scholarly journals Applications of Single-Cell Omics to Dissect Tumor Microenvironment

2020 ◽  
Vol 11 ◽  
Author(s):  
Tingting Guo ◽  
Weimin Li ◽  
Xuyu Cai
Keyword(s):  
Tumor Microenvironment ◽  
Single Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
Cell Types ◽  
Immune Checkpoint Blockade ◽  
Lineage Tracing ◽  
Great Success ◽  
Novel Technologies ◽  
Single Cell Sequencing

The recent technical and computational advances in single-cell sequencing technologies have significantly broaden our toolkit to study tumor microenvironment (TME) directly from human specimens. The TME is the complex and dynamic ecosystem composed of multiple cell types, including tumor cells, immune cells, stromal cells, endothelial cells, and other non-cellular components such as the extracellular matrix and secreted signaling molecules. The great success on immune checkpoint blockade therapy has highlighted the importance of TME on anti-tumor immunity and has made it a prime target for further immunotherapy strategies. Applications of single-cell transcriptomics on studying TME has yielded unprecedented resolution of the cellular and molecular complexity of the TME, accelerating our understanding of the heterogeneity, plasticity, and complex cross-interaction between different cell types within the TME. In this review, we discuss the recent advances by single-cell sequencing on understanding the diversity of TME and its functional impact on tumor progression and immunotherapy response driven by single-cell sequencing. We primarily focus on the major immune cell types infiltrated in the human TME, including T cells, dendritic cells, and macrophages. We further discuss the limitations of the existing methodologies and the prospects on future studies utilizing single-cell multi-omics technologies. Since immune cells undergo continuous activation and differentiation within the TME in response to various environmental cues, we highlight the importance of integrating multimodal datasets to enable retrospective lineage tracing and epigenetic profiling of the tumor infiltrating immune cells. These novel technologies enable better characterization of the developmental lineages and differentiation states that are critical for the understanding of the underlying mechanisms driving the functional diversity of immune cells within the TME. We envision that with the continued accumulation of single-cell omics datasets, single-cell sequencing will become an indispensable aspect of the immune-oncology experimental toolkit. It will continue to drive the scientific innovations in precision immunotherapy and will be ultimately adopted by routine clinical practice in the foreseeable future.

484 Bioturing browser: interactively explore public single cell sequencing data

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

scholarly journals P02.10 FocuSCOPE: a single cell, multi-omics solution to simultaneously analyze tumor variants and microenvironment

2021 ◽  
Vol 9 (Suppl 1) ◽  
pp. A12.1-A12
Author(s):  
Y Arjmand Abbassi ◽  
N Fang ◽  
W Zhu ◽  
Y Zhou ◽  
Y Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
High Throughput ◽  
Immune Cells ◽  
Genetic Variants ◽  
Expression Profiles ◽  
Single Cells ◽  
Gene Expression Profiles ◽  
Single Cell Sequencing

Recent advances of high-throughput single cell sequencing technologies have greatly improved our understanding of the complex biological systems. Heterogeneous samples such as tumor tissues commonly harbor cancer cell-specific genetic variants and gene expression profiles, both of which have been shown to be related to the mechanisms of disease development, progression, and responses to treatment. Furthermore, stromal and immune cells within tumor microenvironment interact with cancer cells to play important roles in tumor responses to systematic therapy such as immunotherapy or cell therapy. However, most current high-throughput single cell sequencing methods detect only gene expression levels or epigenetics events such as chromatin conformation. The information on important genetic variants including mutation or fusion is not captured. To better understand the mechanisms of tumor responses to systematic therapy, it is essential to decipher the connection between genotype and gene expression patterns of both tumor cells and cells in the tumor microenvironment. We developed FocuSCOPE, a high-throughput multi-omics sequencing solution that can detect both genetic variants and transcriptome from same single cells. FocuSCOPE has been used to successfully perform single cell analysis of both gene expression profiles and point mutations, fusion genes, or intracellular viral sequences from thousands of cells simultaneously, delivering comprehensive insights of tumor and immune cells in tumor microenvironment at single cell resolution.Disclosure InformationY. Arjmand Abbassi: None. N. Fang: None. W. Zhu: None. Y. Zhou: None. Y. Chen: None. U. Deutsch: None.

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

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

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

eLife ◽  
2019 ◽  
Vol 8 ◽  
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.

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

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

scholarly journals Multi-modal single cell analysis reveals brain immune landscape plasticity during aging and gut microbiota dysbiosis

2020 ◽  
Author(s):  
Samantha M. Golomb ◽  
Ian H. Guldner ◽  
Anqi Zhao ◽  
Qingfei Wang ◽  
Bhavana Palakurthi ◽  
...  
Keyword(s):  
Single Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
Cell Types ◽  
Cell Plasticity ◽  
Tissue Microenvironment ◽  
Gut Dysbiosis ◽  
Resolution Single ◽  
The Brain ◽  
Gut Microbiota Dysbiosis

ABSTRACTThe brain contains a diverse array of immune cell types. The phenotypic and functional plasticity of brain immune cells collectively contribute to brain tissue homeostasis and disease progression. Immune cell plasticity is profoundly influenced by local tissue microenvironment cues and systemic factors. Yet, the transcriptional mechanism by which systemic stimuli, such as aging and gut microbiota dysbiosis, reshape brain immune cell plasticity and homeostasis has not been fully delineated. Using Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq), we analyzed compositional and transcriptional changes of the brain immune landscape in response to aging and gut dysbiosis. We first examined the discordance between canonical surface marker-defined immune cell types (Cell-ID) and their transcriptome signatures, which suggested transcriptional plasticity among immune cells despite sharing the same cell surface markers. Specifically, inflammatory and patrolling Ly6C+ monocytes were shifted predominantly to a pro-inflammatory transcriptional program in the aged brain, while brain ILCs shifted toward an ILC2 transcriptional profile. Finally, aging led to an increase of ILC-like cells expressing a T memory stemness (Tscm) signature in the brain. Antibiotics (ABX)-induced gut dysbiosis reduced the frequency of ILCs exhibiting Tscm-like properties in the aged mice, but not in the young mice. Enabled by high-resolution single-cell molecular phenotyping, our study revealed that systemic changes due to aging and gut dysbiosis prime the brain environment for an increased propensity for neuroinflammation, which provided insights into gut dysbiosis in age-related neurological diseases.Manuscript SummaryGolomb et al. performed Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq) on immune cells from the brains of young and aged mice with and without antibiotics-induced gut dysbiosis. High resolution, single cell immunophenotyping enabled the dissection of extensive transcriptional plasticity of canonically identified monocytes and innate lymphoid cells (ILCs) in the aged brain. Through differential gene expression and trajectory inference analyses, the authors revealed tissue microenvironment-dependent cellular responses influenced by aging and gut dysbiosis that may potentiate neuroinflammatory diseases.Graphical Abstract

scholarly journals Knowledge-based classification of fine-grained immune cell types in single-cell RNA-Seq data with ImmClassifier

2020 ◽  
Author(s):  
Xuan Liu ◽  
Sara J.C. Gosline ◽  
Lance T. Pflieger ◽  
Pierre Wallet ◽  
Archana Iyer ◽  
...  
Keyword(s):  
T Cells ◽  
Single Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
Cell Types ◽  
Effector Memory ◽  
Immune Cell Population ◽  
Fine Grained ◽  
Knowledge Based ◽  
Comparable Performance

AbstractSingle-cell RNA sequencing is an emerging strategy for characterizing the immune cell population in diverse environments including blood, tumor or healthy tissues. While this has traditionally been done with flow or mass cytometry targeting protein expression, scRNA-Seq has several established and potential advantages in that it can profile immune cells and non-immune cells (e.g. cancer cells) in the same sample, identify cell types that lack precise markers for flow cytometry, or identify a potentially larger number of immune cell types and activation states than is achievable in a single flow assay. However, scRNA-Seq is currently limited due to the need to identify the types of each immune cell from its transcriptional profile, which is not only time-consuming but also requires a significant knowledge of immunology. While recently developed algorithms accurately annotate coarse cell types (e.g. T cells vs macrophages), making fine distinctions has turned out to be a difficult challenge. To address this, we developed a machine learning classifier called ImmClassifier that leverages a hierarchical ontology of cell type. We demonstrate that ImmClassifier outperforms other tools (+20% recall, +14% precision) in distinguishing fine-grained cell types (e.g. CD8+ effector memory T cells) with comparable performance on coarse ones. Thus, ImmClassifier can be used to explore more deeply the heterogeneity of the immune system in scRNA-Seq experiments.

scholarly journals Single-cell RNA sequencing reveals micro-evolution of the stickleback immune system

2021 ◽  
Author(s):  
Lauren E Fuess ◽  
Daniel I Bolnick
Keyword(s):  
Immune System ◽  
Single Cell ◽  
Immune Cells ◽  
Gasterosteus Aculeatus ◽  
Immune Cell ◽  
Expression Profiles ◽  
Cell Types ◽  
Model Systems ◽  
System Structure ◽  
Ecological Processes

Pathogenic infection is an important driver of many ecological processes. Furthermore, variability in immune function is an important driver of differential infection outcomes. New evidence would suggest that immune variation extends to broad cellular structure of immune systems. However, variability at such broad levels is traditionally difficult to detect in non-model systems. Here we leverage single cell transcriptomic approaches to document signatures of microevolution of immune system structure in a natural system, the three-spined stickleback (Gasterosteus aculeatus). We sampled nine adult fish from three populations with variability in resistance to a cestode parasite, Schistocephalus solidus, to create the first comprehensive immune cell atlas for G. aculeatus. Eight major immune cell types, corresponding to major vertebrate immune cells, were identified. We were also able to document significant variation in both abundance and expression profiles of the individual immune cell types, among the three populations of fish. This variability may contribute to observed variability in parasite susceptibility. Finally, we demonstrate that identified cell type markers can be used to reinterpret traditional transcriptomic data. Combined our study demonstrates the power of single cell sequencing to not only document evolutionary phenomena (i.e. microevolution of immune cells), but also increase the power of traditional transcriptomic datasets.

Therapeutic checkpoint targets: Evaluation of co-expression profiles in individual tumor and immune cells in the tumor microenvironment of FFPE tissue.

2018 ◽  
Vol 36 (5_suppl) ◽  
pp. 176-176
Author(s):  
Annelies Laeremans ◽  
Na Li ◽  
Jeff Kim ◽  
Xiao-Jun Ma ◽  
Emily Park
Keyword(s):  
Tumor Microenvironment ◽  
Single Cell ◽  
Immune Cells ◽  
Immune Checkpoint ◽  
Checkpoint Inhibitors ◽  
Expression Profiles ◽  
Predictive Biomarkers ◽  
Immune Checkpoint Blockade ◽  
Durable Response

176 Background: Interactions between tumor and immune cells in the tumor microenvironment (TME) play a key role in tumor progression and treatment response with accumulating evidence indicating a crucial role for tumor infiltrating immune cells. Although infiltrating cytotoxic T lymphocytes (CTLs) have been correlated with improved clinical outcome, they are ineffective in eradicating tumors due to their inhibition by immune checkpoint molecules. Immune checkpoint inhibitors have demonstrated therapeutic efficacy and durable response for several tumor types including non-small cell lung cancer (NSCLC). However, the majority of patients are resistant or relapse after initial response. Characterizing the TME for checkpoint expression with single-cell and spatial resolution can provide critical insight into new immunotherapeutic strategies and identify new predictive biomarkers for stratifying and identifying patients most likely to benefit from immunotherapy including PD-1/PD-L1 immune checkpoint blockade. Methods: Using RNAscope in situ hybridization, we evaluated in situ co-expression profiles of therapeutic checkpoint targets at single-cell level in the TME of 56 archived NSCLC FFPE tissues. Results: Checkpoint molecules including PD1, PD-L1, PD-L2, TIM3, LAG3, CTLA-4 and GITR were visualized in a highly specific and sensitive manner in individual cells within tissue morphological context. Multiple checkpoint molecules were detected in the same immune environment, especially in highly inflamed tumors. In addition to PD-L1, tumor cell-intrinsic expression of PD1, TIM3, LAG3, and PD-L2 was observed in a subset of samples. Furthermore, co-expression of therapeutic checkpoint targets including PD1, LAG3, and TIM3 was observed in infiltrating immune cells and tumor cells. Conclusions: Single-cell co-expression profiles of checkpoint molecules could shed light on how cancer cells evade the host immune surveillance and develop resistance against checkpoint blockades. Also, they could reveal valuable insights into combinatorial therapies for checkpoint markers co-expressed by the patient’s immune cells in the TME.

scholarly journals NFIL3 mutations alter immune homeostasis and sensitise for arthritis pathology

2018 ◽  
Vol 78 (3) ◽  
pp. 342-349 ◽  
Author(s):  
Susan Schlenner ◽  
Emanuela Pasciuto ◽  
Vasiliki Lagou ◽  
Oliver Burton ◽  
Teresa Prezzemolo ◽  
...  
Keyword(s):  
Immune System ◽  
Single Cell ◽  
Immune Cell ◽  
Cell Types ◽  
Monozygotic Twin ◽  
Preclinical Model ◽  
Potential Contribution ◽  
Mutant Form ◽  
Single Cell Sequencing

ObjectivesNFIL3 is a key immunological transcription factor, with knockout mice studies identifying functional roles in multiple immune cell types. Despite the importance of NFIL3, little is known about its function in humans.MethodsHere, we characterised a kindred of two monozygotic twin girls with juvenile idiopathic arthritis at the genetic and immunological level, using whole exome sequencing, single cell sequencing and flow cytometry. Parallel studies were performed in a mouse model.ResultsThe patients inherited a novel p.M170I in NFIL3 from each of the parents. The mutant form of NFIL3 demonstrated reduced stability in vitro. The potential contribution of this mutation to arthritis susceptibility was demonstrated through a preclinical model, where Nfil3-deficient mice upregulated IL-1β production, with more severe arthritis symptoms on disease induction. Single cell sequencing of patient blood quantified the transcriptional dysfunctions present across the peripheral immune system, converging on IL-1β as a pivotal cytokine.ConclusionsNFIL3 mutation can sensitise for arthritis development, in mice and humans, and rewires the innate immune system for IL-1β over-production.

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