Ask about this productRelated genes to: GTPBP4 antibody
- Gene:
- GTPBP4 NIH gene
- Name:
- GTP binding protein 4
- Previous symbol:
- -
- Synonyms:
- CRFG, NGB, FLJ10690, FLJ10686, NOG1
- Chromosome:
- 10p15.3
- Locus Type:
- gene with protein product
- Date approved:
- 2003-08-11
- Date modifiied:
- 2019-01-21
Related products to: GTPBP4 antibody
Related articles to: GTPBP4 antibody
- Colorectal cancer remains a leading cause of cancer death globally, creating an urgent need for novel therapeutic targets. Here, we investigate the expression, function, and regulatory mechanism of GTP-binding protein 4 (GTPBP4) in colorectal cancer. Analysis of The Cancer Genome Atlas (TCGA) colon adenocarcinoma (COAD) dataset showed that GTPBP4 is upregulated in colorectal tumors relative to normal mucosa, and high GTPBP4 expression correlates significantly with reduced overall survival. We observed a strong positive correlation between GTPBP4 and MYC expression across the cohort, leading us to generate stable GTPBP4-knockdown HCT116 and SW620 cells, as well as isogenic rescue lines overexpressing MYC. GTPBP4 depletion markedly suppressed cell proliferation, as determined by Cell Counting Kit-8 (CCK-8), 5-ethynyl-2'-deoxyuridine (EdU) incorporation, and clonogenic assays. Mechanistically, GTPBP4 knockdown reduced both MYC mRNA and protein levels, accelerated MYC protein turnover, and increased MYC ubiquitination (all P < 0.05), indicating dual transcriptional and post-translational regulation. Concurrently, GTPBP4 silencing downregulated key glycolytic enzymes and decreased glycolytic flux, effects that were fully reversed by ectopic MYC expression (P < 0.05). In a subcutaneous xenograft model, GTPBP4 knockdown significantly inhibited tumor growth, reduced MYC and Ki-67 proliferation antigen (Ki-67) expression, and blunted glycolytic metabolism (P < 0.01 or P < 0.05). Co-expression of MYC restored all these parameters and reversed the enhanced MYC ubiquitination (P < 0.05). Collectively, our data demonstrate that GTPBP4 sustains MYC expression through dual mechanisms to drive glycolytic reprogramming and colorectal cancer growth, identifying the GTPBP4/MYC/glycolysis axis as a promising therapeutic target. - Source: PubMed
Publication date: 2026/05/15
Zhao KaiWei JiayuShen YingJiang AnqiGu MingyangDeng Jianzhong - We employed an integrated bioinformatics screening approach along with Mendelian randomization (MR) analysis to explore potential genetic targets for varicose veins of lower extremities (VVs) and identify potential treatment options for VVs. Differential expression analysis was conducted using R software to identify differentially expressed genes (DEGs) of VVs from the Gene Expression Omnibus database. Weighted gene co-expression network analysis (WGCNA) was performed to identify co-expression networks. Functional enrichment analyses were conducted for the identified genes. A protein-protein interaction network was constructed to analyze the interactions among the identified genes. Additionally, genome-wide association studies data for VVs were downloaded for MR analysis. Various methods, including inverse-variance weighted, were employed to assess potential causal associations with VVs risk, followed by sensitivity analysis. The DEGs identified from the VVs Gene Expression Omnibus dataset included 180 upregulated genes and 335 downregulated genes. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis revealed that the downregulated DEGs were significantly associated with nuclear protein-containing complexes and nucleic acid binding (P < .05). WGCNA highlighted a highly significant "turquoise" module comprising 78 downregulated genes (P = 2e - 04). The protein-protein interaction network analysis of the significant DEGs and the WGCNA "turquoise" module identified 224 nodes and 491 edges, uncovering several hub genes such as BRCA1, NCBP2, GTPBP4, HDAC2, KHDRBS1, and HNRNPR. Detailed functional enrichment analysis indicated involvement in tumor-like cellular proliferation and differentiation processes, including protein acetylation, RNA splicing, and metabolic processes. MR analysis revealed a causal association between the tumor-related gene Ecto-NOX disulfide-thiol exchanger 2 (ENOX2) and the risk of VVs, with a statistical significance (odds ratio: 1.0016; 95% confidence interval: 1.0003-1.0029; P = .015) according to inverse-variance weighted analysis. Sensitivity analysis confirmed the absence of heterogeneity and horizontal pleiotropy in the observed associations (P > .05). "Leave-one-out" validation analysis did not indicate any changes. Our study unveils the involvement of ENOX2 and the related mechanisms in the pathogenesis of VVs, suggesting their potential as genetic targets for treatment. - Source: PubMed
He QiuruiZhang XiaohongTao ChenChen ChenmingYan Weiming - BACKGROUND: Migraine and Meniere’s disease (MD) show high clinical comorbidity, shared symptoms such as vertigo and overlapping mechanisms like neurogenic inflammation suggest common pathophysiology. However, the core immunogenetic drivers underlying this comorbidity, particularly at cellular resolution, remain uncharacterized. METHODS: We integrated cross-trait genetic analyses using summary statistics from large genome-wide association study (GWAS) and single-cell expression quantitative trait locus (sc-eQTL), followed by Bayesian colocalization. Candidate genes were validated with independent single-cell RNA sequencing (scRNA-seq) and their therapeutic potential was assessed via drug repurposing and Phenome-wide association studies (PheWAS). RESULTS: We identified a significant genetic correlation (rg = 0.226) and 4 high-confidence shared prioritized genes (cell division cycle 42 [CDC42], dicarbonyl and L-xylulose reductase [DCXR], GTP binding protein 4 [GTPBP4], sterol-c5-desaturase [SC5D]). Single-cell analyses confirmed their cell-type-specific dysregulation. Drug target interrogation identified existing pharmacological agents interacting with these genes, including Lorlatinib for CDC42. PheWAS highlighted distinct safety profiles for each target, informing future therapeutic development priorities. CONCLUSIONS: This study reveals a shared immunogenetic basis between migraine and MD at single-cell resolution, providing novel targets and a translational roadmap for therapeutic development. CLINICAL TRIAL: Not applicable. - Source: PubMed
Publication date: 2026/04/18
Hu XiaoWang YangYu Si-JiePan Chun-YaLiang Bing-YuJiang Shang-ShangChen Shan-WenHan Yan-Xun - Production of the eukaryotic ribosomal subunits (40S and 60S) is a highly dynamic process in which numerous assembly factors (AFs) coordinate structural rearrangements of pre-ribosomal complexes to achieve their mature, functional architectures. Across the domains of life, GTPases leverage their functions as molecular switches to induce conformational changes that drive key steps in subunit maturation. Three GTPases, GTPBP4, GNL2, and GNL3, have been detected in nucleolar/nucleoplasmic human pre-60S complexes. Here, we compositionally analyze the pre-ribosomal particles associated with each of these GTPases and demonstrate the requirement of these enzymes, and their abilities to bind and hydrolyze GTP, for distinct steps in pre-ribosomal RNA processing. We further reveal that the GNL3 paralog, GNL3L, also associates with pre-ribosomes, and we map GNL3L binding sites on pre-rRNAs as well as identifying RNA contact sites on GNL3L. Lack of GNL3L impairs synthesis of the 60S rRNAs and expression of GTPase-inactive GNL3L causes defects in early steps of pre-rRNA processing. Impaired GTP hydrolysis by GNL3L leads to its accumulation on pre-60S particles, together with other AFs with proximal binding sites. Our data further demonstrate that the GTPase activity of GNL3L is required for maintaining 60S subunit levels, protein synthesis, and cellular proliferation. - Source: PubMed
Thomé Chairini CLemus-Diaz NicolasBloch von Blottnitz Katja ITagnères SophieKlein Helmkamp MerleHonemann-Capito MonaHackert PhilippMoshkovskii SergeiLenz ChristofBohnsack Markus TUrlaub HenningBohnsack Katherine E - Breast cancer is the most common cancer among women, and metastasis to the lung is associated with poor prognosis. Reliable biomarkers for predicting lung metastasis are urgently needed to improve early detection and clinical decision-making. This study used microarray data sets comprising gene expression profiles and clinical data from primary breast cancer patients who were followed up for lung metastasis outcomes. High-throughput screening combined with Venn diagram analysis was used to identify common candidate probes, and the least absolute shrinkage and selection operator method were used to select 11 genes for model development. Logistic regression was used to construct predictive models, and the final risk signature consisted of 10 candidate genes (CDK19, GLUD1, GTPBP4, HLCS, HYI, KCND3, MAP2K1, NMUR1, PRKD3, and SLC16A3). The model achieved strong performance in training and validation cohorts (areas under the curve >0.87) and generalized to the independent METABRIC data set (area under the curve = 0.706). Subset analyses restricted to patients with early-stage disease confirmed that the signature retained predictive value. Kaplan-Meier analyses showed that patients with high-risk scores had shorter lung metastasis-free survival, recurrence-free survival, and overall survival. Multivariate Cox analysis confirmed that the risk signature provided independent predictive information from clinical variables. In conclusion, the risk signature accurately identifies patients with breast cancer at risk of lung metastasis, enabling clinicians to better assess risk and tailor effective treatment strategies. - Source: PubMed
Publication date: 2025/11/27
Nguyen Thanh DatNguyen Quynh-Mai ThiNguyen Tuong VanBui Phuong ThiNguyen Kim Nhuong ThiNguyen Minh Nam