Ask about this productRelated genes to: EDN2 antibody
- Gene:
- EDN2 NIH gene
- Name:
- endothelin 2
- Previous symbol:
- -
- Synonyms:
- ET2
- Chromosome:
- 1p34.2
- Locus Type:
- gene with protein product
- Date approved:
- 1989-09-06
- Date modifiied:
- 2016-10-05
Related products to: EDN2 antibody
Related articles to: EDN2 antibody
- Sheep () is a poly-ovulatory species, with litter size varying considerably within and among breeds. Litter size reflects ewe prolificacy, and prolific breeds represent valuable genetic resources for the sheep industry. Belclare is a composite sheep breed developed primarily for reproductive performance and used for meat production. Artificial selection for beneficial alleles related to reproductive traits can create detectable genomic patterns known as selection signatures (SS). This study aimed to detect selection signatures on autosomes and the X chromosome in Belclare sheep and annotate candidate regions associated with reproductive traits. A total of 8421 ewes genotyped with the OvineSNP50 BeadChip were analyzed. Breeds were classified into two groups: prolific (Belclare) and less prolific (Beltex, Charollais, Suffolk, and Texel). Inter-population selection signatures were detected using Cross-Population Extended Haplotype Homozygosity (XP-EHH) and Fixation Index (FST) in 100-kb non-overlapping windows across autosomes (top 1%) and the X chromosome (top 10%). Overlapping signals formed regions ranging from 200-400 kb. Using XP-EHH, regions of 400 kb were detected on OAR3 and OAR5, while one shared SS between XP-EHH and F was identified on OARX. The genes within these regions were associated with reproductive traits in both ewes and rams. X-linked genes, including , and , were associated with sperm motility. Genes involved in ovarian processes, including follicular development, ovulation, and early pregnancy, such as , and , were also identified within the SS regions. Overall, the SS detected in Belclare elucidated the genetic basis underlying its prolificacy relative to less prolific breeds. - Source: PubMed
Publication date: 2026/04/15
Lisboa Rodrigues JuliaSchramm Schenkel FlavioGraciano Braga LarissaAlmeida Rollo de Paz Ana CarolinaNakamura Watanabe RafaelMcHugh NoirinPearse Berry DonaghEli Buzanskas MarcosPrado Munari Danísio - Distant metastasis is the main cause of breast cancer (BC) mortality, yet current prognostic models remain largely tumor-centric and underutilize stromal biology. In this study, we quantified reactive stroma, a collagen-rich and fibrotic fraction of the stromal compartment, as a subtype-independent biomarker of metastatic risk. A retrospective cohort of 182 FFPE primary BC biopsies (2006-2020) was analyzed. Total stroma was quantified on H&E-stained sections and reactive stroma on Masson's trichrome using QuPath with pathologist validation. Cutoffs were defined using maximally selected rank statistics, and overall survival (OS) and metastasis-free survival (MFS) were evaluated by Kaplan-Meier analysis and multivariable Cox regression. RNA sequencing was performed in a subset of cases to characterize associated transcriptomic programs. While total stromal content showed univariate associations with OS and MFS, it was not independently prognostic after adjustment. In contrast, high reactive stroma (cutoff 53.2%) independently predicted shorter MFS (HR = 3.76; < 0.001), irrespective of molecular subtype and clinicopathological variables. Tumors with high reactive stroma exhibited upregulation of extracellular matrix and profibrotic genes (including FN1, OLR1, and EDN2), enrichment of collagen remodeling and TGF-β signaling pathways, and reduced T-cell activation signatures. These findings demonstrate that quantitative assessment of reactive stroma from standard histological stains is a reproducible, subtype-independent biomarker of metastatic risk in BC and can be readily integrated into routine pathology workflows to improve risk stratification. - Source: PubMed
Publication date: 2026/02/26
Barrera Daniela PNúñez Muriel ACerda I ValentinaContreras-Riquelme J SebastiánHenríquez JennyCarrasco GuillermoPereira AlejandraFigueroa VaniaToledo VerónicaChahuan BadirSapunar-Zenteno JorgeRodríguez XimenaMoreno DanielLarach José TomásPrieto BenjamínGarcía PatriciaMoyano LeonorPeña JoséCerda-Infante Javier - BACKGROUND: Meningiomas are the most common central nervous system tumors and are primarily managed through surgical resection and radiation therapy. The development of meningioma is associated with sex steroid hormone-related risk factors. However, anti-sex steroid hormone therapy in meningiomas is still unclear. METHODS: Expression levels of sex steroid hormone receptors were determined in meningioma tissues and cell lines via quantitative PCR. The effects of androgen receptor inhibitor (enzalutamide; ENZ) on meningioma cell growth were investigated via cell viability test, cell cycle analysis and senescence-associated β-galactosidase activity. RESULTS: Androgen receptor (AR) expression was observed in all WHO grade meningiomas. In comparison, progesterone receptor (PR) expression was detected mainly in WHO grade 1 meningiomas but was absent in grade 3 meningiomas. Targeting AR with ENZ significantly inhibited the growth of malignant meningioma cells (HKBMM and IOMM-Lee). Malignant meningioma cells, particularly IOMM-Lee cells, were sensitive to ENZ. ENZ induced cell cycle arrest and increased the sub-G1 population in both malignant meningioma cell lines. Elevated cyclin D1 expression and loss of replicative potential via the reduction of Ki-67 nuclei were also observed. ENZ induced senescence-associated β-galactosidase activity, associated with up-regulation of p21 and down-regulation of the anti-apoptotic protein Mcl-1, in both malignant meningioma cell lines. Additionally, down-regulation of AR-positive cells and AR target genes, including EDN2, TMPRSS2, and KLK3, was observed only in HKBMM cells expressing AR. CONCLUSIONS: Our findings suggest that ENZ induces a senescence-like phenotype in malignant meningioma cells via p21-dependent induction. Lastly, ENZ may serve as a promising targeted therapy for meningiomas, particularly for aggressive subtypes or in cases of recurrence. - Source: PubMed
Publication date: 2026/03/13
Trasaktaweesakul ThanawatAsavaritikrai PunditKhuansonthi PhattraraJaturutthaweechot PitchanunNaewwan NoppornTalabnin KrajangTalabnin Chutima - Pulmonary hypertension (PH) encompasses a clinical spectrum of diseases with high morbidity and poor survival rates. Over the decades, many studies have reported that endothelin-1 (Edn1) plays a role in several subtypes of PH. However, the beneficial effects of its targeted drugs are only found in patients with group 1 pulmonary arterial hypertension but not in group 3 PH, which is related to lung diseases and hypoxia. In the present study, we revealed contrasting findings for Edn1 and its highly similar peptide endothelin-2 (Edn2) in hypoxia-induced PH. Edn2 expression exhibited a distinct and transient pattern under hypoxic conditions. Moreover, epithelial cell-specific Edn2-knockout mice showed exacerbated PH phenotypes compared with wild-type mice. We further demonstrated that acute changes in oxygen levels, but not the low-oxygen condition, were pivotal for Edn2 expression regulation, suggesting that Edn2 is involved in oxygen sensing. Supporting these findings, the specific deletion of Edn2 in sensory-specialised lung cells called pulmonary neuroendocrine cells led to an exacerbated PH phenotype. In conclusion, our study revealed a previously unknown protective role of Edn2 in the development of hypoxia-induced PH. Owing to the contradictory findings between Edn1 and Edn2 in the pathogenesis of lung diseases, careful consideration is required when using endothelin receptor antagonists for PH associated with lung disease and hypoxia. - Source: PubMed
Suzuki YokoRamadhiani RisaRyanto Gusty Rizky TeguhMusthafa AhmadWardhana Donytra ArbyMorimoto MitsuruKo Chemyong JayNagano TatsuyaHara TetsuyaYanagisawa MasashiEmoto Noriaki - Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease globally, yet early diagnosis remains challenging due to conventional biomarker limitations, including UACR variability and reduced eGFR sensitivity. While machine learning shows promise in diabetes prediction, its application to early DKD identification using routine parameters remains underexplored. This study aimed to develop and validate machine learning models incorporating routine blood and biochemical parameters for early DKD prediction. - Source: PubMed
Publication date: 2026/01/28
Yong WeiPeng Dan-DanYe KaiGao Jun-JieCao Ruo-Xue