chronic autoimmune diseases specific to thyroid and mainly include Graves’ disease (GD) and Hashimoto’ thyroiditis (HT). The adaptive immunoreactivity of CD4+ T cells plays a crucial role in the pathogenesis of AITDs, but very little has been known about its changes in disease status. MethodsWe collected peripheral CD4+ T cells from 12 GD patients, including 6 newly diagnosed GD (NGD) and 6 refractory GD (RGD) patients, 6 HT patients and 6 healthy controls, and examined the gene expression profiles and colon types of T cells receptor (TCR) β chain complementarity determining region 3 (CDR3) using high-throughput sequencing. ResultsThe TCR repertoire were significantly expanded in AITDs groups, and some TCR genes were expressed more preferentially in AITDs group than in the healthy control group, including TRBV15 (P = 0.001), TRBV4-2 (P = 0.003), TRBV9 (P = 0.007), TRBV3-2 (P = 0.012), TRBV7-8 (P = 0.015), TRBV25-1 (P = 0.019), TRBV12-4 (P = 0.019) and TRBV27 (P = 0.02) in GD patients as well as TRBV29-1 (P = 0.004), TRBV12-4 (P = 0.004), TRBV6-5 (P = 0.011), TRBV7-2 (P = 0.012), TRBV27 (P = 0.012), TRBV9 (P = 0.031) and TRBV4-2 (P = 0.032) in HT patients. Moreover, subgroup analysis showed that the difference in the TCR spectrum between the normal group and NGD was not obvious, but a large number of differential genes appeared in the RGD group. ConclusionTCR spectrum has changed in patients with AITDs with expanded repertoire and many upregulated TRBV genes. Moreover, this difference is not apparent in GD patients at the initial stage, but as the disease progresses, the differences in TCR profiles became more pronounced.

Repertoire analyses reveal T cell antigen receptor sequence features that influence T cell fate.

T cells acquire a regulatory phenotype when their T cell receptors (TCRs) experience an intermediate-to-high affinity interaction with a self-peptide presented via the major histocompatibility complex (MHC). Using TCRβ sequences from flow-sorted human cells, we identified TCR features that promote regulatory T cell (Treg) fate. From these results, we developed a scoring system to quantify TCR-intrinsic regulatory potential (TiRP). When applied to the tumor microenvironment, TiRP scoring helped to explain why only some T cell clones maintained the Tconv phenotype through expansion. To elucidate drivers of these predictive TCR features, we then examined the two elements of the Treg TCR ligand separately: the self-peptide, and the human MHC II molecule. These analyses revealed that hydrophobicity in the third complementarity determining region (CDR3β) of the TCR promotes reactivity to self-peptides, while TCR variable gene (TRBV gene) usage shapes the TCR’s general propensity for human MHC II-restricted activation.

A High-Throughput Strategy for T-Cell Receptor Cloning and Expression.

Expression of T-cell receptor (TCR) genes is a critical step for TCR characterization and epitope identification. The recent interest in using specific TCRs for cancer immunotherapy has further increased the demand for practical and robust methods to rapidly clone and express TCRs. We show that a recombination-based cloning protocol facilitates simple and rapid transfer of the TCR transgene into different expression systems. In this protocol, we first constructed all the human TRAV and TRBV genes into individual plasmid. To clone any TCR, we only need to ligate a short CDR3 fragment to its corresponding V gene plasmid using Golden Gate cloning. This strategy significantly improves the efficiency of individual TCR cloning and mutagenesis, providing a flexible high-throughput method for TCR analysis and TCR-mediated therapeutics.

Azacitidine-induced reconstitution of the bone marrow T cell repertoire is associated with superior survival in AML patients

Hypomethylating agents (HMA) like azacitidine are licensed for the treatment of acute myeloid leukemia (AML) patients ineligible for allogeneic hematopoietic stem cell transplantation. Biomarker-driven identification of HMA-responsive patients may facilitate the choice of treatment, especially in the challenging subgroup above 60 years of age. Since HMA possesses immunomodulatory functions that constitute part of their anti-tumor effect, we set out to analyze the bone marrow (BM) immune environment by next-generation sequencing of T cell receptor beta (TRB) repertoires in 51 AML patients treated within the RAS-AZIC trial. Patients with elevated pretreatment T cell diversity (11 out of 41 patients) and those with a boost of TRB richness on day 15 after azacitidine treatment (12 out of 46 patients) had longer event-free and overall survival. Both pretreatment and dynamic BM T cell metrics proved to be better predictors of outcome than other established risk factors. The favorable broadening of the BM T cell space appeared to be driven by antigen since these patients showed significant skewing of TRBV gene usage. Our data suggest that one course of AZA can cause reconstitution to a more physiological T cell BM niche and that the T cell space plays an underestimated prognostic role in AML.Trial registration: DRKS identifier: DRKS00004519

Specific T Cell Receptor Gene Repertoire Profiles in Subgroups of CLL Patients with Distinct Genomic Aberrations

Chronic lymphocytic leukemia (CLL) B cells engage in multifaceted bi-directional interactions with bystander cells, including T cells. Immunogenetic studies in CLL revealed clonal expansions of T cells and shared T cell clonotypes between different patients, strongly implying clonal selection by antigens. Although the exact nature of these antigens remains largely elusive, evidence exists that the clonotypic B cell receptor immunoglobulin (BcR IG) may serve as a source of antigenic epitopes for T cells. That said, recurrent genomic aberrations associated with distinct abnormal expression profiles could represent an alternative, non mutually exclusive, source of potent immunogenic onco-antigens that might shape the T cell repertoire in CLL. On these grounds, here we interrogated the T cell receptor (TR) gene repertoire of CLL patients with different genomic aberration profiles with the aim to identify unique signatures that would allude to distinct antigen selection pressures. The study group included 46 patients with CLL, sampled before treatment initiation, who were categorized in 5 subgroups defined by a unique genomic aberration, as follows: +12, n=18; del(11q), n=10; del(13q), n=7; del(17p)/TP53mut, n=6; NOTCH1mut, n=5. Confounding effects of multiple aberrations have been minimized, as we previously established through comprehensive characterization (including FISH, SNP arrays and gene panels) that the analyzed patients carried only one of the above aberrations. Starting material was RNA extracted from blood mononuclear cells. TRBV-TRBD-TRBJ gene rearrangements were RT-PCR amplified and subjected to paired-end next generation sequencing (NGS). Raw NGS reads (n=13,213,563| median: 294,757/sample) were processed through a purpose-built bioinformatics pipeline. Only productive rearrangements (n=9,249,546 | median=199,184/sample) were taken into consideration for the computation of clonotypes i.e. TRB rearrangements with identical TRBV gene usage and amino acid complementarity-determining region 3 (CDR3) sequence. Overall, 513,984 distinct clonotypes (median=10,304 clonotypes/sample) were assessed. The main measure of clonality employed in this study was the median cumulative frequency of the 10 most expanded T cell clonotypes/sample (MCF-10). For comparisons of the clonality profiles, a group of 17 aged-matched healthy individuals were used as controls. All patients displayed oligoclonal T cell expansions with the following MCF-10 values: del(11q): 21.6%, +12: 25%, del(13q): 20.6%, NOTCH1mut: 9.1%, del(17p)/TP53mut: 12.9%; the difference between the del(11q) and +12 groups versus the NOTCH1mut group was statistically significant (p<0.05). The MCF-10 value of the control group was estimated at 17.5%, supporting the notion of age-related decrease in TR repertoire diversity. However, the del(11q), +12 and del(13q) CLL groups displayed elevated clonality, reaching statistical significance (p<0.002) in the case of +12. TRBV gene repertoire analysis revealed that the TRBV12-3 gene predominated in most groups, except for the del(17p)/TP53mut, where the predominant gene was TRBV10-3. Clonotype comparisons disclosed the presence of shared TR clonotypes both within a particular group but also between groups. Overall, 446/513,984 clonotypes were found to be shared by at least two patients across all groups; the vast majority (392/446, 88%) of shared clonotypes appeared to be CLL-biased since they did not match entries in public databases of TR clonotypes from various contexts. Subgroup-specific clonotypes were identified for all aberrations examined; these emerged as unique to the particular subgroups, as revealed by extensive comparisons against both public databases but also a large TR clonotype database from CLL available to us from our previous studies. In conclusion, recurrent genomic aberrations, especially large chromosomal abnormalities, display an oligoclonal TR gene repertoire. The distinct immunogenetic profile of each group examined here and, most importantly, the existence of subgroup-specific clonotypes, suggest that abnormal protein expression and gene dosage effects likely represent a relevant source of CLL-specific selecting antigens. DisclosuresScarfo: Janssen: Honoraria, Other: Travel grants; Astra Zeneca: Honoraria; Abbvie: Honoraria. Anagnostopoulos: Abbvie: Other: clinical trials; Sanofi: Other: clinical trials ; Ocopeptides: Other: clinical trials ; GSK: Other: clinical trials; Incyte: Other: clinical trials ; Takeda: Other: clinical trials ; Amgen: Other: clinical trials ; Janssen: Other: clinical trials; novartis: Other: clinical trials; Celgene: Other: clinical trials; Roche: Other: clinical trials; Astellas: Other: clinical trials . Ghia: AbbVie: Consultancy, Honoraria, Research Funding; Acerta/AstraZeneca: Consultancy, Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria, Research Funding; ArQule/MSD: Consultancy, Honoraria; BeiGene: Consultancy, Honoraria; Celgene/Juno/BMS: Consultancy, Honoraria; Gilead: Consultancy, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria; Sunesis: Research Funding. Haferlach: MLL Munich Leukemia Laboratory: Other: Part ownership. Rosenquist: Roche: Honoraria; Janssen: Honoraria; Illumina: Honoraria; AstraZeneca: Honoraria; Abbvie: Honoraria. Stamatopoulos: Gilead: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding. Baliakas: Janssen: Honoraria; Gilead: Honoraria, Research Funding; Abbvie: Honoraria. Chatzidimitriou: Abbvie: Honoraria, Research Funding; Janssen: Honoraria, Research Funding.

Chronic Graft-Versus-Host Disease Immunoprofiling Reveals T Cell Clonal Dynamics That Correlate with Disease Activity: A Novel Molecular “Biomarker”?

Chronic graft-versus-host disease (cGVHD) is the main cause of morbidity and transplant-related mortality following allogeneic hematopoietic stem cell transplantation (alloHSCT), however effective treatment options are limited. Lack of objective surrogates (biomarkers) for treatment response has hindered progress in this respect. T cells are considered the major effectors of cGVHD, yet the respective repertoires are insufficiently charted. Here, we investigated the dynamic architecture of T-cell repertoires in cGVHD by exploiting next-generation sequencing (NGS), aiming to uncover immunogenetic signatures linked with cGHVD occurrence and response to treatment.We analyzed 53 blood samples from 15 patients with hematological malignancies who underwent alloHSCT, with an intended bias towards patients who developed cGVHD (n=12). The remaining 3 patients had no cGVHD (control group). Patients with cGVHD were analyzed at cGVHD onset and/or prior to a new line of treatment (n=17 samples) as well as at clinically relevant timepoints following treatment: (i) partial response (PR, n=8), (ii) complete response (CR, n=3), (iii) stable disease (SD, n=18), (iv) progression (PD, n=1). Treatment modalities involved corticosteroids, mycophenolate myfetil, extracorporeal phototherapy, ruxolitinib and ibrutinib. Patients with no cGVHD were analyzed at 3 months (+3mo) and 6 months (+6mo) post-alloHSCT (n=6 samples). Starting material was PB mononuclear cells. TRBV-TRBD-TRBJ gene rearrangements were RT-PCR amplified and subjected to paired-end NGS and detailed bioinformatics analysis. Only productive TRBV-TRBD-TRBJ rearrangements were evaluated (n= 13,059,730, 89.9% of filtered-in sequences, median 219,063/sample). For repertoire characterization, clonotypes (i.e., TRB rearrangements with identical TRBV gene usage and amino acid complementarity-determining region 3 sequence) were considered (median 9,725 distinct clonotypes/sample). The 10 most frequent clonotypes/sample were defined as “major”. To purge T cell clones expanded secondary to viruses common in the alloHSCT setting, we compared all major clonotypes against the GenBank TRB sequence database (n=18,402), as well as an extensive TR repertoire dataset from a previous study by our group, profiling tri-virus-specific (CMV, EBV, BK) T cell products generated from immunocompetent donors (n=947,298).Overall, we identified 289 unique major clonotypes; 38 were excluded due to match within the tri-VST database (no match within GenBank). All cases with cGVHD displayed significant clonal T cell expansions both pre- and post-treatment (overall median cumulative frequency of the 6 most expanded T cell clonotypes/sample 32.4%). However, clonality tended to decrease in PR samples compared to pre-treatment (19.8% vs 33.9%, respectively), although not reaching statistical significance possibly due to small sample size (p=0.06). Patients with no cGVHD, on the other hand, consistently displayed a clonality decrease overtime (31.8% at +3mo vs 18.4% at +6mo, p=0.02). Importantly, patients with no GVHD displayed TR repertoire reconstitution with few major T cell clones of the +3mo timepoint persisting at +6mo (median 20%). In clear contrast, cGVHD T cell repertoires were dominated by clones which persisted overtime (median 60%). In fact, repertoire persistence was most evident in SD (median 66.7%) and significantly lower in PR and CR (33.3% and 10.0%, respectively, p<0.05), suggesting that the persisting T cell clones are implicated in cGVHD pathogenesis. Notably, repertoire comparisons across patients in our cohort revealed 6 “public” clonotypes [5 clonotypes shared among a single pair of patients (Pt1 and Pt2) and 1 clonotype shared among the same pair plus an additional patient, Pt3], suggesting the existence of a common antigenic trigger.In conclusion, NGS immunoprofiling in cGVHD reveals expanded T cell clones with clonal dynamics that correlate with clinical response, indicating a causal relationship to cGVHD pathogenesis. Identification and longitudinal tracking of T cell clones associated with cGHVD could serve as a molecular surrogate marker for disease activity, with evident benefits for cGVHD monitoring and evaluation of response to various treatments. DisclosuresAnagnostopoulos: Abbvie: Other: clinical trials; Sanofi: Other: clinical trials ; Ocopeptides: Other: clinical trials ; GSK: Other: clinical trials; Incyte: Other: clinical trials ; Takeda: Other: clinical trials ; Amgen: Other: clinical trials ; Janssen: Other: clinical trials; novartis: Other: clinical trials; Celgene: Other: clinical trials; Roche: Other: clinical trials; Astellas: Other: clinical trials . Chatzidimitriou: Janssen: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding.

Mapping the spatial distribution of T cells in repertoire dimension

T cells mediate adaptive immunity in diverse anatomic compartments through recognition of specific antigens via unique T cell receptor (TCR) structures. However, little is known about the spatial distribution of an organism’s TCR repertoire. Here, using high-throughput TCR sequencing (TCRseq), we investigated the TCR repertoires of sixteen tissues in healthy C57B/L6 mice. We found that TCR repertoires generally classified into three categories (lymph nodes, non-lymph node tissues and small intestine) based on sequence similarity. Clonal distribution and diversity analyses showed that small intestine compartment had a more skewed repertoire as compared to lymph nodes and non-lymph node tissues. However, analysis of TRBV and TRBJ gene usage across tissue compartments, as well as comparison of CDR3 length distributions, showed no significant tissue-dependent differences. Interestingly, analysis of clonotype sharing between mice showed that although non-redundant public clonotypes were found more easily in lymph nodes, small intestinal CD4 + T cells harbored more abundant public clonotypes. These findings under healthy physiological conditions offer an important reference dataset, which may contribute to our ability to better manipulate T cell responses against infection and vaccination.