CD32A

The connection between head and neck squamous cell carcinoma (HNSC) and M2 tumour-associated macrophages is not yet fully understood. We gathered gene expression profiles and clinical data from HNSC patients in the TCGA database. Using Consensus Clustering, we categorized these patients into M2 macrophage-related clusters. We developed a M2 macrophage-related signature (MRS) through statistical analyses. Additionally, we assessed gene expression in HNSC cells using single-cell sequencing data (GSE139324). We identified three distinct M2 macrophage-related clusters in HNSC, each with different prognostic outcomes and immune characteristics. Patients with different MRS profiles exhibited variations in immune infiltration, genetic mutations and prognosis. FCGR2A may play a role in creating an immunosuppressive tumour microenvironment and could potentially serve as a therapeutic target for HNSC. Our study demonstrated that M2 macrophage-related genes significantly impact the development and progression of HNSC. The M2 macrophage-related model offered a more comprehensive assessment of HNSC patient prognosis, genetic mutations and immune features. FCGR2A was implicated in immunosuppressive microenvironments and may hold promise for the development of novel immunotherapeutic strategies for HNSC.

Kidney transplantation stands out as the most effective renal replacement therapy for patients grappling with end-stage renal disease. However, post-transplant renal fibrosis is a prevalent and irreversible consequence, imposing a substantial clinical burden. Unfortunately, the clinical landscape remains devoid of reliable biological markers for diagnosing post-transplant renal interstitial fibrosis.

We obtained transcriptome and single-cell sequencing datasets of patients with renal fibrosis from NCBI Gene Expression Omnibus (GEO). Subsequently, we employed Weighted Gene Co-Expression Network Analysis (WGCNA) to identify potential genes by integrating core modules and differential genes. Functional enrichment analysis was conducted to unveil the involvement of potential pathways. To identify key biomarkers for renal fibrosis, we utilized logistic analysis, a LASSO-based tenfold cross-validation approach, and gene topological analysis within Cytoscape. Furthermore, histological staining, Western blotting (WB), and quantitative PCR (qPCR) experiments were performed in a murine model of renal fibrosis to verify the identified hub genes. Moreover, molecular docking and molecular dynamics simulations were conducted to explore possible effective drugs.

Through WGCNA, the intersection of core modules and differential genes yielded a compendium of 92 potential genes. Logistic analysis, LASSO-based tenfold cross-validation, and gene topological analysis within Cytoscape identified four core genes (CD3G, CORO1A, FCGR2A, and GZMH) associated with renal fibrosis. The expression of these core genes was confirmed through single-cell data analysis and validated using various machine learning methods. Wet experiments also verified the upregulation of these core genes in the murine model of renal fibrosis. A positive correlation was observed between the core genes and immune cells, suggesting their potential role in bolstering immune system activity. Moreover, four potentially effective small molecules (ZINC000003830276-Tessalon, ZINC000003944422-Norvir, ZINC000008214629-Nonoxynol-9, and ZINC000085537014-Cobicistat) were identified through molecular docking and molecular dynamics simulations.

Four potential hub biomarkers most associated with post-transplant renal fibrosis, as well as four potentially effective small molecules, were identified, providing valuable insights for studying the molecular mechanisms underlying post-transplant renal fibrosis and exploring new targets.

Like rheumatoid arthritis (RA) in humans, collagen-induced arthritis (CIA) in mice is associated with not only MHC class II genetic polymorphism but also, to some extent, with other loci including genes encoding Fc gamma receptors (FCGRs) and complement C5. In this study, we used a cartilage antibody-induced arthritis (CAIA) model in which arthritis develops within a 12-h timeframe, to determine the relative importance of FCGRs and C5 (Hc). In CAIA, inhibiting or deleting FCGR3 substantially hindered arthritis development, underscoring the crucial role of this receptor. Blocking FCGR3 also reduced the levels of FCGR4, and vice versa. When employing an IgG1 arthritogenic cocktail that exclusively interacts with FCGR2B and FCGR3, joint inflammation was promptly initiated in Fcgr2b^--  mice but not in Fcgr3^--  mice, suggesting that FCGR3 is sufficient for CAIA development. Regarding complement activation, Fcgr2b⁺⁺ .Hc^** mice with C5 mutated were fully resistant to CAIA, whereas Fcgr2b^-- .Hc^** mice developed arthritis rapidly. We conclude that FCGR3 is essential and sufficient for CAIA development, particularly when induced by IgG1 antibodies. The human ortholog of mouse FCGR3, FCGR2A, may be associated with RA pathogenesis. FCGR2B deficiency allows for rapid arthritis progression and overrides the resistance conferred by C5 deficiency.