Le récepteur de forte affinité pour l’IgE : leçons d’une analyse structurale

Blank, Ulrich; Jouvin, Marie-Hélène; Guérin-Marchand, Claudine; Kinét, Jean-Pierre

doi:10.1051/medsci/200319163

Cited by 9 publications

(5 citation statements)

References 41 publications

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“…TYROBP functions to mediate signaling and cell activation following ligand binding by the receptors (Lanier et al, 1998a,b;Dietrich et al, 2000). Interaction of an allergen with FCER1G triggers cell activation, which induces the release of numerous mediators involved in allergic responses (Blank et al, 2003). Extremely tight correlation was observed between these two genes in all human and mouse macrophage microarray datasets (Figures 2A,B).…”

Section: Discussionmentioning

confidence: 98%

Computational Approach to Identifying Universal Macrophage Biomarkers

et al. 2020

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Macrophages engulf and digest microbes, cellular debris, and various diseaseassociated cells throughout the body. Understanding the dynamics of macrophage gene expression is crucial for studying human diseases. As both bulk RNAseq and single cell RNAseq datasets become more numerous and complex, identifying a universal and reliable marker of macrophage cell becomes paramount. Traditional approaches have relied upon tissue specific expression patterns. To identify universal biomarkers of macrophage, we used a previously published computational approach called BECC (Boolean Equivalent Correlated Clusters) that was originally used to identify conserved cell cycle genes. We performed BECC analysis using the known macrophage marker CD14 as a seed gene. The main idea behind BECC is that it uses massive database of public gene expression dataset to establish robust co-expression patterns identified using a combination of correlation, linear regression and Boolean equivalences. Our analysis identified and validated FCER1G and TYROBP as novel universal biomarkers for macrophages in human and mouse tissues.

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Section: Discussionmentioning

confidence: 98%

Computational Approach to Identifying Universal Macrophage Biomarkers

et al. 2020

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“…FCER1G acts as a high-affinity receptor for IgE, which induces the release of allergic response mediators and modulates allergic reactions. [43] The chemokine receptor network controls immune responses and guides the migration of immune cells. CCR1 is one of the C-C chemokine receptors and has corresponding responses to a variety of inflammatory chemokines.…”

Section: Discussionmentioning

confidence: 99%

Using bioinformatics and systems biology methods to identify the mechanism of interaction between COVID-19 and nonalcoholic fatty liver disease

et al. 2023

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Nonalcoholic fatty liver disease (NAFLD) is considered a risk factor for severe COVID-19, but the mechanism remains unknown. This study used bioinformatics to help define the relationship between these diseases. The GSE147507 (COVID-19), GSE126848 (NAFLD), and GSE63067 (NAFLD-2) datasets were screened using the Gene Expression Omnibus. Common differentially expressed genes were then identified using a Venn diagram. Gene ontology analysis and KEGG pathway enrichment were performed on the differentially expressed genes. A protein–protein interaction network was also constructed using the STRING platform, and key genes were identified using the Cytoscape plugin. GES63067 was selected for validation of the results. Analysis of ferroptosis gene expression during the development of the 2 diseases and prediction of their upstream miRNAs and lncRNAs. In addition, transcription factors (TFs) and miRNAs related to key genes were identified. Effective drugs that act on target genes were found in the DSigDB. The GSE147507 and GSE126848 datasets were crossed to obtain 28 co-regulated genes, 22 gene ontology terms, 3 KEGG pathways, and 10 key genes. NAFLD may affect COVID-19 progression through immune function and inflammatory signaling pathways. CYBB was predicted to be a differential ferroptosis gene associated with 2 diseases, and the CYBB-hsa-miR-196a/b-5p-TUG1 regulatory axis was identified. TF-gene interactions and TF-miRNA coregulatory network were constructed successfully. A total of 10 drugs, (such as Eckol, sulfinpyrazone, and phenylbutazone) were considered as target drugs for Patients with COVID-19 and NAFLD. This study identified key gene and defined molecular mechanisms associated with the progression of COVID-19 and NAFLD. COVID-19 and NAFLD progression may regulate ferroptosis through the CYBB-hsa-miR-196a/b-5p-TUG1 axis. This study provides additional drug options for the treatment of COVID-19 combined with NAFLD disease.

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“…The high affinity Ig E receptor, FCER1G, is a key molecule involved in allergic reactions. This tetramer is composed of one alpha, one beta, and two gamma chains [ 32 ]. Gamma chains are also subunits of other Fc receptors [ 32 ].…”

Section: Discussionmentioning

confidence: 99%

“…This tetramer is composed of one alpha, one beta, and two gamma chains [ 32 ]. Gamma chains are also subunits of other Fc receptors [ 32 ]. FCER1G is essential for chronic inflammation and plays an important role in death-activating signaling, inducing apoptosis [ 33 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of Prognostic Related Genes of Tumor Microenvironment Derived From Esophageal Cancer Patients

Yuan¹,

Yan²,

Liu³

et al. 2021

Pathol. Oncol. Res.

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Background and Objective: Esophageal cancer (ESCA) is a commonly occurring cancer worldwide with poor survival and limited therapeutic options. Due to the lack of biomarkers that facilitate early detection, its treatment remains a great challenge. This study aims at identifying the tumor microenvironment (TME)-related genes, which might affect prognosis and accelerate clinical treatment for ESCA patients.Methods: We integrated the expression profiles from ESCA patients in The Cancer Genome Atlas. Then, we determined the stromal and immune scores of each sample using the R package. The Gene Expression Omnibus database was used to validate the expression profile of the key genes.Results: Tumor mutational burden showed a significant difference between the groups of ESCA patients with high and low ESTIMATE scores. We identified 859 intersection genes among patients with different immune and stromal scores. Moreover, gene ontology analysis demonstrated that these 859 intersection genes were closely related to adaptive immune response and regulation of lymphocyte activation. Kyoto Encyclopedia of Genes and Genomes showed the enrichment of cytokine-cytokine receptor interaction and chemokine signaling pathway in the TME. Furthermore, the protein–protein interaction network consisted of 175 nodes. We selected 35 hub genes, including ITGAM, CXCL10, CCR2, CCR5, and CCR1. Of these, 23 intersection genes predicted the overall survival rate. C1QA and FCER1G correlated with overall survival of the ESCA patients in the two databases.Conclusion: We identified a set of stromal and immune score-related prognostic differentially expressed genes that could influence the complexity of the TME. C1QA and FCER1G were identified and validated with respect to their role in the progression of ESCA.

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Le récepteur de forte affinité pour l’IgE : leçons d’une analyse structurale

Cited by 9 publications

References 41 publications

Computational Approach to Identifying Universal Macrophage Biomarkers

Computational Approach to Identifying Universal Macrophage Biomarkers

Using bioinformatics and systems biology methods to identify the mechanism of interaction between COVID-19 and nonalcoholic fatty liver disease

Identification of Prognostic Related Genes of Tumor Microenvironment Derived From Esophageal Cancer Patients

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