IRF8 Rabbit Polyclonal Antibody
- Known as:
- IRF8 Rabbit Polyclonal Antibody
- Catalog number:
- CYT-3401
- Product Quantity:
- 0.1 mg
- Category:
- -
- Supplier:
- Zyagen
- Gene target:
- IRF8 Rabbit Polyclonal Antibody
Related genes to: IRF8 Rabbit Polyclonal Antibody
- Gene:
- IRF8 NIH gene
- Name:
- interferon regulatory factor 8
- Previous symbol:
- ICSBP1
- Synonyms:
- IRF-8, ICSBP
- Chromosome:
- 16q24.1
- Locus Type:
- gene with protein product
- Date approved:
- 1993-09-09
- Date modifiied:
- 2019-04-23
Related products to: IRF8 Rabbit Polyclonal Antibody
Related articles to: IRF8 Rabbit Polyclonal Antibody
- Short-chain fatty acids (SCFAs) are produced by the gut microbiota as secondary metabolites during fermentation process of dietary fibers. Although SCFAs are beneficial for immuno-related diseases because they regulate the gene expression and functions of myeloid cells, the effects of SCFAs on the development of DCs remain unclear. - Source: PubMed
Publication date: 2026/06/18
Zhao WeitingNagata KazukiAkiyama RisakoYamazaki YukiKouda HirotoMiura RyosukeIshii KentaTokita RyuseiIto NaotoYamasaki NorimasaKaminuma OsamuNishiyama Chiharu - Aging-related molecular reprogramming profoundly influences melanoma progression and therapeutic sensitivity, yet underlying mechanisms remain poorly understood. We constructed a comprehensive multi-omics atlas integrating mutations, transcription, methylation, and copy number variations, utilizing the MOFA algorithm to uncover key age-driving factors. Among 20 factors, Factor6 exhibited significant negative age correlation and survival protection (HR = 0.95, P = 4.494e-05), defined as "RevitalAge Marker (RAM)". Integration of three single-cell RNA sequencing datasets revealed 4,796 RAM+ cells (predominantly endothelial cells and fibroblasts) exerting tumor-suppressive functions through VEGFA-VEGFR2 angiogenic pathways and mitochondrial ATP synthesis, while 7,229 RAM- cells (dominated by malignant cells) exhibited enhanced EMT, hypoxic adaptation, and MAPK signaling activation. RAM+ cells were governed by ZFP42 and IRF8 maintaining anti-tumor immunity, while RAM- cells controlled by ILF2 and ISL1 promoted metastasis and immune evasion, with RAM- malignant cells enriched in patients over 65 years and associated with immunotherapy resistance. Machine learning analysis of RAM-associated genes identified five core signatures (GPR143, ST3GAL4, RAB38, GMPR, FDFT1) demonstrating superior immunotherapy response prediction (AUC = 0.78-1.00). Drug sensitivity profiling revealed ST3GAL4 exhibited strong correlations with AZ628 (pan-RAF inhibitor) and RDEA119 (MEK inhibitor), which was further validated by molecular docking showing excellent binding affinities (binding energies: -8.7 and - 7.2 kcal/mol). This study provides structural evidence for targeted therapeutic strategies in ST3GAL4-overexpressing melanoma and establishes foundations for age-stratified immunotherapy. - Source: PubMed
Publication date: 2026/06/16
Zhou HanxiaoWei BenliangTan WenluShi JiRen ChangyuanZhang JinhaoYang ChanglinZhao ZhengNing Shangwei - Primary cutaneous follicle center lymphomas (PCFCLs) are indolent B-cell neoplasms limited to the skin and effectively managed with local therapies. Distinguishing PCFCL from systemic follicular lymphoma (sFL) with cutaneous involvement (FL_CI) is challenging due to overlapping features. We performed an integrated pathological and genetic analysis of skin samples of 24 PCFCL and 10 FL_CI, which showed subtle pathological changes (decreased BCL2 and CD10, increased CD23 expression in PCFCL), but markedly distinct mutational landscapes. FL_CI exhibited recurrent mutations in chromatin-modifying genes ( 90%, 90%, and 30%), closely resembling sFL. In contrast, PCFCL displayed a more heterogeneous profile, with mutations affecting B-cell development, cell adhesion, and immune evasion. These molecular alterations identified three distinct PCFCL subgroups. Group 1 (44%) harbored mutations in immune evasion genes (, , , and ) and was associated with CD10 negativity, diffuse architecture, and localization in non-photoexposed areas. Group 2 (20%) showed activating and mutations, consistent CD23 and CD10 positivity, and exclusive presentation in sun-exposed sites. Group 3 (20%) shared a similar clinicopathological profile to Group 2 but was defined by mutations. Clonal origin and mutational evolution were studied in five patients, one with synchronous PCFCL and four with sequential samples from two PCFCL and 2 FL_CI. This analysis supports a model of PCFCL oncogenesis driven by circulating progenitors following complex evolutionary patterns, including convergent evolution and greater clonal diversity at relapse. Overall, our study refines the mechanisms driving PCFCL pathogenesis, while providing a framework for PCFCL differential diagnosis and clinical management. - Source: PubMed
Publication date: 2026/05/29
Combalia AndreaVidal-Robau NuriaNadeu FerranLópez CristinaFrigola GerardLopez-Oreja IreneGarcia NoeliaBashiri MelikaMozas PabloLopez-Guillermo ArmandoSalaverria ItziarEstrach TeresaCampo EliasGarcia-Herrera AdrianaAlbero Robert - Interleukin (IL)-33 is a pleiotropic cytokine in the immune system and inflammatory responses, which is involved in cerebral ischemia/reperfusion (I/R) injury. Evidence indicates that IL-33 plays an essential role in macrophage polarization activation, yet the potential molecular mechanisms remain elusive. This study explored the role of IL-33 in the activation of microglia/macrophage-mediated autophagy for cerebral I/R injury via in vitro experiments. - Source: PubMed
Publication date: 2026/01/23
Yong FanLili LinKailiang HuangJinying LinJunping XuXiaohui ZhouYongkai Yang - : Type 1 diabetes (T1D) and multiple sclerosis (MS) are autoimmune, multifactorial, organ-specific disorders mediated by immune cells. Their co-occurrence has been partially attributed to shared genetics and environmental factors. We aimed to dissect the shared genetic architecture between T1D and MS using large-scale genome-wide association studies (GWASs) and colocalization analyses. : We applied a Bayesian colocalization framework to two large-scale GWAS data sets: a T1D study comprising 18,942 cases and 501,638 controls, and an MS GWAS including 14,802 cases and 26,703 controls. : We identified 26 shared colocalizing association signals between T1D and MS. Among them, seven loci (, , , , , , and ) were novel for T1D and two ( and ) for MS. Several signals showed supportive evidence in additional datasets and demonstrated functional annotation characteristics consistent with disease involvement. : Colocalization can be a powerful discovery tool for disorders with co-divided genetic architecture, as prioritizing shared rather than individual causal variants may enhance the detection of novel loci. Our findings indicate that T1D and MS predominantly share general autoimmune susceptibility signals (17/26), rather than disease-specific (private), often with opposite direction of effect (9/26), underscoring their immunological heterogeneity. - Source: PubMed
Publication date: 2026/04/30
Steri MaristellaTestori AlessandroOrrù ValeriaZoledziewska Magdalena