scholarly journals Single-cell transcriptomics reveals regulators underlying immune cell diversity and immune subtypes associated with prognosis in nasopharyngeal carcinoma

Cell Research ◽  
2020 ◽  
Vol 30 (11) ◽  
pp. 1024-1042 ◽  
Author(s):  
Yu-Pei Chen ◽  
Jian-Hua Yin ◽  
Wen-Fei Li ◽  
Han-Jie Li ◽  
Dong-Ping Chen ◽  
...  
Keyword(s):  
Dendritic Cells ◽  
Nasopharyngeal Carcinoma ◽  
Single Cell ◽  
Plasma Cells ◽  
Immune Cell ◽  
Cellular Heterogeneity ◽  
Normal Sample ◽  
Malignant Cells ◽  
Promising Therapeutic Approach ◽  
Cell Diversity

Abstract Nasopharyngeal carcinoma (NPC) is an aggressive malignancy with extremely skewed ethnic and geographic distributions. Increasing evidence indicates that targeting the tumor microenvironment (TME) represents a promising therapeutic approach in NPC, highlighting an urgent need to deepen the understanding of the complex NPC TME. Here, we generated single-cell transcriptome profiles for 7581 malignant cells and 40,285 immune cells from fifteen primary NPC tumors and one normal sample. We revealed malignant signatures capturing intratumoral transcriptional heterogeneity and predicting aggressiveness of malignant cells. Diverse immune cell subtypes were identified, including novel subtypes such as CLEC9A+ dendritic cells (DCs). We further revealed transcriptional regulators underlying immune cell diversity, and cell–cell interaction analyses highlighted promising immunotherapeutic targets in NPC. Moreover, we established the immune subtype-specific signatures, and demonstrated that the signatures of macrophages, plasmacytoid dendritic cells (pDCs), CLEC9A+ DCs, natural killer (NK) cells, and plasma cells were significantly associated with improved survival outcomes in NPC. Taken together, our findings represent a unique resource providing in-depth insights into the cellular heterogeneity of NPC TME and highlight potential biomarkers for anticancer treatment and risk stratification, laying a new foundation for precision therapies in NPC.

scholarly journals EMBR-27. NEOPLASTIC AND IMMUNE SINGLE CELL TRANSCRIPTOMICS DEFINE SUBGROUP-SPECIFIC INTRA-TUMORAL HETEROGENEITY OF CHILDHOOD MEDULLOBLASTOMA

2021 ◽  
Vol 23 (Supplement_1) ◽  
pp. i11-i12
Author(s):  
Andrew Donson ◽  
Kent Riemondy ◽  
Sujatha Venkataraman ◽  
Nicholas Willard ◽  
Anandani Nellan ◽  
...  
Keyword(s):  
Single Cell ◽  
Immune Cell ◽  
Myeloid Cell ◽  
Genetically Engineered ◽  
Cellular Heterogeneity ◽  
Cell Subpopulation ◽  
Neoplastic Cells ◽  
Brush Cells ◽  
Transcriptomic Data ◽  
Cell Diversity

Abstract Medulloblastoma (MB) is a heterogeneous disease in which neoplastic cells and associated immune cells contribute to disease progression. To better understand cellular heterogeneity in MB we used single-cell RNA sequencing, immunohistochemistry and deconvolution of transcriptomic data to profile neoplastic and immune populations in childhood MB samples and MB genetically engineered mouse models (GEMM). Neoplastic cells clustered primarily according to individual sample of origin which is in part due to the effect of chromosomal copy number gains and losses. Harmony alignment of single cell transcriptomic data revealed novel MB subgroup/subtype-associated subpopulations that recapitulate neurodevelopmental processes and are associated with clinical outcomes. This includes photoreceptor-like cells and glutamatergic lineage unipolar brush cells in both GP3 and GP4 subgroups of MB, and a SHH subgroup nodule-associated neuronally-differentiated cell subpopulation. We definitively chart the spectrum of MB immune cell infiltrates, which reveals unexpected degree of myeloid cell diversity. Myeloid subpopulations include subgroup/subtype-associated developmentally-related neuron-pruning as well as antigen presenting myeloid cells. Human MB cellular diversity is recapitulated in subgroup-specific MB GEMM, supporting the fidelity of these models. These findings provide a clearer understanding of both the neoplastic and immune cell heterogeneity in MB and how these impact subgroup/subtype classification and clinical outcome.

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 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.

scholarly journals Single-Cell Transcriptional Profiling of Zebrafish Hematopoiesis Offers Insight into Early Lymphocyte Development and Reveals Novel Immune Cell Populations

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 4294-4294
Author(s):  
Sara A. Rubin ◽  
Chloé S. Baron ◽  
Alexandra F. Corbin ◽  
Song Yang ◽  
Leonard I. Zon
Keyword(s):  
B Cells ◽  
B Cell ◽  
Single Cell ◽  
Immune Cell ◽  
Transcriptional Profiling ◽  
Cell Development ◽  
Cell Populations ◽  
Publicly Traded ◽  
Cell Diversity ◽  
Privately Held

Abstract The advent of single-cell RNA sequencing (scRNA-seq) has greatly expanded our appreciation for cell state diversity beyond classical developmental hierarchies and simple population subsets. In particular, rich transcriptional heterogeneity has been observed within immune cell populations leading to the identification of novel cell types. Except for a few notable exceptions, intensive work in this area has largely been confined to mammals. Much of the transcriptional profiling of blood cell development in zebrafish has failed to capture early stages of lymphocyte development as the majority of research has not included thymus datasets or captured sufficient marrow B cells to explore developmental trajectories. To gain insight into T and B cell development in the zebrafish and immune cell diversity more broadly, we performed scRNA-seq using 10x Genomics Next GEM technology on adult zebrafish kidney marrows (n = 5 biological replicates) in addition to whole juvenile thymi at 4 weeks post-fertilization (wpf) (n = 4 technical replicates) and whole adult thymi at 3-4 months post-fertilization (n = 4 biological replicates). After filtering out low quality cellular barcodes, 34,492 kidney marrow cells and 35,268 thymus cells remained for analysis. With respect to T cell development, we identified putative early thymic progenitors from their clustering with hematopoietic stem and progenitor cells and shared transcriptional signatures, including the enrichment of CD34, CSF1R, FLI1, and DNMT3B human orthologs. Multiple subsets of thymic and marrow T cells were characterized, including a subset of gamma delta T cells readily identified by their expression of T-cell receptor gamma and delta chain components and expression of a SOX13 ortholog in addition to a Th2-like population expressing IL4, IL13, and GATA3 orthologs. Among other immune cell populations, rich transcriptional diversity was present. Two distinct populations of B cells, largely mutually exclusive for ighd and ighz expression (dual detection <1%), were present across all datasets, including the 4 wpf thymi, a surprisingly early time point in zebrafish B cell ontogeny. A clustering of the adult datasets demonstrated ighz predominance in the thymus (63% of thymic B cells), whereas the majority of marrow B cells (85%) fell within the ighd cluster. Stages of B cell development were also clearly evident, with the earliest B cell progenitors expressing orthologs of human PAX5, DNTT, RAG1, and RAG2, in addition to sid1, an understudied gene proposed to be orthologous to VPREB1. The expression of dntt was notably absent from more mature subsets of rag1 and rag2+ B cell progenitors, analogous to its expression in mammals. Transcriptional signatures unique but reminiscent of mammalian dendritic cell subsets were identified: Plasmacytoid-like dendritic cells characterized by high expression of TLR7, TLR9, and IRF8 orthologs and conventional-like dendritic cells characterized by high expression of CKB, BATF3, and ZNF366 were present in both marrow and thymus datasets, suggestive of greater dendritic-like cell diversity in the zebrafish than previously appreciated. These findings illustrate the power of single-cell transcriptional profiling for illuminating immune cell development and heterogeneity in the zebrafish, demonstrating increasing parallels to the mammalian system. Disclosures Zon: Celularity: Consultancy; Branch Biosciences: Current holder of individual stocks in a privately-held company, Other: Founder; Scholar Rock: Current equity holder in publicly-traded company, Other: Founder; Amagma Therapeutics: Current holder of individual stocks in a privately-held company, Other: Founder; CAMP4 Therapeutics: Current holder of individual stocks in a privately-held company, Other: Founder; Fate Therapeutics: Current equity holder in publicly-traded company, Other: Founder; Cellarity: Consultancy.

scholarly journals Single-Cell Proteomics Defines the Cellular Heterogeneity of Localized Prostate Cancer

2021 ◽  
Author(s):  
Laura De Vargas Roditi ◽  
Andrea Jacobs ◽  
Jan H. Rueschoff ◽  
Pete Bankhead ◽  
Stephane Chevrier ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Single Cell ◽  
Immune Cell ◽  
Cell Mass ◽  
Prognostic Biomarkers ◽  
Cellular Heterogeneity ◽  
Localized Prostate Cancer ◽  
Tissue Samples ◽  
Molecular Alterations ◽  
Cell To Cell Variability

ABSTRACTLocalized prostate cancer exhibits multiple genomic alterations and heterogeneity at the proteomic level. Single-cell technologies capture important cell-to-cell variability responsible for heterogeneity in biomarker expression that may be overlooked when molecular alterations are based on bulk tissue samples. The aim of this study was to identify novel prognostic biomarkers and describe the heterogeneity of prostate cancer and the associated immune cell infiltrates by simultaneously quantifying 36 proteins using single-cell mass cytometry analysis of over 1,6 million cells from 58 men with localized prostate cancer. To perform this task, we proposed a novel computational pipeline, Franken, which showed unprecedented combination of performance, sensitivity and scalability for high dimensional clustering compared to state of the art methods. We were able to describe subpopulations of immune, stromal, and prostate cells, including unique changes occurring in tumor tissues and high grade disease providing insights into the coordinated progression of prostate cancer. Our results further indicated that men with localized disease already harbor rare subpopulations that typically occur in castration-resistant and metastatic disease, which were confirmed through imaging. Our methodology could be used to discover novel prognostic biomarkers to personalize treatment and improve outcomes.

scholarly journals Single-cell RNA-Seq reveals transcriptional heterogeneity and immune subtypes associated with disease activity in human myasthenia gravis

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Wanlin Jin ◽  
Qi Yang ◽  
Yuyao Peng ◽  
Chengkai Yan ◽  
Yi Li ◽  
...  
Keyword(s):  
T Cells ◽  
B Cells ◽  
Myasthenia Gravis ◽  
Disease Activity ◽  
Single Cell ◽  
Immune Cell ◽  
Large Cell ◽  
Cellular Heterogeneity ◽  
T Cell Subsets ◽  
The Impact

AbstractMyasthenia gravis (MG) is a rare autoimmune disease. Although the impact of immune cell disorder in MG has been extensively studied, little is known about the transcriptomes of individual cells. Here, we assessed the transcriptional profiles of 39,243 cells by single-cell sequencing and identified 13 major cell clusters, along with 39 subgroups of cells derived from patients with new-onset myasthenia gravis and healthy controls. We found that B cells, CD4+ T cells, and monocytes exhibited more heterogeneity in MG patients. CD4+ T cells were expanded in MG patients. We reclustered B cells and CD4+ T cells, and predict their essential regulators. Further analyses demonstrated that B cells in MG exhibited higher transcriptional activity towards plasma cell differentiation, CD4+ T cell subsets were unbalanced, and inflammatory pathways of monocytes were highly activated. Notably, we discovered a disease-relevant subgroup, CD180− B cells. Increased CD180− B cells in MG are indicative of a high IgG composition and were associated with disease activity and the anti-AChR antibody. Together, our data further the understanding of the cellular heterogeneity involved in the pathogenesis of MG and provide large cell-type-specific markers for subsequent research.

Single-cell profiling identifies myeloid cell subsets with distinct fates during neuroinflammation

Science ◽  
2019 ◽  
Vol 363 (6425) ◽  
pp. eaat7554 ◽  
Author(s):  
Marta Joana Costa Jordão ◽  
Roman Sankowski ◽  
Stefanie M. Brendecke ◽  
Sagar ◽  
Giuseppe Locatelli ◽  
...  
Keyword(s):  
Single Cell ◽  
Immune Cell ◽  
Myeloid Cell ◽  
Innate Immune ◽  
Functional Studies ◽  
Cell Diversity ◽  
Single Cell Profiling ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

The innate immune cell compartment is highly diverse in the healthy central nervous system (CNS), including parenchymal and non-parenchymal macrophages. However, this complexity is increased in inflammatory settings by the recruitment of circulating myeloid cells. It is unclear which disease-specific myeloid subsets exist and what their transcriptional profiles and dynamics during CNS pathology are. Combining deep single-cell transcriptome analysis, fate mapping, in vivo imaging, clonal analysis, and transgenic mouse lines, we comprehensively characterized unappreciated myeloid subsets in several CNS compartments during neuroinflammation. During inflammation, CNS macrophage subsets undergo self-renewal, and random proliferation shifts toward clonal expansion. Last, functional studies demonstrated that endogenous CNS tissue macrophages are redundant for antigen presentation. Our results highlight myeloid cell diversity and provide insights into the brain’s innate immune system.

scholarly journals Integration and Iteration: Using Advanced, High-Content Imaging and Single-Cell Gene Expression Analysis to Uncover Unique Aspects of Follicular Lymphoma Biology

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 9-10
Author(s):  
Andrea J. Radtke ◽  
Arthur L. Shaffer ◽  
Stefania Pittaluga ◽  
Alexander Bagaev ◽  
Nishant Thakur ◽  
...  
Keyword(s):  
Dendritic Cells ◽  
B Cells ◽  
Follicular Lymphoma ◽  
B Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Imaging Method ◽  
Malignant Cells ◽  
Private Company ◽  
High Content Imaging

BACKGROUND: Follicular lymphoma (FL) is an indolent malignancy of germinal center B-cell origin. FL patients experience remarkable heterogeneity in their disease trajectory, with many patients slowly progressing over several years, and a subset of patients experiencing an aggressive clinical course. Uncovering the cell-intrinsic and -extrinsic factors that govern differential progression and outcome in FL patients is thus essential. Beyond the genetic and epigenetic aberrations that contribute to FL oncogenesis, the tumor microenvironment (TME) plays an integral role in supporting the proliferation and survival of malignant cells. In a process described as "re-education", FL tumor cells may actively subvert the normal functions of non-malignant cells present in the TME, including T cells, follicular dendritic cells (FDCs), macrophages, dendritic cells, and stromal cells to support their survival and growth. METHODS: To address the importance of the TME in FL, we molecularly profiled excisional lymph node biopies from untreated FL patients using multiple platforms: bulk RNA sequencing (RNAseq), single-cell RNA sequencing (scRS), and a unique high content imaging method, Iterative Bleaching Extends MultipleXity (IBEX), which utilizes chemical bleaching to image 40+ proteins in the same tissue section by antibody staining. In combination with advanced computational tools for the quantitative analysis of cell types and distribution in tissues, we have used this approach to evaluate the TME:FL interaction within 8 FL samples, with 4 normal lymph nodes as controls. RESULTS: Both FL and TME components reconstructed from bulk RNA-seq were similar to the cellular composition revealed by scRS and IBEX analyses. Moreover, the bulk RNAseq and scRS identified the expression of genes involved in tumorigenesis and oncogenic signaling, often unique to each case. However, RNAseq-based approaches often miss important cellular and acellular components not readily extracted from dense tissues. For example, IBEX imaging can trace the pattern of blood vessels within a section, which cannot be achieved with non-imaging methods. In one case, our multi-parameter imaging studies revealed the close spatial interaction between clonal FL B cells, expressing a B-cell receptor (BCR) possessing a de novo N-linked glycosylation site introduced by somatic hypermutation, and cells expressing dendritic cell-specific intercellular adhesion molecule-3-grabbing non-integrin (DC-SIGN). This contact may activate pro-survival signaling in the malignant B cells. CONCLUSIONS: Integration of bulk RNAseq, scRS, clonotype analysis, and IBEX reveals both shared and unique aspects of different FL tumors. These data highlight the importance of integrating direct tissue analysis by high-content imaging with methods examining aspects of isolated cells. This approach may provide a more complete understanding of tumor biology, which in turn will identify patients at risk for developing aggressive disease and rationally improve treatment strategies for FL. This research was supported in part by the Intramural Research Program of the NIH, NIAID and NCI Figure Disclosures Bagaev: BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Plotnikova:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Galkin:BostonGene: Current Employment, Patents & Royalties. Postovalova:BostonGene: Current Employment, Current equity holder in private company. Svekolkin:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Isaev:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Lozinsky:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Meerson:BostonGene: Current Employment. Varlamova:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Ovcharov:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Polyakova:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Nomie:BostonGene: Current Employment, Current equity holder in private company. Kotlov:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Tsiper:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Frenkel:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Attaulakhanov:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Fowler:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties.

scholarly journals Single-cell transcriptional analysis of the immune tumour microenvironment during myeloma disease evolution

2021 ◽  
Author(s):  
Danielle C Croucher ◽  
Laura M Richards ◽  
Daniel Waller ◽  
Zhihua Li ◽  
Xian Fang Huang ◽  
...  
Keyword(s):  
Single Cell ◽  
Immune Cell ◽  
Killer Cell ◽  
Tumour Microenvironment ◽  
Transcriptional Analysis ◽  
Malignant Cells ◽  
Early Disease ◽  
Disease Evolution ◽  
Adaptive Immune ◽  
Overt Disease

Multiple myeloma is universally preceded by a premalignant disease state. However, efforts to develop preventative therapeutic strategies are hindered by an incomplete understanding of the immune mechanisms associated with progression. Using single-cell RNA-sequencing, we profiled 104,880 cells derived from the bone marrow of Vκ*MYC mice across the myeloma progression spectrum, of which 97,720 were identified as non-malignant cells of the tumour microenvironment. Analysis of the non-malignant cells comprising the immune microenvironment identified mechanisms associated with disease progression in innate and adaptive immune cell populations. This included activation of IL-17 signaling in myeloid cells from precursor mice, accompanied by upregulation of Il6 gene expression in basophils. In the T/Natural killer cell compartment, we identified Tox-expressing CD8+ T cells enriched in the tumour microenvironment of mice with overt disease, with co-expression of LAG3 and PD-1, as well as elevated T cell exhaustion signatures in mice with early disease. We subsequently showed that early intervention with combinatorial blockade of LAG3 and PD-1 using neutralizing monoclonal antibodies delayed tumor progression and improved survival of Vκ*MYC mice. Together, this work provides insight into the biology of myeloma evolution and nominates a treatment strategy for early disease.

Sign in / Sign up

Export Citation Format

Share Document