Ask about this productRelated genes to: RBM11 Blocking Peptide
- Gene:
- RBM11 NIH gene
- Name:
- RNA binding motif protein 11
- Previous symbol:
- -
- Synonyms:
- -
- Chromosome:
- 21q11.2
- Locus Type:
- gene with protein product
- Date approved:
- 2000-05-23
- Date modifiied:
- 2016-10-05
Related products to: RBM11 Blocking Peptide
Related articles to: RBM11 Blocking Peptide
- This study investigated the biological functions and molecular mechanisms of RNA-binding motif protein 11 (RBM11) in bladder cancer (BCa) progression. Integrated bioinformatics analysis of the TCGA database and validation in clinical tissues revealed that RBM11 is significantly upregulated in BCa and positively correlated with advanced tumor stage, poor prognosis, and epithelial-mesenchymal transition (EMT). RBM11 knockdown effectively suppressed migration, invasion, proliferation, and chemoresistance of BCa cells, whereas RBM11 overexpression produced opposite effects. Mechanistically, RBM11 promotes GNPDA1 expression by regulating alternative splicing of GNPDA. Furthermore, GNPDA1 directly interacts with PKM2 and inhibits its ubiquitin-proteasome-mediated degradation, thereby stabilizing PKM2 protein levels, enhancing glycolysis, and promoting malignant progression of BCa. Collectively, these findings indicate that RBM11 drives malignant progression of BCa through the GNPDA1-PKM2 axis, enhancing glucose metabolism reprogramming and EMT process, suggesting that RBM11 may be a potential therapeutic target for BCa. - Source: PubMed
Publication date: 2026/03/17
Tong HangLi TinghaoZhu JunlongDou QianYu QiongSun YanHe Weiyang - Sheep and goats, among the earliest domesticated animals, hold significant historical importance in Chinese animal husbandry. The rapid advancement of modern biotechnology has rendered genome wide association studies (GWAS) and selection signature analyses have become indispensable tools in livestock genetic research. This review summarizes recent progress in the application of these methods to sheep and goat breeding in China, analyzes existing challenges in the research, and suggests potential research strategies. GWAS and selection signature analyses have identified key genomic regions associated with agronomically important traits. Genes such as LHX2, FGF12 and Notch3 are associated with hair follicle growth and development, while RBM11, SMARCA5 and GAB1 are linked to body size in sheep. Additionally, BMPRIB has been identified as a determinant of reproductive performance and growth rate in both sheep and goats. Despite progress, several challenges remain, including incomplete reference genomes, insufficient phenotypic data, inadequate algorithms, and a lack of functional validation and practical application of findings. Future work must prioritize genomic refinement, the integration of multi-omics, and the development of algorithm. Enhanced international collaboration is crucial to deciphering the genetic basis of key traits, thereby advancing global industry. These initiatives will enable highly precise breeding strategies. Through precise identification and selection of individuals with desirable genetic traits, breeders can significantly enhance the efficiency of genetic improvement. Using Hua sheep 50k chip as an example, it effectively identifies individuals with superior reproductive genes (such as BMPRIB) at an early stage, increases the lambing rate by 27.7%, accelerates the propagation of high-quality breeding groups, provides a large number of breeding sheep with excellent genetic traits for the global sheep industry, and improve the overall quality of germplasm. This will ultimately enhance the sustainable development of global sheep and goat production. - Source: PubMed
Publication date: 2025/10/22
Han MingxuanRong YoujunMa BingjieWang XinleAo XiaofangShang FangzhengSu RuiWang RuijunZhang Yanjun - Acute myeloid leukemia (AML) is the most common type of leukemia in adults, primarily caused by multiple gene mutations and abnormal gene expression. Molecular heterogeneity among AML patients can lead to the variation of treatment outcomes, and the prognostic significance of genetic disruptions is crucial for treatment decisions. Therefore, in this study, we intended to identify novel potential prognosis-related genes in AML patients. This study comprehensively assessed transcriptomic data of primary AML patients from TARGET and BEAT-AML cohorts from the TCGA database. The common differentially expressed mRNAs (DEmRNAs) of the study groups were determined and screened to identify genes that indicated a correlation between their expression levels and the overall survival (OS) of AML patients. Moreover, RT-PCR was used to compare the expression of the identified prognosis-related genes between AML patients and non-leukemic groups to confirm the obtained bioinformatics data. The analysis resulted in the identification of 39 common significant DEmRNAs in both cohorts. Moreover, among the identified common genes, the expression levels of two genes, MME and RBM11, significantly correlated with the OS of AML patients; it was revealed that there was a significant negative correlation between a higher survival rate in AML patients and the lower expression of MME (log-rank P = 1.3*10 and Hazard Ratio (HR = 1.38 (1.22-1.56)) and RBM11 (log-rank P = 0.016 and HR = 1.25 (1.04-1.5)). Furthermore, RT-PCR data confirmed the expected differential expression of identified genes between patient and control samples. In conclusion, our investigation resulted in the identification of two potential prognosis-related genes that can be used in further prognostic evaluation studies. - Source: PubMed
Publication date: 2025/07/23
Shafiei Fatemeh SadatAbroun SaeidVahdat SadafAnoushirvani Ali ArashRafiee Mohammad - Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, fibrotic interstitial pneumonia with a poor prognosis and a pathogenesis that has not been fully elucidated. Oxidative stress is closely associated with IPF. In this research, we aimed to identify reliable diagnostic biomarkers associated with the oxidative stress through bioinformatics techniques. The gene expression profile data from the GSE70866 dataset was retrieved from the gene expression omnibus (GEO) database. We extracted 437 oxidative stress-related genes (ORGs) from gene set enrichment analysis (GSEA). The GSE141939 dataset was used for single-cell RNA-seq analysis to identify the expression of diagnostic genes in different cell clusters. A total of 10 differentially expressed oxidative stress-related genes (DE-ORGs) were screened. Subsequently, SOD3, CD36, ACOX2, RBM11, CYP1B1, SNCA, and MPO from the 10 DE-ORGs were identified as diagnostic genes based on random forest algorithm with randomized least absolute shrinkage and selection operator (LASSO) regression. A nomogram was constructed to evaluate the risk of disease. The decision curve analysis (DCA) and clinical impact curves indicated that the nomogram based on these seven biomarkers had extraordinary predictive power. Immune cell infiltration analysis results revealed that DE-ORGs were closely related to various immune cells, especially CYP1B1 was in positive correlation with monocytes and negative correlation with macrophages M1. Single-cell RNA-seq analysis showed that CYP1B1 was mainly associated with macrophages, and SNCA was mainly associated with basal cells. CYP1B1 and SNCA were diagnostic genes associated with oxidative stress in IPF. - Source: PubMed
Publication date: 2024/02/14
Du XianglinMa ZhenXing YanqingFeng LitingLi YupengDong ChuanchuanMa XinkaiHuo RujieTian Xinrui - Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal lung disease with limited treatment options. N6-methyladenosine (m6A) is a reversible RNA modification and has been implicated in various biological processes. However, there are few studies on m6A in IPF. This project mainly explores the prognostic value of m6A-related genes as potential biomarkers in IPF, in order to establish a set of accurate prognostic prediction model. In this study, we used GSE28042 dataset in GEO database to screen out 218 m6A-related candidate genes with high IPF correlation and high differential expression through differentially expressed gene analysis, WGCNA and m6A correlation analysis. The genes associated with the prognosis of IPF were screened out by univariate Cox regression analysis, LASSO analysis, and multivariate Cox regression analysis, and the multivariate Cox model of prognostic risk of related genes was constructed. We found that RBM11, RBM47, RIC3, TRAF5 and ZNF14 were key genes in our model. Finally, the prognostic prediction ability and independent prognostic characteristics of the risk model were evaluated by survival analysis and independent prognostic analysis, and verified by the GSE93606 dataset, which proved that the prognostic risk model we constructed has a strong and stable prediction efficiency. - Source: PubMed
Publication date: 2022/11/29
Wang ZhiqiangShen LanyuWang JunjieHuang JiaqianTao HuiminZhou Xiumin