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      CircEHD2, CircNETO2 and CircEGLN3 as Diagnostic and Prognostic Biomarkers for Patients with Renal Cell Carcinoma

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          Abstract

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          Circular RNA (circRNA) plays an important role in cancer, but little is known about its role in clear cell renal cell carcinoma (ccRCC). The study was designed to analyze the role of circRNAs in ccRCC. We show that circEHD2, circENGLN3, and circNETO2 are upregulated in ccRCC compared with non-malignant renal tissue. Increased circEHD2 levels were significant and independent predictors of progression-free and cancer-specific survival of ccRCC patients. Thus, the analysis of circRNAs may be of diagnostic and prognostic relevance in patients with ccRCC.

          Abstract

          Background: Circular RNA (circRNA) plays an important role in the carcinogenesis of various tumors. It is assumed that circRNAs have a high tissue and tumor specificity, thus they are discussed as cancer biomarkers. The knowledge about circRNAs in clear cell renal carcinoma (ccRCC) is limited so far, and thus we studied the expression profile of seven circRNAs (circCOL5A1, circEHD2, circEDEM2, circEGNL3, circNETO2, circSCARB1, circSOD2) in a cohort of ccRCC patients. Methods: Fresh-frozen normal and cancerous tissues were prospectively collected from patients with ccRCC undergoing partial/radical nephrectomy. Total RNA was isolated from 121 ccRCC and 91 normal renal tissues, and the circRNA expression profile was determined using quantitative real-time PCR. Results: circEHD2, circENGLN3, and circNETO2 were upregulated in ccRCC compared with non-malignant renal tissue. circENGLN3 expression was highly discriminative between normal and cancerous tissue. None of the circRNAs was correlated with clinicopathological parameters. High circEHD2 and low circNETO2 levels were an independent predictor of a shortened progression-free survival, cancer-specific survival, and overall survival in patients with ccRCC undergoing nephrectomy. Conclusions: The analysis of circRNAs may provide diagnostic and prognostic information. Thus, circRNAs could help to optimize the individual treatment and ultimately improve ccRCC patients’ survival.

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          Most cited references27

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          CircInteractome: A web tool for exploring circular RNAs and their interacting proteins and microRNAs.

          Circular RNAs (circRNAs) are widely expressed in animal cells, but their biogenesis and functions are poorly understood. CircRNAs have been shown to act as sponges for miRNAs and may also potentially sponge RNA-binding proteins (RBPs) and are thus predicted to function as robust posttranscriptional regulators of gene expression. The joint analysis of large-scale transcriptome data coupled with computational analyses represents a powerful approach to elucidate possible biological roles of ribonucleoprotein (RNP) complexes. Here, we present a new web tool, CircInteractome (circRNA interactome), for mapping RBP- and miRNA-binding sites on human circRNAs. CircInteractome searches public circRNA, miRNA, and RBP databases to provide bioinformatic analyses of binding sites on circRNAs and additionally analyzes miRNA and RBP sites on junction and junction-flanking sequences. CircInteractome also allows the user the ability to (1) identify potential circRNAs which can act as RBP sponges, (2) design junction-spanning primers for specific detection of circRNAs of interest, (3) design siRNAs for circRNA silencing, and (4) identify potential internal ribosomal entry sites (IRES). In sum, the web tool CircInteractome, freely accessible at http://circinteractome.nia.nih.gov, facilitates the analysis of circRNAs and circRNP biology.
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            Sunitinib Alone or after Nephrectomy in Metastatic Renal-Cell Carcinoma

            Cytoreductive nephrectomy has been the standard of care in metastatic renal-cell carcinoma for 20 years, supported by randomized trials and large, retrospective studies. However, the efficacy of targeted therapies has challenged this standard. We assessed the role of nephrectomy in patients with metastatic renal-cell carcinoma who were receiving targeted therapies.
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              Cutoff Finder: A Comprehensive and Straightforward Web Application Enabling Rapid Biomarker Cutoff Optimization

              Gene or protein expression data are usually represented by metric or at least ordinal variables. In order to translate a continuous variable into a clinical decision, it is necessary to determine a cutoff point and to stratify patients into two groups each requiring a different kind of treatment. Currently, there is no standard method or standard software for biomarker cutoff determination. Therefore, we developed Cutoff Finder, a bundle of optimization and visualization methods for cutoff determination that is accessible online. While one of the methods for cutoff optimization is based solely on the distribution of the marker under investigation, other methods optimize the correlation of the dichotomization with respect to an outcome or survival variable. We illustrate the functionality of Cutoff Finder by the analysis of the gene expression of estrogen receptor (ER) and progesterone receptor (PgR) in breast cancer tissues. This distribution of these important markers is analyzed and correlated with immunohistologically determined ER status and distant metastasis free survival. Cutoff Finder is expected to fill a relevant gap in the available biometric software repertoire and will enable faster optimization of new diagnostic biomarkers. The tool can be accessed at http://molpath.charite.de/cutoff.
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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Cancers (Basel)
                Cancers (Basel)
                cancers
                Cancers
                MDPI
                2072-6694
                30 April 2021
                May 2021
                : 13
                : 9
                : 2177
                Affiliations
                [1 ]Department of Urology, University Hospital Bonn, 53127 Bonn, Germany; s4lifrey@ 123456uni-bonn.de (L.F.); niklas.kluemper@ 123456ukbonn.de (N.K.); doris.schmidt@ 123456ukbonn.de (D.S.); mritter@ 123456ukbonn.de (M.R.); abdullah.alajati@ 123456ukbonn.de (A.A.)
                [2 ]Institute of Pathology, University Hospital Bonn, 53127 Bonn, Germany; glen.kristiansen@ 123456ukbonn.de (G.K.); marieta.toma@ 123456ukbonn.de (M.T.)
                Author notes
                [* ]Correspondence: joerg.ellinger@ 123456ukbonn.de ; Tel.: +49 228-287-14180; Fax: +49-228-287-14185
                Author information
                https://orcid.org/0000-0002-7526-0857
                Article
                cancers-13-02177
                10.3390/cancers13092177
                8124893
                33946584
                3989ea2a-9f71-41be-942a-6db5f2fbc340
                © 2021 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 ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 17 February 2021
                : 26 April 2021
                Categories
                Article

                circular rna,renal cell carcinoma,biomarker,circehd2,circneto2,circegln3

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