scholarly journals EPEN-07. SINGLE-CELL RNA SEQUENCING IDENTIFIES A UNIQUE MYELOID SUBPOPULATION ASSOCIATED WITH MESENCHYMAL TUMOR SUBPOPULATION IN POOR OUTCOME PEDIATRIC EPENDYMOMA

2021 ◽  
Vol 23 (Supplement_1) ◽  
pp. i14-i15
Author(s):  
Andrea Griesinger ◽  
Kent Riemondy ◽  
Andrew Donson ◽  
Nicholas Willard ◽  
Eric Prince ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Tumor Necrosis ◽  
Expression Profiles ◽  
Myeloid Cells ◽  
Gene Expression Profiles ◽  
Myeloid Cell ◽  
Mesenchymal Tumor ◽  
Immune Gene ◽  
Poor Outcome

Abstract We have previously shown immune gene phenotype variations between posterior fossa ependymoma subgroups. PFA1 tumors chronically secrete IL-6, which induces secretion of myeloid cell IL-8 and pushes the infiltrating myeloid cells to an immune suppressive function. In contrast, PFA2 tumors have a more immune activated phenotype associated with a better prognosis. The objective of this study was to use single-cell(sc) RNAseq to descriptively characterize the infiltrating myeloid cells. We analyzed approximately 8500 cells from 21 PFA patient samples. Using advanced machine learning, we identified eight myeloid cell subpopulations with unique gene expression profiles. Interestingly, only one subpopulation was significantly enriched in PFA1 tumors. This subpopulation, denoted as the hypoxia myeloid subpopulation, was defined by genes associated with angiogenesis, response to hypoxia, wound healing, cell migration, neutrophil activation and response to oxygen levels. These myeloid cells also share similar gene expression profile to a mesenchymal tumor subpopulation (MEC) enriched in PFA1 and associated with poor outcome in EPN patients. This tumor subpopulation was the only population expressing IL-6. Using immunohistochemistry, we found the hypoxia myeloid located in regions of tumor necrosis and perivascular niches. The MEC cells were also more abundant in these regions. In an independent single-cell cytokine release assay, we identified eight subpopulations of functional myeloid cells. One subpopulation significantly secreted IL-8, which represented the hypoxia subpopulation based on IL-8 gene expression in the scRNAseq dataset. This data suggests the tumor necrosis resulting in the development of MEC tumor subpopulation is driving the immune suppressive myeloid phenotype in PFA1 tumors through polarization of myeloid cells to the hypoxia subpopulation. Further studies are needed to determine how these myeloid cells interact with the lymphocyte subpopulations and whether they contribute to the progression of PFA1 EPN.

4 Molecularly guided multiplexed digital spatial analysis reveals differential gene expression profiles in the WNT-β-catenin pathway between melanoma and prostate tumors

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A4-A4
Author(s):  
Anushka Dikshit ◽  
Dan Zollinger ◽  
Karen Nguyen ◽  
Jill McKay-Fleisch ◽  
Kit Fuhrman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Single Molecule ◽  
Spatial Information ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Fluorescence Assay ◽  
Differentially Expressed ◽  
Tumor Type ◽  
Prostate Tumors

BackgroundThe canonical WNT-β-catenin signaling pathway is vital for development and tissue homeostasis but becomes strongly tumorigenic when dysregulated. and alter the transcriptional signature of a cell to promote malignant transformation. However, thorough characterization of these transcriptomic signatures has been challenging because traditional methods lack either spatial information, multiplexing, or sensitivity/specificity. To overcome these challenges, we developed a novel workflow combining the single molecule and single cell visualization capabilities of the RNAscope in situ hybridization (ISH) assay with the highly multiplexed spatial profiling capabilities of the GeoMx™ Digital Spatial Profiler (DSP) RNA assays. Using these methods, we sought to spatially profile and compare gene expression signatures of tumor niches with high and low CTNNB1 expression.MethodsAfter screening 120 tumor cores from multiple tumors for CTNNB1 expression by the RNAscope assay, we identified melanoma as the tumor type with the highest CTNNB1 expression while prostate tumors had the lowest expression. Using the RNAscope Multiplex Fluorescence assay we selected regions of high CTNNB1 expression within 3 melanoma tumors as well as regions with low CTNNB1 expression within 3 prostate tumors. These selected regions of interest (ROIs) were then transcriptionally profiled using the GeoMx DSP RNA assay for a set of 78 genes relevant in immuno-oncology. Target genes that were differentially expressed were further visualized and spatially assessed using the RNAscope Multiplex Fluorescence assay to confirm GeoMx DSP data with single cell resolution.ResultsThe GeoMx DSP analysis comparing the melanoma and prostate tumors revealed that they had significantly different gene expression profiles and many of these genes showed concordance with CTNNB1 expression. Furthermore, immunoregulatory targets such as ICOSLG, CTLA4, PDCD1 and ARG1, also demonstrated significant correlation with CTNNB1 expression. On validating selected targets using the RNAscope assay, we could distinctly visualize that they were not only highly expressed in melanoma compared to the prostate tumor, but their expression levels changed proportionally to that of CTNNB1 within the same tumors suggesting that these differentially expressed genes may be regulated by the WNT-β-catenin pathway.ConclusionsIn summary, by combining the RNAscope ISH assay and the GeoMx DSP RNA assay into one joint workflow we transcriptionally profiled regions of high and low CTNNB1 expression within melanoma and prostate tumors and identified genes potentially regulated by the WNT- β-catenin pathway. This novel workflow can be fully automated and is well suited for interrogating the tumor and stroma and their interactions.GeoMx Assays are for RESEARCH ONLY, not for diagnostics.

scholarly journals EPEN-22. SINGLE-CELL RNA SEQUENCING IDENTIFIES UPREGULATION OF IKZF1 IN PFA2 MYELOID SUBPOPULATION DRIVING AN ANTI-TUMOR PHENOTYPE

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii312-iii312
Author(s):  
Andrea Griesinger ◽  
Eric Prince ◽  
Andrew Donson ◽  
Kent Riemondy ◽  
Timothy Ritzman ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
T Cell Activation ◽  
Expression Profiles ◽  
Myeloid Cells ◽  
Cell Subset ◽  
Lineage Tracing ◽  
Machine Learning Techniques ◽  
Cell Subpopulation ◽  
Immune Gene

Abstract We have previously shown immune gene phenotype variations between posterior fossa ependymoma subgroups. PFA1 tumors chronically secrete IL-6, which pushes the infiltrating myeloid cells to an immune suppressive function. In contrast, PFA2 tumors have a more immune activated phenotype and have a better prognosis. The objective of this study was to use single-cell(sc) RNAseq to descriptively characterize the infiltrating myeloid cells. We analyzed approximately 8500 cells from 21 PFA patient samples and used advanced machine learning techniques to identify distinct myeloid and lymphoid subpopulations. The myeloid compartment was difficult to interrupt as the data shows a continuum of gene expression profiles exist within PFA1 and PFA2. Through lineage tracing, we were able to tease out that PFA2 myeloid cells expressed more genes associated with an anti-viral response (MHC II, TNF-a, interferon-gamma signaling); while PFA1 myeloid cells had genes associated with an immune suppressive phenotype (angiogenesis, wound healing, IL-10). Specifically, we found expression of IKZF1 was upregulated in PFA2 myeloid cells. IKZF1 regulates differentiation of myeloid cells toward M1 or M2 phenotype through upregulation of either IRF5 or IRF4 respectively. IRF5 expression correlated with IKZF1, being predominately expressed in the PFA2 myeloid cell subset. IKZF1 is also involved in T-cell activation. While we have not completed our characterization of the T-cell subpopulation, we did find significantly more T-cell infiltration in PFA2 than PFA1. Moving forward these studies will provide us with valuable information regarding the molecular switches involved in the tumor-immune microenvironment and to better develop immunotherapy for PFA ependymoma.

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 Single-cell immune repertoire and transcriptome sequencing reveals that clonally expanded and transcriptionally distinct lymphocytes populate the aged central nervous system in mice

2021 ◽  
Vol 288 (1945) ◽  
pp. 20202793
Author(s):  
Alexander Yermanos ◽  
Daniel Neumeier ◽  
Ioana Sandu ◽  
Mariana Borsa ◽  
Ann Cathrin Waindok ◽  
...  
Keyword(s):  
Gene Expression ◽  
Central Nervous System ◽  
Nervous System ◽  
B Cells ◽  
Single Cell ◽  
Somatic Hypermutation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Receptor ◽  
The Central Nervous System

Neuroinflammation plays a crucial role during ageing and various neurological conditions, including Alzheimer's disease, multiple sclerosis and infection. Technical limitations, however, have prevented an integrative analysis of how lymphocyte immune receptor repertoires and their accompanying transcriptional states change with age in the central nervous system. Here, we leveraged single-cell sequencing to simultaneously profile B cell receptor and T cell receptor repertoires and accompanying gene expression profiles in young and old mouse brains. We observed the presence of clonally expanded B and T cells in the central nervous system of aged male mice. Furthermore, many of these B cells were of the IgM and IgD isotypes, and had low levels of somatic hypermutation. Integrating gene expression information additionally revealed distinct transcriptional profiles of these clonally expanded lymphocytes. Our findings implicate that clonally related T and B cells in the CNS of elderly mice may contribute to neuroinflammation accompanying homeostatic ageing.

scholarly journals The single-cell transcriptional landscape of lung carcinoid tumors

2021 ◽  
Author(s):  
Philip Bischoff ◽  
Alexandra Trinks ◽  
Jennifer Wiederspahn ◽  
Benedikt Obermayer ◽  
Jan Patrick Pett ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Carcinoid Tumor ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Carcinoid Tumors ◽  
Cellular Composition ◽  
Cell Gene Expression ◽  
Cell Gene ◽  
Lung Carcinoid

AbstractLung carcinoid tumors, also referred to as pulmonary neuroendocrine tumors or lung carcinoids, are rare neoplasms of the lung with a more favorable prognosis than other subtypes of lung cancer. Still, some patients suffer from relapsed disease and metastatic spread while no consensus treatment exists for metastasized carcinoids. Several recent single-cell studies have provided detailed insights into the cellular heterogeneity of more common lung cancers, such as adeno- and squamous cell carcinoma. However, the characteristics of lung carcinoids on the single-cell level are yet completely unknown.To study the cellular composition and single-cell gene expression profiles in lung carcinoids, we applied single-cell RNA sequencing to three lung carcinoid tumor samples and normal lung tissue. The single-cell transcriptomes of carcinoid tumor cells reflected intertumoral heterogeneity associated with clinicopathological features, such as tumor necrosis and proliferation index. The immune microenvironment was specifically enriched in noninflammatory monocyte-derived myeloid cells. Tumor-associated endothelial cells were characterized by distinct gene expression profiles. A spectrum of vascular smooth muscle cells and pericytes predominated the stromal microenvironment. We found a small proportion of myofibroblasts exhibiting features reminiscent of cancer-associated fibroblasts. Stromal and immune cells exhibited potential paracrine interactions which may shape the microenvironment via NOTCH, VEGF, TGFβ and JAK/STAT signaling. Moreover, single-cell gene signatures of pericytes and myofibroblasts demonstrated prognostic value in bulk gene expression data.Here, we provide first comprehensive insights into the cellular composition and single-cell gene expression profiles in lung carcinoids, demonstrating the non-inflammatory and vessel-rich nature of their tumor microenvironment, and outlining relevant intercellular interactions which could serve as future therapeutic targets.

High-throughput single-cell RNA-seq data imputation and characterization with surrogate-assisted automated deep learning

2021 ◽  
Author(s):  
Xiangtao Li ◽  
Shaochuan Li ◽  
Lei Huang ◽  
Shixiong Zhang ◽  
Ka-chun Wong
Keyword(s):  
Gene Expression ◽  
Neural Networks ◽  
Single Cell ◽  
Deep Neural Networks ◽  
Expression Profiles ◽  
Marker Gene ◽  
Gene Expression Profiles ◽  
Underlying Mechanisms ◽  
Cell Data ◽  
Gene Expression Levels

Abstract Single-cell RNA sequencing (scRNA-seq) technologies have been heavily developed to probe gene expression profiles at single-cell resolution. Deep imputation methods have been proposed to address the related computational challenges (e.g. the gene sparsity in single-cell data). In particular, the neural architectures of those deep imputation models have been proven to be critical for performance. However, deep imputation architectures are difficult to design and tune for those without rich knowledge of deep neural networks and scRNA-seq. Therefore, Surrogate-assisted Evolutionary Deep Imputation Model (SEDIM) is proposed to automatically design the architectures of deep neural networks for imputing gene expression levels in scRNA-seq data without any manual tuning. Moreover, the proposed SEDIM constructs an offline surrogate model, which can accelerate the computational efficiency of the architectural search. Comprehensive studies show that SEDIM significantly improves the imputation and clustering performance compared with other benchmark methods. In addition, we also extensively explore the performance of SEDIM in other contexts and platforms including mass cytometry and metabolic profiling in a comprehensive manner. Marker gene detection, gene ontology enrichment and pathological analysis are conducted to provide novel insights into cell-type identification and the underlying mechanisms. The source code is available at https://github.com/li-shaochuan/SEDIM.

scholarly journals Microbial single-cell RNA sequencing by split-pool barcoding

Science ◽  
2020 ◽  
Vol 371 (6531) ◽  
pp. eaba5257 ◽  
Author(s):  
Anna Kuchina ◽  
Leandra M. Brettner ◽  
Luana Paleologu ◽  
Charles M. Roco ◽  
Alexander B. Rosenberg ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
High Throughput ◽  
Single Cell Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Growth Stages ◽  
High Throughput Analysis ◽  
Single Cell Rna Sequencing

Single-cell RNA sequencing (scRNA-seq) has become an essential tool for characterizing gene expression in eukaryotes, but current methods are incompatible with bacteria. Here, we introduce microSPLiT (microbial split-pool ligation transcriptomics), a high-throughput scRNA-seq method for Gram-negative and Gram-positive bacteria that can resolve heterogeneous transcriptional states. We applied microSPLiT to >25,000 Bacillus subtilis cells sampled at different growth stages, creating an atlas of changes in metabolism and lifestyle. We retrieved detailed gene expression profiles associated with known, but rare, states such as competence and prophage induction and also identified unexpected gene expression states, including the heterogeneous activation of a niche metabolic pathway in a subpopulation of cells. MicroSPLiT paves the way to high-throughput analysis of gene expression in bacterial communities that are otherwise not amenable to single-cell analysis, such as natural microbiota.

scholarly journals Aortic heterogeneity across segments and under high fat/salt/glucose conditions at the single-cell level

2020 ◽  
Vol 7 (5) ◽  
pp. 881-896 ◽  
Author(s):  
Dongxu He ◽  
Aiqin Mao ◽  
Chang-Bo Zheng ◽  
Hao Kan ◽  
Ka Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
The Body ◽  
Dietary Salt ◽  
High Fat ◽  
High Blood Glucose ◽  
Thoracic And Abdominal

Abstract The aorta, with ascending, arch, thoracic and abdominal segments, responds to the heartbeat, senses metabolites and distributes blood to all parts of the body. However, the heterogeneity across aortic segments and how metabolic pathologies change it are not known. Here, a total of 216 612 individual cells from the ascending aorta, aortic arch, and thoracic and abdominal segments of mouse aortas under normal conditions or with high blood glucose levels, high dietary salt, or high fat intake were profiled using single-cell RNA sequencing. We generated a compendium of 10 distinct cell types, mainly endothelial (EC), smooth muscle (SMC), stromal and immune cells. The distributions of the different cells and their intercommunication were influenced by the hemodynamic microenvironment across anatomical segments, and the spatial heterogeneity of ECs and SMCs may contribute to differential vascular dilation and constriction that were measured by wire myography. Importantly, the composition of aortic cells, their gene expression profiles and their regulatory intercellular networks broadly changed in response to high fat/salt/glucose conditions. Notably, the abdominal aorta showed the most dramatic changes in cellular composition, particularly involving ECs, fibroblasts and myeloid cells with cardiovascular risk factor-related regulons and gene expression networks. Our study elucidates the nature and range of aortic cell diversity, with implications for the treatment of metabolic pathologies.

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