IMMU-28. DECONVOLUTION OF SPATIALLY RESOLVED T CELL RECEPTOR PROFILING (SPTCR-seq) UNCOVERED REGIONAL ANTI-TUMOR IMMUNITY IN GLIOBLASTOMA

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi98-vi98
Author(s):  
Jasim Kada Benotmane ◽  
Jan Kückelhaus ◽  
Kevin Joseph ◽  
Jürgen Beck ◽  
Oliver Schnell ◽  
...  
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
Tumor Immunity ◽  
Clonal Evolution ◽  
Cell Receptor ◽  
Sequencing Data ◽  
Spatially Resolved ◽  
Long Read ◽  
T Cell Clonality ◽  
Cell Clonality

Abstract The diversity to T cell responses and clonality in spatially heterogeneous glioblastoma is of paramount importance to explore underlying mechanisms of anti-tumor immunity. Spatial transcriptomics, a novel technology to map the transcriptional architecture, is technically limited to discover T cell receptor (TCR) sequences as the 3' approach lacks sufficient coverage. Here, we established SPTCR-seq, a method to capture TCR sequences followed by long-read sequencing to enable full-length TCR reconstruction. We performed 10X Visium spatial transcriptomics on 9 primary and recurrent glioblastoma with both 3’-sequencing and SPTCR-seq. For SPTCR-seq, we target enriched T cell receptor sequences by capturing by hybridization followed by Oxford-Nanopore long-read sequencing. The on-target rate was above 80% for captured TCR genes and spatial barcode was successfully aligned in more than 60%. IgBlast and MixCR were used to reconstruct the TCR and map T cell clonality. Within our recent developed spatial transcriptomic analysis framework (SPATA2), we build a novel toolbox, SPATA-Immunology, which enables integration of stRNA-sequencing data and spatially resolved TCR sequencing. Our data showed that clonal evolution of T cells is limited to regional areas underpinned by significant spatial autocorrelation coefficient (0.6-0.95, padj< 0.001). In the surrounding tumor cell spots, the recently described transcriptional program “reactive immune” (RI), was significantly enriched. Using spotlight, a computational approach to project scRNA-sequencing into the spatial space, we found a local enrichment of CD163 positive macrophages exclusively in areas of large T cell clonality. Imaging mass cytometry of a consecutive section confirmed the spatial confluence of T-cell infiltration and CD163-positive macrophages. Through DeepTCR we uncovered potential epitopes which correlate with T cell clonality and might help to discover novel targets for CART therapy. Spatial profiling of TCR sequences through SPTCR-seq is a powerful tool to investigate anti-tumor immunity in glioblastoma and allows to discover general and personalized targets for immunotherapy.

Assessment of T-Cell Receptor Repertoire and Clonal Expansion in Peripheral T-Cell Lymphoma Using RNA-Seq Data

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1451-1451
Author(s):  
Chao Wang ◽  
Qiang Gong ◽  
Weiwei Zhang ◽  
Javeed Iqbal ◽  
Yang Hu ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
T Cell Receptor ◽  
Cell Lymphoma ◽  
Cell Receptor ◽  
T Cell Lymphoma ◽  
Rna Seq ◽  
Tcr Repertoire ◽  
T Cell Clonality ◽  
Cell Clonality

Abstract Introduction: Diversity of the T-cell receptor (TCR) repertoire reflects the initial V(D)J recombination events as shaped by selection by self and foreign antigens. Next generation sequencing is a powerful method for profiling the TCR repertoire, including sequences encoding complementarity-determining region 3 (CDR3). Peripheral T-cell lymphoma (PTCL) is a group of malignancies that originate from mature T-cells. T-cell clonality of PTCL is routinely evaluated with a PCR-based method to detect TCR gamma and less frequently beta chain rearrangements using genomic DNA. However, there are limitations with this approach, chief among which is the lack of sequence information. To date, the TCR repertoire of different subtypes of PTCL remains poorly defined. Objective: The purpose of this study was to determine the utility of RNA-seq for assessing T-cell clonality and analyzing the TCR usage in PTCL samples. Methods: We analyzed RNA-seq data from 30 angioimmunoblastic T-cell lymphoma (AITL), 23 Anaplastic large cell lymphoma (ALCL), 10 PTCL-NOS, and 17 NKCL. Data from naïve T cells, TFH cells, and T-effector cells (CD4+ CD45RA− TCRβ+ PD-1lo CXCR5lo PSGL-1hi) were obtained from publicly available resources. Referenced TCR and immunoglobulin transcripts according to the International ImMunoGeneTics Information System (IMGT) database were quantified by Kallisto software. We divided the pattern of Vβ (T-cell receptor beta variable region) into three categories: monoclonal (mono- or bi-allelic), oligoclonal (3-4 dominant clones), and polyclonal. CDR3 sequences were extracted by MiXCR program. PCR of the gamma chain using genomic DNA was utilized to validate the clonality of selected cases. Single nucleotide variants (SNVs) were called from aligned RNA-seq data using Samtools and VarScan 2 programs. Results: Analysis of RNA-seq data identified preferential usage of TCR-Vβ, Dβ (diversity region), and Jβ (joining region), length diversity of CDR3, and usage of nontemplated bases. Dominant clones could be identified by transcriptome sequencing in most cases of AITL (21/30), ALCL (14/23), and PTCL-NOS (7/10). Median CDR3 length is 42 nucleotides (nt) in normal T cells, 41 nt in ALCL, 48 nt in PTCL-NOS, and 44 nt in AITL. In 30 AITL samples, 20 showed monoclonal Vβ with a single peak, and 9 showed polyclonal Vβ. One case had two dominant clones with different CDR3, only one of which was in frame, implying biallelic rearrangements. As many as 3511 clones supported by at least four reads could be detected in polyclonal cases. In monoclonal cases, the dominant clone varied between 11.8% and 92.8% of TCR with Vβ rearrangements. TRBV 20-1, which is the most commonly used segment in normal T cells, is also frequently used in the dominant clones in AITL. The monoclonal AITL cases showed mutation of TET2, RHOA, DNMT3A or IDH2 whereas most of the polyclonal cases were negative or had low VAF mutation suggesting low or absent of tumor infiltrate in the specimen sequenced. There is no obvious correlation of any of the mutations with Vβ usage. Clonal B cell expansion was noted in some AITL samples. The occurrence of a preferential TRBV9 expansion in PTCL-NOS was striking. More than half of ALCL samples (14/23) showed expression of clonal Vβ, but 3/14 dominant clones were out-of-frame. γ chain expression was very low in cells expressing TCRαβ, but both expression levels and clonality were higher in TCRγδ expressing tumors. NKCL did not express significant levels of TCR Vβ or Vγ genes. Discussion/Interpretation: Transcriptome sequencing is a useful tool for understanding the TCR repertoire in T cell lymphoma and for detecting clonality for diagnosis. Clonal, often out-of-frame, Vβ transcripts are detectable in most ALCL cases and preferential TRBV9 usage is found in PTCL-NOS. Disclosures No relevant conflicts of interest to declare.

Replacement therapy with plasma-derived factor VIII concentrates induces skew in T-cell receptor usage and clonal expansion of CD8+ T-cell in HIV-seronegative hemophilia patients

2003 ◽  
Vol 90 (08) ◽  
pp. 279-292 ◽  
Author(s):  
Takaji Matsutani ◽  
Yoshihiko Sakurai ◽  
Takeshi Yoshioka ◽  
Yuji Tsuruta ◽  
Ryuji Suzuki ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Factor Viii ◽  
Replacement Therapy ◽  
T Cell Receptor ◽  
Cd8 T Cells ◽  
Clonal Expansion ◽  
Cell Receptor ◽  
T Cell Clonality ◽  
Cell Clonality

SummaryReplacement therapy with factor VIII (FVIII) products causes immune abnormalities in human immunodeficiency virus (HIV)-seronegative hemophilia patients. However, the question remains why an absolute increase in the number of CD8+ T-cells and diminished proliferation responses of lymphocytes to antigen stimulation in vitro occurs in HIV-seronegative hemophilia patients.To examine whether the FVIII products induce skewing of T-cell receptor (TCR) repertoires, TCR variable region α-chain and β–chain repertoires were analyzed for peripheral blood mononuclear cells (PBMCs) from 15 hemophilia patients treated with heated and/or non-heated plasma-derived FVIII concentrates and 10 age-matched healthy adults. Also, T-cell clonality was compared between these groups using complementarity-determining region 3 (CDR3) size spectratyping. The skewing of TCR repertoires was significantly greater for hemophilia patients than healthy controls. The extent of T-cell clonality was greater for hemophilia patients than the controls, indicating that clonal T-cells frequently expanded in hemophilia patients. The skew in TCR usage and clonal expansion were primarily observed in patients treated with non-heated plasma-derived products.The spectratyping and sequencing of CDR3 regions revealed that the clonal expansion of T-cells was observed for CD8+ T-cells, but not CD4+ T-cells.These results suggest that extensive expansion of CD8+ T-cells is induced by some viruses other than HIV present in FVIII preparations, and the resulting accumulation of CD8+ T-cells is responsible for changes in peripheral T-cell population in HIV-seronegative hemophilia patients.

scholarly journals T cell clonality assessment: past, present and future

2017 ◽  
Vol 71 (3) ◽  
pp. 195-200 ◽  
Author(s):  
Etienne Mahe ◽  
Tevor Pugh ◽  
Suzanne Kamel-Reid
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
Clonal Diversity ◽  
Cell Receptor ◽  
And Function ◽  
Next Generation Sequencing Ngs ◽  
Conceptual Foundations ◽  
T Cell Clonality ◽  
Cell Proliferations ◽  
Cell Clonality

T cell clonality testing has important clinical and research value, providing a specific and reproducible assessment of clonal diversity in T cell proliferations. Here we review the conceptual foundations of T cell clonality assays, including T cell ontogeny and T cell receptor structure and function; we also provide an introduction to T cell receptor genomics and the concept of the T cell clonotype. This is followed by a review of historical and current methods by which T cell clonality may be assayed, including current assay limitations. Some of these assay limitations have been overcome by employing next-generation sequencing (NGS)-based technologies that are becoming a mainstay of modern molecular pathology. In this vein, we provide an introduction to NGS technologies, including a review of the preanalytical, analytical and postanalytical technologies relevant to T cell clonality NGS assays.

scholarly journals T-Cell Lymphoma Clonality by Copy Number Variation Analysis of T-Cell Receptor Genes

Cancers ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 340
Author(s):  
Ming Liang Oon ◽  
Jing Quan Lim ◽  
Bernett Lee ◽  
Sai Mun Leong ◽  
Gwyneth Shook-Ting Soon ◽  
...  
Keyword(s):  
T Cell ◽  
B Cell ◽  
T Cell Receptor ◽  
Copy Number ◽  
Nk Cell ◽  
Cell Receptor ◽  
T Cell Lymphomas ◽  
Number Variation ◽  
Diagnostic Applications ◽  
Cell Clonality

T-cell lymphomas arise from a single neoplastic clone and exhibit identical patterns of deletions in T-cell receptor (TCR) genes. Whole genome sequencing (WGS) data represent a treasure trove of information for the development of novel clinical applications. However, the use of WGS to identify clonal T-cell proliferations has not been systematically studied. In this study, based on WGS data, we identified monoclonal rearrangements (MRs) of T-cell receptors (TCR) genes using a novel segmentation algorithm and copy number computation. We evaluated the feasibility of this technique as a marker of T-cell clonality using T-cell lymphomas (TCL, n = 44) and extranodal NK/T-cell lymphomas (ENKTLs, n = 20), and identified 98% of TCLs with one or more TCR gene MRs, against 91% detected using PCR. TCR MRs were absent in all ENKTLs and NK cell lines. Sensitivity-wise, this platform is sufficiently competent, with MRs detected in the majority of samples with tumor content under 25% and it can also distinguish monoallelic from biallelic MRs. Understanding the copy number landscape of TCR using WGS data may engender new diagnostic applications in hematolymphoid pathology, which can be readily adapted to the analysis of B-cell receptor loci for B-cell clonality determination.

scholarly journals Human T cell receptor occurrence patterns encode immune history, genetic background, and receptor specificity

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
William S DeWitt ◽  
Anajane Smith ◽  
Gary Schoch ◽  
John A Hansen ◽  
Frederick A Matsen ◽  
...  
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
Genetic Background ◽  
Cell Receptor ◽  
Sequencing Data ◽  
Human T Cell ◽  
Disease Associations ◽  
Repertoire Sequencing ◽  
Mhc Polymorphism ◽  
Occurrence Patterns

The T cell receptor (TCR) repertoire encodes immune exposure history through the dynamic formation of immunological memory. Statistical analysis of repertoire sequencing data has the potential to decode disease associations from large cohorts with measured phenotypes. However, the repertoire perturbation induced by a given immunological challenge is conditioned on genetic background via major histocompatibility complex (MHC) polymorphism. We explore associations between MHC alleles, immune exposures, and shared TCRs in a large human cohort. Using a previously published repertoire sequencing dataset augmented with high-resolution MHC genotyping, our analysis reveals rich structure: striking imprints of common pathogens, clusters of co-occurring TCRs that may represent markers of shared immune exposures, and substantial variations in TCR-MHC association strength across MHC loci. Guided by atomic contacts in solved TCR:peptide-MHC structures, we identify sequence covariation between TCR and MHC. These insights and our analysis framework lay the groundwork for further explorations into TCR diversity.

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