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      Potential ferroptosis key genes in calcific aortic valve disease

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          Abstract

          Calcific aortic valve disease (CAVD) is a highly prevalent condition that comprises a disease continuum, ranging from microscopic changes to profound fibro-calcific leaflet remodeling, culminating in aortic stenosis, heart failure, and ultimately premature death. Ferroptosis has been hypothesized to contribute to the pathogenesis of CAVD. We aimed to study the association between ferroptosis genes and CAVD and reveal the potential roles of ferroptosis in CAVD. CAVD-related differentially expressed genes (DEGs) were identified via bioinformatic analysis of Datasets GSE51472 and GSE12644 obtained from Gene Expression Omnibus. A ferroptosis dataset containing 259 genes was obtained from the Ferroptosis Database. We then intersected with CAVD-related DEGs to identify the ferroptosis DEGs. Subsequently, protein–protein interaction networks and functional enrichment analyses were performed for ferroptosis DEGs. Then, we used miRWalk3.0 to predict the target pivotal microRNAs. An in vitro model of CAVD was constructed using human aortic valve interstitial cells. The qRT-PCR and western blotting methods were used to validate the ferroptosis DEGs identified by the microarray data. A total of 21 ferroptosis DEGs in CAVD containing 12 upregulated and nine downregulated genes were identified. The results of the Gene Set Enrichment Analysis (GSEA) and analysis of the KEGG pathway by WebGestalt indicated that the ferroptosis DEGs were enriched in six signaling pathways among which NAFLD (including IL-6, BID, and PRKAA2 genes) and HIF-1 (including IL-6, HIF-1, and HMOX1 genes) signaling pathways were also verified by DAVID and/or Metascape. Finally, the in vitro results showed that the mRNA and protein expression levels of IL-6, HIF-1α, HMOX1, and BID were higher, while the levels of PRKAA2 were lower in the Pi-treated group than those in the control group. However, the addition of ferrostatin-1 (a selective ferroptosis inhibitor) significantly reversed the above changes. Therefore, IL-6, HIF-1α, HMOX1, BID, and PRKAA2 are potential key genes closely associated with ferroptosis in CAVD. Further work is required to explore the underlying ferroptosis-related molecular mechanisms and provide possible therapeutic targets for CAVD.

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          Most cited references41

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          Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

          Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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            Ferroptosis: A Regulated Cell Death Nexus Linking Metabolism, Redox Biology, and Disease

            Ferroptosis is a form of regulated cell death characterized by the iron-dependent accumulation of lipid hydroperoxides to lethal levels. Emerging evidence suggests that ferroptosis represents an ancient vulnerability caused by the incorporation of polyunsaturated fatty acids into cellular membranes, and cells have developed complex systems that exploit and defend against this vulnerability in different contexts. The sensitivity to ferroptosis is tightly linked to numerous biological processes, including amino acid, iron, and polyunsaturated fatty acid metabolism, and the biosynthesis of glutathione, phospholipids, NADPH, and coenzyme Q10. Ferroptosis has been implicated in the pathological cell death associated with degenerative diseases (i.e., Alzheimer's, Huntington's, and Parkinson's diseases), carcinogenesis, stroke, intracerebral hemorrhage, traumatic brain injury, ischemia-reperfusion injury, and kidney degeneration in mammals and is also implicated in heat stress in plants. Ferroptosis may also have a tumor-suppressor function that could be harnessed for cancer therapy. This Primer reviews the mechanisms underlying ferroptosis, highlights connections to other areas of biology and medicine, and recommends tools and guidelines for studying this emerging form of regulated cell death.
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              The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible

              A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein–protein association data for a large number of organisms. The associations in STRING include direct (physical) interactions, as well as indirect (functional) interactions, as long as both are specific and biologically meaningful. Apart from collecting and reassessing available experimental data on protein–protein interactions, and importing known pathways and protein complexes from curated databases, interaction predictions are derived from the following sources: (i) systematic co-expression analysis, (ii) detection of shared selective signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computational transfer of interaction knowledge between organisms based on gene orthology. In the latest version 10.5 of STRING, the biggest changes are concerned with data dissemination: the web frontend has been completely redesigned to reduce dependency on outdated browser technologies, and the database can now also be queried from inside the popular Cytoscape software framework. Further improvements include automated background analysis of user inputs for functional enrichments, and streamlined download options. The STRING resource is available online, at http://string-db.org/.
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                Author and article information

                Contributors
                Journal
                Front Cardiovasc Med
                Front Cardiovasc Med
                Front. Cardiovasc. Med.
                Frontiers in Cardiovascular Medicine
                Frontiers Media S.A.
                2297-055X
                08 August 2022
                2022
                : 9
                : 916841
                Affiliations
                [1] 1Department of Cardiology, Guangzhou Key Laboratory on the Molecular Mechanisms of Major Cardiovascular Disease, Guangdong Provincial Key Laboratory of Arrhythmia and Electrophysiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University , Guangzhou, China
                [2] 2Department of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University , Guangzhou, China
                [3] 3Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University , Guangzhou, China
                Author notes

                Edited by: Junjie Xiao, Shanghai University, China

                Reviewed by: Zhi Xin Shan, Guangdong Provincial People's Hospital, China; Ishita Tandon, University of Arkansas, United States

                *Correspondence: Jing-Wei Gao gaojw5@ 123456mail2.sysu.edu.cn

                This article was submitted to General Cardiovascular Medicine, a section of the journal Frontiers in Cardiovascular Medicine

                †These authors have contributed equally to this work

                Article
                10.3389/fcvm.2022.916841
                9395208
                36003913
                a813b3d6-4995-42b1-82d9-a8a276daa90e
                Copyright © 2022 Li, Xiong, Zhang, Hao, Gao, Wang, Gao and Liu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 11 April 2022
                : 13 July 2022
                Page count
                Figures: 6, Tables: 3, Equations: 0, References: 41, Pages: 14, Words: 6955
                Funding
                Funded by: National Natural Science Foundation of China, doi 10.13039/501100001809;
                Award ID: 81870315
                Award ID: 81900379
                Award ID: 81970683
                Award ID: 82170457
                Categories
                Cardiovascular Medicine
                Original Research

                calcific aortic valve disease,ferroptosis,biomarkers,non-alcoholic fatty liver disease,hypoxia-inducible factor 1 (hif-1) signaling

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