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      LncRNA-mRNA Co-Expression Analysis Identifies AL133346.1/CCN2 as Biomarkers in Pediatric B-Cell Acute Lymphoblastic Leukemia

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          Abstract

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          Dysregulation of noncoding RNAs has been described in numerous types of cancers and it has been associated with oncogenic or tumor suppressor activities. However, the signature of clinically relevant noncoding RNAs in pediatric B-cell acute lymphoblastic leukemia is still poorly understood. In a search for long non-coding RNAs that characterize pediatric B-cell acute lymphoblastic leukemia, we found that the long non-coding RNA AL133346.1 and a neighbouring protein-coding mRNA (CCN2) were significantly over-expressed in leukemia samples compared to healthy bone marrow. Survival analysis showed that patients with high CCN2 expression had a significantly better prognosis. These data suggest that AL133346.1/CCN2 could be useful for discriminating subtypes of leukemia and that CCN2 expression could predict the prognosis of pediatric patients with B-cell acute lymphoblastic leukemia.

          Abstract

          Pediatric acute B-cell lymphoblastic leukemia (B-ALL) constitutes a heterogeneous and aggressive neoplasia in which new targeted therapies are required. Long non-coding RNAs have recently emerged as promising disease-specific biomarkers for the clinic. Here, we identified pediatric B-ALL-specific lncRNAs and associated mRNAs by comparing the transcriptomic signatures of tumoral and non-tumoral samples. We identified 48 lncRNAs that were differentially expressed between pediatric B-ALL and healthy bone marrow samples. The most relevant lncRNA/mRNA pair was AL133346.1/CCN2 (previously known as RP11-69I8.3/CTGF), whose expression was positively correlated and increased in B-ALL samples. Their differential expression pattern and their strong correlation were validated in external B-ALL datasets (Therapeutically Applicable Research to Generate Effective Treatments, Cancer Cell Line Encyclopedia). Survival curve analysis demonstrated that patients with “high” expression levels of CCN2 had higher overall survival than those with “low” levels ( p = 0.042), and this gene might be an independent prognostic biomarker in pediatric B-ALL. These findings provide one of the first detailed descriptions of lncRNA expression profiles in pediatric B-ALL and indicate that these potential biomarkers could help in the classification of leukemia subtypes and that CCN2 expression could predict the survival outcome of pediatric B-cell acute lymphoblastic leukemia patients.

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          Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

          Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr.
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            Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool

            Background System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes/proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries. While many enrichment analysis tools and gene-set libraries databases have been developed, there is still room for improvement. Results Here, we present Enrichr, an integrative web-based and mobile software application that includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. We applied Enrichr to analyze nine cancer cell lines by comparing their enrichment signatures to the enrichment signatures of matched normal tissues. We observed a common pattern of up regulation of the polycomb group PRC2 and enrichment for the histone mark H3K27me3 in many cancer cell lines, as well as alterations in Toll-like receptor and interlukin signaling in K562 cells when compared with normal myeloid CD33+ cells. Such analyses provide global visualization of critical differences between normal tissues and cancer cell lines but can be applied to many other scenarios. Conclusions Enrichr is an easy to use intuitive enrichment analysis web-based tool providing various types of visualization summaries of collective functions of gene lists. Enrichr is open source and freely available online at: http://amp.pharm.mssm.edu/Enrichr.
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              REVIGO Summarizes and Visualizes Long Lists of Gene Ontology Terms

              Outcomes of high-throughput biological experiments are typically interpreted by statistical testing for enriched gene functional categories defined by the Gene Ontology (GO). The resulting lists of GO terms may be large and highly redundant, and thus difficult to interpret. REVIGO is a Web server that summarizes long, unintelligible lists of GO terms by finding a representative subset of the terms using a simple clustering algorithm that relies on semantic similarity measures. Furthermore, REVIGO visualizes this non-redundant GO term set in multiple ways to assist in interpretation: multidimensional scaling and graph-based visualizations accurately render the subdivisions and the semantic relationships in the data, while treemaps and tag clouds are also offered as alternative views. REVIGO is freely available at http://revigo.irb.hr/.
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                Author and article information

                Journal
                Cancers (Basel)
                Cancers (Basel)
                cancers
                Cancers
                MDPI
                2072-6694
                17 December 2020
                December 2020
                : 12
                : 12
                : 3803
                Affiliations
                [1 ]Department of Biochemistry and Molecular Biology III and Immunology, University of Granada, Av. de la Investigación 11, 18016 Granada, Spain; mcuadros@ 123456ugr.es (M.C.); djgargar@ 123456ugr.es (D.J.G.); maria.rodriguez@ 123456genyo.es (M.I.R.); fruizc@ 123456ugr.es (F.R.-C.)
                [2 ]GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, Av. de la Ilustración 114, 18016 Granada, Spain; alande@ 123456ugr.es (A.A.); amam@ 123456ugr.es (A.M.A.); isabel.fernandezcoira@ 123456unige.ch (I.F.C.); carlos.balinas@ 123456genyo.es (C.B.-G.); paola.peinado@ 123456genyo.es (P.P.); carlosalvarez@ 123456ugr.es (J.C.Á.-P.)
                [3 ]Instituto de Investigación Biosanitaria (ibs. Granada), Av. Fuerzas Armadas 2, 18014 Granada, Spain
                [4 ]Department of Biochemistry and Molecular Biology I, University of Granada, Av. de Fuente Nueva S/N, 18071 Granada, Spain
                [5 ]Department of Clinical Analysis and Immunology, UGC Laboratorio Clínico, University Hospital Virgen de las Nieves, 18014 Granada, Spain
                [6 ]Hematology Laboratory, Institut de Recerca Hospital Sant Joan de Déu, 08950 Barcelona, Spain; mcamos@ 123456hsjdbcn.org
                [7 ]Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), ISCIII, 28029 Madrid, Spain
                [8 ]Leukemia and Other Pediatric Hemopathies, Developmental Tumors Biology Group, Institut de Recerca Hospital Sant Joan de Déu, 08950 Barcelona, Spain
                [9 ]Hematology Laboratory, Universitary Regional Hospital, Av. de Carlos Haya, 29010 Málaga, Spain; a.jimenez.velasco@ 123456gmail.com
                Author notes
                [* ]Correspondence: pedromedina@ 123456ugr.es ; Tel.: +34-958-243-252
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0001-5611-534X
                https://orcid.org/0000-0001-9042-8964
                https://orcid.org/0000-0002-5995-2968
                https://orcid.org/0000-0003-3368-4691
                https://orcid.org/0000-0001-6396-311X
                https://orcid.org/0000-0002-2247-3293
                https://orcid.org/0000-0002-7834-7093
                Article
                cancers-12-03803
                10.3390/cancers12123803
                7765782
                33348573
                f591c1b4-491e-4647-abae-035329dcbe7d
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 02 November 2020
                : 15 December 2020
                Categories
                Communication

                ctgf,ccn2,al133346.1,lncrna expression,biomarker,pediatric b-all

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