Comprehensive Analysis of TSPAN32 Regulatory Networks and Their Role in Immune Cell Biology.

Tetraspanin 32 (TSPAN32), a member of the tetraspanin superfamily, is one of several tumor-suppressing subtransferable fragments located in the imprinted gene domain of chromosome 11p15.5, a critical tumor-suppressor gene region. Although the biology of TSPAN32 remains largely unexplored, accumulating evidence suggests its involvement in hematopoietic functions.

Tetraspanin32 (TSPAN32) is downregulated in rheumatoid arthritis: Evidence from animal models and patients.

This study aimed to investigate the role of TSPAN32, a member of the tetraspanin family, in rheumatoid arthritis (RA). The objective was to assess the expression levels of TSPAN32 in experimental RA models and in RA patient immune cells, exploring its potential as a regulatory factor in RA pathogenesis. The study employed adjuvant-induced arthritis in rats and collagen-induced arthritis (CIA) in mice as experimental models.

Serum and urinary levels of MIF, CD74, DDT and CXCR4 among patients with type 1 diabetes mellitus, type 2 diabetes and healthy individuals: Implications for further research.

Background: Macrophage migration inhibitory factor (MIF) is a highly conserved cytokine with pleiotropic properties, mainly pro-inflammatory. MIF seems to exert its pro-inflammatory features by binding to its transmembrane cellular receptor CD74. MIF also has CXCR4, which acts as a co-receptor in this inflammatory process.

Identification of Poliovirus Receptor-like 3 Protein as a Prognostic Factor in Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) represents an aggressive subtype of breast cancer, with a bad prognosis and lack of targeted therapeutic options. Characterized by the absence of estrogen receptors, progesterone receptors, and HER2 expression, TNBC is often associated with a significantly lower survival rate compared to other breast cancer subtypes. Our study aimed to explore the prognostic significance of 83 immune-related genes, by using transcriptomic data from the TCGA database.