High EIF4E2 expression is an independent prognostic risk factor for poor overall survival and recurrence-free survival in uveal melanoma

Yang, Binghua; Gu, Aiping; Wu, Yi Long

doi:10.1016/j.exer.2021.108558

Cited by 7 publications

(4 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, High EIF4E2 expression has been shown by Yang et al to be an independent prognostic risk factor for UM patients. During the course of UM, EIF4E2 may be crucial in hypoxia-related signaling pathways [ 44 ]. A regulatory mechanism for this potential tumor suppressor in the inhibition of HIF-2- and eIF4E2-mediated translation activation of oncogenic mRNAs was discovered by other researchers, who found that DDX28 (DEAD Box Protein Family Member) is a Negative Regulator of Hypoxia-Inducible Factor 2α- and Eukaryotic Initiation Factor 4E2-Directed Hypoxic Translation [ 45 ].…”

Section: Discussionmentioning

confidence: 99%

N7-methylguanosin regulators-mediated methylation modification patterns and characterization of the immune microenvironment in lower-grade glioma

et al. 2023

View full text Add to dashboard Cite

N7-methylguanosine (m7G) modification signature has recently emerged as a crucial regulator of tumor progression and treatment in cancer. However, there is limited information available on the genomic profile of lower-grade gliomas (LGGs) related to m7G methylation modification genes’ function in tumorigenesis and progression. In this study, we employed bioinformatics methods to characterize m7G modifications in individuals with LGG from The Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA). We used gene set enrichment analysis (GSEA), single sample GSEA (ssGSEA), CIBERSORT algorithm, ESTIMATE algorithm, and TIDE to evaluate the association between m7G modification patterns, tumor microenvironment (TME) cell infiltration properties, and immune infiltration markers. The m7G scoring scheme using principal component analysis (PCA) was employed to investigate the m7G modification patterns quantitatively. We examined the m7G modification hub genes' expression levels in normal samples, refractory epilepsy samples, and LGG samples using immunohistochemistry, western-blotting, and qRT-PCR. Our findings revealed that individuals with LGG could be categorized into two groups based on m7G scores (high and low) according to the properties of m7G. Moreover, we observed that high m7G score was associated with significant clinical benefit and prolonged survival duration in the anti-PD-1 cohort, while low m7G score was associated with improved prognostic outcomes and increased likelihood of complete or partial response in the anti-PD-L1 cohort. Different m7G subtypes also showed varying Tumor Mutational Burden (TMB) and immune profiles and might have distinct responses to immunotherapy. Furthermore, we identified five potential genetic markers that were highly correlated with the m7G score signature index. These findings provide insight into the features and classification associated with m7G methylation modifications and may aid in improving the clinical outcome of LGG.

show abstract

Section: Discussionmentioning

confidence: 99%

N7-methylguanosin regulators-mediated methylation modification patterns and characterization of the immune microenvironment in lower-grade glioma

et al. 2023

View full text Add to dashboard Cite

show abstract

“…SARS-CoV-2 can effectively replicate in target cells by utilizing the ERK/MNK1/EIF4E pathway [ 50 , 51 ]. Extensive research has found that EIF4E2 plays a crucial role in tumor progression and metastasis [ 52 ]. Furthermore, Yang et al demonstrated that high EIF4E2 expression serves as an independent prognostic risk factor for patients with uveal melanoma (UM) [ 53 ].…”

Section: Discussionmentioning

confidence: 99%

Predicting the risk of primary Sjögren's syndrome with key N7-methylguanosine-related genes: A novel XGBoost model

Xie,

Deng,

et al. 2024

Heliyon

View full text Add to dashboard Cite

“…The differentially expressed genes (DEGs) in this subtype are primarily involved in cytokine-cytokine receptor interaction, antigen processing and presentation, and primary immunode ciency. Notably, a recent report highlighted the association between higher expression of CCL18 and worse clinical outcomes and tumor-speci c death 24 . Antigen presentation plays a critical role in the body's anti-tumor immunity, and immune dysregulation can lead to tumor immune escape.…”

Section: Discussionmentioning

confidence: 99%

Machine Learning-based Classifier to Decipher Immune Landscape of Uveal Melanoma and Predict Patient Outcomes

Zhang,

Shen,

Jiang

et al. 2023

Preprint

View full text Add to dashboard Cite

Uveal melanoma (UVM) is influenced by immune infiltration features, making the analysis of UVM genomic and immune signatures crucial for predicting patient prognosis and identifying potential targeted therapies.To address this issue, we leveraged multi-omics data from The Cancer Genome Atlas and GEO datasets, especially immune infiltration data, to classify UVM into distinct immune-related subgroups using an unsupervised clustering algorithm. The resulting subgroups were denoted as uveal melanoma carcinoma subtype 1 (UMCS1) and subtype 2 (UMCS2). We further examined differences in the immune microenvironment, immunotherapy response, and tumor metabolic pathways between these subgroups, aiming to identify targets related to immune infiltration. Additionally, we devised a risk scoring system based on subtype-specific markers to forecast the prognosis of UVM patients. Performance evaluation of the risk scoring system was conducted using receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves.Our analysis successfully identified two distinct subtypes of UVM patients, characterized by genomic mutations and disparities in the immune environment. These subtypes exhibited diverse clinical features and biological processes. The aggressive subtype, UMCS2, presented a higher TNM stage and poorer patient survival. UMCS2 was distinguished by elevated metabolism and increased immune infiltration. However, UMCS2 also demonstrated a higher tumor mutational burden and immune dysfunction, resulting in diminished responsiveness to immunotherapy. Notably, the two subgroups exhibited differential sensitivity to targeted drugs due to substantial variances in metabolic and immune environments, with UMCS2 displaying lower sensitivity. Finally, we developed a risk scoring system utilizing subtype-specific biomarkers and assessed its diagnostic performance for UVM patients, achieving satisfactory results through ROC curves, decision curve analysis, and calibration curves. Our findings suggest that the remodeled immunometabolic pathways and the immune microenvironment contribute to the relatively low sensitivity of UVM to immunotherapy. Targeting these mutated pathways and immune infiltrating molecules may potentially address the current treatment dilemma in UVM. Moreover, the newly developed risk assessment system not only aids in predicting patient prognosis but also facilitates the identification of suitable populations for combination therapy.

show abstract

High EIF4E2 expression is an independent prognostic risk factor for poor overall survival and recurrence-free survival in uveal melanoma

Cited by 7 publications

References 28 publications

N7-methylguanosin regulators-mediated methylation modification patterns and characterization of the immune microenvironment in lower-grade glioma

N7-methylguanosin regulators-mediated methylation modification patterns and characterization of the immune microenvironment in lower-grade glioma

Predicting the risk of primary Sjögren's syndrome with key N7-methylguanosine-related genes: A novel XGBoost model

Machine Learning-based Classifier to Decipher Immune Landscape of Uveal Melanoma and Predict Patient Outcomes

Contact Info

Product

Resources

About