Ask about this productRelated genes to: EXOC4 antibody
- Gene:
- EXOC4 NIH gene
- Name:
- exocyst complex component 4
- Previous symbol:
- SEC8L1
- Synonyms:
- KIAA1699, MGC27170, SEC8, Sec8p
- Chromosome:
- 7q33
- Locus Type:
- gene with protein product
- Date approved:
- 2004-01-08
- Date modifiied:
- 2016-10-05
Related products to: EXOC4 antibody
Related articles to: EXOC4 antibody
- Chemoradiotherapy resistance remains a major obstacle in gastric cancer treatment, primarily due to enhanced DNA repair mechanisms that allow tumor cells to overcome therapeutic damage. Here, we demonstrate that nuclear-localized Exocyst Complex Component 4 (EXOC4) promotes chemoradiotherapy resistance in gastric cancer by enhancing non-homologous end joining-mediated DNA repair. Specifically, p300-mediated acetylation of EXOC4 at lysine 433 induces its nuclear translocation. In the nucleus, EXOC4 facilitates the interaction between PRMT5 and KU70, inducing PRMT5-catalyzed methylation of KU70 at arginine 318. This modification increases the DNA-binding affinity of the KU complex, thereby accelerating double-strand break repair. A peptide targeting EXOC4 K433 inhibits acetylation-dependent nuclear import, reducing KU70 methylation and restoring chemoradiotherapy sensitivity in preclinical models. Collectively, our findings identify the p300-EXOC4-KU70 axis as a critical mediator of chemoradiotherapy resistance and a promising therapeutic target. - Source: PubMed
Publication date: 2026/03/14
Li HaojieSun HaoyuYang XuJiang WenchaoLiu XinyouLi BosenTian ChenyuZhao JunjieRuan YuanyuanSun JieWang Xuefei - Chronic and acute pancreatitis (CP and AP, respectively) are debilitating conditions with significant morbidity and mortality, necessitating a comprehensive understanding of their underlying mechanisms. This study provides a high-resolution, multi-omics investigation into the genetic and immune cell underpinnings of pancreatitis, integrating rare familial CP with a large cohort of patients with AP. Utilizing an integrative approach that combined whole-exome sequencing (WES) from two pediatric CP patients and their family members with single-cell RNA sequencing (scRNA-seq) and bulk transcriptomics from a public AP cohort ( = 119), we identified a shared molecular and cellular pathology. WES of the CP family revealed heterozygous mutations in 12 novel genes, including , , and . Functional enrichment analysis highlighted autophagy, cell adhesion, and vesicle-mediated transport as the key biological processes implicated in the pathophysiology of both conditions. Single-cell profiling of peripheral blood mononuclear cells (PBMCs) from the CP family revealed a marked increase in the proportion of naive B cells and an altered activity of CD8 T cells, suggesting a dysregulated B-cell-mediated immune response. This observation was corroborated in the AP cohort, where CIBERSORT analysis revealed a significant increase in both naive B cells and CD8 T cells correlating with the disease severity. Weighted gene co-expression network analysis (WGCNA) on the AP cohort uncovered 14 gene modules associated with disease progression. These modules were significantly enriched for pathways central to the innate immune response, including complement-dependent cytotoxicity and neutrophil degranulation, providing a molecular link to the observed immune cell infiltration. An artificial intelligence (AI)-driven model incorporating 110 CP family-related genes (GTCPFs) demonstrated exceptional predictive capability (average AUC > 0.84) for AP severity, highlighting the translational potential of our findings. The model identified a robust signature of 17 genes, including , , and , which may serve as novel diagnostic and prognostic biomarkers. Our findings provide a unified view of the pathogenesis of pancreatitis, linking novel genetic variants to specific immune cell and transcriptomic signatures. This integrative approach underscores the critical importance of both genetic and immune factors in CP and AP, identifying potential biomarkers and therapeutic targets and paving the way for personalized medicine in the management of these challenging conditions. - Source: PubMed
Publication date: 2026/01/12
Li FuHuang Jin-XinSun Wen-JieZeng Jing-QingGan Ke-XinGong BiaoJi Jian-MeiChen JianDeng Zhao-HuiXu Dong-Liang - Gut microbiota is a potential therapeutic target for type 2 diabetes (T2D), but its role remains unclear. Investigating causal associations between them could further our understanding of their biological and clinical significance. A two-sample Mendelian randomization (MR) analysis was conducted to assess the causal relationship between gut microbiota and T2D. Key genes and mechanisms were identified through the integration of Genome-Wide Association Studies (GWAS) and cis-expression quantitative trait loci (cis-eQTL) data. Network pharmacology was applied to identify potential drugs and targets. Additionally, gut microbiota community analysis and machine learning models were used to construct a diagnostic model for T2D. MR analysis identified 17 gut microbiota taxa associated with T2D, with three showing significant associations: (odds ratio [OR] = 1.106; 95% confidence interval [CI]: 1.06-1.15; < 0.01; adjusted -value [] = 0.0003), (UCG010 group) (OR = 0.897; 95% CI: 0.85-0.95; < 0.01; = 0.018), and (OR = 1.072; 95% CI: 1.03-1.12; < 0.01; = 0.029). Ten key genes, such as and , were linked to T2D risk. Network pharmacology identified and as target driver genes, with drugs like Dienestrol showing promise. Gut microbiota analysis revealed reduced α-diversity in T2D patients ( < 0.05), and β-diversity showed microbial community differences (R = 0.012, = 0.001). Furthermore, molecular docking confirmed the binding affinity of potential therapeutic agents to their targets. Finally, we developed a class-weight optimized Extreme Gradient Boosting (XGBoost) diagnostic model, which achieved an area under the curve (AUC) of 0.84 with balanced sensitivity (95.1%) and specificity (83.8%). Integrating machine learning predictions with MR causal inference highlighted as a key biomarker. Our findings elucidate the gut microbiota-T2D causal axis, identify therapeutic targets, and provide a robust tool for precision diagnosis. - Source: PubMed
Publication date: 2026/01/21
Jin XinqiChen XuanyiChen HeshanHong Xiaojuan - High-altitude pregnancy presents the complex physiological challenge of fulfilling maternal, placental, and fetal metabolic demands under chronic ambient hypoxia. Highland Andeans exhibit signs of adaptation to high-altitude hypoxia, showing relative protection against altitude-associated fetal growth restriction (FGR) and the positive selection of metabolic genes linked to placental mitochondrial capacity. Not all infants are protected, with both FGR and preeclampsia occurring among highland-resident Andeans. In Andeans, placental metabolic dysfunction is evident. By integrating metabolomic studies of maternal-placental-fetal triads with adaptive genetic signals in the fetal genome, we sought to identify adaptive and maladaptive placental metabolic phenotypes in highland Andeans (La Paz, Bolivia; 3850 m), including normotensive and preeclamptic pregnancies. Widespread differences in metabolite abundance were evident between normotensive and preeclamptic pregnancy across maternal, placental, and fetal compartments. Preeclampsia was characterized by a pronounced accumulation of fatty acid derivatives, specifically medium and long-chain acylcarnitines; these were also associated with low birth weight. Genotype-phenotype association analyses revealed novel links between putatively adaptive fetal haplotypes and placental metabolite abundance. Carriers of specific adaptive fetal haplotypes comprising genes linked to lipid metabolism had a greater abundance of placental short-chain acetyl-carnitine alongside decreased levels of linolenic acid (CPT2/LRP8), lower levels of the medium-chain octanoylcarnitine (EXOC4), and greater abundance of free carnitine (LIPG). Collectively, our study reveals a distinct metabolic phenotype in Andean preeclampsia characterized by incomplete fatty acid oxidation and highlights novel links between putatively adaptive fetal haplotypes and healthy placental metabolic phenotypes. - Source: PubMed
O'Brien Katie AToledo-Jaldin LilianGu WanjunHouck Julie ALazo-Vega LitziMiranda-Garrido ValquiriaYung Hong WYasini HussnaMoore Lorna GReisz Julie ASimonson Tatum SShortt JonathanStalker MargaretD'Alessandro AngeloJulian Colleen G - Multiple genes within the (Disrupted-in-Schizophrenia-1) interactome have been implicated in psychotic disorders, which are characterized by hallucinations, delusions, negative symptoms, and disorganized behavior. However, the genetic associations of specific psychotic symptoms remain poorly understood. - Source: PubMed
Publication date: 2025/09/08
Gutiérrez-Rodríguez AraceliGenis-Mendoza Alma DeliaVillatoro-Velázquez Jorge AmethMedina-Mora María ElenaNicolini Humberto