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Siranush Sarkizova

Bio: Siranush Sarkizova is an academic researcher from Broad Institute. The author has contributed to research in topics: Human leukocyte antigen & Biology. The author has an hindex of 6, co-authored 11 publications receiving 2119 citations.

Papers
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Journal ArticleDOI
21 Apr 2017-Science
TL;DR: This refined analysis has identified, among others, a previously unknown dendritic cell population that potently activates T cells and reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability.
Abstract: INTRODUCTION Dendritic cells (DCs) and monocytes consist of multiple specialized subtypes that play a central role in pathogen sensing, phagocytosis, and antigen presentation. However, their identities and interrelationships are not fully understood, as these populations have historically been defined by a combination of morphology, physical properties, localization, functions, developmental origins, and expression of a restricted set of surface markers. RATIONALE To overcome this inherently biased strategy for cell identification, we performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells. This single-cell profiling strategy and unbiased genomic classification, together with follow-up profiling and functional and phenotypic characterization of prospectively isolated subsets, led us to identify and validate six DC subtypes and four monocyte subtypes, and thus revise the taxonomy of these cells. RESULTS Our study reveals: 1) A new DC subset, representing 2 to 3% of the DC populations across all 10 donors tested, characterized by the expression of AXL , SIGLEC1 , and SIGLEC6 antigens, named AS DCs. The AS DC population further divides into two populations captured in the traditionally defined plasmacytoid DC (pDC) and CD1C + conventional DC (cDC) gates. This split is further reflected through AS DC gene expression signatures spanning a spectrum between cDC-like and pDC-like gene sets. Although AS DCs share properties with pDCs, they more potently activate T cells. This discovery led us to reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability. 2) A new subdivision within the CD1C + DC subset: one defined by a major histocompatibility complex class II–like gene set and one by a CD14 + monocyte–like prominent gene set. These CD1C + DC subsets, which can be enriched by combining CD1C with CD32B, CD36, and CD163 antigens, can both potently induce T cell proliferation. 3) The existence of a circulating and dividing cDC progenitor giving rise to CD1C + and CLEC9A + DCs through in vitro differentiation assays. This blood precursor is defined by the expression of CD100 + CD34 int and observed at a frequency of ~0.02% of the LIN – HLA-DR + fraction. 4) Two additional monocyte populations: one expressing classical monocyte genes and cytotoxic genes, and the other with unknown functions. 5) Evidence for a relationship between blastic plasmacytoid DC neoplasia (BPDCN) cells and healthy DCs. CONCLUSION Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease. The discovery of AS DCs within the traditionally defined pDC population explains many of the cDC properties previously assigned to pDCs, highlighting the need to revisit the definition of pDCs. Furthermore, the discovery of blood cDC progenitors represents a new therapeutic target readily accessible in the bloodstream for manipulation, as well as a new source for better in vitro DC generation. Although the current results focus on DCs and monocytes, a similar strategy can be applied to build a comprehensive human immune cell atlas.

1,468 citations

01 Apr 2017
TL;DR: In this paper, the authors performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells, which led them to identify and validate six Dendritic cells (DCs) and four monocyte subtypes.
Abstract: INTRODUCTION Dendritic cells (DCs) and monocytes consist of multiple specialized subtypes that play a central role in pathogen sensing, phagocytosis, and antigen presentation. However, their identities and interrelationships are not fully understood, as these populations have historically been defined by a combination of morphology, physical properties, localization, functions, developmental origins, and expression of a restricted set of surface markers. RATIONALE To overcome this inherently biased strategy for cell identification, we performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells. This single-cell profiling strategy and unbiased genomic classification, together with follow-up profiling and functional and phenotypic characterization of prospectively isolated subsets, led us to identify and validate six DC subtypes and four monocyte subtypes, and thus revise the taxonomy of these cells. RESULTS Our study reveals: 1) A new DC subset, representing 2 to 3% of the DC populations across all 10 donors tested, characterized by the expression of AXL , SIGLEC1 , and SIGLEC6 antigens, named AS DCs. The AS DC population further divides into two populations captured in the traditionally defined plasmacytoid DC (pDC) and CD1C + conventional DC (cDC) gates. This split is further reflected through AS DC gene expression signatures spanning a spectrum between cDC-like and pDC-like gene sets. Although AS DCs share properties with pDCs, they more potently activate T cells. This discovery led us to reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability. 2) A new subdivision within the CD1C + DC subset: one defined by a major histocompatibility complex class II–like gene set and one by a CD14 + monocyte–like prominent gene set. These CD1C + DC subsets, which can be enriched by combining CD1C with CD32B, CD36, and CD163 antigens, can both potently induce T cell proliferation. 3) The existence of a circulating and dividing cDC progenitor giving rise to CD1C + and CLEC9A + DCs through in vitro differentiation assays. This blood precursor is defined by the expression of CD100 + CD34 int and observed at a frequency of ~0.02% of the LIN – HLA-DR + fraction. 4) Two additional monocyte populations: one expressing classical monocyte genes and cytotoxic genes, and the other with unknown functions. 5) Evidence for a relationship between blastic plasmacytoid DC neoplasia (BPDCN) cells and healthy DCs. CONCLUSION Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease. The discovery of AS DCs within the traditionally defined pDC population explains many of the cDC properties previously assigned to pDCs, highlighting the need to revisit the definition of pDCs. Furthermore, the discovery of blood cDC progenitors represents a new therapeutic target readily accessible in the bloodstream for manipulation, as well as a new source for better in vitro DC generation. Although the current results focus on DCs and monocytes, a similar strategy can be applied to build a comprehensive human immune cell atlas.

1,306 citations

Journal ArticleDOI
TL;DR: In this paper, the authors evaluated the long-term effects of personal neoantigen vaccines and found that they can induce durable and specific memory T cell clones that have cytotoxic gene signatures and can diversify to include non-vaccine specificities.
Abstract: Personal neoantigen vaccines have been envisioned as an effective approach to induce, amplify and diversify antitumor T cell responses. To define the long-term effects of such a vaccine, we evaluated the clinical outcome and circulating immune responses of eight patients with surgically resected stage IIIB/C or IVM1a/b melanoma, at a median of almost 4 years after treatment with NeoVax, a long-peptide vaccine targeting up to 20 personal neoantigens per patient ( NCT01970358 ). All patients were alive and six were without evidence of active disease. We observed long-term persistence of neoantigen-specific T cell responses following vaccination, with ex vivo detection of neoantigen-specific T cells exhibiting a memory phenotype. We also found diversification of neoantigen-specific T cell clones over time, with emergence of multiple T cell receptor clonotypes exhibiting distinct functional avidities. Furthermore, we detected evidence of tumor infiltration by neoantigen-specific T cell clones after vaccination and epitope spreading, suggesting on-target vaccine-induced tumor cell killing. Personal neoantigen peptide vaccines thus induce T cell responses that persist over years and broaden the spectrum of tumor-specific cytotoxicity in patients with melanoma. Personalized neoantigen vaccination in patients with melanoma elicits durable and specific memory T cell clones that have cytotoxic gene signatures and can diversify to include nonvaccine neoantigen specificities.

193 citations

Journal ArticleDOI
22 Jul 2021-Cell
TL;DR: This article reported the first HLA-I immunopeptidome of SARS-CoV-2 in two cell lines at different times post infection using mass spectrometry and found HLAI peptides derived not only from canonical open reading frames (ORFs) but also from internal out-of-frame ORFs in spike and nucleocapsid not captured by current vaccines.

71 citations

Journal ArticleDOI
TL;DR: It is found that disabled 2 mitogen-responsive phosphoprotein (DAB2) is highly expressed in tumor-infiltrating TAMs and its genetic ablation significantly impairs lung metastasis formation, identifying DAB2 as potential prognostic biomarker for cancer patient stratification.
Abstract: Tumor-associated macrophages (TAM) are regulators of extracellular matrix (ECM) remodeling and metastatic progression, the main cause of cancer-associated death. We found that disabled homolog 2 mitogen-responsive phosphoprotein (DAB2) is highly expressed in tumor-infiltrating TAMs and that its genetic ablation significantly impairs lung metastasis formation. DAB2-expressing TAMs, mainly localized along the tumor-invasive front, participate in integrin recycling, ECM remodeling, and directional migration in a tridimensional matrix. DAB2+ macrophages escort the invasive dissemination of cancer cells by a mechanosensing pathway requiring the transcription factor YAP. In human lobular breast and gastric carcinomas, DAB2+ TAMs correlated with a poor clinical outcome, identifying DAB2 as potential prognostic biomarker for stratification of patients with cancer. DAB2 is therefore central for the prometastatic activity of TAMs. SIGNIFICANCE: DAB2 expression in macrophages is essential for metastasis formation but not primary tumor growth. Mechanosensing cues, activating the complex YAP-TAZ, regulate DAB2 in macrophages, which in turn controls integrin recycling and ECM remodeling in 3-D tissue matrix. The presence of DAB2+ TAMs in patients with cancer correlates with worse prognosis.This article is highlighted in the In This Issue feature, p. 1611.

33 citations


Cited by
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Journal ArticleDOI
TL;DR: An analytical strategy for integrating scRNA-seq data sets based on common sources of variation is introduced, enabling the identification of shared populations across data sets and downstream comparative analysis.
Abstract: Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.

7,741 citations

Journal ArticleDOI
24 Jun 2021-Cell
TL;DR: Weighted-nearest neighbor analysis as mentioned in this paper is an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities.

3,369 citations

Posted ContentDOI
12 Oct 2020-bioRxiv
TL;DR: ‘weighted-nearest neighbor’ analysis is introduced, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities.
Abstract: The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce ‘weighted-nearest neighbor’ analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity. Availability Installation instructions, documentation, tutorials, and CITE-seq datasets are available at http://www.satijalab.org/seurat

2,924 citations

Journal ArticleDOI
18 Oct 2018-Nature
TL;DR: A compendium of single-cell transcriptomic data from the model organism Mus musculus that comprises more than 100,000 cells from 20 organs and tissues is presented, representing a new resource for cell biology and enabling the direct and controlled comparison of gene expression in cell types that are shared between tissues.
Abstract: Here we present a compendium of single-cell transcriptomic data from the model organism Mus musculus that comprises more than 100,000 cells from 20 organs and tissues. These data represent a new resource for cell biology, reveal gene expression in poorly characterized cell populations and enable the direct and controlled comparison of gene expression in cell types that are shared between tissues, such as T lymphocytes and endothelial cells from different anatomical locations. Two distinct technical approaches were used for most organs: one approach, microfluidic droplet-based 3'-end counting, enabled the survey of thousands of cells at relatively low coverage, whereas the other, full-length transcript analysis based on fluorescence-activated cell sorting, enabled the characterization of cell types with high sensitivity and coverage. The cumulative data provide the foundation for an atlas of transcriptomic cell biology.

1,757 citations

Journal ArticleDOI
Aviv Regev1, Aviv Regev2, Aviv Regev3, Sarah A. Teichmann4, Sarah A. Teichmann5, Sarah A. Teichmann6, Eric S. Lander7, Eric S. Lander1, Eric S. Lander2, Ido Amit8, Christophe Benoist7, Ewan Birney4, Bernd Bodenmiller9, Bernd Bodenmiller4, Peter J. Campbell5, Peter J. Campbell6, Piero Carninci5, Menna R. Clatworthy10, Hans Clevers11, Bart Deplancke12, Ian Dunham4, James Eberwine13, Roland Eils14, Roland Eils15, Wolfgang Enard16, Andrew Farmer, Lars Fugger17, Berthold Göttgens5, Nir Hacohen7, Nir Hacohen1, Muzlifah Haniffa18, Martin Hemberg6, Seung K. Kim19, Paul Klenerman20, Paul Klenerman17, Arnold R. Kriegstein21, Ed S. Lein22, Sten Linnarsson23, Emma Lundberg24, Emma Lundberg19, Joakim Lundeberg24, Partha P. Majumder, John C. Marioni5, John C. Marioni6, John C. Marioni4, Miriam Merad25, Musa M. Mhlanga26, Martijn C. Nawijn27, Mihai G. Netea28, Garry P. Nolan19, Dana Pe'er29, Anthony Phillipakis1, Chris P. Ponting30, Stephen R. Quake19, Wolf Reik6, Wolf Reik5, Wolf Reik31, Orit Rozenblatt-Rosen1, Joshua R. Sanes7, Rahul Satija32, Ton N. Schumacher33, Alex K. Shalek1, Alex K. Shalek34, Alex K. Shalek2, Ehud Shapiro8, Padmanee Sharma35, Jay W. Shin, Oliver Stegle4, Michael R. Stratton6, Michael J. T. Stubbington6, Fabian J. Theis36, Matthias Uhlen37, Matthias Uhlen24, Alexander van Oudenaarden11, Allon Wagner38, Fiona M. Watt39, Jonathan S. Weissman, Barbara J. Wold40, Ramnik J. Xavier, Nir Yosef38, Nir Yosef34, Human Cell Atlas Meeting Participants 
05 Dec 2017-eLife
TL;DR: An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease.
Abstract: The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

1,391 citations