Lateral dimension and amino-functionalization on the balance to assess the single-cell toxicity of graphene on fifteen immune cell types

Abstract Background Knowledge of immune cell phenotypes, function, and developmental trajectory in acute myeloid leukemia (AML) microenvironment is essential for understanding mechanisms of evading immune surveillance and immunotherapy response of targeting special microenvironment components. Methods Using a single-cell RNA sequencing (scRNA-seq) dataset, we analyzed the immune cell phenotypes, function, and developmental trajectory of bone marrow (BM) samples from 16 AML patients and 4 healthy donors, but not AML blasts. Results We observed a significant difference between normal and AML BM immune cells. Here, we defined the diversity of dendritic cells (DC) and macrophages in different AML patients. We also identified several unique immune cell types including T helper cell 17 (TH17)-like intermediate population, cytotoxic CD4+ T subset, T cell: erythrocyte complexes, activated regulatory T cells (Treg), and CD8+ memory-like subset. Emerging AML cells remodels the BM immune microenvironment powerfully, leads to immunosuppression by accumulating exhausted/dysfunctional immune effectors, expending immune-activated types, and promoting the formation of suppressive subsets. Conclusion Our results provide a comprehensive AML BM immune cell census, which can help to select pinpoint targeted drug and predict efficacy of immunotherapy.

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484 Bioturing browser: interactively explore public single cell sequencing data

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2020-sitc2020.0484 ◽

2020 ◽

Vol 8 (Suppl 3) ◽

pp. A520-A520

Author(s):

Son Pham ◽

Tri Le ◽

Tan Phan ◽

Minh Pham ◽

Huy Nguyen ◽

...

Keyword(s):

Single Cell ◽

Immune Cell ◽

Expression Profiles ◽

Meta Analysis ◽

Cell Types ◽

Sequencing Data ◽

Single Cell Sequencing ◽

Data Formats ◽

Cancer Types ◽

Cell Data

BackgroundSingle-cell sequencing technology has opened an unprecedented ability to interrogate cancer. It reveals significant insights into the intratumoral heterogeneity, metastasis, therapeutic resistance, which facilitates target discovery and validation in cancer treatment. With rapid advancements in throughput and strategies, a particular immuno-oncology study can produce multi-omics profiles for several thousands of individual cells. This overflow of single-cell data poses formidable challenges, including standardizing data formats across studies, performing reanalysis for individual datasets and meta-analysis.MethodsN/AResultsWe present BioTuring Browser, an interactive platform for accessing and reanalyzing published single-cell omics data. The platform is currently hosting a curated database of more than 10 million cells from 247 projects, covering more than 120 immune cell types and subtypes, and 15 different cancer types. All data are processed and annotated with standardized labels of cell types, diseases, therapeutic responses, etc. to be instantly accessed and explored in a uniform visualization and analytics interface. Based on this massive curated database, BioTuring Browser supports searching similar expression profiles, querying a target across datasets and automatic cell type annotation. The platform supports single-cell RNA-seq, CITE-seq and TCR-seq data. BioTuring Browser is now available for download at www.bioturing.com.ConclusionsN/A

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Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling

BMC Genomics ◽

10.1186/s12864-020-07358-4 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Tracy M. Yamawaki ◽

Daniel R. Lu ◽

Daniel C. Ellwanger ◽

Dev Bhatt ◽

Paolo Manzanillo ◽

...

Keyword(s):

Single Cell ◽

High Throughput ◽

Immune Cell ◽

Cell Types ◽

Data Interpretation ◽

Detection Sensitivity ◽

Rna Seq ◽

Cell Recovery

Abstract Background Elucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation. Results Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluated methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5′ v1 and 3′ v3 methods. We demonstrate that these methods have fewer dropout events, which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures. Conclusion Overall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.

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Peer Review #2 of "Single cell transcriptional analysis reveals novel innate immune cell types (v0.2)"

10.7287/peerj.452v0.2/reviews/2 ◽

2014 ◽

Keyword(s):

Single Cell ◽

Peer Review ◽

Immune Cell ◽

Cell Types ◽

Innate Immune ◽

Innate Immune Cell ◽

Transcriptional Analysis

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Single Cell Atlas of Human Dura Reveals Cellular Meningeal Landscape and Insights into Meningioma Immune Response

10.1101/2021.08.03.454066 ◽

2021 ◽

Author(s):

Anthony Z Wang ◽

Jay Bowman-Kirigin ◽

Rupen Desai ◽

Pujan Patel ◽

Bhuvic Patel ◽

...

Keyword(s):

Single Cell ◽

Immune Cell ◽

Immune Surveillance ◽

Copy Number Variant ◽

Cell Types ◽

Cell Receptor ◽

Immune Microenvironment ◽

Clinical Models ◽

Insight Into

Recent investigation of the meninges, specifically the dura layer, has highlighted its importance in CNS immune surveillance beyond a purely structural role. However, most of our understanding of the meninges stems from the use of pre-clinical models rather than human samples. In this study, we use single cell RNA-sequencing to perform the first characterization of both non-tumor-associated human dura and meningioma samples. First, we reveal a complex immune microenvironment in human dura that is transcriptionally distinct from that of meningioma. In addition, through T cell receptor sequencing, we show significant TCR overlap between matched dura and meningioma samples. We also identify a functionally heterogeneous population of non-immune cell types and report copy-number variant heterogeneity within our meningioma samples. Our comprehensive investigation of both the immune and non-immune cell landscapes of human dura and meningioma at a single cell resolution provide new insight into previously uncharacterized roles of human dura.

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Enabling out-of-clinic human immunity studies via single-cell profiling of capillary blood

10.1101/2020.07.25.210468 ◽

2020 ◽

Author(s):

Tatyana Dobreva ◽

David Brown ◽

Jong Hwee Park ◽

Matt Thomson

Keyword(s):

Gene Expression ◽

Immune System ◽

Environmental Factors ◽

Single Cell ◽

Immune Cell ◽

Cell Types ◽

Capillary Blood ◽

Specific Gene ◽

Human Immune ◽

Over Time

AbstractAn individual’s immune system is driven by both genetic and environmental factors that vary over time. To better understand the temporal and inter-individual variability of gene expression within distinct immune cell types, we developed a platform that leverages multiplexed single-cell sequencing and out-of-clinic capillary blood extraction to enable simplified, cost-effective profiling of the human immune system across people and time at single-cell resolution. Using the platform, we detect widespread differences in cell type-specific gene expression between subjects that are stable over multiple days.SummaryIncreasing evidence implicates the immune system in an overwhelming number of diseases, and distinct cell types play specific roles in their pathogenesis.1,2 Studies of peripheral blood have uncovered a wealth of associations between gene expression, environmental factors, disease risk, and therapeutic efficacy.4 For example, in rheumatoid arthritis, multiple mechanistic paths have been found that lead to disease, and gene expression of specific immune cell types can be used as a predictor of therapeutic non-response.12 Furthermore, vaccines, drugs, and chemotherapy have been shown to yield different efficacy based on time of administration, and such findings have been linked to the time-dependence of gene expression in downstream pathways.21,22,23 However, human immune studies of gene expression between individuals and across time remain limited to a few cell types or time points per subject, constraining our understanding of how networks of heterogeneous cells making up each individual’s immune system respond to adverse events and change over time.

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Molecular mechanisms governing circulating immune cell heterogeneity across different species revealed by single cell sequencing

10.1101/2021.12.17.472326 ◽

2021 ◽

Author(s):

Zhibin Li ◽

chengcheng Sun ◽

Fei Wang ◽

Xiran Wang ◽

Jiacheng Zhu ◽

...

Keyword(s):

Single Cell ◽

Immune Cells ◽

Evolutionary Biology ◽

Regulatory Networks ◽

Molecular Mechanisms ◽

Mononuclear Cells ◽

Immune Cell ◽

Cell Types ◽

Genetic Regulatory Networks ◽

Peripheral Blood Mononuclear

Background: Immune cells play important roles in mediating immune response and host defense against invading pathogens. However, insights into the molecular mechanisms governing circulating immune cell diversity among multiple species are limited. Methods: In this study, we compared the single-cell transcriptomes of 77 957 immune cells from 12 species using single-cell RNA-sequencing (scRNA-seq). Distinct molecular profiles were characterized for different immune cell types, including T cells, B cells, natural killer cells, monocytes, and dendritic cells. Results: The results revealed the heterogeneity and compositions of circulating immune cells among 12 different species. Additionally, we explored the conserved and divergent cellular cross-talks and genetic regulatory networks among vertebrate immune cells. Notably, the ligand and receptor pair VIM-CD44 was highly conserved among the immune cells. Conclusions: This study is the first to provide a comprehensive analysis of the cross-species single-cell atlas for peripheral blood mononuclear cells (PBMCs). This research should advance our understanding of the cellular taxonomy and fundamental functions of PBMCs, with important implications in evolutionary biology, developmental biology, and immune system disorders

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Single cell analysis reveals immune cell–adipocyte crosstalk regulating the transcription of thermogenic adipocytes

eLife ◽

10.7554/elife.49501 ◽

2019 ◽

Vol 8 ◽

Cited By ~ 17

Author(s):

Prashant Rajbhandari ◽

Douglas Arneson ◽

Sydney K Hart ◽

In Sook Ahn ◽

Graciel Diamante ◽

...

Keyword(s):

Single Cell ◽

Immune Cells ◽

Immune Cell ◽

Single Cell Analysis ◽

Metabolic Response ◽

Cell Types ◽

Specific Cell ◽

Beneficial Effects ◽

Thermogenic Adipocytes ◽

And Function

Immune cells are vital constituents of the adipose microenvironment that influence both local and systemic lipid metabolism. Mice lacking IL10 have enhanced thermogenesis, but the roles of specific cell types in the metabolic response to IL10 remain to be defined. We demonstrate here that selective loss of IL10 receptor α in adipocytes recapitulates the beneficial effects of global IL10 deletion, and that local crosstalk between IL10-producing immune cells and adipocytes is a determinant of thermogenesis and systemic energy balance. Single Nuclei Adipocyte RNA-sequencing (SNAP-seq) of subcutaneous adipose tissue defined a metabolically-active mature adipocyte subtype characterized by robust expression of genes involved in thermogenesis whose transcriptome was selectively responsive to IL10Rα deletion. Furthermore, single-cell transcriptomic analysis of adipose stromal populations identified lymphocytes as a key source of IL10 production in response to thermogenic stimuli. These findings implicate adaptive immune cell-adipocyte communication in the maintenance of adipose subtype identity and function.

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PATH-26. EVALUATING THE DISTRIBUTION AND PROGNOSIS OF IMMUNE CELL SIGNATURES OF THE TUMOR MICRO-ENVIRONMENT IN DIFFUSE GLIOMAS

Neuro-Oncology ◽

10.1093/neuonc/noab196.478 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi120-vi120

Author(s):

Bharati Mehani ◽

Saleembhasha Asanigari ◽

Hye-Jung Chung ◽

Kenneth Aldape

Keyword(s):

Gene Expression ◽

Single Cell ◽

Immune Cell ◽

Tumor Grade ◽

Cell Types ◽

Idh Mutation ◽

Mutation Status ◽

Cluster Analyses ◽

Diffuse Gliomas ◽

Cell Expression

Abstract The tumor micro-environment (TME) plays an important role in the biology of cancer, including gliomas. Single cell studies have highlighted the role of specific TME components in gliomas, and the methods to deconvolve bulk profiling data may serve to complement these studies on clinically annotated tumors. In this study, we estimated cell type proportions in 3 large glioma datasets (TCGA, CGGA-325, CGGA-693) using CIBERSORTx. Using a signature matrix comprising 22 immune cell types, we identified IDH mutation status-specific immune cell distributions and found that the proportions of 10 cell types were significantly different between IDHmut and IDHwt tumors across the 3 datasets. Looking further within IDHmut tumors, we found that monocytes were enriched in 1p/19q non-co-deleted tumors across the 3 glioma datasets, consistent with prior single cell studies. We then examined estimated gene expression among immune cell types relative to IDH mutation status and found clear separation of gene expression in 15 of 22 cell types in all 3 datasets. When we applied these 22 gene expression signatures in each tumor sample onto cluster-of-cluster analyses to identify tumor groups with distinct immune signature patterns, we found that samples were distributed largely according to the IDH status in all 3 datasets, confirming that immune cell expression is distinct based on IDH status. Among IDH-specific groups, cluster-of-cluster analyses showed that immune cell-based cluster groups had distinct survival outcomes, and that IDHwt samples were distributed significantly based on tumor grades as well as based on EGFR overexpression. Among IDHmut tumors, the distributions of tumor grade and 1p/19q co-deletion status were significantly different in the immune-based clusters in 2 of the 3 datasets examined. Overall, these results highlight the biological and clinical significance of the immune cell environment in gliomas, including distinctions based on IDH mutation status as well as prognosis within IDH-specific groups.

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Patient-derived micro-organospheres recapitulate tumor microenvironment and heterogeneity for precision oncology.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.3076 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. 3076-3076

Author(s):

Shengli Ding ◽

Zhaohui Wang ◽

Marcos Negrete Obando ◽

Grecia rivera Palomino ◽

Tomer Rotstein ◽

...

Keyword(s):

Drug Discovery ◽

Tumor Microenvironment ◽

Single Cell ◽

Stromal Cells ◽

Mononuclear Cells ◽

Immune Cell ◽

Tumor Biology ◽

Cell Types ◽

Precision Oncology ◽

Original Tumor

3076 Background: Preclinical models that can recapitulate patients’ intra-tumoral heterogeneity and microenvironment are crucial for tumor biology research and drug discovery. In particular, the ability to retain immune and other stromal cells in the microenvironment is vital for the development of immuno-oncology assays. However, current patient-derived organoid (PDO) models are largely devoid of immune components. Methods: We first developed an automated microfluidic and membrane platform that can generate tens of thousands of micro-organospheres from resected or biopsied clinical tumor specimens within an hour. We next characterized growth rate and drug response of micro-organospheres. Finally, extensive single-cell RNA-seq profiling were performed on both micro-organospheres and original tumor samples from lung, ovarian, kidney, and breast cancer patients. Results: Micro-organospheres derived from clinical tumor samples preserved all original tumor and stromal cells, including fibroblasts and all immune cell types. Single-cell analysis revealed that unsupervised clustering of tumor and non-tumor cells were identical between original tumors and the derived micro-organospheres. Quantification showed similar cell composition and percentages for all cell types and also preserved functional intra-tumoral heterogeneity.. An automated, end-to-end, high-throughput drug screening pipeline demonstrated that matched peripheral blood mononuclear cells (PBMCs) from the same patient added to micro-organospheres can be used to assess the efficacy of immunotherapy moieties. Conclusions: Micro-organospheres are a rapid and scalable platform to preserve patient tumor microenvironment and heterogeneity. This platform will be useful for precision oncology, drug discovery, and immunotherapy development. Funding sources: NIH U01 CA217514, U01 CA214300, Duke Woo Center for Big Data and Precision Health

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