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      New miRNA Signature Heralds Human NK Cell Subsets at Different Maturation Steps: Involvement of miR-146a-5p in the Regulation of KIR Expression

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          Abstract

          Natural killer cells are cytotoxic innate lymphoid cells that play an important role for early host defenses against infectious pathogens and surveillance against tumor. In humans, NK cells may be divided in various subsets on the basis of the relative CD56 expression and of the low-affinity FcγRIIIA CD16. In particular, the two main NK cell subsets are represented by the CD56 bright/CD16 −/dim and the CD56 dim/CD16 bright NK cells. Experimental evidences indicate that CD56 bright and CD56 dim NK cells represent different maturative stages of the NK cell developmental pathway. We identified multiple miRNAs differentially expressed in CD56 bright/CD16 and CD56 dim/CD16 bright NK cells using both univariate and multivariate analyses. Among these, we found a few miRNAs with a consistent differential expression in the two NK cell subsets, and with an intermediate expression in the CD56 bright/CD16 dim NK cell subset, representing a transitional step of maturation of NK cells. These analyses allowed us to establish the existence of a miRNA signature able to efficiently discriminate the two main NK cell subsets regardless of their surface phenotype. In addition, by analyzing the putative targets of representative miRNAs we show that hsa-miR-146a-5p, may be involved in the regulation of killer Ig-like receptor (KIR) expression. These results contribute to a better understanding of the physiologic significance of miRNAs in the regulation of the development/function of human NK cells. Moreover, our results suggest that hsa-miR-146a-5p targeting, resulting in KIR down-regulation, may be exploited to generate/increment the effect of NK KIR-mismatching against HLA-class I + tumor cells and thus improve the NK-mediated anti-tumor activity.

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          Most cited references54

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          miRDB: an online resource for microRNA target prediction and functional annotations

          MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in many physiological and disease processes. One major challenge in miRNA studies is the identification of genes regulated by miRNAs. To this end, we have developed an online resource, miRDB (http://mirdb.org), for miRNA target prediction and functional annotations. Here, we describe recently updated features of miRDB, including 2.1 million predicted gene targets regulated by 6709 miRNAs. In addition to presenting precompiled prediction data, a new feature is the web server interface that allows submission of user-provided sequences for miRNA target prediction. In this way, users have the flexibility to study any custom miRNAs or target genes of interest. Another major update of miRDB is related to functional miRNA annotations. Although thousands of miRNAs have been identified, many of the reported miRNAs are not likely to play active functional roles or may even have been falsely identified as miRNAs from high-throughput studies. To address this issue, we have performed combined computational analyses and literature mining, and identified 568 and 452 functional miRNAs in humans and mice, respectively. These miRNAs, as well as associated functional annotations, are presented in the FuncMir Collection in miRDB.
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            Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites

            mirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.
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              HLA-E binds to natural killer cell receptors CD94/NKG2A, B and C.

              The protein HLA-E is a non-classical major histocompatibility complex (MHC) molecule of limited sequence variability. Its expression on the cell surface is regulated by the binding of peptides derived from the signal sequence of some other MHC class I molecules. Here we report the identification of ligands for HLA-E. We constructed tetramers in which recombinant HLA-E and beta2-microglobulin were refolded with an MHC leader-sequence peptide, biotinylated, and conjugated to phycoerythrin-labelled Extravidin. This HLA-E tetramer bound to natural killer (NK) cells and a small subset of T cells from peripheral blood. On transfectants, the tetramer bound to the CD94/NKG2A, CD94/NKGK2B and CD94/NKG2C NK cell receptors, but did not bind to the immunoglobulin family of NK cell receptors (KIR). Surface expression of HLA-E was enough to protect target cells from lysis by CD94/NKG2A+ NK-cell clones. A subset of HLA class I alleles has been shown to inhibit killing by CD94/NKG2A+ NK-cell clones. Only the HLA alleles that possess a leader peptide capable of upregulating HLA-E surface expression confer resistance to NK-cell-mediated lysis, implying that their action is mediated by HLA-E, the predominant ligand for the NK cell inhibitory receptor CD94/NKG2A.
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                15 October 2018
                2018
                : 9
                : 2360
                Affiliations
                [1] 1Department of Experimental Medicine (DIMES), University of Genoa , Genoa, Italy
                [2] 2Department of Informatic Bioengeneering, Robotic and System Engeneering, University of Genoa , Genoa, Italy
                [3] 3Centre of Excellence for Biomedical Research (CEBR), University of Genoa , Genoa, Italy
                [4] 4Immunology Operative Unit, IRCCS San Martino Polyclinical Hospital , Genoa, Italy
                [5] 5Department of Immunology, IRCCS Bambino Gesù Children's Hospital , Rome, Italy
                [6] 6Department of Integrated Oncological Therapies, IRCCS San Martino Polyclinical Hospital , Genoa, Italy
                [7] 7Department of Earth Science, Environment and Life (DISTAV), University of Genoa , Genoa, Italy
                Author notes

                Edited by: Alexander Rölle, Nationales Centrum für Tumorerkrankungen (NCT), Germany

                Reviewed by: Markus Uhrberg, Heinrich Heine Universität Düsseldorf, Germany; Jacques Zimmer, Luxembourg Institute of Health (LIH), Luxembourg

                *Correspondence: Simona Sivori simona.sivori@ 123456unige.it

                This article was submitted to NK and Innate Lymphoid Cell Biology, a section of the journal Frontiers in Immunology

                †These authors have contributed equally to this work

                ‡These authors share senior authorship

                §We dedicate this contribution to Alessandro Moretta who sadly passed away in mid February. We mourn his invaluable scientific insight and mentorship and, even more, his humanity, irony and smile

                Article
                10.3389/fimmu.2018.02360
                6196268
                30374356
                9699890e-4c41-4d7b-aecc-7ae4e975e811
                Copyright © 2018 Pesce, Squillario, Greppi, Loiacono, Moretta, Moretta, Sivori, Castagnola, Barla, Candiani and Marcenaro.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 31 July 2018
                : 24 September 2018
                Page count
                Figures: 8, Tables: 1, Equations: 0, References: 75, Pages: 18, Words: 11825
                Categories
                Immunology
                Original Research

                Immunology
                nk cells,mirna,kir,cd56bright,cd56dim,nk cell subsets,mirna microarrays,multivariate statistical analysis

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