scholarly journals Comprehensive single-cell sequencing reveals the stromal dynamics and tumor-specific characteristics in the microenvironment of nasopharyngeal carcinoma

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lanqi Gong ◽  
Dora Lai-Wan Kwong ◽  
Wei Dai ◽  
Pingan Wu ◽  
Shanshan Li ◽  
...  
Keyword(s):  
Nasopharyngeal Carcinoma ◽  
Single Cell ◽  
Rna Sequencing ◽  
Progression Free Survival ◽  
Developmental Trajectory ◽  
Free Survival ◽  
Genetic Profiling ◽  
Single Cell Rna Sequencing ◽  
Infiltrating Cells ◽  
Patient Prognosis

AbstractThe tumor microenvironment (TME) of nasopharyngeal carcinoma (NPC) harbors a heterogeneous and dynamic stromal population. A comprehensive understanding of this tumor-specific ecosystem is necessary to enhance cancer diagnosis, therapeutics, and prognosis. However, recent advances based on bulk RNA sequencing remain insufficient to construct an in-depth landscape of infiltrating stromal cells in NPC. Here we apply single-cell RNA sequencing to 66,627 cells from 14 patients, integrated with clonotype identification on T and B cells. We identify and characterize five major stromal clusters and 36 distinct subpopulations based on genetic profiling. By comparing with the infiltrating cells in the non-malignant microenvironment, we report highly representative features in the TME, including phenotypic abundance, genetic alternations, immune dynamics, clonal expansion, developmental trajectory, and molecular interactions that profoundly influence patient prognosis and therapeutic outcome. The key findings are further independently validated in two single-cell RNA sequencing cohorts and two bulk RNA-sequencing cohorts. In the present study, we reveal the correlation between NPC-specific characteristics and progression-free survival. Together, these data facilitate the understanding of the stromal landscape and immune dynamics in NPC patients and provides deeper insights into the development of prognostic biomarkers and therapeutic targets in the TME.

Developmental trajectory of oligodendrocyte progenitor cells in the human brain revealed by single cell RNA sequencing

Glia ◽  
2020 ◽  
Vol 68 (6) ◽  
pp. 1291-1303 ◽  
Author(s):  
Kelly Perlman ◽  
Charles P. Couturier ◽  
Moein Yaqubi ◽  
Arnaud Tanti ◽  
Qiao‐Ling Cui ◽  
...  
Keyword(s):  
Human Brain ◽  
Single Cell ◽  
Progenitor Cells ◽  
Rna Sequencing ◽  
Developmental Trajectory ◽  
Oligodendrocyte Progenitor Cells ◽  
Oligodendrocyte Progenitor ◽  
Single Cell Rna Sequencing

Landscape of Cell Heterogeneity and Evolutionary Trajectory in Ulcerative Colitis-associated Colon Cancer Revealed by Single-cell Rna Sequencing

2020 ◽  
Author(s):  
Quan Wang ◽  
Zhu Wang ◽  
Zhen Zhang ◽  
Wei Zhang ◽  
Mengmeng Zhang ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Colon Cancer ◽  
Single Cell ◽  
Rna Sequencing ◽  
Developmental Trajectory ◽  
The Cancer Genome Atlas ◽  
Cell Heterogeneity ◽  
Evolutionary Trajectory ◽  
Cell Clusters ◽  
Single Cell Rna Sequencing

Abstract Background: Patients with colitis-associated cancer (CAC), a particular kind of colorectal cancer that develops from inflammatory bowel diseases (IBDs), have an earlier morbidity and a poorer prognosis. However, in CAC, single cell transcriptome analysis of the microenvironment composition and characteristics has yet to be performed. To understand the intra-tumor heterogeneity in CAC and to reveal a potential evolutionary trajectory from ulcerative colitis (UC) to CAC at the single cell level. Methods: Fresh samples of tumor- and adjacent tissue, from a CAC patient with pT3N1M0, were examined by single cell RNA sequencing (scRNA-seq). Data from The Cancer Genome Atlas (TCGA) and The Human Protein Atlas were used to confirm the different expression levels in normal and tumor tissues and to determine their relationships with prognosis. Results: Ultimately, 4,777 single-cell transcriptomes (1220 genes per cell) were studied, which composed of 2,250 (47%) and 2,527(53%) originated from tumor- and non-malignant tissue, respectively. And we defined the composition of cancer-associated stromal cells and identified six cell clusters included myeloid, T and B cells, fibroblasts, endothelial and epithelial cells. Likewise, the notable pathways and transcription factors (TFs) involved of these cell clusters were analyzed and described. Moreover, we graphed the precise cellular composition and developmental trajectory from UC to UC-associated colon cancer, and predicted that CD74, CLCA1 and DPEP1 had a potential role in the disease progression. Conclusions: scRNA-seq technology could reveal intratumor cell heterogeneity in ulcerative colitis-associated colon cancer, and might provide a promising direction to seek the novel potential therapeutic targets in the evolution from IBD to CAC.

scholarly journals Single-cell RNA-sequencing identifies the developmental trajectory of C-Myc-dependent NK1.1− T-bet+ intraepithelial lymphocyte precursors

2019 ◽  
Vol 13 (2) ◽  
pp. 257-270 ◽  
Author(s):  
Jonas F. Hummel ◽  
Patrice Zeis ◽  
Karolina Ebert ◽  
Jonas Fixemer ◽  
Philip Konrad ◽  
...  
Keyword(s):  
T Cells ◽  
Single Cell ◽  
Rna Sequencing ◽  
Intraepithelial Lymphocytes ◽  
Developmental Trajectory ◽  
High Avidity ◽  
Clonal Deletion ◽  
Adaptive Immune Cells ◽  
Single Cell Rna Sequencing ◽  
Factor C

Abstract Natural intraepithelial lymphocytes (IELs) are thymus-derived adaptive immune cells, which are important contributors to intestinal immune homeostasis. Similar to other innate-like T cells, they are induced in the thymus through high-avidity interaction that would otherwise lead to clonal deletion in conventional CD4 and CD8 T cells. By applying single-cell RNA-sequencing (scRNA-seq) on a heterogeneous population of thymic CD4−CD8αβ−TCRαβ+NK1.1− IEL precursors (NK1.1− IELPs), we define a developmental trajectory that can be tracked based on the sequential expression of CD122 and T-bet. Moreover, we identify the Id proteins Id2 and Id3 as a novel regulator of IELP development and show that all NK1.1− IELPs progress through a PD-1 stage that precedes the induction of T-bet. The transition from PD-1 to T-bet is regulated by the transcription factor C-Myc, which has far reaching effects on cell cycle, energy metabolism, and the translational machinery during IELP development. In summary, our results provide a high-resolution molecular framework for thymic IEL development of NK1.1− IELPs and deepen our understanding of this still elusive cell type.

scholarly journals Single‐Cell Transcriptomics of Engineered Cardiac Tissues From Patient‐Specific Induced Pluripotent Stem Cell–Derived Cardiomyocytes Reveals Abnormal Developmental Trajectory and Intrinsic Contractile Defects in Hypoplastic Right Heart Syndrome

2020 ◽  
Vol 9 (20) ◽  
Author(s):  
Yin‐Yu Lam ◽  
Wendy Keung ◽  
Chun‐Ho Chan ◽  
Lin Geng ◽  
Nicodemus Wong ◽  
...  
Keyword(s):  
Stem Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Pluripotent Stem Cell ◽  
Cardiac Tissue ◽  
Induced Pluripotent Stem Cell ◽  
Developmental Trajectory ◽  
Single Cell Rna Sequencing ◽  
Human Cardiac Tissue ◽  
Induced Pluripotent

Background To understand the intrinsic cardiac developmental and functional abnormalities in pulmonary atresia with intact ventricular septum (PAIVS) free from effects secondary to anatomic defects, we performed and compared single‐cell transcriptomic and phenotypic analyses of patient‐ and healthy subject–derived human‐induced pluripotent stem cell–derived cardiomyocytes (hiPSC‐CMs) and engineered tissue models. Methods and Results We derived hiPSC lines from 3 patients with PAIVS and 3 healthy subjects and differentiated them into hiPSC‐CMs, which were then bioengineered into the human cardiac anisotropic sheet and human cardiac tissue strip custom‐designed for electrophysiological and contractile assessments, respectively. Single‐cell RNA sequencing (scRNA‐seq) of hiPSC‐CMs, human cardiac anisotropic sheet, and human cardiac tissue strip was performed to examine the transcriptomic basis for any phenotypic abnormalities using pseudotime and differential expression analyses. Through pseudotime analysis, we demonstrated that bioengineered tissue constructs provide pro‐maturational cues to hiPSC‐CMs, although the maturation and development were attenuated in PAIVS hiPSC‐CMs. Furthermore, reduced contractility and prolonged contractile kinetics were observed with PAIVS human cardiac tissue strips. Consistently, single‐cell RNA sequencing of PAIVS human cardiac tissue strips and hiPSC‐CMs exhibited diminished expression of cardiac contractile apparatus genes. By contrast, electrophysiological aberrancies were absent in PAIVS human cardiac anisotropic sheets. Conclusions Our findings were the first to reveal intrinsic abnormalities of cardiomyocyte development and function in PAIVS free from secondary effects. We conclude that hiPSC‐derived engineered tissues offer a unique method for studying primary cardiac abnormalities and uncovering pathogenic mechanisms that underlie sporadic congenital heart diseases.

scholarly journals Single Cell Transcriptomics Maps the Embryonic Emergence of HSC and Identifies Intercellular Interactions Regulating HSC Genesis

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 5086-5086
Author(s):  
Brandon Hadland ◽  
Barbara Varnum-Finney ◽  
Stacey Dozono ◽  
Dana Jackson ◽  
Shahin Rafii ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Embryonic Development ◽  
Single Cell ◽  
Rna Sequencing ◽  
Developmental Trajectory ◽  
Self Renewal ◽  
Intercellular Interactions ◽  
Transcriptional Profiles ◽  
Single Cell Rna Sequencing

Abstract Hematopoietic stem cells (HSC) are generated during a transient window of embryonic development from endothelial-like hemogenic precursors within specific arterial vessels such as the aorta of the AGM (aorta-gonad-mesonephros region). During HSC emergence, hemogenic precursors must acquire and maintain HSC-defining properties such as the ability to self-renew, home, and provide multilineage hematopoiesis, properties which distinguish rare HSC from a multitude of other hematopoietic progenitors arising simultaneously in the developing embryo. However, the precise niche-derived signals necessary and sufficient to support the acquisition and maintenance of these properties remains poorly defined. Toward identification of these signals, we generated a platform consisting of endothelial cells from the embryonic AGM (AGM-EC) which supports the specification and self-renewal of engrafting HSC from clonal embryo-derived hemogenic precursors in vitro. Using this platform to assay functional HSC potential at the single cell level, we determined a phenotype (VE-Caderin+CD61+EPCRhigh) that encompasses the population of hemogenic precursors during their asynchronous transition to HSC between E9.5 and E11.5 in murine embryonic development. To elucidate the transcriptional changes associated with the emergence of HSC from hemogenic precursors, we analyzed the global transcriptional profiles of FACS-purified VE-Caderin+CD61+EPCRhigh cells at various stages of embryonic development by single cell RNA-sequencing and reconstructed their developmental trajectory in "pseudotime" based on incremental changes in their transcriptional profiles. Complementary analysis of AGM-EC by bulk and single cell RNA-sequencing revealed a unique transcriptional profile of niche endothelial cells supporting HSC development enriched for immune/inflammatory signals. Combining the transcriptional profiles of emerging HSC with niche AGM-EC, we have identified candidate ligand-receptor pairs regulating intercellular interactions during HSC specification and self-renewal and have begun to validate the functional importance of these interactions in supporting HSC generation from hemogenic precursors in vitro. We expect these studies will enhance our understanding of the unique signal pathways necessary for the development of functional HSC, a critical step toward engineering HSC in vitro for clinical applications in disease modeling, drug discovery, and gene modification to identify novel therapies for hematologic and immunologic disorders. Disclosures Rafii: Angiocrine Bioscience: Equity Ownership.

scholarly journals Model-based Trajectory Inference for Single-Cell RNA Sequencing Using Deep Learning with a Mixture Prior

2020 ◽  
Author(s):  
Jin-Hong Du ◽  
Ming Gao ◽  
Jingshu Wang
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Developmental Trajectories ◽  
Probabilistic Method ◽  
Synthetic Data ◽  
Developmental Trajectory ◽  
Projection Neurons ◽  
Single Cell Rna Sequencing ◽  
Mixture Prior ◽  
Inference Methods

AbstractTrajectory inference methods analyze thousands of cells from single-cell sequencing technologies and computationally infer their developmental trajectories. Though many tools have been developed for trajectory inference, most of them lack a coherent statistical model and reliable uncertainty quantification. In this paper, we present VITAE, a probabilistic method combining a latent hierarchical mixture model with variational autoencoders to infer trajectories from posterior approximations. VITAE is computationally scalable and can adjust for confounding covariates to integrate multiple datasets. We show that VITAE outperforms other state-of-the-art trajectory inference methods on both real and synthetic data under various trajectory topologies. We also apply VITAE to jointly analyze two single-cell RNA sequencing datasets on mouse neocortex. Our results suggest that VITAE can successfully uncover a shared developmental trajectory of the projection neurons and reliably order cells from both datasets along the inferred trajectory.

scholarly journals Transcriptomic entropy benchmarks stem cell-derived cardiomyocyte maturation against endogenous tissue at single cell level

2020 ◽  
Author(s):  
Suraj Kannan ◽  
Michael Farid ◽  
Brian L. Lin ◽  
Matthew Miyamoto ◽  
Chulan Kwon
Keyword(s):  
Stem Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Pluripotent Stem Cell ◽  
Developmental Trajectory ◽  
Single Cell Level ◽  
Batch Effects ◽  
Cell Level ◽  
Single Cell Rna Sequencing

The immaturity of pluripotent stem cell (PSC)-derived tissues has emerged as a universal problem for their biomedical applications. While efforts have been made to generate adult-like cells from PSCs, direct benchmarking of PSC-derived tissues against in vivo development has not been established. Thus, maturation status is often assessed on an ad-hoc basis. Single cell RNA-sequencing (scRNA-seq) offers a promising solution, though cross-study comparison is limited by dataset-specific batch effects. Here, we developed a novel approach to quantify PSC-derived cardiomyocyte (CM) maturation through transcriptomic entropy. Transcriptomic entropy is robust across datasets regardless of differences in isolation protocols, library preparation, and other potential batch effects. With this new model, we analyzed over 45 scRNA-seq datasets and over 52,000 CMs, and established a cross-study, cross-species CM maturation reference. This reference enabled us to directly compare PSC-CMs with the in vivo developmental trajectory and thereby to quantify PSC-CM maturation status. We further found that our entropy-based approach can be used for other cell types, including pancreatic beta cells and hepatocytes. Our study presents a biologically relevant and interpretable metric for quantifying PSC-derived tissue maturation, and is extensible to numerous tissue engineering contexts.Significance StatementThere is significant interest in generating mature cardiomyocytes from pluripotent stem cells. However, there are currently few effective metrics to quantify the maturation status of a single cardiomyocyte. We developed a new metric for measuring cardiomyocyte maturation using single cell RNA-sequencing data. This metric, called entropy score, uses the gene distribution to estimate maturation at the single cell level. Entropy score enables comparing pluripotent stem cell-derived cardiomyocytes directly against endogenously-isolated cardiomyocytes. Thus, entropy score can better assist in development of approaches to improve the maturation of pluripotent stem cell-derived cardiomyocytes.

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