High Expression of EIF4G2 Mediated by the TUG1/Hsa-miR-26a-5p Axis Is Associated with Poor Prognosis and Immune Infiltration of Gastric Cancer

Construction and analysis of competitive endogenous RNA networks and prognostic models associated with ovarian cancer based on the exoRBase database

OBJECTIVE

To construct a competitive endogenous RNA (ceRNA) regulatory network in blood exosomes of patients with ovarian cancer (OC) using bioinformatics and explore its pathogenesis.

METHODS

The exoRbase2.0 database was used to download blood exosome gene sequencing data from patients OC and normal controls and the expression profiles of exosomal mRNA, long non-coding RNA (lncRNA), and circular RNA (circRNA) were detected independently using R language for differential expression analysis. TargetScan and miRanda databases were combined for the prediction and differential expression of mRNA-binding microRNAs (miRNA). The miRcode and starBase databases were used to predict miRNAs that bind to differentially expressed lncRNAs and circRNAs repectively. The relevant mRNA, circRNA, lncRNA and their corresponding miRNA prediction data were imported into Cytoscape software for visualization of the ceRNA network. The R language and KEGG Orthology-based Annotation System (KOBAS) were used to execute and illustrate the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Hub genes were identified using The CytoHubba plugin.

RESULTS

Thirty-one differentially expressed mRNAs, 17 differentially expressed lncRNAs, and 24 differentially expressed circRNAs were screened. Cytoscape software was used to construct the ceRNA network with nine mRNA nodes, two lncRNA nodes, eight circRNA nodes, and 51 miRNA nodes. Both GO and KEGG were focused on the Spliceosome pathway, indicating that spliceosomes are closely linked with the development of OC, while heterogenous nuclear ribonucleoprotein K and RNA binding motif protein X-linked genes were the top 10 score Hub genes screened by Cytoscape software, including two lncRNAs, four mRNAs, and four circRNAs. In patients with OC, the expression of eukaryotic translation initiation factor 4 gamma 2 (EIF4G2), SERPINE 1 mRNA binding protein 1 (SERBP1), ribosomal protein L15 (RPL15) and human leukocyte antigen complex P5 (HCP5) was significantly higher whereas that of testis expressed transcript, Y-linked 15 and DEAD-box helicase 3 Y-linked genes was lower compared to normal controls Immunocorrelation scores revealed that SERBP1 was significantly and negatively correlated with endothelial cells and CD4+ T cells and positively correlated with natural killer (NK) cells and macrophages, respectively; RPL15 was significantly positively correlated with macrophages and endothelial cells and negatively correlated with CD8+ T cells and uncharacterized cells, respectively. EIF4G2 was significantly and negatively correlated with endothelial cells and CD4+ T cells, and positively correlated with uncharacterized cells, respectively. Based on the survival data and the significant correlation characteristics derived from the multifactorial Cox analysis (P < 0.05), the survival prediction curves demonstrated that the prognostic factors associated with 3-year survival in patients with OC were The prognostic factors associated with survival were Macrophage, RPL15.

CONCLUSION

This study successfully constructs a ceRNA regulatory network in blood exosomes of OV patients, which provides the specific targets for diagnosis and treatment of OC.

RNA modification-related EIF4G2 is an immunotherapy determinant in osteosarcoma: A single-cell sequencing analysis

The clinical outcomes of osteosarcoma are relatively dismal. As immunotherapy has revolutionized treatment for solid tumors, exploring novel immunotherapy-related therapeutic targets for osteosarcoma is important. In this study, we aimed to establish the connection between RNA modification and immunotherapy in osteosarcoma to identify novel therapeutic targets. An RNA modification-related signature was first developed using weight gene correlation network analysis and a machine-learning algorithm, random forest. The signature's prognostic value, drug prediction, and immune characteristics were analyzed. EIF4G2 from the signature was next identified as a critical immunotherapy determinant. EIF4G2 could also promote tumor proliferation, migration, and M2 macrophage migration by single-cell sequencing analysis and in vitro validation. Our signature and EIF4G2 are expected to provide valuable insights into the clinical management of osteosarcoma.

Loss of EIF4G2 mediates aggressiveness in distinct human endometrial cancer subpopulations with poor survival outcome in patients

The non-canonical translation initiation factor EIF4G2 plays essential roles in cellular stress responses via translation of selective mRNA cohorts. Currently there is limited and conflicting information regarding its involvement in cancer development and progression. Here we assessed its role in endometrial cancer (EC), in a cohort of 280 EC patients across different types, grades, and stages, and found that low EIF4G2 expression highly correlated with poor overall- and recurrence-free survival in Grade 2 EC patients, monitored over a period of up to 12 years. To establish a causative connection between low EIF4G2 expression and cancer progression, we stably knocked-down EIF4G2 in two human EC cell lines in parallel. EIF4G2 depletion resulted in increased resistance to conventional therapies and increased the prevalence of molecular markers for aggressive cell subsets, altering their transcriptional and proteomic landscapes. Prominent among the proteins with decreased abundance were Kinesin-1 motor proteins, KIF5B and KLC1, 2, 3. Multiplexed imaging of the EC patient tumor cohort showed a correlation between decreased expression of the kinesin proteins, and poor survival in patients with tumors of certain grades and stages. These findings reveal potential novel biomarkers for Grade 2 EC with ramifications for patient stratification and therapeutic interventions.

Loss-of-function cancer-linked mutations in the EIF4G2 non-canonical translation initiation factor

Tumor cells often exploit the protein translation machinery, resulting in enhanced protein expression essential for tumor growth. Since canonical translation initiation is often suppressed because of cell stress in the tumor microenvironment, non-canonical translation initiation mechanisms become particularly important for shaping the tumor proteome. EIF4G2 is a non-canonical translation initiation factor that mediates internal ribosome entry site (IRES)- and uORF-dependent initiation mechanisms, which can be used to modulate protein expression in cancer. Here, we explored the contribution of EIF4G2 to cancer by screening the COSMIC database for EIF4G2 somatic mutations in cancer patients. Functional examination of missense mutations revealed deleterious effects on EIF4G2 protein-protein interactions and, importantly, on its ability to mediate non-canonical translation initiation. Specifically, one mutation, R178Q, led to reductions in protein expression and near-complete loss of function. Two other mutations within the MIF4G domain specifically affected EIF4G2's ability to mediate IRES-dependent translation initiation but not that of target mRNAs with uORFs. These results shed light on both the structure-function of EIF4G2 and its potential tumor suppressor effects.

A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis

BACKGROUND

Gastric cancer (GC) ranks among the most common malignancies worldwide. This study aimed to find critical genes/pathways in GC pathogenesis.

METHODS

Gene interactions were analyzed, and the protein-protein interaction network was drawn. Then enrichment analysis of the hub genes was performed and network cluster analysis and promoter analysis of the hub genes were done. Age/sex analysis was done on the identified genes.

RESULTS

Eleven hub genes in GC were identified in the current study (ATP5A1, ATP5B, ATP5D, MT-ATP8, COX7A2, COX6C, ND4, ND6, NDUFS3, RPL8, and RPS16), mostly involved in mitochondrial functions. There was no report on the ATP5D, ND6, NDUFS3, RPL8, and RPS16 in GC. Our results showed that the most affected processes in GC are the metabolic processes, and the oxidative phosphorylation pathway was considerably enriched which showed the significance of mitochondria in GC pathogenesis. Most of the affected pathways in GC were also involved in neurodegenerative diseases. Promoter analysis showed that negative regulation of signal transduction might play an important role in GC pathogenesis. In the analysis of the basal expression pattern of the selected genes whose basal expression presented a change during the age, we found that a change in age may be an indicator of changes in disease insurgence and/or progression at different ages.

CONCLUSIONS

These results might open up new insights into GC pathogenesis. The identified genes might be novel diagnostic/prognostic biomarkers or potential therapeutic targets for GC. This work, being based on bioinformatics analysis act as a hypothesis generator that requires further clinical validation.

Molecular interplay between EIF4 family and circular RNAs in cancer: Mechanisms and therapeutics

The eukaryotic translation initiation factor 4 (EIF4) family is a major contributor to the recruitment of mRNAs to ribosomes during the initial translation stage in eukaryotes, whose dysregulation either allows for cancer transformation or prevents disordered cancerous cell growth. Circular RNAs (circRNAs), which exhibit distinctive structures and are widely expressed in eukaryotes, are anticipated to be a clinical diagnostic biomarker for cancer therapy. There is considerable evidence that EIF4s can influence the biogenesis, transport, and function of circRNAs and, in turn, circRNAs can control the expressions of EIF4s through certain molecular pathways. Herein, we primarily review the emerging studies of the EIF4 family and pinpoint the roles of dysregulated EIF4s in cancer. We also evaluate the patterns of intricate interactions between circRNAs and EIF4s and discuss the potential utility of circRNA-based therapeutics targeting EIF4s in clinical cancer research.