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      In vivo NCL targeting affects breast cancer aggressiveness through miRNA regulation

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The regulatory protein nucleolin controls the expression of a subset of miRNAs involved in breast cancer progression and can be targeted to inhibit breast cancer growth in vivo.

          Abstract

          Numerous studies have described the altered expression and the causal role of microRNAs (miRNAs) in human cancer. However, to date, efforts to modulate miRNA levels for therapeutic purposes have been challenging to implement. Here we find that nucleolin (NCL), a major nucleolar protein, posttranscriptionally regulates the expression of a specific subset of miRNAs, including miR-21, miR-221, miR-222, and miR-103, that are causally involved in breast cancer initiation, progression, and drug resistance. We also show that NCL is commonly overexpressed in human breast tumors and that its expression correlates with that of NCL-dependent miRNAs. Finally, inhibition of NCL using guanosine-rich aptamers reduces the levels of NCL-dependent miRNAs and their target genes, thus reducing breast cancer cell aggressiveness both in vitro and in vivo. These findings illuminate a path to novel therapeutic approaches based on NCL-targeting aptamers for the modulation of miRNA expression in the treatment of breast cancer.

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          Aptamers as therapeutics

          Anthony Keefe, Supriya Pai, Andrew Ellington (2010)
          Key Points Aptamers are single-stranded oligonucleotides that fold into defined architectures and bind to targets such as proteins. In binding proteins they often inhibit protein–protein interactions and thereby may elicit therapeutic effects such as antagonism. Aptamers are discovered using SELEX (systematic evolution of ligands by exponential enrichment), a directed in vitro evolution technique in which large libraries of degenerate oligonucleotides are iteratively and alternately partitioned for target binding. They are then amplified enzymatically until functional sequences are identified by the sequencing of cloned individuals. For most therapeutic purposes, aptamers are truncated to reduce synthesis costs, modified at the sugars and capped at their termini to increase nuclease resistance, and conjugated to polyethylene glycol or another entity to reduce renal filtration rates. The first aptamer approved for a therapeutic application was pegaptanib sodium (Macugen; Pfizer/Eyetech), which was approved in 2004 by the US Food and Drug Administration for macular degeneration. Eight other aptamers are currently undergoing clinical evaluation for various haematology, oncology, ocular and inflammatory indications. Aptamers are ultimately chemically synthesized in a readily scalable process in which specific conjugation points are introduced with defined stereochemistry. Unlike some protein therapeutics, aptamers do not elicit antibodies, and because aptamers generally contain sugars modified at their 2′-positions, Toll-like receptor-mediated innate immune responses are also abrogated. As aptamers are oligonucleotides they can be readily assembled into supramolecular multi-component structures using hybridization. Owing to the fact that binding to appropriate cell-surface targets can lead to internalization, aptamers can also be used to deliver therapeutic cargoes such as small interfering RNA. Supramolecular assemblies of aptamers and delivery agents have already been demonstrated in vivo and may pave the way for further therapeutic strategies with this modality in the future.
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            Variance stabilization applied to microarray data calibration and to the quantification of differential expression.

            Wolfgang Huber, Anja von Heydebreck, Holger Sültmann … (2002)
            We introduce a statistical model for microarray gene expression data that comprises data calibration, the quantification of differential expression, and the quantification of measurement error. In particular, we derive a transformation h for intensity measurements, and a difference statistic Deltah whose variance is approximately constant along the whole intensity range. This forms a basis for statistical inference from microarray data, and provides a rational data pre-processing strategy for multivariate analyses. For the transformation h, the parametric form h(x)=arsinh(a+bx) is derived from a model of the variance-versus-mean dependence for microarray intensity data, using the method of variance stabilizing transformations. For large intensities, h coincides with the logarithmic transformation, and Deltah with the log-ratio. The parameters of h together with those of the calibration between experiments are estimated with a robust variant of maximum-likelihood estimation. We demonstrate our approach on data sets from different experimental platforms, including two-colour cDNA arrays and a series of Affymetrix oligonucleotide arrays.
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              MicroRNA control of signal transduction.

              Masafumi Inui, Graziano Martello, Stefano Piccolo (2010)
              MicroRNAs (miRNAs) are integral elements in the post-transcriptional control of gene expression. After the identification of hundreds of miRNAs, the challenge is now to understand their specific biological function. Signalling pathways are ideal candidates for miRNA-mediated regulation owing to the sharp dose-sensitive nature of their effects. Indeed, emerging evidence suggests that miRNAs affect the responsiveness of cells to signalling molecules such as transforming growth factor-beta, WNT, Notch and epidermal growth factor. As such, miRNAs serve as nodes of signalling networks that ensure homeostasis and regulate cancer, metastasis, fibrosis and stem cell biology.
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                Author and article information

                Journal
                Journal ID (nlm-ta): J Exp Med
                Journal ID (iso-abbrev): J. Exp. Med
                Journal ID (hwp): jem
                Title: The Journal of Experimental Medicine
                Publisher: The Rockefeller University Press
                ISSN (Print): 0022-1007
                ISSN (Electronic): 1540-9538
                Publication date (Print): 6 May 2013
                Volume: 210
                Issue: 5
                Pages: 951-968
                Affiliations
                [1 ]Division of Hematology and [2 ]Division of Oncology, Department of Internal Medicine ; and [3 ]Department of Molecular Virology, Immunology, and Medical Genetics; College of Medicine ; and [4 ]Comprehensive Cancer Center; The Ohio State University, Columbus, OH 43210
                [5 ]Laboratorio di ricerca pre-clinica/traslazionale, Istituto di Ricovero e Cura a Carattere Scientifico Centro di Riferimento Oncologico della Basilicata, 85028 Rionero in Vulture (PZ), Italy
                [6 ]Divisione di Ematologia, Università di Torino, Azienda Ospedaliero Universitaria San Giovanni Battista, 10149 Turin, Italy
                [7 ]Start-Up Unit, Department of Experimental Oncology, Tumor National Institute, 20133 Milan, Italy
                [8 ]Department of Clinical and Molecular Biomedicine, University of Catania, 95122 Catania, Italy
                [9 ]Phylogeny Inc., Powell, OH 43065
                [10 ]Data Mining for Analysis of Microarrays, Department of Morphology and Embryology, University of Ferrara, 44100 Ferrara, Italy
                Author notes
                CORRESPONDENCE Flavia Pichiorri: flavia.pichiorri@ 123456osumc.edu OR Carlo M. Croce: carlo.croce@ 123456osumc.edu

                F. Pichiorri and D. Palmieri contributed equally to this paper.

                Article
                Publisher ID: 20120950
                DOI: 10.1084/jem.20120950
                PMC ID: 3646490
                PubMed ID: 23610125
                SO-VID: 44a39588-eb8f-424a-97bf-a442130130a9
                Copyright © © 2013 Pichiorri et al.
                License:

                This article is distributed under the terms of an Attribution–Noncommercial–Share Alike–No Mirror Sites license for the first six months after the publication date (see http://www.rupress.org/terms). After six months it is available under a Creative Commons License (Attribution–Noncommercial–Share Alike 3.0 Unported license, as described at http://creativecommons.org/licenses/by-nc-sa/3.0/).

                History
                Date received : 4 May 2012
                Date accepted : 22 March 2013
                Categories
                Subject: Article

                ScienceOpen disciplines: Medicine
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                ScienceOpen disciplines: Medicine

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