&lt;p&gt;Identification of Key Genes Associated with Changes in the Host Response to Severe Burn Shock: A Bioinformatics Analysis with Data from the Gene Expression Omnibus (GEO) Database&lt;/p&gt;

Xiao, Fang; Duan, Shu-Fang; Gong, Yuzhou; Wang, Fei; Chen, Xu-Lin

doi:10.2147/jir.s282722

Cited by 28 publications

(19 citation statements)

References 63 publications

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“…Bioinformatics study on the data derived from gene chips has become a promising and efficient tool to screen the significant genetic or epigenetic variations associated with multiple diseases. 16 For the first time, we attempted to use public dataset to evaluate the distinct expression pattern of m6A regulators in human AAA tissues. With further bioinformatics analyses, including differential expression, target gene prediction, functional enrichment analysis, protein–protein interaction (PPI) and competing endogenous RNA (ceRNA) network construction, we sought to construct the whole picture of m6A regulators in AAA disease.…”

Section: Introductionmentioning

confidence: 99%

Expression Pattern and Clinical Value of Key m6A RNA Modification Regulators in Abdominal Aortic Aneurysm

Wang

Jing

et al. 2021

JIR

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Background Aberrant expression of N6-methyladenosine (m6A) RNA modification regulators plays a critical role in a variety of human diseases. However, their implication in abdominal aortic aneurysm (AAA) remains largely unknown. Herein, we sought to explore the general expression pattern and potential functions of m6A regulators in AAA. Methods We analyzed gene expression data of m6A regulators in human AAA and normal tissues from public GEO database. The R package and other tools such as m6A2Target database, Gene ontology (GO) functional and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses, gene set variation analysis (GSVA), Search Tool for the Retrieval of Interacting Genes (STRING), starBase, miRDB and Cytoscape software were applied for bioinformatics analysis to investigate the downstream molecular mechanisms and upstream regulatory mechanisms for distinctly expressed regulators. Quantitative real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA) were performed to validate the expression of key m6A regulators in our collected human AAA specimens. Results We found that METTL14 and HNRNPC were the downregulated m6A regulators, and RBM15B was the upregulated methylation transferase in human AAA. The modified genes were primarily enriched in RNA catabolic process, regulation of translation, focal adhesion, transcription coregulator activity, ribosome, RNA transport, cell cycle, et al. METTL14, HNRNPC and RBM15B levels were correlated with the immune infiltration degree of Tcm, macrophages, mast cells, Tgd and NK CD56bright cells. A total of 154 and 76 target genes of three regulators were separately involved in body metabolism and autophagy in AAA disease, and their interactive relationships and hub genes were identified. The lncRNA-miRNA-mRNA interaction regulatory networks were also constructed for METTL14, HNRNPC and RBM15B. Based on our clinical tissue and serum samples, METTL14 exhibited lower expression levels in AAA and its rupture type, and low METTL14 expression was associated with high levels of WBC and CRP (all P < 0.05). Conclusion Our study presents an overview of the expression pattern and functional significance of m6A regulators in human AAA. Our findings will provide a valuable resource that may guide both mechanistic and therapeutic analyses about the role of key m6A regulators in AAA.

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Section: Introductionmentioning

confidence: 99%

Expression Pattern and Clinical Value of Key m6A RNA Modification Regulators in Abdominal Aortic Aneurysm

Wang

Jing

et al. 2021

JIR

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“…We have constructed a complex interaction network to identify the key nodes through their common DEGs. This comprehensive bioinformatics method has been proven to be reliable in a variety of diseases ( 43 , 44 ). In addition, we also analyzed related TFs and verified their expression levels in the original data set.…”

Section: Discussionmentioning

confidence: 99%

Exploring the Pathogenesis of Psoriasis Complicated With Atherosclerosis via Microarray Data Analysis

Zhao

Wei

et al. 2021

Front. Immunol.

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BackgroundAlthough more and more evidence has supported psoriasis is prone to atherosclerosis, the common mechanism of its occurrence is still not fully elucidated. The purpose of this study is to further explore the molecular mechanism of the occurrence of this complication.MethodsThe gene expression profiles of psoriasis (GSE30999) and atherosclerosis (GSE28829) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) of psoriasis and atherosclerosis, three kinds of analyses were performed, namely functional annotation, protein‐protein interaction (PPI) network and module construction, and hub gene identification and co-expression analysis.ResultsA total of 94 common DEGs (24 downregulated genes and 70 upregulated genes) was selected for subsequent analyses. Functional analysis emphasizes the important role of chemokines and cytokines in these two diseases. In addition, lipopolysaccharide-mediated signaling pathway is closely related to both. Finally, 16 important hub genes were identified using cytoHubba, including LYN, CSF2RB, IL1RN, RAC2, CCL5, IRF8, C1QB, MMP9, PLEK, PTPRC, FYB, BCL2A1, LCP2, CD53, NCF2 and TLR2.ConclusionsOur study reveals the common pathogenesis of psoriasis and atherosclerosis. These common pathways and hub genes may provide new ideas for further mechanism research.

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“…Contrast to prognostic models for platelet, coagulation disorders, IFN-γ, IL-2, IL-4, Burn Severity Index ( ABSI ) score, Ryan score, Belgium Outcome Burn Injury ( BOBI ) score and modi ed Baux score, our prognostic model was based on gene expression pro le and had higher accuracy and more convenient for clinical operation. [8][9][10] Others use bioinformatics methods to study the pathophysiology of severe burns, but most are limited to animal models or have unstable and inaccurate prognostic indicators [43][44][45] . We rst introduced WGCNA, CIBERSORT, GSVA and Lasso in the analysis to nd prognostic factors from the pathophysiological mechanism of immunosuppression after severe burn, so our prognostic model is more stable and reliable.…”

Section: Discussionmentioning

confidence: 99%

Identification of important modules and biomarkers that related to immune cell in severe burns based on weighted gene co-expression network analysis(WGCNA)

zhang

Wang

Yin

et al. 2021

Preprint

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Background Immunosuppression is an important factor inducing infection which is a significant cause of death in severe burns. Nevertheless, the prognostic value of immune-related genes are still unclear. This study was conducted to find biomarkers related to immunosuppression in severe burns. Methods Here, we download the gene expression profile and clinical data of 185 burns and 75 healthy samples from GEO database. Immune infiltration analysis and gene set variation analysis were utilized to identify the disorder of circulating immune cells. WGCNA was carried out to select immune-related gene modules. Enrichment analysis and protein-protein interaction (PPI) network was performed to select hub genes. Next, lasso and logistic regression was utilized to construct the hazard regression model. Finally, we explored correlation between high and low risk patients in total burn surface area (TBSA), age, and inhalation injury. Results In Gene set variation analysis(GSVA) and immune infiltration analysis, neutrophil increased and T cell decreased in severe burns. In WGCNA, four modular that differently expressed in burns and controls were related with immune cells. Based on PPI and enrichment analysis, 210 immune-related genes were identified mainly involved in T cell inhibited and neutrophil activated. In lasso and logistic regression, we screened out key genes, LCK, SKAP1, GZMB and LY9. They are excellent biomarkers of prognosis in burns with AUC: 0.945. Finally, we discovered that key genes were related with T cells and regression model performed well accompanied by TBSA and age. Conclusion We found that LCK, SKAP1, GZMB and LY9 were excellent prognostic biomarkers which were likely function for T cell disorder in post-burn immunosuppression and were potential immunotherapeutic targets to convert T cell dysfunction.

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<p>Identification of Key Genes Associated with Changes in the Host Response to Severe Burn Shock: A Bioinformatics Analysis with Data from the Gene Expression Omnibus (GEO) Database</p>

Cited by 28 publications

References 63 publications

Expression Pattern and Clinical Value of Key m6A RNA Modification Regulators in Abdominal Aortic Aneurysm

Expression Pattern and Clinical Value of Key m6A RNA Modification Regulators in Abdominal Aortic Aneurysm

Exploring the Pathogenesis of Psoriasis Complicated With Atherosclerosis via Microarray Data Analysis

Identification of important modules and biomarkers that related to immune cell in severe burns based on weighted gene co-expression network analysis(WGCNA)

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