The T Cell Repertoires from Nickel Sensitized Joint Implant Failure Patients

Nickel (Ni2+) is one of the most common allergens, affecting around 10–15% of the general population. As the demand for orthopedic implant surgery rises, the number of surgical revisions due to joint implant failure also increases. There is evidence that some patients develop joint failure due to an immune response to a component of the implant, and we have found that Ni2+ is an especially important cause. Hence, understanding the mechanisms by which Ni2+ allergy induces joint implant failure becomes a critical research question. The structural basis of Ni2+ activation of pathogenic T cells is still not clear. The purpose of this study was to characterize Ni2+-reactive T cell repertoires derived from the peripheral blood of joint failure patients due to Ni2+ sensitization using single-cell sequencing techniques. We stimulated the proliferation of Ni2+ -reactive T cells from two implant failure patients in vitro, and sorted them for single-cell VDJ sequencing (10× genomics). We identified 2650 productive V-J spanning pairs. Both TCR α chains and β chains were enriched. TRBV18 usage is the highest in the P7 CD4+ population (18.1%), and TRBV5-1 usage is the highest in the P7 CD8+ population (12.1%). TRBV19 and TRBV20-1 segments are present in a high percentage of both P7 and P9 sequenced T cells. Remarkably, the alpha and beta chain combination of TRAV41-TRBV18 accounts for 13.5% of the CD4+ population of P7 patient. Compared to current Ni specific T cell repertoire studies of contact dermatitis, the Vα and Vβ usages of these joint implant failure patients were different. This could be due to the different availability of self-peptides in these two different tissues. However, TRBV19 (Vβ17) was among frequently used TCR β chains, which are common in previous reports. This implies that some pathogenic T cells could be similar in Ni2+ hypersensitivities in skin and joints. The alignment of the TCR CDR3β sequences showed a conserved glutamic acid (Glu) that could potentially interact with Ni2+. The study of these Ni2+ specific TCRs may shed light on the molecular mechanism of T cell activation by low molecular weight chemical haptens.

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Single-cell transcriptomics of human T cells reveals tissue and activation signatures in health and disease

Nature Communications ◽

10.1038/s41467-019-12464-3 ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 54

Author(s):

Peter A. Szabo ◽

Hanna Mendes Levitin ◽

Michelle Miron ◽

Mark E. Snyder ◽

Takashi Senda ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Single Cell ◽

T Cell Activation ◽

Cell Activation ◽

Interferon Response ◽

Functional Responses ◽

Multiple Tumor ◽

Human T Cell ◽

Human T Cells

Abstract Human T cells coordinate adaptive immunity in diverse anatomic compartments through production of cytokines and effector molecules, but it is unclear how tissue site influences T cell persistence and function. Here, we use single cell RNA-sequencing (scRNA-seq) to define the heterogeneity of human T cells isolated from lungs, lymph nodes, bone marrow and blood, and their functional responses following stimulation. Through analysis of >50,000 resting and activated T cells, we reveal tissue T cell signatures in mucosal and lymphoid sites, and lineage-specific activation states across all sites including distinct effector states for CD8+ T cells and an interferon-response state for CD4+ T cells. Comparing scRNA-seq profiles of tumor-associated T cells to our dataset reveals predominant activated CD8+ compared to CD4+ T cell states within multiple tumor types. Our results therefore establish a high dimensional reference map of human T cell activation in health for analyzing T cells in disease.

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Blinatumomab-Induced T Cell Activation at Single Cell Transcriptome Resolution

Blood ◽

10.1182/blood-2019-124636 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 3886-3886

Author(s):

Hong Yin ◽

Yi Huo ◽

Zhen Sheng ◽

Chi-Ming Li ◽

Daniel C Ellwanger ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Single Cell ◽

T Cell Activation ◽

Cell Activation ◽

Ex Vivo ◽

Target Cells ◽

Ex Vivo Model ◽

Naive T Cells ◽

Naïve T Cells

Introduction Blinatumomab, a bi-specific T cell engager (BiTE®) combining the VH and VL domains of two antibodies against human CD19 and CD3, has been approved by U.S. Food and Drug Administration (FDA) for the treatment of patients with relapsed or refractory B precursor ALL (r/r B-ALL) for its clinical benefit demonstrated in different clinical trials. Clinical trials have also shown that there are still patients refractory to blinatumomab. It is thus important to understand the resistance mechanisms. Blinatumomab connects patients' autologous T cells and target cells to form immunologic synapse which potently triggers the activation signaling cascades in T cells and guides T cells to recognize and induce perforin/granzyme-mediated lysis of CD19+ B-ALL cells. Previous studies showed blinatumomab-mediated cytotoxicity involves different T cell subpopulations. But response of each T cell subpopulation to blinatumomab treatment remained largely unknown. Methods and Results In this study, we used 10X Genomics based single cell RNA sequencing to analyze the transcriptome of single T cells before and after blinatumomab treatment. First, ex vivo blinatumomab cytotoxicity model was established, in which healthy PBMCs were used as effector cells and cocultured with target cells (RS4;11 cells or SUP-B15 cells) at an effector-to-target cell ratio of 10:1 with 0.1 ng/mL blinatumomab. Then, PBMCs and BMMCs from 2 B-ALL patients were cultured with 10 ng/mL blinatumomab. Cells from both ex vivo model and patient samples were sequenced using 10X Genomics platform. In total, transcriptome of 17920 single T cells from the ex vivo model and 2271 single T cells from patient sample were analyzed. Based on T cell trajectory analysis, we identified four distinct populations of blinatumomab-activated T cells, which were derived from CD8+ effector memory T (TEM) cells, CD4+ central memory (TCM) cells, naïve T cells and Tregs, respectively. The differentially expressed genes in activated clusters were analyzed to reflect T cell activation mechanisms. The result showed blinatumomab induced the upregulation of aerobic glycolysis pathway (PKM, PGAM1, ENO1, GAPDH and LDHA), cytoskeleton dynamics pathway (ACTD1, ACTB, NME1 and TUBA1B), IFN-responsive pathway (GBP1, PSME2, WARS, CXCL10 and STAT1), and the upregulation of well-known immune-related genes (TNFRSF4, TNFRSF18, LAG3, CD69, IL2RA, MIR155HG, BATF, SH2D2A, LTA, NFKBIA and NDFIP2). We found blinatumomab-activated CD8+ TEM cells showed stronger cytotoxic capability than other activated populations with specific production of cytotoxic factors (PRF1, IFNG and FASLG) and cytokines (CCL2, CCL3, CCL3L1, CCL4, CCL4L2, CCL8, XCL1, XCL2, TNFSF9 and TNFSF14). Last, differential gene expression analysis revealed that co-stimulatory (TNFRSF4,TNFRSF9 and TNFRSF18) and co-inhibitory receptors (LAG3 and TIGIT) were similarly up-regulated in clusters activated from memory and naïve T cells, indicating ligand dependent T cell functional outcomes induced by blinatumomab. Conclusion In summary, we used single cell sequencing to map the blinatumomab-mediated T cell activation state transition and reveal the molecular changes in different T cell subpopulations. Memory T cells, naïve T cells and Tregs were identified functional populations after blinatumomab treatment. CD8+ TEM accounted for the majority of blinatumomab-induced cytotoxicity. Furthermore, T cell co-regulatory receptors were identified as potential targets accountable for blinatumomab sensitivity or resistance mechanisms. The study demonstrated that the collected cellular transcriptional profiles can serve as resource to explore novel strategies to enhance the efficacy of blinatumomab. Disclosures Yin: Amgen: Employment. Huo:Amgen: Employment. Sheng:Amgen: Employment. Li:Amgen: Employment. Ellwanger:Amgen: Employment. Lu:Amgen: Employment. Homann:Amgen: Employment. Wang:Amgen: Employment. Ren:Ruijin hospital: Employment.

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P853 Single cell transcriptome analysis identifies unique features in circulating CD8+ T cells that can predict immunotherapy response in melanoma patients

Journal for ImmunoTherapy of Cancer ◽

10.1136/lba2019.7 ◽

2020 ◽

Vol 8 (Suppl 1) ◽

pp. A5.1-A5

Author(s):

Chuan Li ◽

Yee Peng Phoon ◽

Keaton Karlinsey ◽

Ye Tian ◽

Samjhana Thapaliya ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

High Resolution ◽

Single Cell ◽

T Cell Activation ◽

Cd8 T Cells ◽

Peripheral Blood ◽

Cell Activation ◽

Melanoma Patients ◽

Cluster 2

BackgroundImmune checkpoint blockade (ICB) has greatly advanced the treatment of melanoma. A key component of ICB is the stimulation of CD8+ T cells in the tumor. However, ICB therapy only benefits a subset of patients and a reliable prediction method that does not require invasive biopsies is still a major challenge in the field.MethodsWe conducted a set of comprehensive single-cell transcriptomic analyses of CD8+ T cells in the peripheral blood (mPBL) and tumors (mTIL) from 8 patients with metastatic melanoma.ResultsCompared to circulating CD8+ T cells from healthy donors (hPBL), mPBLs contained subsets resembling certain features of mTIL. More importantly, three clusters (2, 6 and 15) were represented in both mPBL and mTIL. Cluster 2 was the major subset of the majority of hPBL, which phenocopied hallmark parameters of resting T cells. Cluster 6 and 15 were uniquely presented in melanoma patients. Cluster 15 had the highest PD-1 levels, with elevated markers of both activation and dysfunction/exhaustion; while Cluster 6 was enriched for ‘dormant’ cells with overall toned-down transcriptional activity except PPAR signaling, a known suppressor for T cell activation. Interestingly, unlike other mTIL clusters that would classically be defined as exhausted, Cluster 15 exhibited the highest metabolic activity (oxidative-phosphorylation and glycolysis). We further analyzed total sc-transcriptomics using cell trajectory algorithms and identified that these three clusters were the most distinct subtypes of CD8 T cells from each other, representing: resting (cluster 2), metabolically active-dysfunctional (cluster 15), and dormant phenotypes (cluster 6). Further, three unique intracellular programs in melanoma drive the transition of resting CD8+ T cells (cluster 2) to both metabolic/dysfunctional (cluster 15) and dormant states (cluster 6) that are unique to tumor bearing conditions. Based on these high-resolution analyses, we developed original algorithms to build a novel ICB response predictive model using immune-blockade co-expression gene patterns. The model was trained and tested using previously published GEO datasets containing CD8 T cells from anti-PD-1 treated patients and presented an AUC of 0.82, with 92% and 89% accuracy of ICB response in the two datasets.ConclusionsWe identified and analyzed unique populations of CD8+ T cells in circulation and tumor using high-resolution single-cell transcriptomics to define the landscape of CD8+ T cell states, revealing critical subsets with shared features in PBLs and TILs. Most importantly, we established an innovative model for ICB response prediction by using peripheral blood lymphocytes.Ethics ApprovalThis study was performed under an IRB approved protocol.

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Single-Cell RNA-Seq Reveals AML Cellular Hierarchies Relevant to Clinical Outcomes and Immunity

Blood ◽

10.1182/blood-2018-99-113502 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 542-542

Author(s):

Peter Van Galen ◽

Volker Hovestadt ◽

Marc Wadsworth II ◽

Travis Hughes ◽

Gabriel Kenneth Griffin ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Single Cell ◽

T Cell Activation ◽

Cell Activation ◽

Cell Types ◽

Healthy Controls ◽

Cell Type ◽

Healthy Donors ◽

Type Composition

Abstract Acute myeloid leukemia (AML) is a heterogeneous disease with functionally diverse cells. While primitive leukemia cells are thought to be responsible for clonal expansion, other cell types may play roles in immune evasion and paracrine signaling. To analyze the complex AML ecosystem, we developed a technology for high throughput single-cell RNA-sequencing (scRNA-seq) combined with single-cell genotyping to capture mutations in cancer driver genes. We used this technology to parse normal and malignant hematopoietic systems. We profiled 38,410 cells from bone marrow (BM) aspirates from five healthy donors and 16 AML patients that span different WHO subtypes and cytogenetic abnormalities. Within the normal donors, we identified 15 diverse hematopoietic cell types demarcated by established markers such as CD34 (HSC/Progenitors), CD14 (monocytes) and CD3 (T-cells), confirming expected differentiation trajectories. To systematically distinguish between malignant and normal cell types within tumors, we developed a machine learning classifier that integrated scRNA-seq and single-cell genotyping data. Malignant cells were classified into six types: HSC-like, progenitor-like, granulocyte macrophage progenitor (GMP)-like, promonocyte-like, monocyte-like and dendritic-like cells. Each cell type was represented by at least 1,000 cells and identified in at least ten patients. To assess the significance of these six malignant cell types, we estimated their abundance in an independent cohort of 179 AMLs that were analyzed by bulk RNA-seq (TCGA). We found that the cell type composition of a tumor closely correlates to its underlying genetic lesions. For example, RUNX1-RUNX1T1 translocations are associated with GMP-like cells and TP53 mutations with undifferentiated cells (P < 0.001). NPM1+FLT3-ITD mutated tumors are enriched for more primitive cells compared to NPM1+FLT3-TKD mutants, which may relate to the worse outcomes of patients with FLT3-ITD mutations. The correspondence between genetic lesions and tumor cell type composition can guide strategies for genotype-specific therapies that target appropriate cellular states. Further investigation of primitive cells showed that gene expression programs associated with stemness (e.g. EGR1, MSI2) are mutually exclusive with myeloid priming (e.g. MPO, ELANE) in primitive cells of healthy donors. In contrast, these programs are often co-expressed within the same individual AML cells. When we applied our single cell-derived gene signatures to the TCGA dataset, stratification of these bulk expression profiles showed that patients with HSC-like progenitors had significantly poorer outcomes than patients with GMP-like progenitors (P < 0.0001). Aberrant co-expression of stemness and myeloid programs may underlie simultaneous self-renewal and proliferation, and expression of myeloid priming factors may provide a therapeutic window to target primitive AML cells while sparing normal HSCs. Examination of T-cells in our single-cell dataset showed that AML patients have fewer CD8+ cytotoxic T-lymphocytes within the CD3+ T-cell compartment compared to healthy controls, which was validated by immunohistochemistry on BM core biopsies (69% in healthy controls vs. 54% in AML, P < 0.05). We observed increased CD25+FOXP3+ T-regulatory cells in AML patients (1.2% in healthy controls vs. 3.6% in AML, P < 0.001), indicating an immunosuppressive tumor environment. To investigate mechanisms of immunosuppression, we used a T-cell activation bioassay that reports Nuclear Factor of Activated T-cells (NFAT). We compared the immunosuppressive function of different AML cell types, and found that CD14+ monocyte-like cells most effectively inhibit T-cell activation (P < 0.0001). The malignant status of these differentiated AML cells was confirmed by genotyping, and they express multiple factors associated with immunosuppression and T-cell engagement, including TIM-3 (HAVCR2), HVEM (TNFRSF14), CD155 (PVR) and HLA-DR. These results suggest that AMLs can differentiate into monocyte-like cells that suppress T-cell activation. In conclusion, we use novel technologies to parse heterogeneous cell states within the AML ecosystem. Our findings nominate strategies for precision therapies targeting AML progenitors or immunosuppressive functions of their differentiated progeny. Disclosures Pozdnyakova: Promedior, Inc.: Consultancy. Lane:N-of-one: Consultancy; Stemline Therapeutics: Research Funding.

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Single-Cell TCR Sequencing Reveals the Dynamics of T Cell Repertoire Profiling During Pneumocystis Infection

Frontiers in Microbiology ◽

10.3389/fmicb.2021.637500 ◽

2021 ◽

Vol 12 ◽

Author(s):

Hu-Qin Yang ◽

Yi-Shan Wang ◽

Kan Zhai ◽

Zhao-Hui Tong

Keyword(s):

T Cells ◽

T Cell ◽

Single Cell ◽

T Cell Activation ◽

Th17 Cells ◽

Cell Activation ◽

Cell Receptor ◽

Cell Repertoire ◽

Highly Expressed Genes ◽

Pneumocystis Infection

T cell responses play critical roles in host adaptive immunity against Pneumocystis. However, the dynamics and diversity of the T cell immune repertoire in human immunodeficiency virus (HIV)-negative Pneumocystis pneumonia (PCP) remains unclear. In this study, single-cell RNA and single-cell T cell receptor (TCR) sequencing were applied to cells sorted from lung tissues of mice infected with Pneumocystis. Our findings demonstrated the clonal cells were mainly composed of CD4+ T cells in response to Pneumocystis, which were marked by highly expressed genes associated with T cell activation. Mice infected with Pneumocystis showed reduced TCR diversity in CD4+ T cells and increased diversity in CD8+ T cells compared with uninfected controls. Furthermore, Th17 cells were mostly clonal CD4+ T cells, which exhibited the phenotype of tissue-resident memory-like Th17 cells. In addition, Pneumocystis-infected mice showed biased usage of TCRβ VDJ genes. Taken together, we characterized the transcriptome and TCR immune repertoires profiles of expanded T cell clones, which demonstrate a skewed TCR repertoire after Pneumocystis infection.

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Cite-Seq Profiling of T Cells in Multiple Myeloma Patients Undergoing BCMA Targeting CAR-T or Bites Immunotherapy

Blood ◽

10.1182/blood-2020-137650 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 11-12

Author(s):

Noemie Leblay ◽

Ranjan Maity ◽

Elie Barakat ◽

Sylvia McCulloch ◽

Peter Duggan ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Cell Surface ◽

Single Cell ◽

T Cell Activation ◽

Cell Activation ◽

Surface Protein ◽

T Cell Subsets ◽

Cell Surface Protein ◽

Car T

Adaptive T cell therapy using chimeric antigen receptor (CAR) T cells and bispecific T cell engagers (BiTEs) have demonstrated encouraging responses in heavily pre-treated multiple myeloma (MM) patients. However, the cellular and molecular predictors of clinical response are not fully understood as well as the mediators of acquired resistance remain elusive. Local immune suppression and T cell exhaustion are important mediators of responses therefore, it is plausible to speculate that a tolerant tumor microenvironment and the expansion of specific T cell populations may dictate clinical responses. In this study, we performed at the single cell level a broad immunophenotypic and transcriptomic characterization of the blood and bone marrow (BM) T cells of sensitive and resistant MM patients treated with adaptive T cell therapies. Using cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) we measured the expansion of variable T cell subsets, T cell specific activation and inhibitor markers and their functional states in order to identify cellular mediators of resistance to these adoptive immune therapies. Serial blood samples and BM aspirates (n=12) were collected from patients treated with anti-BCMA CAR-T or BCMA-CD3 BiTEs at variable time points, prior and post initiation of therapy and at relapse. Bone marrow mononuclear fractions were isolated through ficoll density gradients coupled with magnetic sorting of CD3pos T cells. Unbiased mRNA profiling coupled with feature barcoding technology for cell surface protein (TotalSeq-B) of BM CD3pos T cells was then performed by using the chromium single cell (10x Genomics). Paired-end sequencing was performed on Illumina platform. Cell Ranger and Seurat pipeline were used for sample de-multiplexing, barcode processing, single-cell 3′ gene counting, cell surface protein expression and data analysis. CAR-T cells were identified by the expression of the chimeric CAR-T cell transcript. The parallel measurement of transcripts and cell surface protein phenotypes of CD3pos T cells using a panel of 19 immune surface markers underlined the T cell repertoire diversity and identified different T cell subsets among the CD8pos and CD4pos T cells. Notably, the cell surface protein information overlaid on the transcript-generated UMA allowed accurate identification of all main immune clusters, in particular for the CD45RA and CD45RO positive cells. Comparison of CITE-Seq features revealed that the T cells composition of the blood and BM niches differed significantly between sensitive and resistant patients. As such an enrichment of CD4pos T cells with a higher CD4:CD8 ratio was noted in responding patients. Phenotypic (CD45RA, CD45RO, CD95, CCR7, CD62L, CD28, CD27) and transcriptional signatures (TCF7, LEF1, GATA3, EOMES, TBX21, PRDM1) also identified a higher proportion of memory like T cells (Tscm, Tcm) in responding patients. In contrast, T cells of resistant patients were enriched with terminally exhausted (Tex) and senescent cells with loss of CD28, high GMZHand GMZB, CD57pos, CD69pos and CD160pos as well as upregulation of TBX21. Expression of T cell checkpoint inhibitors such as LAG3, TIGIT and PD1 was high in these Tex cells as well as in some Tem. Of note, ex vivo T cell activation studies with TIGIT blockade demonstrated T cell activation in an autologous MM and T cell co-culture system with enhanced MM cells death. An expanded cluster of regulatory T cells (Treg) FOXP3pos,CD25pos was also observed in two resistant patients. Of note, no loss of BCMA transcript or surface expression was noted in MM cells at the time of acquired resistance. Single cell transcriptome of primary MM cells and chromatin accessibility (ATAC-seq) analyses of T cells of these patients are ongoing to investigate the transcriptional programs and epigenetic factors underlying the immune escape. Combined single cell features profiling of the transcriptome and surface protein expression of T cells from MM patients receiving BCMA targeted CAR-T or BiTEs therapies revealed potential mediators of resistance. In particular, T cells composition (low CD4:CD8 ratio and reduced population of Tscm, Tcm) along with an enrichment of terminally exhausted T cells are the main features observed in resistant patients. Delineating these mechanisms will guide future T cells engineering studies to enhance the efficacy and response durability of adoptive immunotherapy in MM. Disclosures McCulloch: Amgen: Honoraria; Sanofi: Honoraria; Celgene: Honoraria; Janssen: Honoraria. Duggan:Jannsen: Consultancy; Amgen: Consultancy; Novartis: Honoraria; Celgene: Consultancy; Astra Zeneca: Consultancy. Jimenez-Zepeda:Janssen, Celgene, Amgen, Takeda: Honoraria. Bahlis:AbbVie: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; GSK: Consultancy, Honoraria; Genentech: Consultancy, Honoraria; BMS/Celgene and Janssen: Consultancy, Honoraria, Other: Travel, Accomodations, Research Funding; Karyopharm Therapeutics: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria. Neri:Celgene/BMS: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria.

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Single-cell integrative analysis of CAR-T cell activation reveals a predominantly TH1/TH2 mixed response independent of differentiation

10.1101/435693 ◽

2018 ◽

Author(s):

Iva Xhangolli ◽

Burak Dura ◽

GeeHee Lee ◽

Dongjoo Kim ◽

Yang Xiao ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Single Cell ◽

T Cell Activation ◽

Cell Activation ◽

Objective Response ◽

Effector Memory ◽

Car T Cells ◽

Mixed Response ◽

Car T

We present the first comprehensive portrait of single-cell level transcriptional and cytokine signatures of anti-CD19 4-1BB/CD28/CD3ζ CAR-T cells upon antigen-specific stimulation. Both CD4+ ‘helper’ and CD8+ cytotoxic CAR-T cells are equally effective in directly killing target tumor cells and their cytotoxic activity is associated with the elevation of a range of TH1 and TH2 signature cytokines (e.g., IFNγ, TNFα, IL5, and IL13), as confirmed by the expression of master transcription factors TBX21 (T-bet) and GATA3. However, rather than conforming to stringent TH1 or TH2 subtypes, single-cell analysis reveals that the predominant response is a highly mixed TH1/TH2 function in the same cell and the regulatory T cell (Treg) activity, although observed in a small fraction of activated cells, emerges from this hybrid TH1/TH2 population. GM-CSF is produced from the majority of cells regardless of the polarization states, further contrasting CAR-T to classic T cells. Surprisingly, the cytokine response is minimally associated with differentiation status although all major differentiation subsets such as naïve, central memory, effector memory and effector are detected. All these suggest that the activation of CAR-engineered T cells is a canonical process that leads to a highly mixed response combining both type 1 and type 2 cytokines together with GMCSF, supporting the notion that ‘polyfunctional’ CAR-T cells correlate with objective response of patients in clinical trials. This work provides new insights to the mechanism of CAR activation and implies the necessity for cellular function assays to characterize the quality of CAR-T infusion products and monitor therapeutic responses in patients.

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Engineering γδT cells limits tonic signaling associated with chimeric antigen receptors

Science Signaling ◽

10.1126/scisignal.aax1872 ◽

2019 ◽

Vol 12 (598) ◽

pp. eaax1872 ◽

Cited By ~ 5

Author(s):

Jonathan Fisher ◽

Roshan Sharma ◽

Dilu Wisidagamage Don ◽

Marta Barisa ◽

Marina Olle Hurtado ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Single Cell ◽

T Cell Activation ◽

Time Course ◽

Cell Activation ◽

Leukemic Cells ◽

Γδt Cells ◽

Car T Cell ◽

Car T

Despite the benefits of chimeric antigen receptor (CAR)–T cell therapies against lymphoid malignancies, responses in solid tumors have been more limited and off-target toxicities have been more marked. Among the possible design limitations of CAR-T cells for cancer are unwanted tonic (antigen-independent) signaling and off-target activation. Efforts to overcome these hurdles have been blunted by a lack of mechanistic understanding. Here, we showed that single-cell analysis with time course mass cytometry provided a rapid means of assessing CAR-T cell activation. We compared signal transduction in expanded T cells to that in T cells transduced to express second-generation CARs and found that cell expansion enhanced the response to stimulation. However, expansion also induced tonic signaling and reduced network plasticity, which were associated with expression of the T cell exhaustion markers PD-1 and TIM-3. Because this was most evident in pathways downstream of CD3ζ, we performed similar analyses on γδT cells that expressed chimeric costimulatory receptors (CCRs) lacking CD3ζ but containing DAP10 stimulatory domains. These CCR-γδT cells did not exhibit tonic signaling but were efficiently activated and mounted cytotoxic responses in the presence of CCR-specific stimuli or cognate leukemic cells. Single-cell signaling analysis enabled detailed characterization of CAR-T and CCR-T cell activation to better understand their functional activities. Furthermore, we demonstrated that CCR-γδT cells may offer the potential to avoid on-target, off-tumor toxicity and allo-reactivity in the context of myeloid malignancies.

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Single-Cell Transcriptomic Analysis Reveals a Tumor-Reactive T Cell Signature Associated With Clinical Outcome and Immunotherapy Response In Melanoma

Frontiers in Immunology ◽

10.3389/fimmu.2021.758288 ◽

2021 ◽

Vol 12 ◽

Author(s):

Min Yan ◽

Jing Hu ◽

Yanyan Ping ◽

Liwen Xu ◽

Gaoming Liao ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Single Cell ◽

Clinical Outcomes ◽

T Cell Activation ◽

Cd8 T Cells ◽

Cell Activation ◽

Cell Receptor ◽

Integrated Analysis ◽

Data Sets

The infiltration of tumor-reactive T cells in the tumor site is associated with better survival and immunotherapy response. However, tumor-reactive T cells were often represented by the infiltration of total CD8+ T cells, which was confounded by the presence of bystander T cells. To identify tumor-reactive T cells at the cancer lesion, we performed integration analyses of three scRNA-seq data sets of T cells in melanoma. Extensive heterogeneous functional states of T cells were revealed in the tumor microenvironment. Among these states, we identified a subset of tumor-reactive T cells which specifically expressed tumor-reactive markers and T cell activation signature, and were strongly enriched for larger T cell receptor (TCR) clones. We further identified and validated a tumor-reactive T cell signature (TRS) to evaluate the tumor reactivity of T cells in tumor patients. Patients with high TRS scores have strong immune activity and high mutation burden in the TCGA-SKCM cohort. We also demonstrated a significant association of the TRS with the clinical outcomes of melanoma patients, with higher TRS scores representing better survival, which was validated in four external independent cohorts. Furthermore, the TRS scores exhibited greater performance on prognosis prediction than infiltration levels of CD8+ T cells and previously published prognosis-related signatures. Finally, we observed the capability of TRS to predict immunotherapy response in melanoma. Together, based on integrated analysis of single-cell RNA-sequencing, we developed and validated a tumor-reactive-related signature that demonstrated significant association with clinical outcomes and response to immunotherapy.

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889 DuoBody®-CD3x5T4 induces efficient T-cell activation and killing of patient-derived head and neck cancer cells in vitro and ex vivo

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2021-sitc2021.889 ◽

2021 ◽

Vol 9 (Suppl 3) ◽

pp. A932-A932

Author(s):

Rieneke van de Ven ◽

Sonja Ganzevles ◽

Myrthe Veth ◽

Patrick Franken ◽

Esther Breij ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Single Cell ◽

Cell Lines ◽

T Cell Activation ◽

Healthy Donor ◽

Cell Activation ◽

Cell Suspensions ◽

Hnscc Cell

Background5T4, also known as trophoblast glycoprotein, is expressed in many solid cancers, including non-small cell lung cancer, triple-negative breast cancer, bladder, esophageal, prostate, uterine and head and neck squamous cell carcinomas (HNSCCs). DuoBody-CD3x5T4 is a CD3 bispecific antibody that efficiently induces T-cell mediated cytotoxicity of 5T4-positive tumor cells. Currently, DuoBody-CD3x5T4 is being evaluated in a first-in-human clinical trial (NCT04424641) in solid cancers in partnership between Genmab and AbbVie. In this study we explored the preclinical mechanism-of-action of DuoBody-CD3x5T4 in vitro and ex vivo, using HNSCC as a case study.Methods5T4 protein expression in HNSCC tumor specimens was determined by immunohistochemistry (IHC) and flow cytometry. T-cell mediated cytotoxicity and T-cell activation induced by DuoBody-CD3x5T4 were studied in co-cultures of healthy donor T cells and patient-derived HNSCC cell lines in vitro. Lastly, the capacity of DuoBody-CD3x5T4 to activate tumor-infiltrating lymphocytes (TILs) was analyzed in freshly dissociated 5T4-expressing HNSCC tumor specimens ex vivo.ResultsIHC analysis confirmed expression of 5T4 in HNSCC oral biopsies, including specimens from primary tumors, recurrent tumors and lymph node metastases. Patient-derived HNSCC cell lines (n=22) demonstrated 5T4 expression on the plasma membrane, ranging from 10,000 - 61,000 5T4 molecules per cell. Moreover, 5T4 expression was evident on EGFR+CD45- tumor cells in single-cell suspensions from freshly dissociated HNSCC biopsies, independent of the tumor site. DuoBody-CD3x5T4 demonstrated potent, target-dependent cytotoxicity in vitro in co-cultures of healthy donor T cells and patient-derived HNSCC cell lines across the range of 5T4 expression levels tested. Tumor cell kill was associated with CD4+ and CD8+ T-cell activation and granzyme B secretion. Importantly, DuoBody-CD3x5T4 induced potent activation of autologous TILs in single-cell suspensions from freshly dissociated HNSCC biopsies. Notably, T-cell activation (as assessed by expression of CD69, CD25 and CD137) was also observed in PD-1+ TILs, suggesting that DuoBody-CD3x5T4 was able to engage antigen-experienced T cells in the tumor microenvironment. In this autologous assay, preliminary data showed that 5T4-expressing HNSCC tumor cells were specifically eradicated.Conclusions5T4 was broadly expressed in HNSCC cell lines, tumor biopsies and primary tumor cell suspensions. DuoBody-CD3x5T4 activated healthy donor T cells in co-cultures with patient-derived HNSCC cell lines, resulting in secretion of granzyme B and efficient tumor cell kill. In single-cell suspensions from freshly dissociated 5T4+ HNSCC biopsies, DuoBody-CD3x5T4 activated autologous CD4+ and CD8+ TILs, including PD-1+ TILs. This dataset adds to the preclinical evidence for targeting 5T4-expressing solid cancers with DuoBody-CD3x5T4.Ethics ApprovalWritten informed consent was obtained from all patients from whom fresh tumor biopsies were used for research, as part of the HNcol protocol at the Department of Otolaryngology|Head and Neck Surgery of Amsterdam UMC (VUmc) as approved by the Institutional Review Board (2008.071|A2016.035). Archival FFPE specimens were used for scientific research in agreement with the medical ethical guidelines described in the Code of Conduct for Proper Secondary Use of Human Tissue of the Dutch Federation of Biomedical Scientific Societies (Federa) in accordance with the Declaration of Helsinki and after Biobank approval (BUP2019-74).

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