scholarly journals Melanoma Single-Cell Biology in Experimental and Clinical Settings

2021 ◽  
Vol 10 (3) ◽  
pp. 506
Author(s):  
Hans Binder ◽  
Maria Schmidt ◽  
Henry Loeffler-Wirth ◽  
Lena Suenke Mortensen ◽  
Manfred Kunz
Keyword(s):  
T Cell ◽  
Single Cell ◽  
Intracellular Signaling ◽  
Cell Biology ◽  
Immune Cell ◽  
Malignant Tumors ◽  
Checkpoint Inhibitor ◽  
Treatment Resistance ◽  
Resistance Mechanisms ◽  
Cellular Heterogeneity

Cellular heterogeneity is regarded as a major factor for treatment response and resistance in a variety of malignant tumors, including malignant melanoma. More recent developments of single-cell sequencing technology provided deeper insights into this phenomenon. Single-cell data were used to identify prognostic subtypes of melanoma tumors, with a special emphasis on immune cells and fibroblasts in the tumor microenvironment. Moreover, treatment resistance to checkpoint inhibitor therapy has been shown to be associated with a set of differentially expressed immune cell signatures unraveling new targetable intracellular signaling pathways. Characterization of T cell states under checkpoint inhibitor treatment showed that exhausted CD8+ T cell types in melanoma lesions still have a high proliferative index. Other studies identified treatment resistance mechanisms to targeted treatment against the mutated BRAF serine/threonine protein kinase including repression of the melanoma differentiation gene microphthalmia-associated transcription factor (MITF) and induction of AXL receptor tyrosine kinase. Interestingly, treatment resistance mechanisms not only included selection processes of pre-existing subclones but also transition between different states of gene expression. Taken together, single-cell technology has provided deeper insights into melanoma biology and has put forward our understanding of the role of tumor heterogeneity and transcriptional plasticity, which may impact on innovative clinical trial designs and experimental approaches.

scholarly journals Single-cell biology to decode the immune cellular composition of kidney inflammation

2021 ◽  
Author(s):  
Yu Zhao ◽  
Ulf Panzer ◽  
Stefan Bonn ◽  
Christian F. Krebs
Keyword(s):  
Single Cell ◽  
Cell Biology ◽  
Computational Analysis ◽  
Immune Cell ◽  
Therapeutic Interventions ◽  
Experimental Setup ◽  
Disease Etiology ◽  
Rna Profiling ◽  
Immune Mediated ◽  
Health And Disease

AbstractSingle-cell biology is transforming the ability of researchers to understand cellular signaling and identity across medical and biological disciplines. Especially for immune-mediated diseases, a single-cell look at immune cell subtypes, signaling, and activity might yield fundamental insights into the disease etiology, mechanisms, and potential therapeutic interventions. In this review, we highlight recent advances in the field of single-cell RNA profiling and their application to understand renal function in health and disease. With a focus on the immune system, in particular on T cells, we propose some key directions of understanding renal inflammation using single-cell approaches. We detail the benefits and shortcomings of the various technological approaches outlined and give advice on potential pitfalls and challenges in experimental setup and computational analysis. Finally, we conclude with a brief outlook into a promising future for single-cell technologies to elucidate kidney function.

scholarly journals MBRS-46. CHARTING NEOPLASTIC AND IMMUNE CELL HETEROGENEITY IN HUMAN AND GEM MODELS OF MEDULLOBLASTOMA USING scRNAseq

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii406-iii406
Author(s):  
Andrew Donson ◽  
Kent Riemondy ◽  
Sujatha Venkataraman ◽  
Ahmed Gilani ◽  
Bridget Sanford ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cell ◽  
Genetically Engineered ◽  
Cellular Heterogeneity ◽  
Cell Heterogeneity ◽  
Transcriptomic Data ◽  
Single Cell Rna Sequencing ◽  
Transcript Profiles

Abstract We explored cellular heterogeneity in medulloblastoma using single-cell RNA sequencing (scRNAseq), immunohistochemistry and deconvolution of bulk transcriptomic data. Over 45,000 cells from 31 patients from all main subgroups of medulloblastoma (2 WNT, 10 SHH, 9 GP3, 11 GP4 and 1 GP3/4) were clustered using Harmony alignment to identify conserved subpopulations. Each subgroup contained subpopulations exhibiting mitotic, undifferentiated and neuronal differentiated transcript profiles, corroborating other recent medulloblastoma scRNAseq studies. The magnitude of our present study builds on the findings of existing studies, providing further characterization of conserved neoplastic subpopulations, including identification of a photoreceptor-differentiated subpopulation that was predominantly, but not exclusively, found in GP3 medulloblastoma. Deconvolution of MAGIC transcriptomic cohort data showed that neoplastic subpopulations are associated with major and minor subgroup subdivisions, for example, photoreceptor subpopulation cells are more abundant in GP3-alpha. In both GP3 and GP4, higher proportions of undifferentiated subpopulations is associated with shorter survival and conversely, differentiated subpopulation is associated with longer survival. This scRNAseq dataset also afforded unique insights into the immune landscape of medulloblastoma, and revealed an M2-polarized myeloid subpopulation that was restricted to SHH medulloblastoma. Additionally, we performed scRNAseq on 16,000 cells from genetically engineered mouse (GEM) models of GP3 and SHH medulloblastoma. These models showed a level of fidelity with corresponding human subgroup-specific neoplastic and immune subpopulations. Collectively, our findings advance our understanding of the neoplastic and immune landscape of the main medulloblastoma subgroups in both humans and GEM models.

Single Cell Profiling Reveals Unique CXCL13 Positive T Cell Subsets in the Tumor Microenvironment of Lymphocyte Rich Classic Hodgkin Lymphoma

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 32-33
Author(s):  
Tomohiro Aoki ◽  
Lauren C. Chong ◽  
Katsuyoshi Takata ◽  
Katy Milne ◽  
Elizabeth Chavez ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
B Cells ◽  
Single Cell ◽  
Immune Cells ◽  
Research Funding ◽  
Immune Cell ◽  
Expression Patterns ◽  
The Other ◽  
Tfh Cells

Introduction: Classic Hodgkin lymphoma (CHL) features a unique crosstalk between malignant cells and different types of normal immune cells in the tumor-microenvironment (TME). On the basis of histomorphologic and immunophenotypic features of the malignant Hodgkin and Reed-Sternberg (HRS) cells and infiltrating immune cells, four histological subtypes of CHL are recognized: Nodular sclerosing (NS), Mixed cellularity, Lymphocyte-rich (LR) and Lymphocyte-depleted CHL. Recently, our group described the high abundance of various types of immunosuppressive CD4+ T cells including LAG3+ and/or CTLA4+ cells in the TME of CHL using single cell RNA sequencing (scRNAseq). However, the TME of LR-CHL has not been well characterized due to the rarity of the disease. In this study, we aimed at characterizing the immune cell profile of LR-CHL at single cell resolution. METHODS: We performed scRNAseq on cell suspensions collected from lymph nodes of 28 primary CHL patients, including 11 NS, 9 MC and 8 LR samples, with 5 reactive lymph nodes (RLN) serving as normal controls. We merged the expression data from all cells (CHL and RLN) and performed batch correction and normalization. We also performed single- and multi-color immunohistochemistry (IHC) on tissue microarray (TMA) slides from the same patients. In addition, an independent validation cohort of 31 pre-treatment LR-CHL samples assembled on a TMA, were also evaluated by IHC. Results: A total of 23 phenotypic cell clusters were identified using unsupervised clustering (PhenoGraph). We assigned each cluster to a cell type based on the expression of genes described in published transcriptome data of sorted immune cells and known canonical markers. While most immune cell phenotypes were present in all pathological subtypes, we observed a lower abundance of regulatory T cells (Tregs) in LR-CHL in comparison to the other CHL subtypes. Conversely, we found that B cells were enriched in LR-CHL when compared to the other subtypes and specifically, all four naïve B-cell clusters were quantitatively dominated by cells derived from the LR-CHL samples. T follicular helper (TFH) cells support antibody response and differentiation of B cells. Our data show the preferential enrichment of TFH in LR-CHL as compared to other CHL subtypes, but TFH cells were still less frequent compared to RLN. Of note, Chemokine C-X-C motif ligand 13 (CXCL13) was identified as the most up-regulated gene in LR compared to RLN. CXCL13, which is a ligand of C-X-C motif receptor 5 (CXCR5) is well known as a B-cell attractant via the CXCR5-CXCL13 axis. Analyzing co-expression patterns on the single cell level revealed that the majority of CXCL13+ T cells co-expressed PD-1 and ICOS, which is known as a universal TFH marker, but co-expression of CXCR5, another common TFH marker, was variable. Notably, classical TFH cells co-expressing CXCR5 and PD-1 were significantly enriched in RLN, whereas PD-1+ CXCL13+ CXCR5- CD4+ T cells were significantly enriched in LR-CHL. These co-expression patterns were validated using flow cytometry. Moreover, the expression of CXCR5 on naïve B cells in the TME was increased in LR-CHL compared to the other CHL subtypes We next sought to understand the spatial relationship between CXCL13+ T cells and malignant HRS cells. IHC of all cases revealed that CXCL13+ T cells were significantly enriched in the LR-CHL TME compared to other subtypes of CHL, and 46% of the LR-CHL cases showed CXCL13+ T cell rosettes closely surrounding HRS cells. Since PD-1+ T cell rosettes are known as a specific feature of LR-CHL, we confirmed co-expression of PD-1 in the rosetting cells by IHC in these cases. Conclusions: Our results reveal a unique TME composition in LR-CHL. LR-CHL seems to be distinctly characterized among the CHL subtypes by enrichment of CXCR5+ naïve B cells and CD4+ CXCL13+ PD-1+ T cells, indicating the importance of the CXCR5-CXCL13 axis in the pathogenesis of LR-CHL. Figure Disclosures Savage: BeiGene: Other: Steering Committee; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie: Honoraria; Roche (institutional): Research Funding; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie, Servier: Consultancy. Scott:Janssen: Consultancy, Research Funding; Celgene: Consultancy; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoString, Research Funding; NIH: Consultancy, Other: Co-inventor on a patent related to the MCL35 assay filed at the National Institutes of Health, United States of America.; Roche/Genentech: Research Funding; Abbvie: Consultancy; AstraZeneca: Consultancy. Steidl:AbbVie: Consultancy; Roche: Consultancy; Curis Inc: Consultancy; Juno Therapeutics: Consultancy; Bayer: Consultancy; Seattle Genetics: Consultancy; Bristol-Myers Squibb: Research Funding.

scholarly journals Single-Cell RNA Sequencing Reveals the Expansion of Cytotoxic CD4+ T Lymphocytes and a Landscape of Immune Cells in Primary Sjögren’s Syndrome

2021 ◽  
Vol 11 ◽  
Author(s):  
Xiaoping Hong ◽  
Shuhui Meng ◽  
Donge Tang ◽  
Tingting Wang ◽  
Liping Ding ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cell ◽  
Susceptibility Genes ◽  
Primary Sjögren’S Syndrome ◽  
Healthy Controls ◽  
Immune Cell Subsets ◽  
Single Cell Rna Sequencing

ObjectivePrimary Sjögren’s syndrome (pSS) is a systemic autoimmune disease, and its pathogenetic mechanism is far from being understood. In this study, we aimed to explore the cellular and molecular mechanisms that lead to pathogenesis of this disease.MethodsWe applied single-cell RNA sequencing (scRNA-seq) to 57,288 peripheral blood mononuclear cells (PBMCs) from five patients with pSS and five healthy controls. The immune cell subsets and susceptibility genes involved in the pathogenesis of pSS were analyzed. Flow cytometry was preformed to verify the result of scRNA-seq.ResultsWe identified two subpopulations significantly expand in pSS patients. The one highly expressing cytotoxicity genes is named as CD4+ CTLs cytotoxic T lymphocyte, and another highly expressing T cell receptor (TCR) variable gene is named as CD4+ TRAV13-2+ T cell. Flow cytometry results showed the percentages of CD4+ CTLs, which were profiled with CD4+ and GZMB+ staining; the total T cells of 10 patients with pSS were significantly higher than those of 10 healthy controls (P= 0.008). The expression level of IL-1β in macrophages, TCL1A in B cells, as well as interferon (IFN) response genes in most cell subsets was upregulated in the patients with pSS. Susceptibility genes including HLA-DRB5, CTLA4, and AQP3 were highly expressed in patients with pSS.ConclusionsOur data revealed disease-specific immune cell subsets and provided some potential new targets of pSS. Specific expansion of CD4+ CTLs may be involved in the pathogenesis of pSS, which might give valuable insights for therapeutic interventions of pSS.

IMMU-04. UNVEILING THE TUMOR-METABOLOME-IMMUNITY AXIS OF GLIOMA

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi92-vi92
Author(s):  
Mirco Friedrich ◽  
Lukas Bunse ◽  
Roman Sankowski ◽  
Wolfgang Wick ◽  
Marco Prinz ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
T Cell Activation ◽  
Cell Activation ◽  
Immune Cell ◽  
Myeloid Cell ◽  
Tumor Evolution ◽  
Large Neutral Amino Acid ◽  
Immune Microenvironment ◽  
Idh Mutations

Abstract The glioma microenvironment orchestrates tumor evolution, progression, and resistance to therapy. In high-grade gliomas, microglia and monocyte-derived macrophages constitute up to 70% of the tumor mass. However, the dynamics and phenotypes of intratumoral myeloid cells during tumor progression are poorly understood. Here we define myeloid cellular states in gliomas by longitudinal single-cell profiling and demonstrate their strict control by the tumor genotype. We report the unexpected and clinically highly relevant finding that human as well as murine gliomas with Isocitrate Dehydrogenase (IDH)1-R132H, a key oncogenic driver mutation of glioma, subdue their innate immune microenvironment by prompting a multifaceted reprogramming of myeloid and T cell metabolism. We employed integrated single-cell transcriptomic, time-of-flight mass cytometry and proteomic analyses of human healthy cortex control and glioma samples to identify myeloid cell subsets with distinct fates in IDH-mutated glioma that diverge from canonical trajectories of antigen-presenting cells as a result of a monocyte-to-macrophage differentiation block. Moving beyond single time point assessments, we now longitudinally describe differential immune cell infiltration and phenotype dynamics during glioma progression that are orchestrated by a fluctuating network of resident microglial cells and educated recruited immune cells. IDH mutations in glioma induce a tolerogenic alignment of their immune microenvironment through increased tryptophan uptake via large neutral amino acid transporter (LAT1)-CD98 and subsequent activation of the aryl hydrocarbon receptor (AHR) in educated blood-borne macrophages. In experimental tumor models, this immunosuppressive phenotype was reverted by LAT1-CD98 and AHR inhibitors. Taken together with direct effects on T cell activation, our findings not only link this oncogenic metabolic pathway to distinct immunosuppressive pathways but also provide the rationale and novel molecular targets for the development of immunotherapeutic concepts addressing the disease-defining microenvironmental effects of IDH mutations.

Recovery of Paired T Cell Receptors from Single-cell Seq-Well Libraries

2019 ◽  
Author(s):  
Ang A. Tu ◽  
Todd M. Gierahn ◽  
Brinda Monian ◽  
Duncan M. Morgan ◽  
Naveen K. Mehta ◽  
...  
Keyword(s):  
T Cells ◽  
Food Allergy ◽  
T Cell ◽  
Single Cell ◽  
T Cell Receptors ◽  
Immune Cell ◽  
Cost Effective ◽  
Antigen Specificity ◽  
Activated T Cells ◽  
Cell Receptors

Abstract High-throughput 3’ single-cell RNA-Sequencing (scRNA-Seq) allows for cost-effective, detailed characterization of thousands of individual immune cells from healthy and diseased tissues. Current techniques, however, are limited in their ability to elucidate essential immune cell features, including the variable sequences of T cell receptors (TCRs) that confer antigen specificity in T cells. Here, we present an enrichment strategy that enables simultaneous analysis of TCR variable sequences and corresponding full transcriptomes from 3’ barcoded scRNA-Seq samples. This approach is compatible with common 3’ scRNA-Seq methods, and adaptable to processed samples post hoc. We applied the technique to resolve clonotype-to-phenotype relationships among antigen-activated T cells from immunized mice and from patients with food allergy. We observed diverse but preferential cellular phenotypes manifest among subsets of expanded clonotypes, including functional Th2 states associated with food allergy. These results demonstrate the utility of our method when studying complex diseases in which clonotype-driven immune responses are critical to understanding the underlying biology.

scholarly journals A Review of T-Cell Related Therapy for Osteosarcoma

2020 ◽  
Vol 21 (14) ◽  
pp. 4877
Author(s):  
Kazushige Yoshida ◽  
Masanori Okamoto ◽  
Kaoru Aoki ◽  
Jun Takahashi ◽  
Naoto Saito
Keyword(s):  
T Cell ◽  
Cell Therapy ◽  
Immune Checkpoint Inhibitor ◽  
Malignant Tumors ◽  
Checkpoint Inhibitor ◽  
T Cell Response ◽  
The Other ◽  
T Cell Therapy ◽  
Tumors Of Bone ◽  
Better Than

Osteosarcoma is one of the most common primary malignant tumors of bone. The combination of chemotherapy and surgery makes the prognosis better than before, but therapy has not dramatically improved over the last three decades. This is partially because of the lack of a novel specialized drug for osteosarcoma, which is known as a tumor with heterogeneity. On the other hand, immunotherapy has been one of the most widely used strategies for many cancers over the last ten years. The therapies related to T-cell response, such as immune checkpoint inhibitor and chimeric antigen receptor T-cell therapy, are well-known options for some cancers. In this review, we offer the accumulated knowledge of T-cell-related immunotherapy for osteosarcoma, and discuss the future of the therapy.

scholarly journals Global immune characterization of HBV/HCV-related hepatocellular carcinoma identifies macrophage and T-cell subsets associated with disease progression

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Guohe Song ◽  
Yang Shi ◽  
Meiying Zhang ◽  
Shyamal Goswami ◽  
Saifullah Afridi ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
T Cell Subsets ◽  
M2 Macrophage ◽  
Advanced Hcc ◽  
Immune Cell Subsets

AbstractDiverse immune cells in the tumor microenvironment form a complex ecosystem, but our knowledge of their heterogeneity and dynamics within hepatocellular carcinoma (HCC) still remains limited. To assess the plasticity and phenotypes of immune cells within HBV/HCV-related HCC microenvironment at single-cell level, we performed single-cell RNA sequencing on 41,698 immune cells from seven pairs of HBV/HCV-related HCC tumors and non-tumor liver tissues. We combined bio-informatic analyses, flow cytometry, and multiplex immunohistochemistry to assess the heterogeneity of different immune cell subsets in functional characteristics, transcriptional regulation, phenotypic switching, and interactions. We identified 29 immune cell subsets of myeloid cells, NK cells, and lymphocytes with unique transcriptomic profiles in HCC. A highly complex immunological network was shaped by diverse immune cell subsets that can transit among different states and mutually interact. Notably, we identified a subset of M2 macrophage with high expression of CCL18 and transcription factor CREM that was enriched in advanced HCC patients, and potentially participated in tumor progression. We also detected a new subset of activated CD8+ T cells highly expressing XCL1 that correlated with better patient survival rates. Meanwhile, distinct transcriptomic signatures, cytotoxic phenotypes, and evolution trajectory of effector CD8+ T cells from early-stage to advanced HCC were also identified. Our study provides insight into the immune microenvironment in HBV/HCV-related HCC and highlights novel macrophage and T-cell subsets that could be further exploited in future immunotherapy.

scholarly journals The New Old CD8+ T Cells in the Immune Paradox of Pregnancy

2021 ◽  
Vol 12 ◽  
Author(s):  
Lilja Hardardottir ◽  
Maria Victoria Bazzano ◽  
Laura Glau ◽  
Luca Gattinoni ◽  
Angela Köninger ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Cd8 T Cells ◽  
Cell Biology ◽  
Immune Cell ◽  
Cd8 T Cell ◽  
Therapeutic Interventions ◽  
Effector Memory ◽  
Pregnant Uterus ◽  
T Cell Biology

CD8+ T cells are the most frequent T cell population in the immune cell compartment at the feto-maternal interface. Due to their cytotoxic potential, the presence of CD8+ T cells in the immune privileged pregnant uterus has raised considerable interest. Here, we review our current understanding of CD8+ T cell biology in the uterus of pregnant women and discuss this knowledge in relation to a recently published immune cell Atlas of human decidua. We describe how the expansion of CD8+ T cells with an effector memory phenotype often presenting markers of exhaustion is critical for a successful pregnancy, and host defense towards pathogens. Moreover, we review new evidence on the presence of long-lasting immunological memory to former pregnancies and discuss its impact on prospective pregnancy outcomes. The formation of fetal-specific memory CD8+ T cell subests in the uterus, in particular of tissue resident, and stem cell memory cells requires further investigation, but promises interesting results to come. Advancing the knowledge of CD8+ T cell biology in the pregnant uterus will be pivotal for understanding not only tissue-specific immune tolerance but also the etiology of complications during pregnancy, thus enabling preventive or therapeutic interventions in the future.

scholarly journals Single-Cell Analysis of Antigen-Specific CD8+ T-Cell Transcripts Reveals Profiles Specific to mRNA or Adjuvanted Protein Vaccines

2021 ◽  
Vol 12 ◽  
Author(s):  
Trine Sundebo Meldgaard ◽  
Fabiola Blengio ◽  
Denise Maffione ◽  
Chiara Sammicheli ◽  
Simona Tavarini ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Cd8 T Cells ◽  
Single Cell Analysis ◽  
Expression Profiles ◽  
Cd8 T Cell ◽  
Cellular Heterogeneity ◽  
Cell Analysis

CD8+ T cells play a key role in mediating protective immunity after immune challenges such as infection or vaccination. Several subsets of differentiated CD8+ T cells have been identified, however, a deeper understanding of the molecular mechanism that underlies T-cell differentiation is lacking. Conventional approaches to the study of immune responses are typically limited to the analysis of bulk groups of cells that mask the cells’ heterogeneity (RNA-seq, microarray) and to the assessment of a relatively limited number of biomarkers that can be evaluated simultaneously at the population level (flow and mass cytometry). Single-cell analysis, on the other hand, represents a possible alternative that enables a deeper characterization of the underlying cellular heterogeneity. In this study, a murine model was used to characterize immunodominant hemagglutinin (HA533-541)-specific CD8+ T-cell responses to nucleic- and protein-based influenza vaccine candidates, using single-cell sorting followed by transcriptomic analysis. Investigation of single-cell gene expression profiles enabled the discovery of unique subsets of CD8+ T cells that co-expressed cytotoxic genes after vaccination. Moreover, this method enabled the characterization of antigen specific CD8+ T cells that were previously undetected. Single-cell transcriptome profiling has the potential to allow for qualitative discrimination of cells, which could lead to novel insights on biological pathways involved in cellular responses. This approach could be further validated and allow for more informed decision making in preclinical and clinical settings.

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