Ask about this productRelated genes to: CD51 antibody
- Gene:
- ITGAV NIH gene
- Name:
- integrin subunit alpha V
- Previous symbol:
- VNRA, MSK8, VTNR
- Synonyms:
- CD51
- Chromosome:
- 2q32.1
- Locus Type:
- gene with protein product
- Date approved:
- 1988-07-19
- Date modifiied:
- 2016-10-05
Related products to: CD51 antibody
Related articles to: CD51 antibody
- Survival of patients diagnosed with advanced-stage high-grade serous ovarian cancer (HGSOC) varies widely. Understanding the biological and molecular differences between tumors associated with short-term and long-term survival may inform prognosis and treatment. - Source: PubMed
Publication date: 2026/05/23
Smick Alexandra HZurek NataliaTaylor-Harding BarbieKarlan Beth YWalts Ann EGertych ArkadiuszOrsulic Sandra - Triple-negative breast cancer (TNBC) is characterized by its aggressive nature and limited treatment options, which contribute to a poor prognosis. However, the potential role of microRNA-563 (miR-563) in this malignancy remains unclear. This study investigates the tumor-suppressive role of miR-563 and its underlying mechanisms, proposing its potential as a novel biomarker in TNBC. - Source: PubMed
Publication date: 2026/05/21
Li XiaoboQin HuilingZhai JingHu XingzhenLiu Lan - Compared with commercial laying hens, indigenous chicken breeds generally exhibit lower reproductive performance. This study aims to elucidate the impact of abdominal fat deposition on the reproductive performance of indigenous chickens, providing a theoretical basis for the breeding of high-yielding chickens. - Source: PubMed
Publication date: 2026/04/28
Yu HailiangWu LeiWang HaoYuan ChenxuShi JiajiaJi QianyunBai YaruZhu XiaoliGuo LipingZhang ChengChen Xingyong - Cardiac fibrosis is a defining pathological feature of diabetic cardiomyopathy (DCM), and excessive activation of cardiac fibroblasts plays a critical role in regulating cardiomyocyte function through paracrine signaling. CCN1 (cellular communication network factor 1), an extracellular matrix protein involved in intercellular communication, has been suggested to influence cardiac remodeling, although its specific impact on cardiomyocytes in DCM has remained unclear. In this study, we found that CCN1 expression was markedly elevated in cardiac tissues from DCM mouse models and in insulin-resistant cell models, with fibroblasts serving as the primary source. Proteomic analysis and co-culture experiments demonstrated that CCN1 suppressed cardiomyocyte macroautophagy/autophagy. To determine its role in vivo, we generated fibroblast-specific knockout mice and established a DCM model, demonstrating that deletion ameliorated cardiac dysfunction and restored autophagic activity. We further identified ITGAV-ITGB1/integrin αvβ1 as the receptor mediating CCN1 signaling in cardiomyocytes. Molecular dynamics simulations and co-immunoprecipitation experiments confirmed that CCN1 engaged ITGAV-ITGB1/integrin αvβ1 through its cysteine-knot-containing (CT) domain. Mechanistically, this interaction activated the downstream PTK2/FAK-MTOR signaling pathway, leading to inhibition of cardiomyocyte autophagy. Together, these findings reveal a previously unrecognized fibroblast-cardiomyocyte signaling axis in which fibroblast-derived CCN1 drives DCM progression by suppressing autophagy through ITGAV-ITGB1/integrin αvβ1-dependent signaling. This work provides mechanistic insight into the pathogenesis of DCM and identifies CCN1 as a potential therapeutic target for mitigating disease onset and progression.: AAV9: adeno-associated virus serotype 9; ADGRE1/EMR1/F4/80: adhesion G protein-coupled receptor E1; BafA1: bafilomycin A; BSA: bovine serum albumin; C8: compound 8; CCN1: cellular communication network factor 1; CF: cardiac fibroblast; CSA: cross-sectional area; DCM: diabetic cardiomyopathy; EIF4EBP1: eukaryotic translation initiation factor 4E binding protein 1; ELISA: enzyme-linked immunosorbent assay; HE: hematoxylin and eosin; HFD: high-fat diet; HG: high glucose; IR: insulin resistance; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MD: molecular dynamics; MTOR: mechanistic target of rapamycin kinase; NRCM: neonatal rat cardiomyocyte; PDGFRA: platelet derived growth factor receptor alpha; PECAM1/CD31: platelet and endothelial cell adhesion molecule 1; PTK2/FAK: protein tyrosine kinase 2; PTPRC/CD45: protein tyrosine phosphatase receptor type C; RPS6KB1: ribosomal protein S6 kinase B1; S100A4/FSP1: S100 calcium binding protein A4; SQSTM1/p62: sequestosome 1; STZ: streptozotocin; TUNEL: terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling; WGA: wheat germ agglutinin. - Source: PubMed
Publication date: 2026/05/07
Hu Bo-AngZhang LeiSong MingKong Yan-RuJiao Ya-QiongJia XuZhu PingLi Yu-LinTi YunZhang WeiWang Zhi-HaoZhong Ming - BACKGROUND High-grade serous ovarian cancer (HGSOC) is an aggressive malignancy with poor prognosis. This study investigates telomerase-associated genes (TAGs) and their cellular interactions in HGSOC to identify novel prognostic markers. MATERIAL AND METHODS Single-cell RNA sequencing and bulk RNA sequencing data were obtained from the Gene Expression Omnibus and the Cancer Genome Atlas databases. We performed cell type identification, pseudotime trajectory analysis, and CellChat analysis for intercellular communication. A prognostic model was developed using the intersection of TAGs and HGSOC differentially expressed genes (DEGs) through univariate Cox and least absolute shrinkage and selection operator analyses. Survival prognosis, immune infiltration, and drug sensitivity analyses were conducted. RESULTS Thirty cell clusters, 12 cell types, and 2089 TAGs were identified. Pseudotime trajectory analysis suggested 3 distinct cell states during HGSOC progression. CellChat analysis indicated intercellular communication via NAMPT-INSR and SPP1 (ITGAV+ITGB1) signaling pathways. In total, 1204 DEGs were identified between the transcriptomically inferred telomerase-active and -inactive cell populations, along with 1925 DEGs between HGSOC and normal tissue samples. Intersection of these gene sets yielded 768 key TAGs. The prognostic risk model categorized patients into high-risk and low-risk groups, with significant survival differences. Immune infiltration analysis displayed differential abundance of 12 immune cell types between the groups. Drug sensitivity analysis suggested a potential association between the low-risk group and increased sensitivity to certain therapeutic agents. Mutations in TP53 and TTN were frequently observed across both risk groups. CONCLUSIONS This study generates the hypothesis that TAGs are linked to HGSOC progression and yields a candidate prognostic model. - Source: PubMed
Publication date: 2026/04/29
Wang XiaohuaHan ShuyuWang XiGuo Yanwei