Ask about this productRelated genes to: NUDT13 antibody
- Gene:
- NUDT13 NIH gene
- Name:
- nudix hydrolase 13
- Previous symbol:
- -
- Synonyms:
- DKFZp586P2219
- Chromosome:
- 10q22.2
- Locus Type:
- gene with protein product
- Date approved:
- 2002-07-22
- Date modifiied:
- 2016-10-05
Related products to: NUDT13 antibody
Related articles to: NUDT13 antibody
- Osteosarcoma typically arises during adolescence, posing a significant challenge. Despite comprehensive treatment strategies encompassing surgery, radiation therapy, and chemotherapy, which can notably enhance long-term survival rates among osteosarcoma patients, the 5-year survival rate for metastatic cases remains discouragingly low. Consequently, early diagnosis and prompt intervention are paramount in improving the prognosis of patients afflicted with this condition. Metabolic reprogramming holds paramount significance in the initiation and progression of tumors. In this meticulous investigation, we devised a risk prediction model that encompasses seven pivotal nucleotide metabolism-related genes: MYC, MUC1, IMPDH1, SAMHD1, NUDT13, UCK2, and NUDT16. This model was formulated leveraging six advanced machine learning algorithms. The results demonstrated that the risk prediction model exhibited robust prognostic predictive capability. Notably, patients identified with a high-risk phenotype exhibited a significantly lower long-term survival rate, coupled with elevated expression of immunosuppressive genes, highlighting the importance of metabolic reprogramming in influencing both survival outcomes and immune status. The multivariate Cox regression analysis confirmed that our model serves as an independent prognostic indicator, significantly impacting the long-term prognosis of osteosarcoma patients. Subsequently, we developed and validated a nomogram, which accurately predicts 1-, 3-, and 5-year survival rates for these patients. Furthermore, we compared chemosensitivity between high- and low-risk groups, gaining valuable insights into potential therapeutic differences. In conclusion, this model demonstrates superior prognostic predictive capability and holds promise in guiding chemotherapy treatment strategies for osteosarcoma patients, thereby enhancing treatment outcomes. - Source: PubMed
Publication date: 2026/05/02
Ju SongliTao LuLi XuyanHuang NijiaoKe Xixian - Metabolic dysregulation has been implicated as a key factor in colorectal cancer (CRC) initiation, however, the underlying driving forces and mechanisms remain poorly understood. Herein, transcriptome profiling of paired early-stage CRCs and adenomas identifies Nudix hydrolase 13 (NUDT13) as a critical suppressor. Elevated NUDT13 expression impedes the proliferation of CRC cells under hypoxic conditions and markedly inhibits CRC initiation by upregulating PKM1. Mechanistically, NUDT13 directly binds and stabilizes PKM1 protein by reducing its poly ADP-ribosylation (PARylation), which is catalyzed by PARP1 at E275/D281/E282/E285/D296, thereby inducing an oxidative phosphorylation (OXPHOS) phenotype in CRC cells. Moreover, spatiotemporal knockout of Nudt13 enhances intestinal tumorigenesis in mice, which can be significantly suppressed by PARP1 inhibitor Olaparib. Notably, residues E245/E248/E249 within the Nudix box motif of NUDT13 are essential for PKM1 PARylation, and a mimic peptide derived from this motif is sufficient to stabilize PKM1 protein and robustly inhibit CRC tumorigenesis. Collectively, this study reveals a previously unknown PARylation-dependent mechanism that regulates PKM1 protein stability and switches the metabolic pathway of CRC cells, providing a promising target for CRC treatment. - Source: PubMed
Publication date: 2025/02/08
Lin JinlongYin YixinCao JinghuaZou BingxuHan KaiChen YufanLi SiyuHuang CijunChen JieweiLv YongruiXu ShuidanXie DanWang Fengwei - Colorectal cancer (CRC) involves epigenetic alterations. Irregular gene-methylation alteration causes and advances CRC tumor growth. Detecting differentially methylated genes (DMGs) in CRC and patient survival time paves the way to early cancer detection and prognosis. However, CRC data including survival times are heterogeneous. Almost all studies tend to ignore the heterogeneity of DMG effects on survival. To this end, we utilized a sparse estimation method in the finite mixture of accelerated failure time (AFT) regression models to capture such heterogeneity. We analyzed a dataset of CRC and normal colon tissues and identified 3406 DMGs. Analysis of overlapped DMGs with several Gene Expression Omnibus datasets led to 917 hypo- and 654 hyper-methylated DMGs. CRC pathways were revealed via gene ontology enrichment. Hub genes were selected based on Protein-Protein-Interaction network including SEMA7A, GATA4, LHX2, SOST, and CTLA4, regulating the Wnt signaling pathway. The relationship between identified DMGs/hub genes and patient survival time uncovered a two-component mixture of AFT regression model. The genes NMNAT2, ZFP42, NPAS2, MYLK3, NUDT13, KIRREL3, and FKBP6 and hub genes SOST, NFATC1, and TLE4 were associated with survival time in the most aggressive form of the disease that can serve as potential diagnostic targets for early CRC detection. - Source: PubMed
Publication date: 2023/12/13
Hajebi Khaniki SaeedehShokoohi FarhadEsmaily HabibollahKerachian Mohammad Amin - Colorectal cancer (CRC) involves epigenetic alterations. Irregular gene-methylation alteration causes and advances CRC tumor growth. Detecting differentially methylated genes (DMGs) in CRC and patient survival time paves the way to early cancer detection and prognosis. However, CRC data including survival times are heterogeneous. Almost all studies tend to ignore the heterogeneity of DMG effects on survival. To this end, we utilized a sparse estimation method in the finite mixture of accelerated failure time (AFT) regression models to capture such heterogeneity. We analyzed a dataset of CRC and normal colon tissues and identified 3,406 DMGs. Analysis of overlapped DMGs with several Gene Expression Omnibus datasets led to 917 hypo- and 654 hyper-methylated DMGs. CRC pathways were revealed via gene ontology enrichment. Hub genes were selected based on Protein-Protein-Interaction network including , , , , and , regulating the Wnt signaling pathway. The relationship between identified DMGs/hub genes and patient survival time uncovered a two-component mixture of AFT regression model. The genes , , , , , , and and hub genes , , and were associated with survival time in the most aggressive form of the disease that can serve as potential diagnostic targets for early CRC detection. - Source: PubMed
Publication date: 2023/05/29
Khaniki Saeedeh HajebiShokoohi FarhadEsmaily HabibollahKerachian Mohammad Amin - Uterine fibroids affect up to 77% of women by menopause and account for up to $34 billion in healthcare costs each year. Although fibroid risk is heritable, genetic risk for fibroids is not well understood. We conducted a two-stage case-control meta-analysis of genetic variants in European and African ancestry women with and without fibroids classified by a previously published algorithm requiring pelvic imaging or confirmed diagnosis. Women from seven electronic Medical Records and Genomics (eMERGE) network sites (3,704 imaging-confirmed cases and 5,591 imaging-confirmed controls) and women of African and European ancestry from UK Biobank (UKB, 5,772 cases and 61,457 controls) were included in the discovery genome-wide association study (GWAS) meta-analysis. Variants showing evidence of association in Stage I GWAS ( < 1 × 10) were targeted in an independent replication sample of African and European ancestry individuals from the UKB (Stage II) (12,358 cases and 138,477 controls). Logistic regression models were fit with genetic markers imputed to a 1000 Genomes reference and adjusted for principal components for each race- and site-specific dataset, followed by fixed-effects meta-analysis. Final analysis with 21,804 cases and 205,525 controls identified 326 genome-wide significant variants in 11 loci, with three novel loci at chromosome 1q24 (sentinel-SNP rs14361789; = 4.7 × 10), chromosome 16q12.1 (sentinel-SNP rs4785384; = 1.5 × 10) and chromosome 20q13.1 (sentinel-SNP rs6094982; = 2.6 × 10). Our statistically significant findings further support previously reported loci including SNPs near , and /. We report evidence of ancestry-specific findings for sentinel-SNP rs10917151 in the / locus ( = 1.76 × 10). Ancestry-specific effect-estimates for rs10917151 were in opposite directions (P-Het-between-groups = 0.04) for predominantly African (OR = 0.84) and predominantly European women (OR = 1.16). Genetically-predicted gene expression of several genes including in vagina ( = 4.6 × 10), in esophageal mucosa ( = 8.7 × 10), in multiple tissues including subcutaneous adipose tissue ( = 3.3 × 10), and in skeletal muscle tissue ( = 5.8 × 10) were associated with fibroids. The finding for was supported by SNP-based summary Mendelian randomization analysis. Our study suggests that fibroid risk variants act through regulatory mechanisms affecting gene expression and are comprised of alleles that are both ancestry-specific and shared across continental ancestries. - Source: PubMed
Publication date: 2019/06/12
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