Ask about this productRelated genes to: MRPL34 antibody
- Gene:
- MRPL34 NIH gene
- Name:
- mitochondrial ribosomal protein L34
- Previous symbol:
- -
- Synonyms:
- L34mt, MGC2633, MGC24974
- Chromosome:
- 19p13.1
- Locus Type:
- gene with protein product
- Date approved:
- 2001-01-26
- Date modifiied:
- 2014-11-19
Related products to: MRPL34 antibody
Related articles to: MRPL34 antibody
- RNA-binding proteins (RBPs) serve essential roles in various cancer types, but their functions in papillary renal cell carcinoma (pRCC) have not been elucidated to date. In our work, differentially expressed RBPs in pRCC were identified after acquisition of RNA-sequencing and clinical data related to pRCC from The Cancer Genome Atlas database(TCGA). Functional enrichment analysis and protein interaction network analysis, along with univariate and multivariate Cox regression analyses, were performed to uncover potential biological effects of the identified RBPs and screen the hub RBPs for pRCC prognosis. We identified 251 up-regulated and 129 down-regulated RBPs, and filtered out seven hub RBPs, namely, SRSF8, CD3EAP, HBS1L, ELAC2, MRPL34, NOP2 and IGF2BP2, for their prognostic relevance. A prognostic risk score model for overall survival of pRCC patients was constructed based on the seven hub RBPs. Further analysis showed that the low-risk group had higher survival rate than the high-risk group in both training and validation cohorts. The predictive accuracy was verified in the Human Protein Atlas database.In addition, we introduced the GSE15641 dataset from the Gene Expression Omnibus (GEO) database for independent external validation, and confirmed the expression levels of HBS1L, MRPL34 and IGF2BP2 through real-time quantitative PCR (RT-qPCR) and Western blotting (WB) using human renal tubular epithelial cell line HK-2 and human papillary renal cell carcinoma cell line Caki-2. In pRCC, CD3EAP was significantly elevated, while ELAC2, IGF2BP2, MRPL34, SRSF8 and HBS1L were significantly reduced. There was no significant difference between tumor and normal tissues in NOP2 expression. Risk score and tumor grade were independent prognostic factors associated with overall survival. In addition, we established a nomogram based on the seven prognostic RBPs to help predict overall survival at 1-3 years. In conclusion, seven differentially expressed hub RBPs were identified as potential prognostic biomarkers for pRCC. Our prognostic model might serve as a support for better treatment decision-making. Our work could provide potential new ideas for diagnosis and research on targeted drugs for pRCC. - Source: PubMed
Publication date: 2026/06/19
Niu TianLi QicongZhang Ao - Bone is one of the distant metastases in patients with Breast Cancer (BC). However, the mechanism of BC bone metastasis is not fully understood. The aim of this study was to investigate the potential mechanisms linking bone metastasis-related genes and BC.The training set consisted of data from The Cancer Genome Atlas (TCGA)-BC dataset, which included 1,104 breast cancer samples (comprising 50 with bone metastasis and 1,052 without) and 114 adjacent normal samples. Differentially expressed genes (DEGs1) between breast cancer and normal tissues, as well as DEGs2 between breast cancer bone metastatic and non-bone metastatic tissues, were identified. Weighted gene co-expression network analysis (WGCNA) was then applied to screen breast cancer-related module genes. The intersection of these three sets was taken to obtain candidate genes. Diagnostic genes were identified via univariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) analysis to construct a risk model, which was subsequently validated using the Gene Expression Omnibus (GEO) dataset GSE20685 (327 samples, validation set). Furthermore, immune infiltration analysis, mRNA-miRNA-lncRNA regulatory network construction, and drug sensitivity analysis were performed in the training set. Finally, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was conducted on clinical samples for validation.There were 756 DEGs between BC and control samples. A sum of 6 BC-related modules were acquired by WGCNA. After screening, 997 bone metastasis-associated genes and 73 candidate genes were acquired. A total of 6 diagnostic genes, namely ABHD8, ESRRA, DHPS, ISOC2, MRPL34 and OGFR, were obtained to construct the risk model. Results of the immune microenvironment analysis revealed that the high-risk group exhibited lower levels of certain immune cells, such as T cells and CD8+ T cells. Based on the public database,ESRRA was regulated by various miRNAs, such as hsa-miR-185-3p, hsa-miR-2115-5p. Based on the results of molecular docking experiments, a sum of 67 drugs had significant differences in IC50 between two risk subgroups. Transcriptomic data from TCGA indicated that all six diagnostic genes were significantly upregulated in the BC group ( < 0.05). However, qRT-PCR validation showed that ESRRA and OGFR were significantly downregulated in the BC group ( < 0.05), while the expression trends of the remaining four genes were consistent with the transcriptomic data.We explored the diagnostic genes (ABHD8, ESRRA, DHPS, ISOC2, MRPL34, and OGFR) of bone metastasis in BC, providing a reference for disease-related study. - Source: PubMed
Publication date: 2026/04/18
Tang JingLiu QiangTao ZhengyongNiu NingkuiZhan WenhuaShi JiandangYang Zongqiang - Multiple omics studies on patients with recurrent pregnancy loss (RPL) have deepened the understanding of its pathogenesis. However, few studies have combined multi-omics techniques to provide a more accurate characterization of RPL. This study aims to identify biomarkers with RPL through proteomic and transcriptomic analyses, providing new insights for its diagnosis and treatment. - Source: PubMed
Publication date: 2026/04/06
Huang ShanMu FangxiangWang KexinWang Fang - The article presents the current state of knowledge on genetic modifiers of ovarian cancer risk in women carrying pathogenic variants (PVs) in the and genes, which are major contributors to hereditary susceptibility to this malignancy. Although PV carriers have high disease penetrance (: ~40% and : 11-27%), substantial variability in individual risk is observed, suggesting the influence of additional genetic variants. Ovarian cancer is characterized by late detection and high mortality, and a significant portion of risk among carriers is shaped by reproductive and environmental factors as well as genetic modifiers. The article emphasizes that carriers of the same PV can exhibit markedly different risk levels depending on additional variants that modulate key biological processes, such as DNA repair, cell cycle regulation, and apoptosis. A systematic literature search covering the years 1996-2025 was conducted in the PubMed database. Initially, 734 publications were identified; after removing duplicates, thematically irrelevant articles, non-full-text papers, and studies not meeting the inclusion criteria, 47 articles were included in the review. These studies covered candidate gene analyses, GWAS, and data from the CIMBA consortium, which enables the examination of large cohorts of PV carriers. The review identified numerous variants associated with increased or decreased ovarian cancer risk in carriers, including the following: , , , , , , , , and The reviewed studies also identified both protective and risk-increasing variants among PV carriers: , , and , and haplotypes in , , , , , and The analysis identified 11 variants affecting both and carriers, most of which increase risk, including the following: , , , , , , and Protective variants include and . The only SNP reaching genome-wide significance ( < 5 × 10) was in . The article summarizes the growing number of genetic modifiers of ovarian cancer risk among carriers and highlights their potential to improve individualized risk assessment, enhance patient stratification, support personalized prevention and surveillance strategies, deepen the understanding of disease biology, and identify potential therapeutic targets. - Source: PubMed
Publication date: 2026/01/23
Cylwik DagmaraDwornik RoksanaBiałkowska Katarzyna - Mitochondrial proteins assume a pivotal role in the onset and progression of diverse diseases. Nonetheless, the causal interconnections with sensorineural hearing loss (SNHL) demand meticulous exploration. Mendelian randomization analysis is a method used in observational epidemiological studies to predict the relationship between exposure factors and outcomes using genetic variants as instrumental variables. In this study, we applied this analytical approach to two distinct samples to predict the causal impact of mitochondrial proteins on SNHL. - Source: PubMed
Publication date: 2024/08/06
Yan JiangyuWu LinrongZheng MengmengLv YuanJiang FengGao WeiboPan Fangfang