The Egr-1/miR-15a-5p/GPX4 axis regulates ferroptosis in acute myocardial infarction

Fan, Kai; Huang, Wei; Qi, Hanping; Song, Chao; He, Cong; Liu, Yongsheng; Zhang, Qianlong; Wang, Lixin; Sun, Hai‐Ying

doi:10.1016/j.ejphar.2021.174403

Cited by 62 publications

(51 citation statements)

References 45 publications

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“…SREBF1 [744], TP53 [745] and EGR1 [746] have been revealed to be highly expressed in CNS disorders, but these genes might be involved in the progression of COVID-19. SREBF1 [747], ELF5 [748], TP53 [749], EGR1 [750], E2F6 [751] and STAT3 [752] have been demonstrated to function in cardiovascular diseases, but these genes might be involved in the progression of COVID-19. ELK1 [753], EGR1 [754] and STAT3 [755] plays a key role in the development of the lung diseases, but these genes might be involved in the progression of COVID-19.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of next-generation sequencing data in COVID-19 and its secondary complications

Vastrad¹,

Vastrad²

2022

Preprint

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The ongoing pandemic of coronavirus disease 2019 (COVID-19) has made a serious public health threat globally. To discover key molecular changes in COVID-19 and its secondary complications, we analyzed next-generation sequencing (NGS) data of COVID-19. NGS data (GSE163151) was screened and downloaded from the Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) were identified in the present study, using DESeq2 package in R programming software. Gene ontology (GO) and pathway enrichment analysis were performed, and the protein-protein interaction (PPI) network, module analysis, miRNA-hub gene regulatory network and TF-hub gene regulatory network were established. Subsequently, receiver operating characteristic curve (ROC) analysis was used to validate the diagonostics valuesof the hub genes. Firstly, 954 DEGs (477 up regulated and 477 down regulated) were identified from the four NGS dataset. GO enrichment analysis revealed enrichment of DEGs in genes related to the immune system process and multicellular organismal process, and REACTOME pathway enrichment analysis showed enrichment of DEGs in the immune system and formation of the cornified envelope. Hub genes were identified from the PPI network, module analysis, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Furthermore, the ROC analysis indicate that COVID-19 and its secondary complications with following hub genes, namely, RPL10, FYN, FLNA, EEF1A1, UBA52, BMI1, ACTN2, CRMP1, TRIM42 and PTCH1, had good diagnostics values. This study identified several genes associated with COVID-19 and its secondary complications, which improves our knowledge of the disease mechanism.

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Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of next-generation sequencing data in COVID-19 and its secondary complications

Vastrad¹,

Vastrad²

2022

Preprint

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“…A previous investigation found that altered expression of STAT3 [295], STAT4 [296], FOXA2 [297], SOX2 [298], EGR1 [299], SMAD1 [300] and VDR (vitamin D receptor) [301] were associated with type 2 diabetes mellitus. Bao et al [302], Reid et al [303], Tian et al [304], Liang et al [305], Fan et al [306] and VDR (vitamin D receptor) in patients with renal diseases.. In this investigation, STX7, RAD18, YWHAZ, RPS15A, RAD51B, hsa-mir-4471, hsa-mir-7159-3p, hsa-mir-4478, hsa-mir-6818-5p, hsa-mir-3150b-3p, hsa-mir-518f-5p, hsa-mir-940, hsa-mir-3666 and RAD21 were might be potential novel modulators of T1DM.…”

Section: Discussionmentioning

confidence: 99%

“…A previous investigation found that altered expression of STAT3 [295], STAT4 [296], FOXA2 [297], SOX2 [298], EGR1 [299], SMAD1 [300] and VDR (vitamin D receptor) [301] were associated with type 2 diabetes mellitus. Bao et al [302], Reid et al [303], Tian et al [304], Liang et al [305], Fan et al [306], Wang et al [307] and Gonzalez-Parra et al [308] showed that STAT3, STAT4, FOXM1, SOX2, EGR1, SMAD1 and VDR (vitamin D receptor) might play an important role in regulating the genetic network related to the occurrence and development of cardiovascular complications. The altered expression of STAT3 [309], FOXM1 [310], SMAD1 [311] and VDR (vitamin D receptor) [312] might be related to the progression of hypertension.…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics Analysis of next generation sequencing data for Risk Prediction in Patients with Type 1 diabetes mellitus

Vastrad¹,

Vastrad²

2022

Preprint

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Type 1 diabetes mellitus (T1DM) comprise the most common forms of autoimmune disease. The aim of this investigation was to apply a bioinformatics approach to reveal related pathways or genes involved in the development of T1DM. The next generation sequencing (NGS) dataset GSE182870 was downloaded from the gene expression omnibus (GEO) database. Differentially expressed gene (DEG) analysis was performed using DESeq2. The g:Profiler was utilized to analyze the functional enrichment, gene ontology (GO) and REACTOME pathway of the differentially expressed genes. Protein-protein interaction (PPI) network, modules, miRNA-hub gene regulatory network, and TF-hub gene regulatory network were conducted via comprehensive target prediction and network analyses. Finally, hub genes were validated by using receiver operating characteristic curve analysis. A total of 860 DEGs were screened out from NGS dataset, among which 477 genes were up regulated and 383 genes were down regulated. GO enrichment analysis indicated that up regulated genes were mainly involved in cellular metabolic process, intracellular anatomical structure and catalytic activity, and the down regulated genes were significantly enriched in cellular nitrogen compound biosynthetic process, protein containing complex and heterocyclic compound binding. REACTOME pathway enrichment analysis showed that the up regulated genes were mainly enriched in metabolism of carbohydrates and the down regulated genes were significantly enriched in metabolism of RNA. A PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed, and hub genes (MAPK14, RHOC, MAD2L1, TAF1, TRAF2, HSP90AA1, TP53, HSP90AB1, UBA52 and RACK1) were identified. This study provides further insights into the underlying pathogenesis of T1DM.

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“…Studies also indicate that other signaling molecules such as NADPH oxidase 4 (NOX4) and GPX4 regulate ferroptosis and thus affect heart disease (Supplementary Table S3). Ferroptosis is increasingly considered a potential cause of cardiovascular morbidity, and inhibition of ferroptosis represents a new strategy for these patients (Liu et al, 2018a;Bai et al, 2018;Chen et al, 2019;Fang et al, 2019;Feng et al, 2019;Fan et al, 2021).…”

Section: Ferroptosis Pathways In Cardiovascular Diseasesmentioning

confidence: 99%

Programmed Cell Death: Complex Regulatory Networks in Cardiovascular Disease

Zhou

Sun

et al. 2021

Front. Cell Dev. Biol.

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Abnormalities in programmed cell death (PCD) signaling cascades can be observed in the development and progression of various cardiovascular diseases, such as apoptosis, necrosis, pyroptosis, ferroptosis, and cell death associated with autophagy. Aberrant activation of PCD pathways is a common feature leading to excessive cardiac remodeling and heart failure, involved in the pathogenesis of various cardiovascular diseases. Conversely, timely activation of PCD remodels cardiac structure and function after injury in a spatially or temporally restricted manner and corrects cardiac development similarly. As many cardiovascular diseases exhibit abnormalities in PCD pathways, drugs that can inhibit or modulate PCD may be critical in future therapeutic strategies. In this review, we briefly describe the process of various types of PCD and their roles in the occurrence and development of cardiovascular diseases. We also discuss the interplay between different cell death signaling cascades and summarize pharmaceutical agents targeting key players in cell death signaling pathways that have progressed to clinical trials. Ultimately a better understanding of PCD involved in cardiovascular diseases may lead to new avenues for therapy.

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The Egr-1/miR-15a-5p/GPX4 axis regulates ferroptosis in acute myocardial infarction

Cited by 62 publications

References 45 publications

Comprehensive analysis of next-generation sequencing data in COVID-19 and its secondary complications

Comprehensive analysis of next-generation sequencing data in COVID-19 and its secondary complications

Bioinformatics Analysis of next generation sequencing data for Risk Prediction in Patients with Type 1 diabetes mellitus

Programmed Cell Death: Complex Regulatory Networks in Cardiovascular Disease

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