scholarly journals Systematic discovery of receptor-ligand biology by engineered cell entry and single-cell genomics

2021 ◽  
Author(s):  
Bingfei Yu ◽  
Quanming Shi ◽  
Julia A Belk ◽  
Kathryn E Yost ◽  
Kevin R Parker ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
Phenotypic Diversity ◽  
Cell Receptor ◽  
Cell Entry ◽  
Effector Memory ◽  
Target Cells ◽  
Receptor Specificity ◽  
Ligand Interaction ◽  
Receptor Ligand

Cells communicate with each other via receptor-ligand interactions on the cell surface. Here we describe a technology for lentiviral-mediated cell entry by engineered receptor- ligand interaction (ENTER) to decode receptor specificity. Engineered lentiviral particles displaying specific ligands deliver fluorescent proteins into target cells upon cognate receptor-ligand interaction, without genome integration or transgene transcription. We optimize ENTER to decode interactions between T cell receptor (TCR)-MHC peptides, antibody-antigen, and other receptor-ligand pairs. We develop an effective presentation strategy to capture interactions between B cell receptor (BCR) and intracellular antigen epitopes. Single-cell readout of ENTER by RNA sequencing (ENTER-seq) enables multiplexed enumeration of TCR-antigen specificities, clonality, cell type, and cell states of individual T cells. ENTER-seq of patient blood samples after CMV infection reveals the viral epitopes that drive human effector memory T cell differentiation and inter-clonal phenotypic diversity that targets the same epitope. ENTER enables systematic discovery of receptor specificity, linkage to cell fates, and cell-specific delivery of gene or protein payloads.

scholarly journals Single-cell transcriptomics identifies multiple pathways underlying antitumor function of TCR- and CD8αβ-engineered human CD4+ T cells

2020 ◽  
Vol 6 (27) ◽  
pp. eaaz7809 ◽  
Author(s):  
Jan A. Rath ◽  
Gagan Bajwa ◽  
Benoit Carreres ◽  
Elisabeth Hoyer ◽  
Isabelle Gruber ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Cell Function ◽  
Xenograft Model ◽  
Cell Receptor ◽  
Target Cells ◽  
Antigen Specificity ◽  
Molecular Features ◽  
Mouse Xenograft Model

Transgenic coexpression of a class I–restricted tumor antigen–specific T cell receptor (TCR) and CD8αβ (TCR8) redirects antigen specificity of CD4+ T cells. Reinforcement of biophysical properties and early TCR signaling explain how redirected CD4+ T cells recognize target cells, but the transcriptional basis for their acquired antitumor function remains elusive. We, therefore, interrogated redirected human CD4+ and CD8+ T cells by single-cell RNA sequencing and characterized them experimentally in bulk and single-cell assays and a mouse xenograft model. TCR8 expression enhanced CD8+ T cell function and preserved less differentiated CD4+ and CD8+ T cells after tumor challenge. TCR8+CD4+ T cells were most potent by activating multiple transcriptional programs associated with enhanced antitumor function. We found sustained activation of cytotoxicity, costimulation, oxidative phosphorylation– and proliferation-related genes, and simultaneously reduced differentiation and exhaustion. Our study identifies molecular features of TCR8 expression that can guide the development of enhanced immunotherapies.

scholarly journals Differential expression profile of gluten-specific T cells identified by single-cell RNA-seq

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258029
Author(s):  
Ying Yao ◽  
Łukasz Wyrozżemski ◽  
Knut E. A. Lundin ◽  
Geir Kjetil Sandve ◽  
Shuo-Wang Qiao
Keyword(s):  
T Cells ◽  
Celiac Disease ◽  
T Cell ◽  
Single Cell ◽  
Differential Expression ◽  
T Cell Receptor ◽  
Cell Receptor ◽  
Effector Memory ◽  
Fatty Acid Transport ◽  
Rna Seq

Gluten-specific CD4+ T cells drive the pathogenesis of celiac disease and circulating gluten-specific T cells can be identified by staining with HLA-DQ:gluten tetramers. In this first single-cell RNA-seq study of tetramer-sorted T cells from untreated celiac disease patients blood, we found that gluten-specific T cells showed distinct transcriptomic profiles consistent with activated effector memory T cells that shared features with Th1 and follicular helper T cells. Compared to non-specific cells, gluten-specific T cells showed differential expression of several genes involved in T-cell receptor signaling, translational processes, apoptosis, fatty acid transport, and redox potentials. Many of the gluten-specific T cells studied shared T-cell receptor with each other, indicating that circulating gluten-specific T cells belong to a limited number of clones. Moreover, the transcriptional profiles of cells that shared the same clonal origin were transcriptionally more similar compared with between clonally unrelated gluten-specific cells.

scholarly journals Discovering tumor-reactive T-cell receptors through single-cell sequencing of tumor-infiltrating lymphocytes

2021 ◽  
Author(s):  
Elinor Gottschalk ◽  
Bulent Arman Aksoy ◽  
Pinar Aksoy ◽  
Marzena Swiderska-Syn ◽  
Caroline Mart ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
T Cell Receptors ◽  
Tumor Model ◽  
Tumor Infiltrating Lymphocytes ◽  
Cell Receptor ◽  
Target Cells ◽  
Single Cell Sequencing ◽  
Human T Cells ◽  
Infiltrating Lymphocytes

We evaluated the utility of single-cell sequencing of tumor-infiltrating lymphocytes (TIL) for tumor-reactive T-cell receptor (TCR) discovery. Using the MC38 cell line as our tumor model in mice, we show that expression of exogenous TCRs via mRNA electroporation in human T cells provides an easy and quick path to validating tumor-specific candidate TCRs. We detail the identification and validation of four novel MC38-reactive mouse TCRs with varying levels of reactivity to the target cells. Validating our process, one of the MC38 TCRs is specific against a previously reported neoantigen (ASMTNMELM in the Adpgk gene). Consideration of these methodologies may aid in the development of rapid TCR-based therapies for the treatment of cancer and human disease.

scholarly journals Targeting CAR to the Peptide-MHC Complex Reveals Distinct Signaling Compared to That of TCR in a Jurkat T Cell Model

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 867
Author(s):  
Ling Wu ◽  
Joanna Brzostek ◽  
Shvetha Sankaran ◽  
Qianru Wei ◽  
Jiawei Yap ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Cell Model ◽  
Cell Receptor ◽  
Target Cells ◽  
Tcr Signaling ◽  
Barr Virus ◽  
Car T ◽  
Epstein Barr ◽  
Lower Magnitude

Chimeric antigen receptor T cells (CAR-T) utilize T cell receptor (TCR) signaling cascades and the recognition functions of antibodies. This allows T cells, normally restricted by the major histocompatibility complex (MHC), to be redirected to target cells by their surface antigens, such as tumor associated antigens (TAAs). CAR-T technology has achieved significant successes in treatment of certain cancers, primarily liquid cancers. Nonetheless, many challenges hinder development of this therapy, such as cytokine release syndrome (CRS) and the efficacy of CAR-T treatments for solid tumors. These challenges show our inadequate understanding of this technology, particularly regarding CAR signaling, which has been less studied. To dissect CAR signaling, we designed a CAR that targets an epitope from latent membrane protein 2 A (LMP2 A) of the Epstein–Barr virus (EBV) presented on HLA*A02:01. Because of this, CAR and TCR signaling can be compared directly, allowing us to study the involvement of other signaling molecules, such as coreceptors. This comparison revealed that CAR was sufficient to bind monomeric antigens due to its high affinity but required oligomeric antigens for its activation. CAR sustained the transduced signal significantly longer, but at a lower magnitude, than did TCR. CD8 coreceptor was recruited to the CAR synapse but played a negligible role in signaling, unlike for TCR signaling. The distinct CAR signaling processes could provide explanations for clinical behavior of CAR-T therapy and suggest ways to improve the technology.

scholarly journals Mapping the immune environment in clear cell renal carcinoma by single-cell genomics

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Nicholas Borcherding ◽  
Ajaykumar Vishwakarma ◽  
Andrew P. Voigt ◽  
Andrew Bellizzi ◽  
Jacob Kaplan ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
Immune Cells ◽  
Clear Cell ◽  
Cell Receptor ◽  
Renal Tissue ◽  
High Response Rate ◽  
Cell Renal Cell Carcinoma ◽  
Tumor Mutational Burden ◽  
Macrophage Populations

AbstractClear cell renal cell carcinoma (ccRCC) is one of the most immunologically distinct tumor types due to high response rate to immunotherapies, despite low tumor mutational burden. To characterize the tumor immune microenvironment of ccRCC, we applied single-cell-RNA sequencing (SCRS) along with T-cell-receptor (TCR) sequencing to map the transcriptomic heterogeneity of 25,688 individual CD45+ lymphoid and myeloid cells in matched tumor and blood from three patients with ccRCC. We also included 11,367 immune cells from four other individuals derived from the kidney and peripheral blood to facilitate the identification and assessment of ccRCC-specific differences. There is an overall increase in CD8+ T-cell and macrophage populations in tumor-infiltrated immune cells compared to normal renal tissue. We further demonstrate the divergent cell transcriptional states for tumor-infiltrating CD8+ T cells and identify a MKI67 + proliferative subpopulation being a potential culprit for the progression of ccRCC. Using the SCRS gene expression, we found preferential prediction of clinical outcomes and pathological diseases by subcluster assignment. With further characterization and functional validation, our findings may reveal certain subpopulations of immune cells amenable to therapeutic intervention.

scholarly journals Fas ligand mediates activation-induced cell death in human T lymphocytes.

1995 ◽  
Vol 181 (1) ◽  
pp. 71-77 ◽  
Author(s):  
M R Alderson ◽  
T W Tough ◽  
T Davis-Smith ◽  
S Braddy ◽  
B Falk ◽  
...  
Keyword(s):  
T Cells ◽  
Cell Death ◽  
T Cell ◽  
Fas Ligand ◽  
Significant Proportion ◽  
Cell Receptor ◽  
Target Cells ◽  
Activated T Cells ◽  
Activation Induced Cell Death ◽  
Fas L

A significant proportion of previously activated human T cells undergo apoptosis when triggered through the CD3/T cell receptor complex, a process termed activation-induced cell death (AICD). Ligation of Fas on activated T cells by either Fas antibodies or recombinant human Fas-ligand (Fas-L) also results in cytolysis. We demonstrate that these two pathways of apoptosis are causally related. Stimulation of previously activated T cells resulted in the expression of Fas-L mRNA and lysis of Fas-positive target cells. Fas-L antagonists inhibited AICD of T cell clones and staphylococcus enterotoxin B (SEB)-specific T cell lines. The data indicate AICD in previously stimulated T cells is mediated by Fas/Fas-L interactions.

scholarly journals New interpretable machine learning method for single-cell data reveals correlates of clinical response to cancer immunotherapy

2019 ◽  
Author(s):  
Evan Greene ◽  
Greg Finak ◽  
Leonard A. D’Amico ◽  
Nina Bhardwaj ◽  
Candice D. Church ◽  
...  
Keyword(s):  
Machine Learning ◽  
Flow Cytometry ◽  
T Cell ◽  
Single Cell ◽  
Cancer Immunotherapy ◽  
Effector Memory ◽  
Machine Learning Method ◽  
Learning Method ◽  
Modeling Framework ◽  
Interpretable Machine Learning

AbstractHigh-dimensional single-cell cytometry is routinely used to characterize patient responses to cancer immunotherapy and other treatments. This has produced a wealth of datasets ripe for exploration but whose biological and technical heterogeneity make them difficult to analyze with current tools. We introduce a new interpretable machine learning method for single-cell mass and flow cytometry studies, FAUST, that robustly performs unbiased cell population discovery and annotation. FAUST processes data on a per-sample basis and returns biologically interpretable cell phenotypes that can be compared across studies, making it well-suited for the analysis and integration of complex datasets. We demonstrate how FAUST can be used for candidate biomarker discovery and validation by applying it to a flow cytometry dataset from a Merkel cell carcinoma anti-PD-1 trial and discover new CD4+ and CD8+ effector-memory T cell correlates of outcome co-expressing PD-1, HLA-DR, and CD28. We then use FAUST to validate these correlates in an independent CyTOF dataset from a published metastatic melanoma trial. Importantly, existing state-of-the-art computational discovery approaches as well as prior manual analysis did not detect these or any other statistically significant T cell sub-populations associated with anti-PD-1 treatment in either data set. We further validate our methodology by using FAUST to replicate the discovery of a previously reported myeloid correlate in a different published melanoma trial, and validate the correlate by identifying it de novo in two additional independent trials. FAUST’s phenotypic annotations can be used to perform cross-study data integration in the presence of heterogeneous data and diverse immunophenotyping staining panels, enabling hypothesis-driven inference about cell sub-population abundance through a multivariate modeling framework we call Phenotypic and Functional Differential Abundance (PFDA). We demonstrate this approach on data from myeloid and T cell panels across multiple trials. Together, these results establish FAUST as a powerful and versatile new approach for unbiased discovery in single-cell cytometry.

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