Ask about this productRelated genes to: MRPL37 antibody
- Gene:
- MRPL37 NIH gene
- Name:
- mitochondrial ribosomal protein L37
- Previous symbol:
- -
- Synonyms:
- RPML2, MRP-L2
- Chromosome:
- 1p32.3
- Locus Type:
- gene with protein product
- Date approved:
- 2001-02-28
- Date modifiied:
- 2016-10-05
Related products to: MRPL37 antibody
Related articles to: MRPL37 antibody
- Mitochondrial ribosomal proteins of the large subunit (MRPLs) are critical for mitochondrial function and cellular energy metabolism. However, the role of the MRPL family in hepatocellular carcinoma (HCC) remains poorly understood. Here, we leveraged The Cancer Genome Atlas (TCGA) liver cancer data to develop a subtype classification and prognostic model based on the MRPL family genes, identifying MRPL37 as a key gene associated with HCC progression. Clinically, MRPL37 upregulation is associated with HCC progression and poor prognosis. Functionally, MRPL37 knockdown significantly inhibits HCC cell proliferation, disrupts cell cycle progression, and induces apoptosis . , silencing MRPL37 reduces tumor growth in both xenograft and spontaneous liver cancer models. Mechanistically, MRPL37 regulates mitochondrial protein synthesis, influencing key metabolic pathways and mitochondrial function, including oxidative phosphorylation. Our results suggest MRPL37 as a critical regulator of energy metabolism in HCC, highlighting its potential as a therapeutic target for liver cancer. - Source: PubMed
Publication date: 2025/11/14
Zhang YiganChen MinjieLi HuidiDeng HaoChen ShuwenNi JiaxinHu JunjieLei SixianHuang LinshengDang ShuangsuoYang ZhuoshunZhou WuhuaDing DepingDong YanbinMeng Zhongji - Bladder cancer (BC) is the predominant malignant tumor in the urinary system globally, with its intricate molecular features greatly influencing patient outcomes and treatment response.Identifying novel biomarkers and therapeutic targets is essential for improving patient management. - Source: PubMed
Publication date: 2025/12/09
Xiao LeiWang YuanXiong YujieZhuang ZhijieHu CongXiao Zhiliang - Alzheimer's disease (AD), a prevalent neurodegenerative disorder, is characterized by mitochondrial dysfunction and immune dysregulation. This study is aimed at developing a risk prediction model for AD by integrating multi-omics data and exploring the interplay between mitochondrial energy metabolism-related genes (MEMRGs) and immune cell dynamics. We integrated four GEO datasets (GSE132903, GSE29378, GSE33000, GSE5281) for differential gene expression analysis, functional enrichment, and weighted gene co-expression network analysis (WGCNA). We identified two key gene modules (turquoise and magenta) significantly correlated with AD. Subsequently, we constructed a risk prediction model incorporating five MEMRGs (MRPL15, RBP4, ABCA1, MPV17, and MRPL37) and clinical factors using LASSO regression. The model demonstrated robust predictive performance (AUC > 0.815) in both internal and external validation (GSE44770) cohorts. Downregulation of MRPL15, RBP4, MPV17, and MRPL37 in AD brain regions (validated using AlzData and qRT-PCR) suggests impaired mitochondrial function. Conversely, ABCA1 upregulation may represent a compensatory response. Furthermore, significant differences in immune cell proportions, particularly gamma delta T cells (p = 0.002) and activated CD4 memory T cells (p = 0.027), were found between AD and non-demented samples. We observed significant correlations between MEMRG expression and specific immune cell fractions, indicating a potential link between mitochondrial dysfunction and immune dysregulation in AD. Our study provides a reliable risk prediction model for AD and highlights the crucial roles of MEMRGs and immune responses in disease pathogenesis, offering potential targets for therapeutic interventions. - Source: PubMed
Publication date: 2025/01/14
Du WenlongYu ShihuiLiu RuiyaoKong QingqingHao XinLiu Yi - Gastric cancer (GC) is a common digestive system cancer, characterized by a significant mortality rate. Mitochondria is an indispensable organelle in eukaryotic cells. It was previously revealed that a series of nucleus-encoded mitochondrial genes (NMG) mutations and dysfunctions potentially contribute to the initiation and progression of GC. However, the correlation between NMG mutations and survival outcomes for GC patients is still unclear. In this study, NMG expression profile and clinical information in GC samples were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Through consistent clustering and functional enrichment analysis, we have identified three NMG clusters and three gene clusters that are associated with patterns of immune cell infiltration. Prognostic genes were identified through Univariate Cox regression analysis. The principal component analysis was conducted to set up a scoring system. Subsequently, the Single‑cell RNA sequencing (scRNA-seq) data of GC patients and cancer cell drug sensitivity data were retrieved from the GEO database. Patients with high NMG scores exhibited increased microsatellite instability status and a heightened tumor mutation rate compared to those with low NMG scores. Survival analysis revealed that GC samples with high NMG scores could achieve a better prognosis. Additionally, These patients were observed to be more responsive to immunotherapy. Moreover, we delved into prognostic genes at the level of single cells, revealing that MRPL4 and MRPL37 exhibit high expression in epithelial cells, while TPM1 demonstrates high expression in tissue stem cells. Utilizing cancer cell drug sensitivity data from the Drug Sensitivity in Cancer (GDSC) database, we noted a heightened sensitivity to chemotherapy in the high NMG group. Furthermore, we discovered a significant enrichment of cuproptosis-related genes in clusters with high NMG scores. Consequently, employing the scoring system could facilitate the prediction of GC patients' sensitivity to cuproptosis-induced therapy. Our study confirmed the potency of this scoring system as a therapeutic response biomarker for gastric cancer, potentially informing clinical treatment strategies. - Source: PubMed
Publication date: 2024/11/18
Wang XuLi SainanShen YuhuanCao LiLu YajuanCao JinghaoLiu YingchaoDeng AoliYang JiyunWang Tongtong - Esophageal cancer, known for its high incidence and low five-year survival rate, poses significant treatment challenges. A key aspect of this challenge is the close link between mitochondria and resistance to chemoradiotherapy (CRT). Currently, there is a scarcity of biomarkers for predicting CRT response and prognosis in esophageal cancer. Our study addresses this gap by developing a prognostic model that incorporates mitochondria-related CRT resistance (MRCRTR) genes, including CTSL, TBL1X, CLN8, MMP1, PDPN, and MRPL37. Survival analysis using Kaplan-Meier curves reveals that patients with high MRCRTR scores have lower survival rates than those with low scores. Utilizing a nomogram, we successfully predict the one-, two-, and three-year overall survival rates for esophageal cancer patients. Cox regression analysis confirms the MRCRTR score as an independent prognostic factor. Furthermore, our single-cell and correlation analyses suggested that MRCRTR genes might influence CRT resistance by modulating the immune microenvironment and impacting angiogenesis. Our pan-cancer analysis also indicates the potential applicability of MRCRTR scores to head and neck squamous cell carcinoma. The validation of these findings, conducted with samples from Xiang-ya Hospital, aligns closely with our bioinformatics results. Our study not only explores the role of MRCRTR genes in predicting the prognosis of esophageal cancer but also enhances the understanding of the interplay between CRT, mitochondria, and patient outcomes. - Source: PubMed
Publication date: 2024/02/06
Liu ZiyuZeinalzadeh ZahraHuang TaoHan YingyingPeng LushanWang DanZhou ZongjiangOusmane DiabateWang Junpu