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      Transcriptional Profiling of Human Dendritic Cell Populations and Models - Unique Profiles of In Vitro Dendritic Cells and Implications on Functionality and Applicability

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          Abstract

          Background

          Dendritic cells (DCs) comprise heterogeneous populations of cells, which act as central orchestrators of the immune response. Applicability of primary DCs is restricted due to their scarcity and therefore DC models are commonly employed in DC-based immunotherapy strategies and in vitro tests assessing DC function. However, the interrelationship between the individual in vitro DC models and their relative resemblance to specific primary DC populations remain elusive.

          Objective

          To describe and assess functionality and applicability of the available in vitro DC models by using a genome-wide transcriptional approach.

          Methods

          Transcriptional profiling was performed with four commonly used in vitro DC models (MUTZ-3-DCs, monocyte-derived DCs, CD34-derived DCs and Langerhans cells (LCs)) and nine primary DC populations (dermal DCs, LCs, blood and tonsillar CD123 +, CD1c + and CD141 + DCs, and blood CD16 + DCs).

          Results

          Principal Component Analysis showed that transcriptional profiles of each in vitro DC model most closely resembled CD1c + and CD141 + tonsillar myeloid DCs (mDCs) among primary DC populations. Thus, additional differentiation factors may be required to generate model DCs that more closely resemble other primary DC populations. Also, no model DC stood out in terms of primary DC resemblance. Nevertheless, hierarchical clustering showed clusters of differentially expressed genes among individual DC models as well as primary DC populations. Furthermore, model DCs were shown to differentially express immunologically relevant transcripts and transcriptional signatures identified for each model DC included several immune-associated transcripts.

          Conclusion

          The unique transcriptional profiles of in vitro DC models suggest distinct functionality in immune applications. The presented results will aid in the selection of an appropriate DC model for in vitro assays and assist development of DC-based immunotherapy.

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          Most cited references63

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          Taking dendritic cells into medicine.

          Dendritic cells (DCs) orchestrate a repertoire of immune responses that bring about resistance to infection and silencing or tolerance to self. In the settings of infection and cancer, microbes and tumours can exploit DCs to evade immunity, but DCs also can generate resistance, a capacity that is readily enhanced with DC-targeted vaccines. During allergy, autoimmunity and transplant rejection, DCs instigate unwanted responses that cause disease, but, again, DCs can be harnessed to silence these conditions with novel therapies. Here we present some medical implications of DC biology that account for illness and provide opportunities for prevention and therapy.
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            Dendritic Cells Induce Peripheral T Cell Unresponsiveness under Steady State Conditions in Vivo

            Dendritic cells (DCs) have the capacity to initiate immune responses, but it has been postulated that they may also be involved in inducing peripheral tolerance. To examine the function of DCs in the steady state we devised an antigen delivery system targeting these specialized antigen presenting cells in vivo using a monoclonal antibody to a DC-restricted endocytic receptor, DEC-205. Our experiments show that this route of antigen delivery to DCs is several orders of magnitude more efficient than free peptide in complete Freund's adjuvant (CFA) in inducing T cell activation and cell division. However, T cells activated by antigen delivered to DCs are not polarized to produce T helper type 1 cytokine interferon γ and the activation response is not sustained. Within 7 d the number of antigen-specific T cells is severely reduced, and the residual T cells become unresponsive to systemic challenge with antigen in CFA. Coinjection of the DC-targeted antigen and anti-CD40 agonistic antibody changes the outcome from tolerance to prolonged T cell activation and immunity. We conclude that in the absence of additional stimuli DCs induce transient antigen-specific T cell activation followed by T cell deletion and unresponsiveness.
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              Singular value decomposition for genome-wide expression data processing and modeling.

              We describe the use of singular value decomposition in transforming genome-wide expression data from genes x arrays space to reduced diagonalized "eigengenes" x "eigenarrays" space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                14 January 2013
                : 8
                : 1
                : e52875
                Affiliations
                [1 ]Department of Immunotechnology, Lund University, Lund, Sweden
                [2 ]Environmental Risk and Health Unit, Flemish Institute for Technological Research (VITO), Mol, Belgium
                [3 ]Department of Medical Oncology, VU University Medical Center, Amsterdam, The Netherlands
                [4 ]Department of Dermatology, VU University Medical Center, Amsterdam, The Netherlands
                University of Bergen, Norway
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: KL ML. Performed the experiments: KL ML AA IN SS. Analyzed the data: KL ML AA. Contributed reagents/materials/analysis tools: KL AA IN SS TDG SG ML . Wrote the paper: KL AA IN SS TDG SG ML.

                Article
                PONE-D-12-26955
                10.1371/journal.pone.0052875
                3544800
                23341914
                0ab73240-eb57-4f26-ae6d-5df6c7d2da93
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 4 September 2012
                : 22 November 2012
                Page count
                Pages: 15
                Funding
                This work was supported by grants from the Swedish Research Council (2008-743-57748-66, http://www.vr.se) and the European Commission as part of the Integrated project ‘Novel Testing Strategies for in vitro Assessment of Allergens; Sens-it-iv’ (LSHB-CT-2005-018681, http://www.sens-it-iv.eu). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Genomics
                Genome Analysis Tools
                Transcriptomes
                Genome Expression Analysis
                Immunology
                Immune Cells
                Antigen-Presenting Cells
                Immunity
                Immune Activation
                Immune Tolerance
                Immunoregulation
                Immunotherapy
                Innate Immunity
                Immunologic Techniques
                Immunoassays
                Allergy and Hypersensitivity
                Antigen Processing and Recognition
                Immunomodulation

                Uncategorized
                Uncategorized

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