EEF1E1 Antibody
- Known as:
- EEF1E1 Antibody
- Catalog number:
- csb-pa007432la01hu
- Product Quantity:
- USD
- Category:
- -
- Supplier:
- CusAb
- Gene target:
- EEF1E1 Antibody
Related genes to: EEF1E1 Antibody
- Gene:
- EEF1E1 NIH gene
- Name:
- eukaryotic translation elongation factor 1 epsilon 1
- Previous symbol:
- P18
- Synonyms:
- AIMP3
- Chromosome:
- 6p24.3
- Locus Type:
- gene with protein product
- Date approved:
- 1999-07-22
- Date modifiied:
- 2015-09-11
Related products to: EEF1E1 Antibody
Related articles to: EEF1E1 Antibody
- Hepatocellular carcinoma (HCC) treatment faces significant challenges, particularly in tumor growth, metastasis, and drug resistance. While several predictive models exist, effective models that accurately predict patient prognosis and guide targeted therapy decisions remain insufficient. Regulated cell death (RCD) pathways play a pivotal role in the development and progression of various cancers, offering potential prognostic indicators and biomarkers of drug sensitivity for HCC patients. We analyzed multi-cohort transcriptomic data (TCGA, GSE14520, ICGC) and single-cell RNA sequencing data (GSE149614) to identify differentially expressed RCD-related genes (DEGs). A prognostic model, the Regulated Cell Death Index (RCDI), was constructed using machine learning algorithms to stratify HCC patients into high- and low-RCDI groups. Single-cell analysis was employed to examine tumor microenvironment heterogeneity between these groups, and drug sensitivity analysis assessed differences in immune therapy, targeted therapy, and chemotherapy responses based on RCDI subgroups. RCDI was significantly associated with poor clinical features and shorter overall survival, with results validated across all cohorts. Enrichment analysis revealed that high RCDI is correlated with key cancer-related pathways, including the PI3K-Akt pathway and cell cycle regulation. High RCDI was also associated with immune cell infiltration and the expression of immune checkpoint molecules, as validated through single-cell RNA sequencing. Patients with high RCDI exhibited higher sensitivity to several targeted therapies, including Vorinostat and Trametinib. Further prioritization analyses identified EEF1E1, ITGB3BP, and SPP1 as promising candidate biomarkers with potential diagnostic and prognostic relevance. The RCDI model effectively stratifies HCC patients based on RCD-related molecular features, providing a valuable tool for predicting survival and therapeutic responses. The identification of key genes offers new insights into the molecular mechanisms of HCC and potential therapeutic targets. - Source: PubMed
Chen JiaxingYang ZhizhaoCui YongqiangZhao ZhileiWu XiaoboCao JiaqiDeng DongfengYu MiaoZhang XiuleiZhang Xiao - Liver hepatocellular carcinoma (LIHC) is a heterogeneous malignancy with poor prognosis, but the landscape of cellular senescence-related genes (CSRGs) in LIHC remains incompletely characterized. Here, we curated 167 CSRGs and performed integrative bulk and single-cell RNA-seq analyses using TCGA, ICGC, and TISCH datasets. Fifteen prognostic CSRGs were identified and stratified LIHC patients into two distinct molecular subtypes: Cluster 2 exhibited an immune-excluded phenotype with poor prognosis, whereas Cluster 1 represented an immune-desert phenotype. A CSRGs-based risk score was constructed and validated as an independent prognostic factor across cohorts. Single-cell analysis identified EEF1E1 as a key CSRG predominantly expressed in malignant hepatocytes, correlating with advanced clinicopathological features and immune infiltration. Functional experiments demonstrated that EEF1E1 knockdown significantly suppressed LIHC cell migration and invasion. Collectively, this study establishes a robust CSRGs-based prognostic signature. It also identifies EEF1E1 as a functionally relevant gene with oncogenic potential and a potential therapeutic target in LIHC. - Source: PubMed
Publication date: 2026/06/10
Liu RentongLi BingLuo YiqianYan XiuweiWang YuanyuanJiang SongGan ChengjieCheng Yiwei - BACKGROUND: Tumor stem cells (TSCs) play a central role in oral mucosal carcinogenesis by promoting tumor growth, invasion, and angiogenesis. Microvascular architectural phenotype heterogeneity (MAPH) and vasculogenic mimicry (VM) contribute to vascular complexity within tumors and resistance to conventional anti-angiogenic therapies. However, the mechanisms through which TSCs influence MAPH and VM formation during oral mucosal carcinogenesis remain poorly understood. In this study, we aimed to investigate the role of TSCs in mediating MAPH and VM throughout oral mucosal carcinogenesis. METHODS: Animal models representing normal mucosa, precancerous lesions, and high-differentiated, moderate-differentiated, and low-differentiated squamous carcinomas were established. TSCs derived from HSC4 cells (isolated through laser capture microdissection (LCM) and validated using stemness markers and sphere-forming assays) were injected into the experimental models. Data were analyzed using one-way analysis of variance (ANOVA) and nonparametric tests, with multiple testing correction applied for proteomic analyses. RESULTS: Microvascular morphology analysis revealed stage-specific heterogeneity. In the TSC-treated groups, fused morphology predominated in the precancerous and highly differentiated stages, budding morphology appeared in the moderately differentiated stage, and finger-like morphology was characteristic of the poorly differentiated stage. LCM proteomics identified 2,215 differential proteins, with angiopoietin-like protein 2 (ANGPTL2), cytokeratin 15 (CK15), and eukaryotic translation elongation factor 1 epsilon 1 (EEF1E1) as key candidates. In the TSC-treated groups, CK15 was upregulated, whereas ANGPTL2 and EEF1E1 were downregulated. In the control groups, CK15 gradually increased across stages, ANGPTL2 peaked in highly differentiated carcinomas, and EEF1E1 peaked in moderately differentiated carcinomas. TSCs intervention shifted ANGPTL2 and EEF1E1 peaks to the precancerous and highly differentiated stages, respectively. CONCLUSIONS: These findings suggest that targeting these molecules may provide novel anti-angiogenic strategies for preventing or treating oral mucosal carcinogenesis. - Source: PubMed
Publication date: 2026/01/16
Liu XuqianChen XiaoWang JieHe LingxiaoYin ShigangChen LiTang YongZheng XiaoliNie Minhai - Despite advances in cancer treatments, epithelial ovarian cancer (EOC) remains the leading cause of death among gynecologic cancers. EOC is stratified into five main histopathological subtypes: high-grade serous carcinoma (HGSC), low-grade serous carcinoma (LGSC), endometrioid carcinoma (EC), clear cell carcinoma (CCC), and mucinous carcinoma (MC). However, personalized treatment strategies and reliable biomarkers for all histotypes remain elusive. Building on our previous work with early-stage EOC, we aim to explore diagnostic and prognostic biomarkers in advanced-stage EOC, updated to the latest World Health Organization classification guidelines from 2020, using comprehensive transcriptomic profiling from total RNA sequencing of 146 EOCs. Differential expression analysis identified top 9 histotype-specific gene panels for HGSC, CCC, MC, and EC, including S100A1 (HGSC), ARID3A (CCC), LGALS4 (MC), and PAX9 (EC). We also identified gene candidates associated with overall survival and disease-specific survival, reflecting both favorable (e.g., OTOF, EEF1E1-BLOC1S5, and STAC3) and unfavorable (e.g., SMOC1, GDPGP1, EPRS1) clinical outcome. Additionally, enrichment analysis revealed tumor progression-related pathways unique to each histotype, offering insights into the molecular mechanisms underlying disease progression and potential therapeutic targets. These findings provide valuable insights into the molecular landscape of advanced-stage EOC, paving the way for more effective diagnostic and prognostic tools across diverse histotypes. - Source: PubMed
Publication date: 2025/10/23
Ittner EllaSwenson HugoWerner LucasRönnerman Elisabeth WernerMateoiu ConstantinaKovács AnikóDahm-Kähler PernillaSaed GhassanKarlsson PerParris Toshima ZHelou Khalil - The prognosis of early recurrence of hepatocellular carcinoma (HCC) remains poor. This study aimed to develop and validate a radiomics model and determine potential biomarkers involved in biological pathways for early recurrence of HCC. - Source: PubMed
Publication date: 2025/09/29
Ren LiyingChen DongboXu TingfengWei RongyuZhao BigengZhou YuanpingHe YongLiao MinjunChen HongsongLiao Weijia