A new approach for immuno-oncology biomarker discovery: High-plex, spatial protein profiling based on NanoString digital quantification.

2017 ◽  
Vol 35 (7_suppl) ◽  
pp. 27-27 ◽  
Author(s):  
David Lee ◽  
Yan Liang ◽  
Chris Merritt ◽  
Fiona Pakiam ◽  
Giang Ong ◽  
...  
Keyword(s):  
Immune Response ◽  
Single Cell ◽  
Spatial Resolution ◽  
Biomarker Discovery ◽  
Immune Cell ◽  
Light Exposure ◽  
Protein Detection ◽  
Protein Profiling ◽  
Ffpe Samples

27 Background: The immune response to cancer is shaped by the abundance and localization of immune cell populations, their activation status, and expression of immunomodulatory factors. To detect proteins at high multiplex with spatial resolution, NanoString optical barcoding technology was used to digitally profile protein expression in formalin fixed paraffin embedded (FFPE) samples and compared to traditional IHC. Methods: NanoString has enabled digital profiling of immuno-oncology protein targets, including immune cell markers and checkpoint proteins. Protein detection is enabled via primary antibodies (Abs) which are attached via a UV cleavable linker to DNA indexing oligos. FFPE samples are stained with a multiplex cocktail of labeled Abs, then DNA oligos are released by UV light exposure. Liberated oligos are then hybridized to optical barcodes for quantitation on a NanoString instrument. This technique enables quantitative, multiplex protein detection over 5 logs of dynamic range. IHC and NanoString spatial protein profiling were performed on alternating sections from blocks of tonsil, melanoma, and colorectal cancer. Sections were fluorescently labeled with panCK, Ki67, and Syto-83 to visualize morphology, and regions of interest (ROI) were selected for profiling using up to 30 oligo-tagged Abs. Results: NanoString counts strongly correlated with quantification of CD3, CD4, CD8, PanCK, Ki67, PD-1, and PD-L1 derived from IHC. To explore limits of detection, ROIs of 1, 2, 4, or 8 cells were profiled. Digital counts were detected above background at the single cell level and linearly correlated with cell count. Furthermore, quantification with two cell lineage markers and double positive cells were demonstrated using a 30-plex Ab cocktail. Conclusions: Multiplex, digital protein profiling with spatial resolution will enable deep characterization of immune responses in tumors. Additionally, single cell profiling enables inter-cellular characterization of variations in immune response. The strong correlation of NanoString data to IHC indicates the feasibility to spatially profile multiple key proteins with minimal consumption of patient tissue.

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

BMC Genomics ◽  
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.

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

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.

scholarly journals Characterization of CRISPR/Cas9 RANKL knockout mesenchymal stem cell clones based on single-cell printing technology and emulsion coupling assay as a low-cellularity workflow for single-cell cloning

2020 ◽  
Author(s):  
Tobias Groß ◽  
Csaba Jeney ◽  
Darius Halm ◽  
Günter Finkenzeller ◽  
G. Björn Stark ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Line ◽  
Large Scale ◽  
Single Cells ◽  
Protein Detection ◽  
Cell Line Development ◽  
Cell Printing ◽  
Cell Clones ◽  
The University

AbstractThe homogeneity of the genetically modified single-cells is a necessity for many applications such as cell line development, gene therapy, and tissue engineering and in particular for regenerative medical applications. The lack of tools to effectively isolate and characterize CRISPR/Cas9 engineered cells is considered as a significant bottleneck in these applications. Especially the incompatibility of protein detection technologies to confirm protein expression changes without a preconditional large-scale clonal expansion, creates a gridlock in many applications. To ameliorate the characterization of engineered cells, we propose an improved workflow, including single-cell printing/isolation technology based on fluorescent properties with high yield, a genomic edit screen (surveyor assay), mRNA rtPCR assessing altered gene expression and a versatile protein detection tool called emulsion-coupling to deliver a high-content, unified single-cell workflow. The workflow was exemplified by engineering and functionally validating RANKL knockout immortalized mesenchymal stem cells showing altered bone formation capacity of these cells. The resulting workflow is economical, without the requirement of large-scale clonal expansions of the cells with overall cloning efficiency above 30% of CRISPR/Cas9 edited cells. Nevertheless, as the single-cell clones are comprehensively characterized at an early, highly parallel phase of the development of cells including DNA, RNA, and protein levels, the workflow delivers a higher number of successfully edited cells for further characterization, lowering the chance of late failures in the development process.Author summaryI completed my undergraduate degree in biochemistry at the University of Ulm and finished my master's degree in pharmaceutical biotechnology at the University of Ulm and University of applied science of Biberach with a focus on biotechnology, toxicology and molecular biology. For my master thesis, I went to the University of Freiburg to the department of microsystems engineering, where I developed a novel workflow for cell line development. I stayed at the institute for my doctorate, but changed my scientific focus to the development of the emulsion coupling technology, which is a powerful tool for the quantitative and highly parallel measurement of protein and protein interactions. I am generally interested in being involved in the development of innovative molecular biological methods that can be used to gain new insights about biological issues. I am particularly curious to unravel the complex and often poorly understood protein interaction pathways that are the cornerstone of understanding cellular functionality and are a fundamental necessity to describe life mechanistically.

scholarly journals Multimodal Single-Cell Characterization of the Human Granulocyte Lineage

2021 ◽  
Author(s):  
Jingjing Qi ◽  
Darwin D'Souza ◽  
Travis Dawson ◽  
Daniel Geanon ◽  
Hiyab Stefanos ◽  
...  
Keyword(s):  
Single Cell ◽  
Immune Cell ◽  
Gene Transcript ◽  
Diverse Range ◽  
Human Whole Blood ◽  
Significant Challenge ◽  
Human Granulocytes ◽  
Gene Transcripts ◽  
Transcript Detection

High throughput single cell transcriptomics (scRNA-seq) has been successfully applied to characterize immune cell heterogeneity across a diverse range of settings; however, analysis of human granulocytes remains a significant challenge due to their low gene expression transcript detection. Consequently, granulocytes are typically either absent or highly under-represented and inaccurately enumerated in most human scRNA-seq datasets. Here, we apply multi-modal CITE-seq profiling to characterize granulocytes in human whole blood and bone marrow, and we show that these populations can be accurately detected and analyzed using the antibody-based modality, and that their frequencies and phenotype align well with antibody-based characterization of the same samples using CyTOF. These analyses also clearly highlight extremely low gene transcript detection across the entire granulocyte lineage including the earliest neutrophil progenitor populations when using the 10X Genomics platform. By contrast, when performing parallel analyses of the same samples using the BD Rhapsody platform, we recovered a much higher proportion of granulocyte gene transcripts, enabling true multi-modal characterization of human granulocyte heterogeneity.

scholarly journals Systematic Comparison of High-Throughput Single-Cell RNAseq Methods for Immune Cell Profiling

2020 ◽  
Author(s):  
Chi-Ming Kevin Li ◽  
Tracy M Yamawaki ◽  
Daniel R Lu ◽  
Daniel C Ellwanger ◽  
Dev Bhatt ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Immune Cell ◽  
Cell Types ◽  
Drop Out ◽  
Detection Sensitivity ◽  
Rna Seq ◽  
Cell Recovery

Abstract Background: Elucidation of immune populations with single-cell RNA-seq has greatly benefited the fieldof immunology by deepening the characterization of immune heterogeneity and leading to thediscovery of new subtypes. However, single-cell methods inherently suffer from limitations in therecovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropoutevents. This issue is often compounded by limited sample availability and limited prior knowledge ofheterogeneity, which can confound data interpretation.Results: Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. Weprepared 21 libraries under identical conditions of a defined mixture of two human and two murinelymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluatemethods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expressionsignatures 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 drop-out events whichfacilitates the identification of differentially-expressed genes and improves the concordance of singlecellprofiles to immune bulk RNA-seq signatures.Conclusion: Overall, our characterization of immune cell mixtures provides useful metrics, which canguide selection of a high-throughput single-cell RNA-seq method for profiling more complex immunecellheterogeneity usually found in vivo.

scholarly journals Identification of Breast Cancer Immune Subtypes by Analyzing Bulk Tumor and Single Cell Transcriptomes

2022 ◽  
Vol 9 ◽  
Author(s):  
Jia Yao ◽  
Shengwei Li ◽  
Xiaosheng Wang
Keyword(s):  
Breast Cancer ◽  
Immune Response ◽  
Single Cell ◽  
Mutation Rate ◽  
Immune Cell ◽  
Growth Factor Receptor ◽  
Intratumor Heterogeneity ◽  
Strong Immune Response ◽  
Survival Prognosis ◽  
Immune Signature

Background: The histological and molecular classification of breast cancer (BC) is being used in the clinical management of this disease. However, subtyping of BC based on the tumor immune microenvironment (TIME) remains insufficiently explored, although such investigation may provide new insights into intratumor heterogeneity in BC and potential clinical implications for BC immunotherapy.Methods: Based on the enrichment scores of 28 immune cell types, we performed clustering analysis of transcriptomic data to identify immune-specific subtypes of BC using six different datasets, including five bulk tumor datasets and one single-cell dataset. We further analyzed the molecular and clinical features of these subtypes.Results: Consistently in the six datasets, we identified three BC subtypes: BC-ImH, BC-ImM, and BC-ImL, which had high, medium, and low immune signature scores, respectively. BC-ImH displayed a significantly better survival prognosis than BC-ImL. Triple-negative BC (TNBC) and human epidermal growth factor receptor-2-positive (HER2+) BC were likely to have the highest proportion in BC-ImH and the lowest proportion in BC-ImL. In contrast, hormone receptor-positive (HR+) BC had the highest proportion in BC-ImL and the lowest proportion in BC-ImH. Furthermore, BC-ImH had the highest tumor mutation burden (TMB) and predicted neoantigens, while BC-ImL had the highest somatic copy number alteration (SCNA) scores. It is consistent with that TMB and SCNA correlate positively and negatively with anti-tumor immune response, respectively. TP53 had the highest mutation rate in BC-ImH and the lowest mutation rate in BC-ImL, supporting that TP53 mutations promote anti-tumor immune response in BC. In contrast, PIK3CA displayed the highest mutation rate in BC-ImM, while GATA3 had the highest mutation rate in BC-ImL. Besides immune pathways, many oncogenic pathways were upregulated in BC-ImH, including ErbB, MAPK, VEGF, and Wnt signaling pathways; the activities of these pathways correlated positively with immune signature scores in BC.Conclusions: The tumors with the strong immune response (“hot” tumors) have better clinical outcomes than the tumors with the weak immune response (“cold” tumors) in BC. TNBC and HER2+ BC are more immunogenic, while HR + BC is less immunogenic. Certain HER2+ or HR + BC patients could be propitious to immunotherapy in addition to TNBC.

scholarly journals Characterization of CRISPR/Cas9 RANKL knockout mesenchymal stem cell clones based on single-cell printing technology and Emulsion Coupling assay as a low-cellularity workflow for single-cell cloning

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0238330
Author(s):  
Tobias Gross ◽  
Csaba Jeney ◽  
Darius Halm ◽  
Günter Finkenzeller ◽  
G. Björn Stark ◽  
...  
Keyword(s):  
Single Cell ◽  
Large Scale ◽  
Single Cells ◽  
Protein Detection ◽  
High Yield ◽  
Fluorescent Properties ◽  
Cell Printing ◽  
Protein Levels ◽  
Cell Clones

The homogeneity of the genetically modified single-cells is a necessity for many applications such as cell line development, gene therapy, and tissue engineering and in particular for regenerative medical applications. The lack of tools to effectively isolate and characterize CRISPR/Cas9 engineered cells is considered as a significant bottleneck in these applications. Especially the incompatibility of protein detection technologies to confirm protein expression changes without a preconditional large-scale clonal expansion creates a gridlock in many applications. To ameliorate the characterization of engineered cells, we propose an improved workflow, including single-cell printing/isolation technology based on fluorescent properties with high yield, a genomic edit screen (Surveyor assay), mRNA RT-PCR assessing altered gene expression, and a versatile protein detection tool called emulsion-coupling to deliver a high-content, unified single-cell workflow. The workflow was exemplified by engineering and functionally validating RANKL knockout immortalized mesenchymal stem cells showing bone formation capacity of these cells. The resulting workflow is economical, without the requirement of large-scale clonal expansions of the cells with overall cloning efficiency above 30% of CRISPR/Cas9 edited cells. Nevertheless, as the single-cell clones are comprehensively characterized at an early, highly parallel phase of the development of cells including DNA, RNA, and protein levels, the workflow delivers a higher number of successfully edited cells for further characterization, lowering the chance of late failures in the development process.

scholarly journals A Catalogus Immune Muris of the mouse immune responses to diverse pathogens

2021 ◽  
Vol 12 (9) ◽  
Author(s):  
Céline Barlier ◽  
Diego Barriales ◽  
Alexey Samosyuk ◽  
Sascha Jung ◽  
Srikanth Ravichandran ◽  
...  
Keyword(s):  
Immune Response ◽  
Immune Responses ◽  
Biomedical Applications ◽  
Immune Cell ◽  
Cell Types ◽  
Computational Method ◽  
Functional Responses ◽  
Macrophage Cell ◽  
Functional States

AbstractImmunomodulation strategies are crucial for several biomedical applications. However, the immune system is highly heterogeneous and its functional responses to infections remains elusive. Indeed, the characterization of immune response particularities to different pathogens is needed to identify immunomodulatory candidates. To address this issue, we compiled a comprehensive map of functional immune cell states of mouse in response to 12 pathogens. To create this atlas, we developed a single-cell-based computational method that partitions heterogeneous cell types into functionally distinct states and simultaneously identifies modules of functionally relevant genes characterizing them. We identified 295 functional states using 114 datasets of six immune cell types, creating a Catalogus Immune Muris. As a result, we found common as well as pathogen-specific functional states and experimentally characterized the function of an unknown macrophage cell state that modulates the response to Salmonella Typhimurium infection. Thus, we expect our Catalogus Immune Muris to be an important resource for studies aiming at discovering new immunomodulatory candidates.

scholarly journals Single-Cell RNA Sequencing of Peripheral Blood Reveals Immune Cell Signatures in Alzheimer’s Disease

2021 ◽  
Vol 12 ◽  
Author(s):  
Hui Xu ◽  
Jianping Jia
Keyword(s):  
Immune Response ◽  
T Cells ◽  
Single Cell ◽  
Immune Cells ◽  
Peripheral Blood ◽  
Immune Cell ◽  
Adaptive Immune Response ◽  
Immune Repertoire ◽  
Adaptive Immune ◽  
Peripheral Immune Cells

The peripheral immune system is thought to affect the pathology of the central nervous system in Alzheimer’s disease (AD). However, current knowledge is inadequate for understanding the characteristics of peripheral immune cells in AD. This study aimed to explore the molecular basis of peripheral immune cells and the features of adaptive immune repertoire at a single cell level. We profiled 36,849 peripheral blood mononuclear cells from AD patients with amyloid-positive status and normal controls with amyloid-negative status by 5’ single-cell transcriptome and immune repertoire sequencing using the cell ranger standard analysis procedure. We revealed five immune cell subsets: CD4+ T cells, CD8+ T cells, B cells, natural killer cells, and monocytes–macrophages cells, and disentangled the characteristic alterations of cell subset proportion and gene expression patterns in AD. Thirty-one cell type-specific key genes, comprising abundant human leukocyte antigen genes, and multiple immune-related pathways were identified by protein–protein interaction network and pathway enrichment analysis. We also found high-frequency amplification clonotypes in T and B cells and decreased diversity in T cells in AD. As clone amplification suggested the activation of an adaptive immune response against specific antigens, we speculated that the peripheral adaptive immune response, especially mediated by T cells, may have a role in the pathogenesis of AD. This finding may also contribute to further research regarding disease mechanism and the development of immune-related biomarkers or therapy.

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