Ask about this productRelated genes to: AIMP2 antibody
- Gene:
- AIMP2 NIH gene
- Name:
- aminoacyl tRNA synthetase complex interacting multifunctional protein 2
- Previous symbol:
- -
- Synonyms:
- p38, PRO0992, JTV-1, JTV1
- Chromosome:
- 7p22.1
- Locus Type:
- gene with protein product
- Date approved:
- 2009-05-20
- Date modifiied:
- 2016-05-10
Related products to: AIMP2 antibody
Related articles to: AIMP2 antibody
- Lung cancer is the leading cause of cancer-related deaths worldwide, yet there has been little attention given to the correlation between the cancer transcriptome and the incidence and mortality of lung cancer across different geographic regions. - Source: PubMed
Zhang LingFan CongShang HuanxiaWang XiaojingZhang XinQiao QingzheNi JiajiaWu Shucai - Age-related hearing loss (HL) and sarcopenia (ARS) are prevalent geriatric syndromes sharing common risk factors. This study aimed to identify shared biomarkers and elucidate convergent pathogenic mechanisms. Transcriptomic datasets were obtained from public database. Differential expression analysis was performed, followed by enrichment analysis. Hub genes were identified via LASSO regression, SVM-RFE, and random forest algorithms. Diagnostic performance was evaluated using receiver operating characteristic curve analysis across 6 independent cohorts. Comprehensive integrative analysis revealed distinct yet overlapping molecular signatures between HL and ARS. In HL, 11 upregulated and 16 downregulated genes were shared between 2 diseases, and complement and coagulation cascades, Toll-like receptor signaling, efferocytosis, as well as immune response processes were found to be associated with these genes. Machine learning identified 10 hub genes (AIMP2, JUN, SEMA5A, RASL12, GUSB, C1QA, GYPC, IRF7, C1QB, SERPING1) as shared biomarkers. Notably, these genes demonstrated robust diagnostic utility: individual genes exhibited area under the curve (AUC) values > 0.7 in most cohorts. Although the combined 10-gene model achieved AUC = 1 in several cohorts, these results should be interpreted with caution due to the limited sample sizes in some datasets (e.g., GSE6045, n = 3 per group), which may inflate performance metrics. Permutation tests confirmed that the AUC values were significantly better than chance in several cohorts (P < .05). This study pioneers a machine-learning framework to uncover shared molecular drivers of HL and ARS, identifying 10 hub genes as promising diagnostic biomarkers. - Source: PubMed
Li Ming - Glioblastoma (GBM) is a highly vascularized, heterogeneous tumor, yet antiangiogenic therapies have yielded limited survival benefits. The lack of validated predictive biomarkers for treatment response stratification remains a major challenge. Aminoacyl tRNA synthetase complex-interacting multicomplex proteins (AIMP) 1/2/3 have been implicated in central nervous system diseases, but their roles in gliomas remain unexplored. We investigated their association with angiogenesis and their significance as predictive biomarkers for antiangiogenic treatment response. In this multi-cohort retrospective study, we analyzed glioma samples from The Cancer Genome Atlas, Chinese Glioma Genome Atlas, REMBRANDT, Gravendeel, BELOB, and REGOMA trials, and four single-cell transcriptomic datasets. Multiomic analyses incorporated transcriptomic, epigenetic, and proteomic data. Kaplan-Meier and Cox proportional hazards models were used to assess the potential prognostic value of AIMPs in heterogeneous and homogeneous treatment groups. Using single-cell transcriptomics, we explored spatial and cell type-specific AIMP2 expression in GBM. AIMP1/2/3 expressions correlated significantly with angiogenesis across The Cancer Genome Atlas cancers. In gliomas, AIMPs were upregulated in tumor versus normal tissues, higher- versus lower-grade gliomas, and recurrent versus primary tumors (P < 0.05). Upon retrospective analysis of two clinical trials assessing different antiangiogenic drugs, we found that high-AIMP2 subgroups had improved response to therapies in GBM [REGOMA: HR, 4.75 (1.96-11.5), P < 0.001; BELOB: HR, 2.3 (1.17-4.49), P = 0.015]. AIMP2-cg04317940methylation emerged as a clinically applicable stratification marker. Single-cell analysis revealed homogeneous AIMP2 expression in tumor tissues, particularly in astrocyte-like cells, suggesting a mechanistic link to tumor angiogenesis. These findings provide novel insights into the role of AIMPs in angiogenesis, offering improved patient stratification and therapeutic outcomes in recurrent GBM. - Source: PubMed
Noor HumairaZheng YuanningItakura HarukaGevaert Olivier - The development of precise molecular biomarkers for breast cancer prognosis holds immense potential to improve treatment outcomes. This study aimed to investigate the role of amino acid metabolism genes as predictive markers for breast cancer prognosis and their association with the immune-tumour microenvironment. By employing advanced machine learning algorithms and bioinformatics analysis techniques, the impact of amino acid metabolism-related genes (AAMRGs) on the immune status and overall survival of patients with breast cancer was examined. An AAMRG-based risk model was established to assess the prognostic significance. Validated risk models (AIMP2, IYD, and QARS1) accurately predicted patient outcomes [1 y: 0.87 (0.96-0.78); 3 y: 0.82 (0.87-0.76); 5 y: 0.80 (0.86-0.75)]. Furthermore, this study revealed evidence suggesting that QARS1 may influence breast cancer cell proliferation through methionine metabolism. This analysis provides valuable insights into the mechanisms of breast cancer, emphasizing the significance of AAMRGs as prognostic biomarkers and potential therapeutic targets for optimizing personalized treatment strategies. - Source: PubMed
Publication date: 2025/06/10
Zhou YudongYu ShiboZhu LizheWang YalongDuan ChenglongLi DanniDu JinsuiZhang JiaqiZhang JianingMa RuichaoHe JianjunRen YuWang Bin - Glioblastoma (GBM) is a highly vascularized, heterogeneous tumor, yet anti-angiogenic therapies have yielded limited survival benefits. The lack of validated predictive biomarkers for treatment response stratification remains a major challenge. Aminoacyl tRNA synthetase complex-interacting multicomplex proteins (AIMPs) 1/2/3 have been implicated in CNS diseases, but their roles in gliomas remain unexplored. We investigated their association with angiogenesis and their significance as predictive biomarkers for anti-angiogenic treatment response. - Source: PubMed
Publication date: 2025/03/14
Noor HumairaZheng YuanningItakura HarukaGevaert Olivier