Ask about this productRelated genes to: ST6GALNAC5 antibody
- Gene:
- ST6GALNAC5 NIH gene
- Name:
- ST6 N-acetylgalactosaminide alpha-2,6-sialyltransferase 5
- Previous symbol:
- SIAT7E
- Synonyms:
- MGC3184, ST6GalNAcV
- Chromosome:
- 1p31.1
- Locus Type:
- gene with protein product
- Date approved:
- 2003-12-05
- Date modifiied:
- 2016-04-29
Related products to: ST6GALNAC5 antibody
Related articles to: ST6GALNAC5 antibody
- Emphysema and pulmonary fibrosis represent distinct patterns of chronic lung remodeling but may share molecular and cellular abnormalities. In this study, we analyzed public transcriptomic datasets of chronic obstructive pulmonary disease, emphysema, and idiopathic pulmonary fibrosis from the Gene Expression Omnibus database to explore shared disease-related signatures. Weighted gene co-expression network analysis and differential expression analysis were used to identify common molecular alterations, followed by functional enrichment, protein-protein interaction network construction, hub gene screening, immune infiltration analysis, transcription factor prediction, and single-cell RNA-sequencing validation. The integrated analysis revealed overlapping signatures related to cell adhesion, extracellular matrix organization, vascular regulation, immune responses, and epithelial homeostasis. Five hub genes were validated, and ST6GALNAC5 was further prioritized because of its association with sialylation and predominant enrichment in epithelial cells. Given that sialylation has been rarely investigated in pulmonary fibrosis and emphysema, we therefore further investigated ST6GALNAC5-related epithelial sialylation. Experimental validation on tissue samples showed reduced Sambucus nigra agglutinin lectin signals and decreased ST6GALNAC5 expression in lungs with coexisting emphysematous and fibrotic injury. In vitro experiments confirmed that ST6GALNAC5 overexpression attenuated bleomycin-induced epithelial cell injury. Together, these findings identify convergent molecular signatures across emphysematous and fibrotic lung diseases and suggest that impaired epithelial sialylation may represent a previously underappreciated feature of chronic lung remodeling. - Source: PubMed
Wang YuanyingCao KeZhao Wei - Accurate risk stratification is essential for guiding treatment decisions and preventing over treatment of prostate cancer, which remains one of the most prevalent cancers among adult men. While the Gleason score, obtained from prostate biopsies, is routinely used to assess tumor aggressiveness, the biopsy procedure carries risks such as pain, infection, and, in some cases, serious complications such as sepsis. In this study, we proposed an artificial intelligence-based framework that integrates mRNA expression profiles with functional interaction networks to classify prostate cancer patients into low-, medium-, and high-risk groups defined by Gleason scores. The pipeline comprised five steps: (1) data collection from The Cancer Genome Atlas (TCGA), (2) preprocessing of gene expression data, (3) two-stage feature selection to identify informative biomarkers, (4) risk classification using a dual-branch graph neural network (GNN) that combines gene-gene interaction graphs with sample-level expression features, and (5) model interpretation using SHAP to quantify feature contributions. Differentially expressed genes were identified in the High (ASPN, GMNN, PEBP4, C2, KNCK17), Medium (C2, IGSF1, ASPN, CDKN3, AMH), and Low (TNMD, VWA5B2, ST6GALNAC5, CYP3A5, PHGR1) risk groups, underscoring the molecular heterogeneity of disease progression. On an independent held-out test set, the model achieved AUCs of 0.86, 0.88, and 0.95 for the low-, medium-, and high-risk groups, respectively, with an overall accuracy of 80%. These results suggest that combining GNN-based modeling with explainable AI can capture both global and local molecular patterns relevant to tumor aggressiveness. However, as the model was developed and evaluated solely on the TCGA cohort, the findings should be regarded as exploratory, and external validation will be required to establish generalizability. Within these limitations, the proposed framework highlights the potential of molecular profiling and graph-based deep learning to support more precise, potentially less invasive, risk assessment and individualized treatment planning in prostate cancer. - Source: PubMed
Publication date: 2026/09/08
Pirmoradi SaeedVaghefi Moghaddam SevilArdalan MohammadrezaSharifi Bonab Mir MohsenTeshnehlab MohammadZununi Vahed Sepideh - Cardiovascular diseases (CVDs) account for approximately 19.8 million deaths annually, with coronary artery disease (CAD) as a major contributor. Genetic factors play an important role in CVD development. Genetic risk can be attributed to monogenic and polygenic risk variants. Patients with rare, Mendelian monogenic CVDs have been shown to have mutations in many causative genes, including LRP6, MEF2A, CYP27A1, and ST6GALNAC5. - Source: PubMed
Publication date: 2026/08/13
Arif NaumanKhan ImranKhan Taj AliAhmad SajjadNauman FatimaAhmad GulzarIjaz MuhammadAhmad BilalHassan Syed MunawarAfaq SaimaHaq Zia Ul - Glaesserella parasuis (G. parasuis), the causative agent of Glässer's disease in pigs, relies on adhesion to host epithelial cells and induction of inflammation for pathogenesis. However, the potential role of ST6GALNAC5, a host sialyltransferase involved in glycan modification, in G. parasuis infection remains unclear. Using the porcine kidney epithelial cell line LLC-PK1, we investigated the function of the host sialyltransferase gene ST6GALNAC5 during G. parasuis infection. Infection significantly upregulated ST6GALNAC5 mRNA expression. CRISPR/Cas9-mediated knockout of ST6GALNAC5 reduced bacterial adhesion to and invasion of host cells. Compared to wild-type cells, ST6GALNAC5-KO cells exhibited higher proliferation and survival rates post-infection. Transcriptomic analysis revealed that ST6GALNAC5 knockout alone altered host cell pathways: DNA replication and cell cycle pathways were activated, while antigen processing and presentation and Toll-like receptor signaling pathways were suppressed. Consistently, upon infection, knockout cells showed significantly reduced expression of pro-inflammatory cytokines TNF-α, IL-8, IL-6, and IL-11. These findings demonstrate that ST6GALNAC5 promotes G. parasuis infection by enhancing bacterial adhesion, invasion and potentiating host inflammatory responses. Therefore, ST6GALNAC5 may serve as a potential host-directed target for controlling G. parasuis infection. - Source: PubMed
Publication date: 2026/07/14
Zhou HuanhuanChen XuexueZeng JiayiDuan ShijiaLiu HailongZeng XinqiZhang XiaoyuXu KeXie ShengsongChen Hongbo - Early identification of genetically superior animals is important for improving growth performance and accelerating genetic gain in swamp buffalo breeding programs. This study investigated the genetic relationships between growth and body structural traits and evaluated their potential use as early selection indicators in Thai swamp buffalo. Phenotypic records from 1034 animals and genotypic data from 462 buffaloes genotyped with 30,979 SNP markers were analyzed using weighted single-step genomic best linear unbiased prediction (WssGBLUP) and weighted single-step Genome-Wide Association Study (WssGWAS) approaches. Moderate to high heritability estimates were observed for growth traits (0.41-0.59), whereas body structural traits showed low to moderate heritability (0.08-0.27). Positive genetic correlations were identified between growth traits and several structural traits, particularly heart girth, hip height, and body depth. Principal component analysis identified two major components explaining 80.1% of the total phenotypic variation, with the first principal component (PC1) representing overall body size and skeletal development. PC1 also showed relatively high heritability (0.57), indicating its potential utility as a composite selection trait. Genome-wide association analysis identified significant SNPs and candidate genes associated with weaning weight and PC1, including , , , , , , and , which are involved in growth regulation, metabolism, cellular development, and stress-response pathways. These findings demonstrate that body structural traits are genetically associated with growth performance and may serve as effective early selection indicators in genomic breeding programs for Thai swamp buffalo. - Source: PubMed
Publication date: 2026/07/01
Kenchaiwong WootichaiChankitisakul VibuntitaDuangjinda MonchaiLomngam RawinanKuha KechaSintala KitsanathonPothikanit KulphatBoonkum Wuttigrai