Restrictions in the T-cell repertoire of chronic lymphocytic leukemia: high-throughput immunoprofiling supports selection by shared antigenic elements

Leukemia ◽  
2016 ◽  
Vol 31 (7) ◽  
pp. 1555-1561 ◽  
Author(s):  
A Vardi ◽  
E Vlachonikola ◽  
M Karypidou ◽  
E Stalika ◽  
V Bikos ◽  
...  
Keyword(s):  
T Cell ◽  
Chronic Lymphocytic Leukemia ◽  
High Throughput ◽  
Lymphocytic Leukemia ◽  
T Cell Repertoire ◽  
Cell Repertoire

scholarly journals Ibrutinib Therapy Increases T Cell Repertoire Diversity in Patients with Chronic Lymphocytic Leukemia

2017 ◽  
Vol 198 (4) ◽  
pp. 1740-1747 ◽  
Author(s):  
Qingsong Yin ◽  
Mariela Sivina ◽  
Harlan Robins ◽  
Erik Yusko ◽  
Marissa Vignali ◽  
...  
Keyword(s):  
T Cell ◽  
Chronic Lymphocytic Leukemia ◽  
Lymphocytic Leukemia ◽  
T Cell Repertoire ◽  
Cell Repertoire ◽  
Repertoire Diversity

scholarly journals Antigen Selection Shapes the T-cell Repertoire in Chronic Lymphocytic Leukemia

2015 ◽  
Vol 22 (1) ◽  
pp. 167-174 ◽  
Author(s):  
Anna Vardi ◽  
Andreas Agathangelidis ◽  
Evangelia Stalika ◽  
Maria Karypidou ◽  
Alexandra Siorenta ◽  
...  
Keyword(s):  
T Cell ◽  
Chronic Lymphocytic Leukemia ◽  
Lymphocytic Leukemia ◽  
T Cell Repertoire ◽  
Cell Repertoire ◽  
Antigen Selection

The number of cytomegalovirus-specific CD4+ T cells is markedly expanded in patients with B-cell chronic lymphocytic leukemia and determines the total CD4+ T-cell repertoire

Blood ◽  
2010 ◽  
Vol 116 (16) ◽  
pp. 2968-2974 ◽  
Author(s):  
Batoul Pourgheysari ◽  
Rachel Bruton ◽  
Helen Parry ◽  
Lucinda Billingham ◽  
Chris Fegan ◽  
...  
Keyword(s):  
Immune Response ◽  
T Cells ◽  
T Cell ◽  
Chronic Lymphocytic Leukemia ◽  
B Cell ◽  
Lymphocytic Leukemia ◽  
Cd4 T Cell ◽  
T Cell Repertoire ◽  
Cell Repertoire ◽  
Cell Chronic Lymphocytic Leukemia

Abstract B-cell chronic lymphocytic leukemia is associated with immune suppression and an altered T-cell repertoire with expansion of memory cells. Cytomegalovirus (CMV) is a common herpes virus that elicits a strong virus-specific T-cell immune response after infection. We studied the CMV-specific CD4+ T-cell response in 45 patients and 35 control subjects and demonstrated that it was markedly expanded in the patient group, averaging 11% of the CD4+ pool compared with 4.7% in controls. The magnitude of the CMV-specific CD4+ immune response increased with disease stage and was particularly high in patients who received chemotherapy. Within this group, the CMV-specific response comprised over 46% of the CD4+ T-cell repertoire in some patients. Serial analysis revealed that CMV-specific immunity increased during treatment with chemotherapy and remained stable thereafter. CMV-seropositive patients exhibited a markedly altered CD4+ T-cell repertoire with increased numbers of CD45R0+ T cells and a reduction in CD27, CD28, and CCR7 expression. Overall survival was reduced by nearly 4 years in CMV-seropositive patients, although this did not reach statistical significance. CLL patients therefore demonstrate an expansion of the CD4+ CMV-specific immune response, which is likely to contribute to the immunological and clinical features of this disease.

scholarly journals Defining the Alloreactive T Cell Repertoire Using High-Throughput Sequencing of Mixed Lymphocyte Reaction Culture

PLoS ONE ◽  
2014 ◽  
Vol 9 (11) ◽  
pp. e111943 ◽  
Author(s):  
Ryan O. Emerson ◽  
James M. Mathew ◽  
Iwona M. Konieczna ◽  
Harlan S. Robins ◽  
Joseph R. Leventhal
Keyword(s):  
T Cell ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Mixed Lymphocyte Reaction ◽  
T Cell Repertoire ◽  
Cell Repertoire ◽  
Alloreactive T Cell

scholarly journals High-throughput sequencing reveals an altered T cell repertoire in X-linked agammaglobulinemia

2015 ◽  
Vol 161 (2) ◽  
pp. 190-196 ◽  
Author(s):  
Manish Ramesh ◽  
Noa Simchoni ◽  
David Hamm ◽  
Charlotte Cunningham-Rundles
Keyword(s):  
T Cell ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
T Cell Repertoire ◽  
Cell Repertoire

Next Generation Sequence Immunoprofiling of the T-Cell Repertoire in Chronic Lymphocytic Leukemia Supports Selection By Shared Antigenic Elements

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 618-618 ◽  
Author(s):  
Anna Vardi ◽  
Maria Karipidou ◽  
Aikaterini Gemenetzi ◽  
Elissavet Vlachonikola ◽  
Vassileios Bikos ◽  
...  
Keyword(s):  
T Cell ◽  
Cell Receptor ◽  
Lymphocytic Leukemia ◽  
Gene Repertoire ◽  
Healthy Controls ◽  
T Cell Repertoire ◽  
Cell Repertoire ◽  
Repertoire Analysis ◽  
Trbv Gene ◽  
Quality Filtering

Abstract Chronic lymphocytic leukemia (CLL) is characterized by remarkable skewing of the B-cell receptor immunoglobulin (BcR IG) repertoire, culminating in the existence of subsets of patients with stereotyped BcR IGs. This implies antigen selection in the natural history of CLL, ultimately affecting clonal behavior. Currently, limited information is available regarding the role of antigens in the selection and activation of cognate T cells, although this is relevant in light of B and T cell interactions inducing T cell tolerance. Our preliminary next-generation sequencing (NGS) studies in 11 patients assigned to stereotyped subset #4, a clinically indolent disease subgroup, indicated T-cell receptor beta chain (TRB) gene repertoire restriction and oligoclonality. Prompted by these observations, here we sought to obtain a comprehensive view of the T-cell repertoire in CLL by extending our analysis to 36 untreated CLL patients, either assigned to major stereotyped subsets [subset #4 (n=11), subset #1 (n=10), subset #2 (n=4), subset #16 (n=1)] or non-subset cases [with mutated-M (n=5) or unmutated-UM clonotypic BcR IGs (n=5)]. Starting material was PB mononuclear cells (n=27), purified CD4+ and CD8+ T-cell subpopulations (n=10), bone marrow (n=2) or lymph node (LN) tissue (n=1). Three patients were studied overtime. Multiple sample and PCR replicates, as well as 3 age-matched healthy controls were also included. TRBV-TRBD-TRBJ gene rearrangements were amplified on cDNA (BIOMED2 protocol) and subjected to paired-end NGS, designed to cover the complementarity determining region 3 (CDR3) twice/sequence. In order to further increase the accuracy of results, raw NGS reads were subjected to a purpose-built, bioinformatics algorithm, performing: (i) length and quality filtering of raw reads; (ii) merging of filtered-in paired reads via local alignment; (iii) length and quality filtering of stitched sequences. No base calls of Q-score<30 were allowed in the 75 nucleotide stretch ahead of the FGXG motif, thus further increasing the CDR3 sequencing reliability. Filtered-in sequences were submitted to IMGT/HighV-QUEST, and metadata was processed by an in-house bioinformatics pipeline designed for clonotype computation and repertoire analysis. Overall, 66 samples were analyzed, producing 23,238,779 filtered-in sequences. Only productive, in-frame TRBV-TRBD-TRBJ rearrangements were included in the analysis (85.8% of filtered-in sequences, median 354,972/sample). For repertoire analysis, clonotypes (i.e. TRB rearrangements with identical TRBV gene usage and amino acid CDR3 sequence) were considered (median 37,550 distinct clonotypes/sample; 13,134 expanded versus 22,550 singletons). The distribution of TRBV genes was asymmetric with only 5 genes [TRBV12-3/12-4 (8.4%), TRBV19 (6.8%), TRBV29-1 (6.6%), TRBV5-1 (6.1%), TRBV6-5 (5.2%)] collectively accounting for one-third of the repertoire, indicating functional constraints. No significant TRBV gene repertoire difference was identified across the different immunogenetic CLL subgroups analyzed. In contrast, significant (p<0.001) differences were seen between CD8+ versus CD4+ cells regarding certain genes (e.g. over-representation of TRBV7-2 in CD4+ and under-representation of TRBV5-1 in CD8+ cells), alluding to distinct immune selective processes. Notably, the TRB repertoire was significantly more oligoclonal in CLL compared to the healthy controls (median frequency of the predominant clonotype: 5.7% versus 1.27%, respectively, p<0.05), albeit with differences between cases with distinct BcR IG, perhaps reflecting their different immunopathogenesis. Overtime analysis showed persistence of most major clonotypes in 2/3 cases studied, likely in a context of persistent antigenic stimulation. Cluster analysis of all CLL cases identified 17,592 different clonotypes (excluding singletons) shared by different patients and not present in the healthy controls, arguing in favor of a disease-biased immunoprofile; formal proof of this claim will require analysis of a larger number of healthy controls, currently underway by our group. In conclusion, massive parallel sequencing documents the restricted nature of the TRB repertoire in CLL, supporting selection by shared antigenic elements. Whether these are the same antigens interacting with the malignant clone remains to be elucidated. Disclosures Stamatopoulos: Janssen Pharmaceuticals: Research Funding; Gilead Sciences: Research Funding.

scholarly journals Longitudinal High-Throughput T Cell Repertoire Profiling of Chronic Lymphocytic Leukemia Patients Under Different Types of Treatment: Implications for Combination Strategies

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 4400-4400
Author(s):  
Anna Vardi ◽  
Elisavet Vlachonikola ◽  
Nikolaos Ioannou ◽  
Fotis Psomopoulos ◽  
Konstantia Kotta ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Clinical Response ◽  
Research Funding ◽  
Post Treatment ◽  
Lymphocytic Leukemia ◽  
Effector Memory ◽  
T Cell Repertoire ◽  
Cell Repertoire ◽  
Activation Markers

Abstract Using next-generation sequencing (NGS), we recently documented the clonal architecture of the T cell repertoire in treatment-naive chronic lymphocytic leukemia (CLL), with ample immunogenetic evidence indicating selection by restricted antigens. Our preliminary NGS study in 16 patients pre- and 3-month post-treatment indicated a differential impact of standard chemoimmunotherapy (FCR) versus B cell receptor signaling inhibitors (BcRi) on CLL T cells. Prompted by these observations, here we sought to comprehensively assess CLL T cell repertoire changes over treatment in relation to both treatment type and clinical response by combining NGS immunoprofiling, flow cytometry and functional assays. NGS profiling of the T cell receptor (TR) gene repertoire was performed in 28 CLL patients who received FCR (n=9), ibrutinib (IB, n=15) and/or rituximab-idelalisib (R-ID, n=10) at successive timepoints (pre, +3mo, +9mo and at deepest clinical response, total samples: n=113). TRBV-TRBD-TRBJ gene rearrangements were RT-PCR amplified and subjected to paired-end NGS. Raw reads were processed through a purpose-built, validated bioinformatics pipeline, culminating to 20,347,768 productive, filtered-in TRB sequences (median 155,479/sample). For repertoire analysis, clonotypes (i.e. rearrangements with identical TRBV gene usage and amino acid complementarity-determining region 3 sequence) were considered (median 11,420 distinct clonotypes/sample). All cases displayed significant clonal T cell expansions both pre- and post-treatment [median clonality, measured as the cumulative frequency of the 10 most expanded (major) clonotypes/sample: 30.3% and 39.6%, respectively]. Median clonality significantly increased at +3mo in the FCR (29.0% to 46.9%, p<.001) and R-ID group (33.0% to 39.1%, p<.001), but not in the IB group (33.3% to 31.2%, p>.05). Overtime analysis revealed a gradual increase of clonality over deepening clinical response (pre-, +3mo, +9mo, deepest response) in the R-ID group (33.0% to 39.1% to 46.0% to 46.1%, respectively; p<.001), but only a trend in this respect for IB (33.3% to 31.2% to 33.8% to 42.0%; p>.05). Considering that FCR resulted in T cell repertoire reconstitution whereas BcRis retained pre-treatment clones, we then focused on major clones persisting over treatment and found that they significantly expanded in the R-ID group, peaking at +3mo (p<.01). Cross-comparison across all CLL patients and against 767,438 unique TRB sequences retrieved from multiple public databases (HSV infections, T-cell lymphoproliferations, autoimmune disorders, healthy individuals), revealed 23/563 major clonotypes shared exclusively among CLL patients, alluding to selection by conserved CLL-related antigens. We then sought to test the functional effect of treatments on T cells. To this end, we evaluated activation markers on CLL T cell subpopulations for 8 CLL patients (R-ID, n=4; IB, n=4) pre- and +3mo post-treatment by flow cytometry and found statistically significant upregulation of T cell activation markers for R-ID compared to IB, particularly for: (i) CD69 in CD4+ effector memory T cells (p<.01); (ii) CD25 in CD8+ TEMRA T cells (p=0.006); and, (iii) CD38 in CD8+ effector memory T cells (p<.05) and CD8+ TEMRA T cells (p<.05). We also investigated the ability of CD3+ T cells, purified from 13 patients pre- and +3mo post-treatment (FCR, n=3; R-ID, n=5; IB, n=5), to form immune synapses with autologous pre-treatment CD19+ tumor cells. Quantitative relative recruitment index (RRI) analysis for F-actin showed that both R-ID (p<.01) and IB (p<.05) treated T cells form polarized immune synapses in contrast to FCR (p>.05). Taken together, NGS immunoprofiling suggests that BcRis retain T cell clones that may have developed in response to CLL-related antigens, which in the case of R-ID expand and peak at +3mo. Phenotypic and immune synapse bioassays support a concurrent restoration of functionality, mostly evident for R-ID, arguably contributing to clinical response. Overall, this data provides rationale for designing combination strategies, e.g. of R-ID with immunomodulating drugs, aiming to boost cytotoxic anti-tumor responses. Moreover, identifying the relevant neoepitopes may eventually pave the way for stratified treatments by means of engineered T cells or peptide vaccines, especially if these epitopes are conserved among CLL. Disclosures Vardi: Janssen: Honoraria; Gilead: Research Funding. Gemenetzi:Gilead: Research Funding. Ramsay:MedImmune: Research Funding; Roche Glycart AG: Research Funding; Celgene Corporation: Research Funding. Stamatopoulos:Janssen: Honoraria, Research Funding; Gilead: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding. Hadzidimitriou:Abbvie: Research Funding; Gilead: Research Funding; Janssen: Honoraria, Research Funding.

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