Ask about this productRelated genes to: UNC93B1 antibody
- Gene:
- UNC93B1 NIH gene
- Name:
- unc-93 homolog B1, TLR signaling regulator
- Previous symbol:
- -
- Synonyms:
- UNC93
- Chromosome:
- 11q13.2
- Locus Type:
- gene with protein product
- Date approved:
- 2002-01-22
- Date modifiied:
- 2019-04-23
Related products to: UNC93B1 antibody
Related articles to: UNC93B1 antibody
- Spontaneous ovarian hyperstimulation syndrome (OHSS) is closely associated with follicle stimulating hormone receptor (FSHR) functional mutations. We observed that estrildid finches naturally carry the gain-of-function FSHR p.Thr449Ala mutation found in humans, yet do not develop OHSS, thereby providing a novel and system to study aspects of OHSS prevention. Cross-species single-cell analysis revealed that macrophages, the most abundant immune cells in ovaries, play a pivotal role in OHSS progression. Macrophage depletion exacerbates the manifestations of OHSS in both birds and rats. Pharmacological activation of the G protein-coupled receptor 183 (GPR183) in ovarian macrophages, significantly alleviates OHSS symptoms. Mechanistically, GPR183 activation in macrophages maintains ovarian immune homeostasis by downregulating inflammatory factors (Interleukin 1 alpha: IL1A, Interleukin 6: IL6, Interleukin 1 beta: IL1B) and upregulating immune regulators responsive to external stimuli (sphingomyelin phosphodiesterase acid like 3A: Smpdl3a, Macrophage-expressed gene 1: Mpeg1, Epithelial stromal interaction 1: Epsti1, Unc-93 homolog B1: Unc93b1, Apolipoprotein B mRNA editing enzyme catalytic subunit 1: Apobec1). It markedly altered CD44 molecule (CD44)/Syndecan-4 (SDC4) -mediated intercellular communication between macrophages and endothelial/stromal cells, thereby modulating the ovarian microenvironment. This study identifies ovarian macrophages as a key therapeutic target for OHSS and proposes GPR183 as a novel receptor target for precision macrophage-based interventions. - Source: PubMed
Publication date: 2026/05/05
Yan XiaofeiHuang YongjieYang JiabaoMa SuLiu SongsongHuang XuanBrosius JuergenZheng HuapingYao BingChen LiLai ShanshanDeng Cheng - Bladder cancer (BLCA) is a common malignancy of the urinary system, yet the therapeutic relevance of transient receptor potential cation channel subfamily M member 4 (TRPM4) remains unclear. By integrating single-cell and whole-genome transcriptomic data, this study revealed significant transient receptor potential cation channel subfamily M member 4 (TRPM4) overexpression in bladder cancer (BLCA) ( < 0.05), particularly in epithelial cells. Intersection analysis identified 220 candidate genes (7,808 DEGs1, 4,683 DEGs2, and 4,802 key cell module genes). A risk model was constructed comprising six screened prognostic marker genes, namely, protein unc-93 homolog B1 (UNC93B1), family with sequence similarity 193 member B (FAM193B), protein O-glucosyltransferase (POGLUT3), fibrillin-1 (FBN1), microtubule-associated protein 1B (MAP1B), and RUNX family transcription factor 2 (RUNX2). The model demonstrated marked differences among the risk groups. Gene set enrichment analysis revealed significant disparities in key pathways, including the melanoma pathway ( < 0.05). Furthermore, immune infiltration analysis has identified 12 distinct immune cell types, including naive B cells, which showed a < 0.05 distribution. The observed distribution was uneven. In the drug sensitivity analysis, 112 drugs (including WZ3105; < 0.05) showed differential responses, and UNC93B1 showed high positive expression in BLCA tissues (positive cell proportion > 75%). Our studies confirmed that TRPM4 has significant prognostic value and is a potential novel diagnostic and therapeutic target for BLCA. - Source: PubMed
Publication date: 2026/04/13
Zhao QiQin ZitongLiu RunzhangZuo KangweiGuo ChenghaoJing SuoshiLi Weiping - Schizophrenia (SCZ) is a complex psychiatric disorder, and its pathogenic mechanisms are not yet fully understood. The identification of reliable blood biomarkers and molecular subtypes for early diagnosis and effective therapy remains a significant challenge. To address this issue, we utilized a combination of bioinformatics and machine learning (ML) to identify potential biomarkers for SCZ. Our approach involved the integration of 12 different ML algorithms to develop a diagnostic signature based on data from several datasets, including GSE18312, GSE27383, GSE38485, GSE54913, and GSE165604. A nomogram was constructed using these datasets for potential clinical applications. In addition, clustering analysis was performed on SCZ patients using consensus clustering and non-negative matrix factorization (NMF) algorithms. We further evaluated subtype differences in biological functions and immune cells through various methods, such as gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), Proteomaps, and IOBR analyses. Our results identified a diagnostic signature composed of 16 genes (APBB2, CLCN1, SYDE1, PAX5, SNAI1, DAZL, UNC93B1, PLAGL2, HS3ST1, ITPKB, PILRA, BTLA, SWAP70, AZI2, ADM, and AVPR2), which demonstrated robust performance in diagnosing SCZ across eight different datasets. A nomogram based on these genes was created, providing clinical benefits for SCZ patients. Among the identified genes, AZI2 was found to be the most critical, influencing inflammation and immunity. We also identified potential chemical compounds that could target these 16 genes. Unsupervised clustering and NMF algorithms revealed two distinct subtypes of SCZ, each associated with unique immune cell profiles, biological functions, and protein expression levels. In conclusion, this study not only developed a diagnostic signature and a novel nomogram for SCZ but also provided new insights into the subtypes of SCZ. These findings may pave the way for personalized diagnosis and treatment strategies for SCZ patients. - Source: PubMed
Publication date: 2026/03/24
Li ZhijunSun QingLi HaoyuGuan NaiyuNi JingWang JingXu XiaoleiShen YeSun SiyuLi Yan - Gain-of-function (GOF) variants in human TLR7 have recently been reported in 11 cases, six of which were diagnosed with systemic lupus erythematosus (SLE). We have identified the X-linked L840R variant in hemizygosity in a male patient with SLE and in heterozygosity in his clinically asymptomatic mother. The leucine 840 is located at the first amino acid of TLR7 transmembrane domain and is conserved across various species. The L840R substitution is predicted to be deleterious by various scoring algorithms and may therefore affect TLR7 function. Molecular dynamics simulations of TLR7-UNC93B1 interactions revealed that R840 alters nearby amino acids interactions, resulting in increased hydrogen bond between E834 of TLR7 with R157 of UNC93B1. Finally, the L840R TLR7 variant has increased activity compared with WT, as measured with a nuclear factor κB (NF-κB)-specific luciferase reporter upon stimulation with TLR7 agonist R848. Hence, hemizygosity for L840R confers GOF for NF-κB activation and underlies SLE by potentially increasing TLR7 binding to UNC93B1. - Source: PubMed
Publication date: 2026/02/24
Sethumadhavan AiswaryaMariasoosai CharlesYamakawa NatsukoChamberlain NicolasDeardorff Matthew AFunaki ShintaroAsano TakakiCasanova Jean-LaurentTorabifard HediehBoisson BertrandMeffre Eric - Pancreatic ductal adenocarcinoma (PDAC) remains among the most lethal solid tumors, largely due to its intricate and immunosuppressive tumor microenvironment (TME). While single-cell sequencing technologies have begun to unravel the cellular heterogeneity of PDAC, a comprehensive understanding of how genetic determinants influence and are influenced by the TME is still lacking. To bridge this knowledge gap, our study employs an integrated multi-omics approach, incorporating single-cell transcriptomics, genomics, and proteomics, complemented by computational biology and machine learning. We aimed to delineate the core molecular drivers of PDAC pathogenesis, with subsequent functional validation focusing on the role of UNC93B1 in malignant phenotypes. The ultimate goal of this research is to inform the development of precise therapeutic strategies to enhance patient survival and quality of life. - Source: PubMed
Publication date: 2026/02/04
Yang HaoLi YukunSu JingZhang HaiyanZhu WenxinShen KangerXu Wei