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      Identification of potential biomarkers associated with cuproptosis and immune microenvironment analysis in acute myocardial infarction: A diagnostic accuracy study

      research-article
      , MM a , * , , , MD a , , MM b , , MM c
      Medicine
      Lippincott Williams & Wilkins
      acute myocardial infarction, bioinformatics, biomarkers, cuproptosis, immune cells

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          Abstract

          Acute myocardial infarction (AMI), a critical cardiovascular condition, is often associated with serious health risks. Recent studies suggest a link between copper-induced apoptosis and immune cell infiltration. Specifically, abnormal accumulation of copper ions can lead to intracellular oxidative stress and apoptosis, while also affecting immune cell function and infiltration. Nevertheless, studies exploring this relationship in the context of AMI are notably scarce, underscoring the necessity of identifying biomarkers associated with cuproptosis in AMI. Consensus clustering analysis was employed to classify distinct subtypes of AMI in the GSE66360 dataset. Concurrently, differential expression analysis was performed to identify differentially expressed genes (DEGs) across subtypes and between AMI and control samples. We employed Venn diagrams to validate the selection of cuproptosis-related DEGs in patients with AMI. A protein–protein interaction network was constructed to pinpoint potential candidate genes. Receiver operating characteristic curves were generated to identify promising biomarkers. The immune infiltration milieu was analyzed using CIBERSORT algorithms. Finally, the expression levels of identified cuproptosis-related biomarkers were validated at the transcriptional level. We classified AMI into 2 distinct cuproptosis-related subtypes, leading to the identification of 157 cuproptosis-related DEGs. Further analysis refined this list to 10 potential candidate genes. Among these, 5 emerged as significant biomarkers for AMI: granzyme A (GZMA), GTPase immunity-associated proteins (GIMPAs) GIMAP7, GIMAP5, GIMAP6, and TRAF3 interacting protein 3 (TRAF3IP3). A comprehensive examination of immune infiltration in AMI samples revealed significant differences in the levels of 11 types of immune cells, with GZMA displaying the highest correlation with activated mast cells and CD8 + T cells. We observed markedly lower expression levels of GZMA, GIMAP6, and TRAF3IP3 in the AMI group compared to controls. This study identified 5 cuproptosis-related biomarkers (GZMA, GIMAP7, GIMAP5, GIMAP6, and TRAF3IP3) associated with AMI, laying a theoretical foundation for the treatment of AMI.

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          Most cited references49

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            clusterProfiler: an R package for comparing biological themes among gene clusters.

            Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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              2017 ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation

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                Author and article information

                Contributors
                Journal
                Medicine (Baltimore)
                Medicine (Baltimore)
                MD
                Medicine
                Lippincott Williams & Wilkins (Hagerstown, MD )
                0025-7974
                1536-5964
                31 January 2025
                31 January 2025
                : 104
                : 5
                : e40817
                Affiliations
                [a ]Department of Cardiovascular Internal Medicine, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
                [b ]Department of Medical Record Management, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
                [c ]Department of Imaging and Nuclear Medicine, The Second Hospital of Shanxi Medical University, Taiyuan, China.
                Author notes
                [* ]Correspondence: Jing Zhang, Department of Cardiovascular Internal Medicine, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan 030032, China (e-mail: z13633442417@ 123456163.com ).
                Author information
                https://orcid.org/0009-0005-3168-506X
                Article
                MD-D-24-05157 00054
                10.1097/MD.0000000000040817
                11789903
                39889200
                d100b8c7-0789-447c-aa8c-4564d7efb672
                Copyright © 2025 the Author(s). Published by Wolters Kluwer Health, Inc.

                This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.

                History
                : 16 May 2024
                : 24 July 2024
                : 15 November 2024
                Funding
                Funded by: Hubei Key Laboratory of Novel Reactor and Green Chemistry Technology, doi 10.13039/501100015219;
                Award ID: 2022RC08
                Award Recipient : Not Applicable
                Categories
                3400
                Research Article
                Diagnostic Accuracy Study
                Custom metadata
                TRUE
                T

                acute myocardial infarction,bioinformatics,biomarkers,cuproptosis,immune cells

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