Regulation of FcRγ function by site-specific serine phosphorylation

Novel targets in renal fibrosis based on bioinformatic analysis

Background: Renal fibrosis is a widely used pathological indicator of progressive chronic kidney disease (CKD), and renal fibrosis mediates most progressive renal diseases as a final pathway. Nevertheless, the key genes related to the host response are still unclear. In this study, the potential gene network, signaling pathways, and key genes under unilateral ureteral obstruction (UUO) model in mouse kidneys were investigated by integrating two transcriptional data profiles. Methods: The mice were exposed to UUO surgery in two independent experiments. After 7 days, two datasets were sequenced from mice kidney tissues, respectively, and the transcriptome data were analyzed to identify the differentially expressed genes (DEGs). Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were executed. A Protein-Protein Interaction (PPI) network was constructed based on an online database STRING. Additionally, hub genes were identified and shown, and their expression levels were investigated in a public dataset and confirmed by quantitative real time-PCR (qRT-PCR) in vivo. Results: A total of 537 DEGs were shared by the two datasets. GO and the KEGG analysis showed that DEGs were typically enriched in seven pathways. Specifically, five hub genes (Bmp1, CD74, Fcer1g, Icam1, H2-Eb1) were identified by performing the 12 scoring methods in cytoHubba, and the receiver operating characteristic (ROC) curve indicated that the hub genes could be served as biomarkers. Conclusion: A gene network reflecting the transcriptome signature in CKD was established. The five hub genes identified in this study are potentially useful for the treatment and/or diagnosis CKD as biomarkers.

CD16+ fibroblasts foster a trastuzumab-refractory microenvironment that is reversed by VAV2 inhibition

The leukocyte Fcγ receptor (FcγR)-mediated response is important for the efficacy of therapeutic antibodies; however, little is known about the role of FcγRs in other cell types. Here we identify a subset of fibroblasts in human breast cancer that express CD16 (FcγRIII). An abundance of these cells in HER2⁺ breast cancer patients is associated with poor prognosis and response to trastuzumab. Functionally, upon trastuzumab stimulation, CD16⁺ fibroblasts reduce drug delivery by enhancing extracellular matrix stiffness. Interaction between trastuzumab and CD16 activates the intracellular SYK-VAV2-RhoA-ROCK-MLC2-MRTF-A pathway, leading to elevated contractile force and matrix production. Targeting of a Rho family guanine nucleotide exchange factor, VAV2, which is indispensable for the function of CD16 in fibroblasts rather than leukocytes, reverses desmoplasia provoked by CD16⁺ fibroblasts. Collectively, our study reveals a role for the fibroblast FcγR in drug resistance, and suggests that VAV2 is an attractive target to augment the effects of antibody treatments.

Identification of FCER1G related to Activated Memory CD4+ T Cells Infiltration by Gene Co-expression Network and Construction of a Risk Prediction Module in Diffuse Large B-Cell Lymphoma

Diffuse large B cell lymphoma (DLBCL) is a group of biologically heterogeneous tumors with different prognoses. The tumor microenvironment plays a vital role in the tumorigenesis and development of DLBCL, and activated memory CD4⁺ T cells are an essential component of immunological cells in the lymphoma microenvironment. So far, there are few reports about activated memory CD4+T cells infiltration and related genes in the DLBCL tumor microenvironment. This study obtained the mRNA expression profile information of the testing GSE87371 dataset and another six validation datasets (GSE53786, GSE181063, GSE10846, GSE32918, GSE32018, GSE9327, GSE3892, TCGA-DLBC) from the GEO and TCGA databases. Weighted Gene Co-expression Network Analysis (WGCNA) screened gene module associated with activated memory CD4⁺ T cells infiltration. CIBERSORT and TIMER (immune cells infiltrating estimation analysis tools) were used to identify the relationship between activated memory CD4⁺ T cells and genes associated with immune infiltrating cells in the tumor microenvironment. The least absolute shrinkage and selection operator (LASSO) built the risk prediction model and verified it using nomogram and Kaplan-Meier analysis. Further functional characterization includes Gene Ontology, KEGG pathway analysis and Gene Set Enrichment Analysis (GSEA) to investigate the role and underlying mechanisms of these genes. These results suggest that the expression of FCER1G can reflect the invasion of activated memory CD4⁺ T cells in DLBCL, which provides a new idea for studying the tumor microenvironment and may become a potential predictive biomarker for the assessment of DLBCL.

Identification of diagnostic markers and immune cell infiltration characteristics in antineutrophil cytoplasmic antibody-associated vasculitis by weighted gene co-expression network analysis

Background

Antineutrophil cytoplasmic antibody-associated vasculitis (AAV) is a group of life-threatening systemic autoimmune diseases. The aim of this study was to determine the relationship between the AAV hub gene and immune cell infiltration, and its value for clinical disease treatment.

Methods

We downloaded the microarray information of 37 AAV patients and 27 controls from Gene Expression Omnibus (GEO). Genes were classified into totally different modules exploitation weighted gene co-expression network analysis (WGCNA). AAV diagnostic indicators were screened and then assessed immune cell infiltration by the least absolute shrinkage and selection operator (LASSO) and CIBERSORT. Finally, Connectivity Map analysis was applied to predict possible AAV glomerulus injury improvement therapies.

Results

WGCNA was developed and differentially expressed genes were classified into 6 modules, the black module was most tightly correlated to AAV. Among them, TIMP1 and FCER1G were most closely related to clinical features. Resting mast cells and monocytes emerged as having the foremost distinguished variations in AAV. C3AR1 and FCER1G were involved in AAV development by immune regulation. Connectivity Map analysis indicated the most significant compound was fisetin.

Conclusions

The present study is that the initial to spot immune cell infiltration with microarray data of glomeruli in AAV, which provides novel proof and clues for additional analysis of the molecular mechanisms.

Enhanced expression of FCER1G predicts positive prognosis in multiple myeloma

Background: Multiple myeloma (MM) is the second most common hematologic malignancy worldwide and does not have sufficient prognostic indicators. FCER1G (Fc fragment Of IgE receptor Ig) is located on chromosome 1q23.3 and is involved in the innate immunity. Early studies have shown that FCER1G participates in many immune-related pathways encompassing multiple cell types. Meanwhile, it is associated with many malignancies. However, the relationship between MM and FCER1G has not been studied.

Methods: In this study, we integrated nine independent gene expression omnibus (GEO) datasets and analyzed the associations of FCER1G expression and myeloma progression, ISS stage, 1q21 amplification and survival in 2296 myeloma patients and 48 healthy donors.

Results: The expression of FCER1G showed a decreasing trend with the advance of myeloma. As ISS stage and 1q21 amplification level increased, the expression of FCER1G decreased (P = 0.0012 and 0.0036, respectively). MM patients with high FCER1G expression consistently had longer EFS and OS across three large sample datasets (EFS: P = 0.0057, 0.0049, OS: P = 0.0014, 0.00065, 0.0019 and 0.0029, respectively). Meanwhile, univariate and multivariate analysis indicated that high FCER1G expression was an independent favorable prognostic factor for EFS and OS in MM patients (EFS: P = 0.006, 0.027, OS: P =0.002,0.025, respectively).

Conclusions: The expression level of FCER1G negatively correlated with myeloma progression, and high FCER1G expression may be applied as a favorable biomarker in MM patients.

Dectin-1 intracellular domain determines species-specific ligand spectrum by modulating receptor sensitivity

C-type lectin receptors (CLRs) comprise a large family of immunoreceptors that recognize polysaccharide ligands exposed on pathogen surfaces and are conserved among mammals. However, interspecies differences in their ligand spectrums are not fully understood. Dectin-1 is a well-characterized CLR that recognizes β-glucan. We report here that seaweed-derived fucan activates cells expressing human Dectin-1 but not mouse Dectin-1. Low-valency β-glucan components within fucan appeared to be responsible for this activation, as the ligand activity was eliminated by β-glucanase treatment. The low-valency β-glucan laminarin also acted as an agonist for human Dectin-1 but not for mouse Dectin-1, whereas the high-valency β-glucan curdlan activated both human and mouse Dectin-1. Reciprocal mutagenesis analysis revealed that the ligand-binding domain of human Dectin-1 does not determine its unique sensitivity to low-valency β-glucan. Rather, we found that its intracellular domain renders human Dectin-1 reactive to low-valency β-glucan ligand. Substitution with two amino acids, Glu² and Pro⁵, located in the human Dectin-1 intracellular domain was sufficient to confer sensitivity to low-valency β-glucan in mouse Dectin-1. Conversely, the introduction of mouse-specific amino acids, Lys² and Ser⁵, to human Dectin-1 reduced the reactivity to low-valency β-glucan. Indeed, low-valency ligands induced a set of proinflammatory genes in human but not mouse dendritic cells. These results suggest that the intracellular domain, not ligand-binding domain, of Dectin-1 determines the species-specific ligand profile.