MXD3 antibody - N-terminal region (ARP30089_T100)
- Known as:
- MXD3 (anti-) - N-terminal region (ARP30089_T100)
- Catalog number:
- arp30089_t100
- Product Quantity:
- USD
- Category:
- -
- Supplier:
- Aviva Systems Biology
- Gene target:
- MXD3 antibody - N-terminal region (ARP30089_T100)
Related genes to: MXD3 antibody - N-terminal region (ARP30089_T100)
- Gene:
- MXD3 NIH gene
- Name:
- MAX dimerization protein 3
- Previous symbol:
- -
- Synonyms:
- MAD3, bHLHc13
- Chromosome:
- 5q35.3
- Locus Type:
- gene with protein product
- Date approved:
- 2002-11-12
- Date modifiied:
- 2015-08-25
Related products to: MXD3 antibody - N-terminal region (ARP30089_T100)
Related articles to: MXD3 antibody - N-terminal region (ARP30089_T100)
- : Prostate cancer (PCa) remains a prevalent malignancy among men, often complicated by recurrence and unfavorable clinical outcomes. Consequently, precise risk stratification and timely clinical intervention are paramount. Initially, we delineated distinct expression profiles of histone modification regulators via unsupervised clustering, identifying PCa subtypes with divergent survival probabilities and biological phenotypes. Subsequently, we sought to develop a prognostic gene signature, derived from the transcriptomic variations among these regulator-defined subtypes, to predict outcomes in PCa patients following radical prostatectomy (RP). : Clinical and transcriptomic data from PCa cohorts were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repositories for comprehensive analysis. Subtypes driven by histone modification regulators were established using unsupervised consensus clustering, followed by in-depth characterization of their molecular features and associated pathways. A risk-scoring model was then developed to evaluate its prognostic efficacy in this patient population. : Stratification based on histone modification regulators yielded four distinct PCa subtypes exhibiting heterogeneous survival outcomes, functional pathways, and genomic mutational landscapes. Following rigorous feature selection, a 21-gene risk signature (HIS_score)-comprising MXD3, CCDC28B, COL11A2, SLC39A5, GPT, DNASE1L2, PIF1, KRTAP5-9, TTLL10, KRTAP5-1, KRTAP5-10, HAGHL, MSLNL, AMH, NKAIN4, CCDC114, SLC9A3, SULT1E1, ALB, SLC6A14, and RPE65-was constructed. Survival analyses demonstrated that patients assigned to the high HIS_score cohort experienced significantly worse clinical outcomes compared to their low-score counterparts. Furthermore, we integrated this signature into a novel clinical nomogram to facilitate individualized prognostic assessments. : Derived from transcriptomic disparities between extreme epigenetic subtypes, the HIS_score and its associated nomogram serve as robust prognostic instruments. These tools effectively encapsulate the downstream transcriptional sequelae of histone modification dysregulation, offering clinicians a valuable framework to accurately predict post-RP outcomes and expedite the formulation of personalized therapeutic strategies. - Source: PubMed
Publication date: 2026/05/28
Gao JialinZhou XueeZuo ZetaoHong JiahongTan YanRong XiaoxiangZhou RuiHuang Zhenhua - Acute pancreatitis (AP) is a severe inflammatory disease where epithelial injury and dysregulated repair are central to pathogenesis, yet the underlying transcriptional mechanisms remain poorly understood. - Source: PubMed
Publication date: 2026/05/01
Jia XianruCui BingbingLiu Xuejin - Clear cell renal cell carcinoma (ccRCC) is characterized by high recurrence and metastatic potential, leading to poor clinical outcomes. There is a critical need to identify reliable prognostic biomarkers and therapeutic targets to improve patient stratification and personalized treatment. - Source: PubMed
Publication date: 2026/01/28
Fu CongSun LinZhou TongBi Yanzhi - Risankizumab has demonstrated remarkable efficacy in the treatment of psoriasis; however, its long-term use faces multiple challenges, including high costs, reduced efficacy over time, and potential safety concerns, such as infections and malignancies. Therefore, identifying potential alternative or adjunctive therapies to risankizumab has significant clinical importance. - Source: PubMed
Publication date: 2026/01/14
Ma YupengZhang ShuminChen XinhongZhang XueZhang Denghai - Prediabetes is one of the main health concerns in public health, and various etiological factors contribute to its onset. This study aimed to evaluate genetic associations and gene-macronutrient interaction with prediabetes-related metabolites to understand how genetic variation and dietary intake contribute to dysglycemia. We analyzed a total of 482 self-identified Mexican American participants recruited from Starr County, Texas in 2018-2019. Untargeted metabolomic profiling was performed using LC-MS. Nutrient densities of six macronutrients were derived from a 106-item food frequency questionnaire. Genetic associations for each metabolite were tested using Generalized linear Mixed Model Association Tests (GMMAT). Gene-macronutrient interactions on prediabetes-associated metabolites were assessed with the Mixed Model Association Test for GEne-Environment Interaction (MAGEE). Age, gender, and BMI were included as covariates in all association tests. Among 308 named and 2,471 unnamed metabolites, 17 novel variant-metabolite pairs were discovered, including rs10947898 in associated with diacylglycerol DG32:1(p-value: 8.95E-09). Among 145 named and 687 unnamed metabolites after filtering, gene-macronutrient interaction analyses identified seven named metabolites, including a variant(rs111251222) in that interacted with monounsaturated fat to influence eicosadienoic acid levels (Interaction p-value: 9.88E-09). Prediabetes and nutrient-related metabolites in Mexican Americans showed significant genetic associations and gene-nutrient interactions. - Source: PubMed
Publication date: 2025/12/16
Chung ShinhyeEvans CharlesBurant Charles FChen HanYu BingAguilar DavidBrown Eric LHanis Craig LJun Goo