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      Altered expression pattern of circular RNAs in primary and metastatic sites of epithelial ovarian carcinoma

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          Abstract

          Recently, a class of endogenous species of RNA called circular RNA (circRNA) has been shown to regulate gene expression in mammals and their role in cellular function is just beginning to be understood. To investigate the role of circRNAs in ovarian cancer, we performed paired-end RNA sequencing of primary sites, peritoneal and lymph node metastases from three patients with stage IIIC ovarian cancer. We developed an in-house computational pipeline to identify and characterize the circRNA expression from paired-end RNA-Seq libraries. This pipeline revealed thousands of circular isoforms in Epithelial Ovarian Carcinoma (EOC). These circRNAs are enriched for potentially effective miRNA seed matches. A significantly larger number of circRNAs are differentially expressed between tumor sites than mRNAs. Circular and linear expression exhibits an inverse trend for many cancer related pathways and signaling pathways like NFkB, PI3k/AKT and TGF-β typically activated for mRNA in metastases are inhibited for circRNA expression. Further, circRNAs show a more robust expression pattern across patients than mRNA forms indicating their suitability as biomarkers in highly heterogeneous cancer transcriptomes. The consistency of circular RNA expression may offer new candidates for cancer treatment and prognosis.

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          Most cited references38

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

            Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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              featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

              Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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                Author and article information

                Journal
                Oncotarget
                Oncotarget
                Oncotarget
                ImpactJ
                Oncotarget
                Impact Journals LLC
                1949-2553
                14 June 2016
                22 April 2016
                : 7
                : 24
                : 36366-36381
                Affiliations
                1 Department of Genetic medicine, Weill Cornell Medicine-Qatar, Education City, Ar-Rayyan, Qatar
                2 Genomics Core, Weill Cornell Medicine-Qatar, Education City, Ar-Rayyan, Qatar
                3 Department of Gynecologic Oncology, Université Montepllier 1, Montpellier, France
                4 Stem Cell and Microenvironment Laboratory, Weill Cornell Medicine-Qatar, Education City, Ar-Rayyan, Qatar
                Author notes
                Correspondence to: Joel A. Malek, jom2042@ 123456qatar-med.cornell.edu
                Article
                8917
                10.18632/oncotarget.8917
                5095006
                27119352
                b7c70502-f1e9-4e65-83db-8722ea6881fc
                Copyright: © 2016 Ahmed et al.

                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
                : 7 December 2015
                : 2 April 2016
                Categories
                Research Paper

                Oncology & Radiotherapy
                circular rna,ovarian cancer,peritoneal metastasis,lymph node metastasis,mirna

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