Ask about this productRelated genes to: RBM17 antibody
- Gene:
- RBM17 NIH gene
- Name:
- RNA binding motif protein 17
- Previous symbol:
- -
- Synonyms:
- SPF45, MGC14439
- Chromosome:
- 10p15.1
- Locus Type:
- gene with protein product
- Date approved:
- 2004-01-30
- Date modifiied:
- 2014-11-19
Related products to: RBM17 antibody
Related articles to: RBM17 antibody
- Acute myeloid leukemia (AML) is a complex hematological malignancy with high mortality, particularly in the elderly. Current treatments, including chemotherapy, targeted therapies, and emerging immunotherapies such as T cell engager (TCE) and CAR-T, face challenges such as drug resistance. Lactylation, a novel post-translational modification, has emerged as a potential regulator of cellular activities and may play a role in AML pathogenesis. - Source: PubMed
Publication date: 2025/11/27
Dai RuixueSui Guodong - Variable splicing (AS) plays important roles in tumor progression. However, the role of the AS factor RBM17 in the progression of hepatocellular carcinoma (HCC) has not yet been elucidated. We used label-free proteomics, single-cell sequencing (scRNA-seq), high throughput sequencing, flow cytometry (FCM), liquid Chromatography-tandem mass spectrometry (LC‒MS/MS), multiparametric immunofluorescence (mIF) and chromatin immunoprecipitation (Chip), to explore the relationship between RBM17 regulation of HCC cell lipid metabolism and the immune microenvironment. Our findings revealed that RBM17 is significantly overexpressed in HCC tissue and is positively correlated with poor prognosis. We found a positive correlation between RBM17 expression and M2 macrophage infiltration. Mechanistically, RBM17 promotes M2 macrophage infiltration by inducing taurocholic acid (T-CA) production, which is achieved through enhancing exon exclusion of CSAD precursor mRNA. Additionally, RBM17 modulates fatty acid metabolism and CD8 T cell infiltration by regulating exon skipping in HACD3 precursor mRNA. Furthermore, RUNX1 activates RBM17 expression and regulates downstream CSAD/T-CA and HACD3/FFA signaling. Importantly, targeting RBM17 can prevent HCC progression, suggesting its potential as a therapeutic target for HCC. Our findings provide new insights into the mechanisms underlying immune cell infiltration and metabolism in HCC and identify RBM17 as a promising therapeutic target. - Source: PubMed
Publication date: 2025/07/23
Wang ZengbinLiu JiayuLai YitingZhong QingSu QianWu LinqingWang ZhihongFang Zhuting - The liver exhibits extensive circadian regulation among organs. Epidemiological studies have substantiated that disruptions in circadian rhythm constitute a risk factor for the oncogenesis of liver cancer. Nonetheless, the molecular underpinnings of how circadian dysregulation influences liver cancer progression remain elusive. Our research aims to elucidate these mechanisms and develop a predictive model for prognosis and treatment responsiveness. Our multi-omics analysis revealed extensive dysregulation of liver circadian genes (LCGs) in liver cancer. Employing machine learning algorithms, we pinpointed four pivotal dysregulated LCGs. Through the integration of single-cell, bulk, and spatial transcriptomics, we further elucidated the interconnections between LCGs dysregulation and the tumor microenvironment. In vivo and in vitro experiments demonstrated that RBM17, identified as a crucial dysregulated LCG, promotes the progression of liver cancer and cisplatin resistance by facilitating cancer stem cell phenotype. The circadian prognosis scores (CPS), based on these four genes, effectively reflected the prognosis of liver cancer patients and their responses to various therapeutic interventions. Mechanism of Action (MOA) analysis suggested that high CPS level may sensitize tumors to cell cycle-targeted therapies. Collectively, our findings provide new insights into the interplay between liver circadian gene regulation and liver cancer progression, and propose novel therapeutic targets for liver cancer. - Source: PubMed
Publication date: 2025/06/13
Yan JingsongYang XiaoLu JiabinWu ShashaWang YanchenDu YuyangZheng JingyiWang FenfenGao HanYang HuiXi ShaoyanLi Yan - Oral squamous cell carcinoma (OSCC) is one of the most common types of cancer in the head and neck region. In advanced stages of OSCC, chemotherapy is commonly used for treatment, despite some cancer cells having low sensitivity to anticancer drugs. We focused on RBM17/SPF45 as an essential drug-sensitizing factor in the context of malignant cells acquiring chemoresistance. Here, we demonstrate how RBM17 affects anticancer drug resistance in OSCC and we suggest the possible mechanism underlying its effects. After exposing oral cancer cell lines to fluorouracil (5-FU) and cisplatin, but not paclitaxel, the gene and protein expression of RBM17 increased. We found that siRNA-mediated -knockdown of the cell lines gained a significantly higher sensitivity to 5-FU, which was remarkably followed by a decrease in the expression of checkpoint kinase 1 (CHEK1) protein, whereas treatment with a CHEK1 inhibitor did not affect RBM17 protein expression in the oral cancer cell lines. These results indicate that RBM17 is a factor involved in the development of resistance to cytotoxic chemotherapy. We propose the underlying mechanism that RBM17 promotes CHEK1 protein expression in the ATM/ATR pathway, triggering the development of chemoresistance in cancer cells. - Source: PubMed
Publication date: 2025/03/28
Nakahara MiyukaArai RyosukeTokuoka IsaoFukumura KazuhiroMayeda AkilaYashiro MasakazuNakahara Hirokazu - ST-segment elevation myocardial infarction (STEMI) is considered a critical cardiac condition with a poor prognosis. Shortly after STEMI occurs, the increased number of circulating leukocytes including macrophages can lead to the accumulation of more cells in the myocardium, affecting the cardiac immune microenvironment. Identifying serum biomarkers associated with immune infiltration after STEMI is important for diagnosing and treating STEMI. In this work, we aimed to use integrated bioinformatics and machine learning methods to identify new biomarkers. First, candidate genes closely associated with M1 macrophage immune infiltration and STEMI were obtained using the limma package, the CIBERSORTx package, weighted gene coexpression network analysis (WGCNA), and protein‒protein interaction (PPI) networks from the GSE59867 dataset, which comprises peripheral blood mononuclear cell (PBMC) samples. The STEMI patients were subsequently stratified into subtypes using the ConsensusClusterPlus package. Furthermore, using machine learning methods, we identified AKT3, GJC2, HMGCL and RBM17 as the genes with the greatest potential to be associated with STEMI subtypes and with M1 macrophage infiltration during the acute phase of STEMI. Finally, the expression profile and diagnostic value of the four feature genes were validated in the GSE59867 and GSE62646 datasets and in 24 patients using real-time PCR. This study revealed logically and comprehensively that AKT3, GJC2, HMGCL and RBM17, which are derived from PBMCs, could enhance the accuracy of STEMI diagnosis and might provide effective treatment options for STEMI patients. - Source: PubMed
Publication date: 2025/04/01
Li HuiyingZhu QiweiWang WeiBao YuBai YongyiLiu HongbinLeng Wenxiu