Poster: MM-253: Single Cell Multi-Omic Analysis And Immune Cell Type Profiling Of Multiple Myeloma With t(4;14)

AbstractSince the outcome of treatments, particularly immunotherapeutic interventions, depends on the tumor immune micro-environment (TIM), several experimental and computational tools such as flow cytometry, immunohistochemistry, and digital cytometry have been developed and utilized to classify TIM variations. In this project, we identify immune pattern of clear cell renal cell carcinomas (ccRCC) by estimating the percentage of each immune cell type in 526 renal tumors using the new powerful technique of digital cytometry. The results, which are in agreement with the results of a large-scale mass cytometry analysis, show that the most frequent immune cell types in ccRCC tumors are CD8+ T-cells, macrophages, and CD4+ T-cells. Saliently, unsupervised clustering of ccRCC primary tumors based on their relative number of immune cells indicates the existence of four distinct groups of ccRCC tumors. Tumors in the first group consist of approximately the same numbers of macrophages and CD8+ T-cells and and a slightly smaller number of CD4+ T cells than CD8+ T cells, while tumors in the second group have a significantly high number of macrophages compared to any other immune cell type (P-value $$<0.01$$ < 0.01 ). The third group of ccRCC tumors have a significantly higher number of CD8+ T-cells than any other immune cell type (P-value $$<0.01$$ < 0.01 ), while tumors in the group 4 have approximately the same numbers of macrophages and CD4+ T-cells and a significantly smaller number of CD8+ T-cells than CD4+ T-cells (P-value $$<0.01$$ < 0.01 ). Moreover, there is a high positive correlation between the expression levels of IFNG and PDCD1 and the percentage of CD8+ T-cells, and higher stage and grade of tumors have a substantially higher percentage of CD8+ T-cells. Furthermore, the primary tumors of patients, who are tumor free at the last time of follow up, have a significantly higher percentage of mast cells (P-value $$<0.01$$ < 0.01 ) compared to the patients with tumors for all groups of tumors except group 3.

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Discovery of New Immune Cell Type May Unlock Strategies against Neurological Disorders and CNS Damage

Genetic Engineering & Biotechnology News ◽

10.1089/gen.40.12.02 ◽

2020 ◽

Vol 40 (12) ◽

pp. 8-9

Keyword(s):

Neurological Disorders ◽

Immune Cell ◽

Cell Type ◽

Immune Cell Type

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Location of tumor affects local and distant immune cell type and number

Immunity Inflammation and Disease ◽

10.1002/iid3.144 ◽

2017 ◽

Vol 5 (1) ◽

pp. 85-94 ◽

Cited By ~ 7

Author(s):

Jonathan A. Hensel ◽

Vinayak Khattar ◽

Reading Ashton ◽

Carnellia Lee ◽

Gene P. Siegal ◽

...

Keyword(s):

Immune Cell ◽

Cell Type ◽

Immune Cell Type

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Epigenetic Quantification of Circulating Immune Cells in Peripheral Blood of Triple-Negative Breast Cancer patients

10.21203/rs.3.rs-508197/v1 ◽

2021 ◽

Author(s):

Mehdi Manoochehri ◽

Thomas Hielscher ◽

Nasim Borhani ◽

Clarissa Gerhäuser ◽

Olivia Fletcher ◽

...

Keyword(s):

Breast Cancer ◽

T Cells ◽

Triple Negative Breast Cancer ◽

Immune Cells ◽

Triple Negative ◽

Immune Cell ◽

Nk Cell ◽

Cell Type ◽

Cell Ratio ◽

Immune Cell Type

Abstract Background: A shift in the proportions of blood immune cells is a hallmark of cancer development. Here, we investigated whether methylation-derived immune cell type ratios and methylation-derived neutrophil-to-lymphocyte ratios (mdNLRs) are associated with triple-negative breast cancer (TNBC). Methods: Leukocyte subtype-specific un/methylated CpG sites were selected and methylation levels at these sites used as proxies for immune cell type proportions and mdNLR estimation in 231 TNBC cases and 231 age-matched controls. Data were validated using the Houseman deconvolution method. Additionally, the natural killer (NK) cell ratio was measured in a prospective sample set of 146 TNBC cases and 146 age-matched controls. Results: The mdNLRs were higher in TNBC cases compared with controls and associated with TNBC (odds ratio (OR) range (2.66-4.29), all Padj.<1e-04). A higher neutrophil ratio and lower ratios of NK cells, CD4+ T cells, CD8+ T cells, monocytes, and B cells were associated with TNBC. The strongest association was observed with decreased NK cell ratio (OR range (1.28-1.42), all Padj.<1e-04). The NK cell ratio was also significantly lower in pre-diagnostic samples of TNBC cases compared with controls (P=0.019).Conclusion: This immunomethylomic study shows that a shift in the ratios/proportions of leukocyte subtypes is associated with TNBC, with decreased NK cell showing the strongest association. These findings improve our knowledge of the role of the immune system in TNBC and point to the possibility of using NK cell level as a non-invasive molecular marker for TNBC risk assessment, early detection, and prevention.

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Integrated single-cell transcriptomics and epigenomics reveals strong germinal center-associated etiology of autoimmune risk loci

10.1101/2021.03.16.435578 ◽

2021 ◽

Author(s):

Hamish W King ◽

Kristen L Wells ◽

Zohar Shipony ◽

Arwa S Kathiria ◽

Lisa E Wagar ◽

...

Keyword(s):

Autoimmune Disease ◽

Single Cell ◽

Germinal Center ◽

Cell Activation ◽

Immune Cell ◽

Peripheral Tolerance ◽

B Cell Activation ◽

Cell Type ◽

Human Tonsil ◽

Regulatory Impact

The germinal center (GC) response is critical for both effective adaptive immunity and establishing peripheral tolerance by limiting auto-reactive B cells. Dysfunction in these processes can lead to defects in immune response to pathogens or contribute to autoimmune disease. To understand the gene regulatory principles underlying the GC response, we generated a single-cell transcriptomic and epigenomic atlas of the human tonsil, a widely studied and representative lymphoid tissue. We characterize diverse immune cell subsets and build a trajectory of dynamic gene expression and transcription factor activity during B cell activation, GC formation, and plasma cell differentiation. We subsequently leverage cell type-specific transcriptomic and epigenomic maps to interpret potential regulatory impact of genetic variants implicated in autoimmunity, revealing that many exhibit their greatest regulatory potential in GC cell populations. Together, these analyses provide a powerful new cell type-resolved resource for the interpretation of cellular and genetic causes underpinning autoimmune disease.

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Tumor Immune Microenvironment Clusters in Localized Prostate Adenocarcinoma: Prognostic Impact of Macrophage Enriched/Plasma Cell Non-enriched Subtypes

10.20944/preprints202005.0462.v1 ◽

2020 ◽

Author(s):

Neil K. Jairath ◽

Mark W. Farha ◽

Sudharsan Srinivasan ◽

Ruple Jairath ◽

Michael D. Green ◽

...

Keyword(s):

Prostate Cancer ◽

Plasma Cell ◽

Immune Cell ◽

Cox Regression ◽

M2 Macrophage ◽

Significant Heterogeneity ◽

Prognostic Impact ◽

Cell Type ◽

Immune Microenvironment ◽

Immune Cell Type

Background: Prostate cancer (PCa) is characterized by significant heterogeneity in its molecular, genomic, and immunologic characteristics. Methods: Whole transcriptome RNAseq data from The Cancer Genome Atlas of prostate adenocarcinomas (n=496) was utilized. The immune microenvironment was characterized using the CIBERSORTX tool to identify immune cell type composition. Unsupervised hierarchical clustering was performed based on immune cell type content. Analyses of progression-free survival (PFS), distant metastases, and overall survival (OS) were performed using Kaplan-Meier estimates and Cox-regression multivariable analyses. Results: Four immune clusters were identified, largely defined by plasma cell, CD4+ Memory Resting T Cells (CD4 MR), M0 and M2 macrophage content (CD4 MRHighPlasma CellHighM0LowM2Low, CD4 MRLowPlasma CellHighM0LowM2Low, CD4 MRHighPlasma CellLowM0HighM2Low, and CD4 MRHighPlasma CellLowM0LowM2High). The two macrophage-enriched/plasma cell non-enriched clusters (3&4) demonstrated worse PFS (HR 2.24, 95% CI 1.46–3.45, p=0.0002) than the clusters 1&2. No metastatic events occurred in the non-macrophage-enriched clusters. Comparing clusters 3 vs 4, in patients treated by surgery alone, cluster 3 had zero progression events (p<0.0001). However, cluster 3 patients had worse outcomes after post-operative radiotherapy (p=0.018). Conclusion: Distinct tumor immune clusters with a macrophage-enriched phenotype and reduced plasma cell enrichment independently characterize an aggressive phenotype in localized prostate cancer that may differentially respond to treatment.

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Comprehensive multi-omics single-cell data integration reveals greater heterogeneity in the human immune system

10.1101/2021.07.25.453651 ◽

2021 ◽

Author(s):

Congmin Xu ◽

Junkai Yang ◽

Astrid Kosters ◽

Benjamin R Babcock ◽

Peng Qiu ◽

...

Keyword(s):

Immune System ◽

Single Cell ◽

Immune Cell ◽

Cell Types ◽

Cell Receptor ◽

Surface Proteins ◽

Cell Type ◽

Human Immune System ◽

Receptor Repertoire ◽

Human Immune

Single-cell transcriptomics enables the definition of diverse human immune cell types across multiple tissue and disease contexts. Still, deeper biological understanding requires comprehensive integration of multiple single-cell omics (transcriptomic, proteomic, and cell receptor repertoire). To improve the identification of diverse cell types and the accuracy of cell-type classification in our multi-omics single-cell datasets, we developed SuPERR-seq, a novel analysis workflow to increase the resolution and accuracy of clustering and allow for the discovery and characterization of previously hidden cell subsets. We show that by incorporating information from cell-surface proteins and immunoglobulin transcript counts, we accurately remove cell doublets and prevent widespread cell-type misclassification. This approach uniquely improves the identification of heterogeneous cell types in the human immune system, including a novel subset of antibody-secreting cells in the bone marrow.

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Deciphering the evolution of vertebrate immune cell types with single-cell RNA-seq

10.7287/peerj.preprints.26858 ◽

2018 ◽

Author(s):

Santiago J Carmona ◽

David Gfeller

Keyword(s):

Single Cell ◽

Immune Cell ◽

Adaptive Immune System ◽

Cell Types ◽

Rna Seq ◽

Cell Type ◽

Recent Developments ◽

Species Specific ◽

Development And Validation ◽

Whole Transcriptome

Single-cell RNA-seq is revolutionizing our understanding of cell type heterogeneity in many fields of biology, ranging from neuroscience to cancer to immunology. In Immunology, one of the main promises of this approach is the ability to define cell types as clusters in the whole transcriptome space (i.e., without relying on specific surface markers), thereby providing an unbiased classification of immune cell types. So far, this technology has been mainly applied in mouse and human. However, technically it could be used for immune cell-type identification in any species without requiring the development and validation of species-specific antibodies for cell sorting. Here we review recent developments using single-cell RNA-seq to characterize immune cell populations in non-mammalian vertebrates, with a focus on zebrafish (Danio rerio). We advocate that single-cell RNA-seq technology is likely to provide key insights into our understanding of the evolution of the adaptive immune system.

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Deciphering the evolution of vertebrate immune cell types with single-cell RNA-seq

10.7287/peerj.preprints.26858v1 ◽

2018 ◽

Author(s):

Santiago J Carmona ◽

David Gfeller

Keyword(s):

Single Cell ◽

Immune Cell ◽

Adaptive Immune System ◽

Cell Types ◽

Rna Seq ◽

Cell Type ◽

Recent Developments ◽

Species Specific ◽

Development And Validation ◽

Whole Transcriptome

Single-cell RNA-seq is revolutionizing our understanding of cell type heterogeneity in many fields of biology, ranging from neuroscience to cancer to immunology. In Immunology, one of the main promises of this approach is the ability to define cell types as clusters in the whole transcriptome space (i.e., without relying on specific surface markers), thereby providing an unbiased classification of immune cell types. So far, this technology has been mainly applied in mouse and human. However, technically it could be used for immune cell-type identification in any species without requiring the development and validation of species-specific antibodies for cell sorting. Here we review recent developments using single-cell RNA-seq to characterize immune cell populations in non-mammalian vertebrates, with a focus on zebrafish (Danio rerio). We advocate that single-cell RNA-seq technology is likely to provide key insights into our understanding of the evolution of the adaptive immune system.

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