The impact of TLR7 agonist R848 treatment on mast cell phenotype and activity

Agier, Justyna; Brzezińska‐Błaszczyk, Ewa; Witczak, Piotr; Żelechowska, Paulina

doi:10.1016/j.cellimm.2020.104241

Cited by 7 publications

(3 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our results also showed that plasma cells were increased in the samples of T1DM patients compared to the normal ones, suggesting that it may play a role in the antigen presentation process. Mast cells are a type of innate immune cells that express MHC molecules [ 31 ]. It has been demonstrated that mast cells negatively regulate T1DM and other autoimmune related diseases [ 32 , 33 ].…”

Section: Discussionmentioning

confidence: 99%

Analysis of immune cell components and immune-related gene expression profiles in peripheral blood of patients with type 1 diabetes mellitus

Lin

Wang

et al. 2021

J Transl Med

View full text Add to dashboard Cite

Background Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disease caused by severe loss of pancreatic β cells. Immune cells are key mediators of β cell destruction. This study attempted to investigate the role of immune cells and immune-related genes in the occurrence and development of T1DM. Methods The raw gene expression profile of the samples from 12 T1DM patients and 10 normal controls was obtained from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified by Limma package in R. The least absolute shrinkage and selection operator (LASSO)—support vector machines (SVM) were used to screen the hub genes. CIBERSORT algorithm was used to identify the different immune cells in distribution between T1DM and normal samples. Correlation of the hub genes and immune cells was analyzed by Spearman, and gene-GO-BP and gene-pathway interaction networks were constructed by Cytoscape plug-in ClueGO. Receiver operating characteristic (ROC) curves were used to assess diagnostic value of genes in T1DM. Results The 50 immune-related DEGs were obtained between the T1DM and normal samples. Then, the 50 immune-related DEGs were further screened to obtain the 5 hub genes. CIBERSORT analysis revealed that the distribution of plasma cells, resting mast cells, resting NK cells and neutrophils had significant difference between T1DM and normal samples. Natural cytotoxicity triggering receptor 3 (NCR3) was significantly related to the activated NK cells, M0 macrophages, monocytes, resting NK cells, and resting memory CD4+ T cells. Moreover, tumor necrosis factor (TNF) was significantly associated with naive B cell and naive CD4+ T cell. NCR3 [Area under curve (AUC) = 0.918] possessed a higher accuracy than TNF (AUC = 0.763) in diagnosis of T1DM. Conclusions The immune-related genes (NCR3 and TNF) and immune cells (NK cells) may play a vital regulatory role in the occurrence and development of T1DM, which possibly provide new ideas and potential targets for the immunotherapy of diabetes mellitus (DM).

show abstract

Section: Discussionmentioning

confidence: 99%

Analysis of immune cell components and immune-related gene expression profiles in peripheral blood of patients with type 1 diabetes mellitus

Lin

Wang

et al. 2021

J Transl Med

View full text Add to dashboard Cite

show abstract

“…Major histocompatibility complexes (MHCs) are related to the immune response, immune regulation, and the production of certain pathological conditions. Mast cells are a type of innate immune cell that can express MHC molecules ( Agier et al, 2021 ). Mast cells are also functional negative regulators in T1DM and other autoimmune-related diseases ( Geoffrey et al, 2006 ; Fehervari, 2018 ).…”

Section: Discussionmentioning

confidence: 99%

Identification and validation of key biomarkers for the early diagnosis of diabetic kidney disease

Wang²,

Wu³

et al. 2022

Front. Pharmacol.

View full text Add to dashboard Cite

Background: Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease. This study explored the core genes and pathways associated with DKD to identify potential diagnostic and therapeutic targets.Methods: We downloaded microarray datasets GSE96804 and GSE104948 from the Gene Expression Omnibus (GEO) database. The dataset includes a total of 53 DKD samples and 41 normal samples. Differentially expressed genes (DEGs) were identified using the R package “limma”. The Metascape database was subjected to Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to identify the pathway and functional annotations of DEGs. A WGCAN network was constructed, the hub genes in the turquoise module were screened, and the core genes were selected using LASSO regression to construct a diagnostic model that was then validated in an independent dataset. The core genes were verified by in vitro and in vivo experiments.Results: A total of 430 DEGs were identified in the GSE96804 dataset, including 285 upregulated and 145 downregulated DEGs. WGCNA screened out 128 modeled candidate gene sets. A total of eight genes characteristic of DKD were identified by LASSO regression to build a prediction model. The results showed accuracies of 99.15% in the training set (GSE96804) and 94.44% and 100%, respectively, in the test (GSE104948-GPL22945 and GSE104948-GPL24120). Three core genes (OAS1, SECTM1, and SNW1) with high connectivity were selected among the modeled genes. In vitro and in vivo experiments confirmed the upregulation of these genes.Conclusion: Bioinformatics analysis combined with experimental validation identified three novel DKD-specific genes. These findings may advance our understanding of the molecular basis of DKD and provide potential therapeutic targets for its clinical management.

show abstract

“…Our results also showed that plasma cells were increased in the samples of T1DM patients compared to the normal ones, suggesting that it may play a role in the antigen presentation process. Mast cells are a type of innate immune cells that express MHC molecules (29). It has been demonstrated that mast cells negatively regulate T1DM and other autoimmune related diseases (30,31).…”

Section: Diagnostic Value Of Tnf and Ncr3mentioning

confidence: 99%

Analysis of immune cell components and immune-related gene expression profiles in peripheral blood of patients with type 1 diabetes mellitus

Lin

Wang

et al. 2021

Preprint

View full text Add to dashboard Cite

Background Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disease caused by severe loss of pancreatic β cells. Immune cells are key mediators of β cell destruction. This study attempted to investigate the role of immune cells and immune-related genes in the occurrence and development of T1DM. Methods The raw gene expression profile of the samples from 12 T1DM patients and 10 normal controls was obtained from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified by Limma package in R. The least absolute shrinkage and selection operator (LASSO) - support vector machines (SVM) were used to screen the hub genes. CIBERSORT algorithm was used to identify the different immune cells in distribution between T1DM and normal samples. Correlation of the hub genes and immune cells was analyzed by Spearman, and gene-GO-BP and gene-pathway interaction networks were constructed by Cytoscape plug-in ClueGO. Receiver operating characteristic (ROC) curves were used to assess diagnostic value of genes in T1DM. Results The 50 immune-related DEGs were obtained between the T1DM and normal samples. Then, the 50 immune-related DEGs were further screened to obtain the 5 hub genes. CIBERSORT analysis revealed that the distribution of plasma cells, resting mast cells, resting NK cells and neutrophils had significant difference between T1DM and normal samples. Natural cytotoxicity triggering receptor 3 (NCR3) was significantly related to the activated NK cells, M0 macrophages, monocytes, resting NK cells, and resting memory CD4+ T cells. Moreover, tumor necrosis factor (TNF) was significantly associated with naive B cell and naive CD4+ T cell. NCR3 [Area under curve (AUC) = 0.918] possessed a higher accuracy than TNF (AUC = 0.763) in diagnosis of T1DM. Conclusions The immune-related genes (NCR3 and TNF) and immune cells (NK cells) may play a vital regulatory role in the occurrence and development of T1DM, which possibly provide new ideas and potential targets for the immunotherapy of diabetes mellitus (DM).

show abstract

The impact of TLR7 agonist R848 treatment on mast cell phenotype and activity

Cited by 7 publications

References 36 publications

Analysis of immune cell components and immune-related gene expression profiles in peripheral blood of patients with type 1 diabetes mellitus

Analysis of immune cell components and immune-related gene expression profiles in peripheral blood of patients with type 1 diabetes mellitus

Identification and validation of key biomarkers for the early diagnosis of diabetic kidney disease

Analysis of immune cell components and immune-related gene expression profiles in peripheral blood of patients with type 1 diabetes mellitus

Contact Info

Product

Resources

About