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      Suppression of lncRNA Gm47283 attenuates myocardial infarction via miR-706/ Ptgs2/ferroptosis axis

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      Bioengineered
      Taylor & Francis
      LncRNA Gm47283, myocardial infarction, ferroptosis, Ptgs2, miR-706

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          ABSTRACT

          Myocardial infarction (MI) is the leading cause of sudden death. Long non-doing RNAs (lncRNAs) were demonstrated to play crucial roles in multiple diseases, including cancer and cardiovascular diseases. Nevertheless, the molecular mechanism of lncNRAs in MI is unclear. In this study, we integrated bioinformatics and molecular biological experiments to identify the novel lncRNA transcripts and elucidated its regulatory mechanism in MI. First, we identified 10 dysregualted lncRNAs and found that lncRNA Gm47283 was the top risk factor in MI. Bioinformatics analysis predicted that lncRNA Gm47283 exerted function via targeting miR-706 and Ptgs2. Ptgs2 was also the known regulator of ferroptosis. Inhibition or overexpression of lncRNA Gm47283 could regulate Ptgs2 expression and downstream ferroptosis activity. Overexpression of miR-706 could inhibit the expression of Ptgs2 and the activity of ferroptosis, thereby attenuated cellular injury. Mechanically, co-transfection experiments showed that overexpression of miR-706 could reverse the damage effect that was caused by lncRNA Gm47283 overexpression, via inhibiting Ptgs2 and ferroptosis. Additionally, inhibition of lncRNA Gm47283 by stem cell membrane coated siRNA could attenuate MI in vivo. Our study elucidated a novel mechanism containing lncRNA Gm47283/ miR-706/ Ptgs2/ferroptosis in MI, which provided a potential therapeutic for MI.

          Graphical Abstract. Stem cell membrane coated siRNA of lncRNA Gm47283 inhibits cardiomyocyte ferroptosis in myocardial infarction rat. Stem cell membrane-coated siRNA of lncRNA Gm47283 increases miR-706, and then miR-706 suppresses the expression of Ptgs2 to reduce lipid peroxidation toxicity, and then inhibits cardiomyocyte ferroptosis. PUFA: polyunsaturated fatty acid.

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          Most cited references45

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          The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets

          Abstract Cellular life depends on a complex web of functional associations between biomolecules. Among these associations, protein–protein interactions are particularly important due to their versatility, specificity and adaptability. The STRING database aims to integrate all known and predicted associations between proteins, including both physical interactions as well as functional associations. To achieve this, STRING collects and scores evidence from a number of sources: (i) automated text mining of the scientific literature, (ii) databases of interaction experiments and annotated complexes/pathways, (iii) computational interaction predictions from co-expression and from conserved genomic context and (iv) systematic transfers of interaction evidence from one organism to another. STRING aims for wide coverage; the upcoming version 11.5 of the resource will contain more than 14 000 organisms. In this update paper, we describe changes to the text-mining system, a new scoring-mode for physical interactions, as well as extensive user interface features for customizing, extending and sharing protein networks. In addition, we describe how to query STRING with genome-wide, experimental data, including the automated detection of enriched functionalities and potential biases in the user's query data. The STRING resource is available online, at https://string-db.org/.
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            Predicting effective microRNA target sites in mammalian mRNAs

            MicroRNA targets are often recognized through pairing between the miRNA seed region and complementary sites within target mRNAs, but not all of these canonical sites are equally effective, and both computational and in vivo UV-crosslinking approaches suggest that many mRNAs are targeted through non-canonical interactions. Here, we show that recently reported non-canonical sites do not mediate repression despite binding the miRNA, which indicates that the vast majority of functional sites are canonical. Accordingly, we developed an improved quantitative model of canonical targeting, using a compendium of experimental datasets that we pre-processed to minimize confounding biases. This model, which considers site type and another 14 features to predict the most effectively targeted mRNAs, performed significantly better than existing models and was as informative as the best high-throughput in vivo crosslinking approaches. It drives the latest version of TargetScan (v7.0; targetscan.org), thereby providing a valuable resource for placing miRNAs into gene-regulatory networks. DOI: http://dx.doi.org/10.7554/eLife.05005.001
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              Heart Disease and Stroke Statistics—2017 Update: A Report From the American Heart Association

              Circulation, 135(10)
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                Author and article information

                Journal
                Bioengineered
                Bioengineered
                Bioengineered
                Taylor & Francis
                2165-5979
                2165-5987
                29 April 2022
                2022
                29 April 2022
                : 13
                : 4
                : 10786-10802
                Affiliations
                [0001]Department Cardiovascular Surgery, Xuzhou Cancer Hospital; , Xuzhou City, Jiangsu, China
                Author notes
                CONTACT Feng Gao xzzlgf2022@ 123456163.com Department Cardiovascular Surgery, Xuzhou Cancer Hospital; , No. 281, North Zhongshan Road, Gulou District, Xuzhou City, Jiangsu, China
                Article
                2065743
                10.1080/21655979.2022.2065743
                9208485
                35485136
                d96f6e57-672a-4d9f-bb13-820cf3559624
                © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Page count
                Figures: 8, References: 45, Pages: 17
                Categories
                Research Article
                Research Paper

                Biomedical engineering
                lncrna gm47283,myocardial infarction,ferroptosis,ptgs2,mir-706
                Biomedical engineering
                lncrna gm47283, myocardial infarction, ferroptosis, ptgs2, mir-706

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