UBE2D2 Antibody
- Known as:
- UBE2D2 Antibody
- Catalog number:
- ENZ-007322-M02
- Product Quantity:
- 0.1mg
- Category:
- Antibodies
- Supplier:
- Zyagen
- Gene target:
- UBE2D2 Antibody
Related genes to: UBE2D2 Antibody
- Gene:
- UBE2D2 NIH gene
- Name:
- ubiquitin conjugating enzyme E2 D2
- Previous symbol:
- -
- Synonyms:
- UbcH5B, UBC4
- Chromosome:
- 5q31.2
- Locus Type:
- gene with protein product
- Date approved:
- 1997-03-21
- Date modifiied:
- 2016-03-14
Related products to: UBE2D2 Antibody
Related articles to: UBE2D2 Antibody
- Prostate adenocarcinoma is characterized by substantial inter-patient heterogeneity, limiting the clinical reliability of conventional diagnostic tools, including prostate-specific antigen testing. This limitation underscores the need for robust molecular biomarkers that may complement conventional diagnostic tools, highlighting the urgent need for biomarkers capable of enhancing diagnostic accuracy and enabling more precise risk stratification. In the present study, transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed using an integrative bioinformatics and machine learning pipeline., The proposed workflow was designed as a stepwise and reproducible biomarker prioritization framework in which differential expression analysis, functional enrichment, protein-protein interaction (PPI) based network interpretation, graph-convolutional feature selection, and hybrid ensemble machine learning were sequentially integrated. Differential gene expression analysis was combined with pathway enrichment (Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome), protein-protein interaction network construction, and graph-convolutional feature selection. Multiple machine learning algorithms, including Random Forest, Gradient Boosting Machine, Support Vector Classifier, Artificial Neural Network, and AdaBoost, were systematically evaluated. A hybrid ensemble model integrating Gradient Boosting Machine and Random Forest (GBM+RF) was subsequently developed. Model performance was assessed using accuracy, sensitivity, specificity, and area under the Receiver Operating Characteristic (ROC) and externally validated using the independent GSE14206 dataset. The analysis revealed a coordinated molecular pattern characterized by dysregulated cell cycle activity and enhanced interferon-mediated immune signaling. Protein-protein interaction analysis identified and as highly connected network hub genes within immune-related and cell-cycle-associated modules. Among the evaluated models, the hybrid GBM+RF framework achieved the highest predictive performance on the TCGA dataset, with AUC: 0.9526; Accuracy: 97.49%. External validation using the GSE14206 dataset confirmed the robustness of this model (AUC: 0.9156; Accuracy: 91.53%). These findings support a broader multi-gene candidate signature in prostate adenocarcinoma, in which machine learning prioritized genes such as , , , , , , , and , while and provided complementary network-level biological relevance. The proposed framework provides a robust and transferable strategy for biomarker discovery and precision oncology. - Source: PubMed
Publication date: 2026/07/25
Kurt Hasan AnılKılıçarslan SabireÇiçekliyurt Meliha MerveKılıçarslan Serhat - Although emerging evidence suggests a role for peroxisomes in tumorigenesis, their functions in digestive cancers remain unclear. This study aims to investigate the association between peroxisomes and digestive tract tumors. - Source: PubMed
Publication date: 2026/06/15
Wen JieWang ZhihuiLuo ShuyangAili AbudureyimujiangZou HongliangNiu ShaoqingLiu HaikuanFan WenzheLi Jiaping - Alternative splicing of STAT3 produces two principal isoforms, STAT3α and STAT3β, that differ in transactivation capacity and DNA-binding behavior. Whereas STAT3α is thought to be a transcriptional activator, STAT3β - due to the lack of the transactivation domain - is thought to be a transcriptional repressor. Therefore, the relative abundance of STAT3α and STAT3β molecules within a leukocyte will be critical for immune homeostasis and for gene-therapeutic strategies targeting STAT3. This study investigates whether short-term exposure to IFN-α, IL-6/sIL-6Rα, or IL-10 alters STAT3α/STAT3β stoichiometry in purified human CD4, CD8, CD14 and CD19 cells. We evaluated in healthy donors PBMCs the STAT3α and STAT3β mRNA and protein levels after stimulation with IFN-α, IL-6/sIL-6Rα or IL-10. For mRNA analysis, twelve candidate reference genes were assessed for stability across subsets and stimuli, with identified as the most stable reference gene. We demonstrate that at mRNA level, cytokine treatment induced and mRNA in a subset-dependent manner. mRNA largely paralleled , and crucially, the / mRNA ratio remained constrained within a narrow range. At protein level, STAT3α predominated markedly, yielding a pronounced transcript-protein decoupling. Together, these data indicate that short-term cytokine signaling with IFN-α, IL-6/sIL-6Rα, and IL-10 co-induces STAT3 isoforms without broadly reprogramming their splice balance in primary human leukocytes and underscore the importance of preserving physiological isoform ratios in gene-therapeutic strategies targeting STAT3. These findings suggest that short-term inflammatory signals alone are insufficient to shift STAT3 isoform production, supporting the idea that additional or more prolonged regulatory inputs are required to modulate STAT3 splicing and that physiologically, the STAT3α/STAT3β ratio may be modulated at protein level. - Source: PubMed
Publication date: 2026/04/01
Ott NilsGrimbacher BodoAndreani Virginia - Porcine reproductive and respiratory syndrome virus (PRRSV) poses a major threat to the swine industry worldwide. The viral matrix (M) protein is essential for virion assembly and infectivity. In this study, we found that the M protein is degraded through the ubiquitin-proteasome system. Immunoprecipitation and mass spectrometry identified the host deubiquitinase OTUB1 as an M-binding partner. Overexpression of OTUB1 increased M protein stability and expression levels, while OTUB1 knockdown promoted M degradation. OTUB1 interacted with the C-terminal ectodomain of the M protein and specifically removed K48-linked ubiquitin chains that target proteins for proteasomal degradation. Mechanistically, a catalytically inactive OTUB1 mutant (C91A) retained the ability to stabilize and deubiquitinate M, while a mutant defective in the non-canonical pathway (D88A) lost this function, indicating that OTUB1 acts primarily by sequestering E2 ubiquitin-conjugating enzymes. Furthermore, we identified UBE2D2 as the specific E2 ubiquitin-conjugating enzyme sequestered by OTUB1 to prevent M protein degradation. Depletion of OTUB1 significantly attenuated PRRSV replication in MARC-145 cells and primary porcine alveolar macrophages. OTUB1 specifically targeted the M protein without stabilizing other PRRSV proteins. Importantly, OTUB1-mediated stabilization was conserved across M proteins from diverse PRRSV strains, including PRRSV-1, PRRSV-2, and emerging NADC30-like and NADC34-like variants. Collectively, our findings revealed a host mechanism exploited by PRRSV to enhance replication and identified OTUB1 as a potential target for antiviral development. - Source: PubMed
Publication date: 2026/03/31
Liu BenjinLiang WenqiLi XingyuJiang ShanShi ZiqiLiu NianZhu RongshengDong XuanzhiZhou HanZhou BinCui Jin - The study of iron and iron-handling proteins in the retina is crucial due to their involvement in age-related diseases. In this study, we aimed to evaluate common housekeeping genes to identify the most appropriate reference genes for retinal gene expression analysis in a context of iron excess, considering sex-specific variations. Eight reference genes were selected for RT-qPCR analysis in 20-week-old male and female mice, intraperitoneally injected with iron-dextran versus controls. RefFinder, a web-based tool integrating geNorm, NormFinder, DeltaCq and BestKeeper algorithms, was used to generate a list of candidate genes according to their stability. The top-ranked candidate genes were validated by using them to normalize RT-qPCR expression data from the target genes transferrin receptor (Tfrc) and divalent metal transporter 1 (Dmt1), across all conditions. Four out of eight candidate reference genes presented sex-dependent expression levels and one iron-dependent expression levels. The stability rank resulted in Rpl13a/Ube2d2 and Rplp0/Actb as the most stable candidates in female and male samples, respectively. Mixed male and female samples resulted in Ube2d2/Actb as the most stable candidate genes. In the three analysis, the least stable candidate reference gene was Rn18s. After normalization with the top ranked candidate genes, Tfrc mRNA reductions were validated in the iron administered male, female and sex-mixed groups. Reductions in Dmt1 mRNA levels were only observed in male retinal samples. Therefore, sex significantly influences mRNA levels of both candidate reference genes and iron-dependent genes. This highlights the importance of accounting for sex-specific variations in RT-qPCR analysis using mouse retinas. - Source: PubMed
Publication date: 2025/10/29
Calafat Joan-FeliuGarcia MiquelManich GemmaRojas SantiagoPampalona Judit