EIF2S2 transcriptionally upregulates HIF1α to promote gastric cancer progression via activating PI3K/AKT/mTOR pathway.

Eukaryotic translation initiation factor 2 subunit beta (EIF2S2) is a protein that controls protein synthesis under various stress conditions and is abnormally expressed in several cancers. However, there is limited insight regarding the expression and molecular role of EIF2S2 in gastric cancer. In this study, we identified the overexpression of EIF2S2 in gastric cancer by immunohistochemical (IHC) staining and found a positive correlation between EIF2S2 expression and shorter overall survival and disease-free survival. Functionally, we revealed that EIF2S2 knockdown suppressed gastric cancer cell proliferation and migration, induced cell apoptosis, and caused G2 phase cell arrest. Additionally, EIF2S2 is essential for in vivo tumor formation. Mechanistically, we demonstrated that EIF2S2 transcriptionally regulated hypoxia induicible factor-1 alpha (HIF1α) expression by NRF1. The promoting role of EIF2S2 in malignant behaviors of gastric cancer cells depended on HIF1α expression. Furthermore, the PI3K/AKT/mTOR signaling was activated upon EIF2S2 overexpression in gastric cancer. Collectively, EIF2S2 exacerbates gastric cancer progression via targeting HIF1α, providing a fundamental basis for considering EIF2S2 as a potential therapeutic target for gastric cancer patients.

Eukaryotic Translation Initiation Factor 2 Subunit ß as a Prognostic Biomarker Associates With Immune Cell Infiltration in Breast Cancer.

INTRODUCTION: The present study aims to explore the expression level of eukaryotic translation initiation factor 2 subunit ß (EIF2S2) in breast cancer tissue, and its role both in breast cancer prognosis and in the immune microenvironment. METHODS: To assess the association between the expression levels of EIF2S2 and prognosis, the Gene Expression Profiling Interactive Analysis database was initially applied to determine differences in the gene expression of EIF2S2 in various malignant and normal tissues. Furthermore, the expression levels of EIF2S2 were determined in the clinical breast cancer tissues and corresponding para-neoplastic tissues using immunohistochemical analysis. In addition, Kaplan-Meier survival and Cox regression analyses were employed to explore the association between EIF2S2 expression levels and patient prognosis. Finally, the correlation between the expression levels of EIF2S2 and immune cell infiltration in breast cancer was analyzed using the TIMER2.0 database, and subsequently validated by immunohistochemical experiments. RESULTS: The Gene Expression Profiling Interactive Analysis database revealed the presence of higher expression levels of EIF2S2 in various different types of cancer compared with normal cells, also correlating its expression with both the age and the tumor stage of patients with breast cancer. The survival analysis results revealed that high expression levels of EIF2S2 could be a risk factor for poor prognosis in patients with breast cancer. Moreover, the EIF2S2 expression level was found to be closely associated with the infiltration levels of various immune cells, including regulatory T cells, CD4+, CD8+, and natural killer cells, in breast cancer. CONCLUSIONS: In conclusion, the present study has demonstrated that an upregulated expression level of EIF2S2 in breast cancer may be associated with poor patient prognosis, affecting immune cell infiltration in breast cancer. Taken together, the findings of the present study have shown that EIF2S2 expression may be a novel therapeutic target for breast cancer.

RBP EIF2S2 Promotes Tumorigenesis and Progression by Regulating MYC-Mediated Inhibition via FHIT-Related Enhancers.

RNA-binding proteins (RBPs) play fundamental roles in cancer; however, we still lack knowledge about to what extent RBPs are dysregulated, as well as about perturbed signaling pathways in cancer. In this study, we integrated analysis of multidimensional data across >10,000 cancer patients and >1,000 cell lines. We identified a top candidate RBP: eukaryotic translation initiation factor 2 subunit beta (EIF2S2). EIF2S2 is highly expressed in tumors and is associated with malignant features as well as patient prognosis. Functional assays performed in cancer cells revealed that EIF2S2 promotes cancer cell proliferation, migration, and invasion in vitro as well as tumor growth and metastasis in vivo. Mechanistic investigations further demonstrated that EIF2S2 promotes tumorigenesis and progression by directly binding to a long non-coding RNA, LINC01600, which physically interacts with the MYC protein and increases its stability. Interestingly, we revealed that the EIF2S2-LINC01600-MYC axis can activate the Wnt/ß-catenin pathway by inhibiting the activity of FHIT-related enhancers and FHIT expression. Finally, EIF2S2 knockdown combined with oxaliplatin treatment could be a potential combination therapy in cancer. Our integrated analysis provided detailed knowledge of the function of the EIF2S2-LINC01600-MYC axis, which will facilitate the development of rational combination therapies for cancer.

EIF2S2 is a novel independent prognostic biomarker and correlated with immune infiltrates in hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is a highly malignant disease with poor prognosis. It is urgent to find effective biomarkers. Eukaryotic Translation Initiation Factor 2 Subunit Beta (EIF2S2) is a subunit of heterotrimeric G protein EIF2, and its function is still unclear. We studied the role of EIF2S2 in the malignant progression of liver cancer and its relationship with immune infiltration. Methods: Download the RNA expression and clinical information of EIF2S2 from the Cancer Genome Atlas (TCGA) database, analyze the relationship between the expression of EIF2S2 and the prognosis and clinicopathological characteristics of HCC, analyze the differential genes by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and tumor related immune infiltrating cells. The Protein expression level of EIF2S2 was obtained from Human Protein Atlas (HPA) databases. The relationship between EIF2S2 expression and immune infiltrates in HCC was analyzed on TIMER 2.0. The data processing analysis based on R language. Drug Sensitivity data from Genomics of Drug Sensitivity in Cancer (GDSC). Results: EIF2S2 is highly expressed in HCC patients and is associated with poor prognosis. The expression of EIF2S2 was also correlated with age, clinical stage and pathological grade. Univariate and multivariate COX regression analysis showed that EIF2S2 was an independent risk factor for survival. The receiver operating characteristic (ROC) curve of EIF2S2 also confirmed the diagnostic value of EIF2S2 in HCC patients. Through GO and KEGG enrichment analysis, EIF2S2 expression was found to be closely related to some immune pathways. The expression of EIF2S2 was correlated with memory B cell, plasma B cell, CD8+ T cell, CD4+ resting memory T cell and the expression of some immune checkpoints, such as PDCD1, TIGIT and CTLA-4. It is also more sensitive to paclitaxel, sunitinib and other drugs. Conclusion: This study shows that EIF2S2 can be used as a prognostic factor for HCC, which is closely related to immune infiltration and immune checkpoints, and may play a potential regulatory role in predicting drug sensitivity.

18F-FDG PET/CT metabolic parameters correlate with EIF2S2 expression status in colorectal cancer.

Background: We sought to investigate whether the expression of the gene EIF2S2 is related to 18F-FDG PET/CT metabolic parameters in patients with colorectal cancer (CRC). Materials and methods: The expression of EIF2S2 in CRC and its relationship with clinicopathological features were obtained through the ONCOMINE, UALCAN and GEPIA databases. EIF2S2 and GLUT1 expression were examined by immunohistochemistry in 42 CRC patients undergoing preoperative PET-CT examination. Spearman correlation analysis was used to assess the relationship between EIF2S2 and GLUT1 levels and clinical parameters. Correlation analysis between EIF2S2 and Reactome-Glycolysis signatures was performed using GEPIA2. We describe the effect of EIF2S2 knockdown on lactate production and the mRNA levels of glycolysis-related genes in human colon cancer SW480 cells. Results: Immunohistochemistry revealed an upregulation of EIF2S2 protein expression in tumor tissues of colorectal cancer patients, which is consistent with the significant upregulation of EIF2S2 transcript levels in the database. These colorectal cancer patients included 24 cases of colon cancer and 18 cases of rectal cancer, ranging in age from 31 to 78 years. The transcription was significantly related to histological subtypes and TP53 mutations (P <0.05). The value of SUVmax in CRC significantly correlated with the expression of EIF2S2 (rho = 0.462, P <0.01). Although SUVmax and SUVmean was not correlate with the expression of GLUT1 (P <0.05), a significant correlation was observed between the expression of GLUT1 and the volumetric PET parameters, such as MTV and TLG (P < 0.01). GLUT1 expression in CRC was positively correlated with EIF2S2 status (rho = 0.470, P <0.01). In SW480 cells, RNAi-mediated depletion of EIF2S2 inhibited lactic acid production (P <0.05) and SLC2A1, SLC2A3, SLC2A10, HK2, PKM2, LDHA mRNA level (P <0.01). Conclusions: Primary CRC FDG uptake is strongly associated with the overexpression of EIF2S2, and EIF2S2 may promote glycolysis in CRC by mediating GLUT1.

Inhibitors of Venezuelan Equine Encephalitis Virus Identified Based on Host Interaction Partners of Viral Non-Structural Protein 3.

Venezuelan equine encephalitis virus (VEEV) is a new world alphavirus and a category B select agent. Currently, no FDA-approved vaccines or therapeutics are available to treat VEEV exposure and resultant disease manifestations. The C-terminus of the VEEV non-structural protein 3 (nsP3) facilitates cell-specific and virus-specific host factor binding preferences among alphaviruses, thereby providing targets of interest when designing novel antiviral therapeutics. In this study, we utilized an overexpression construct encoding HA-tagged nsP3 to identify host proteins that interact with VEEV nsP3 by mass spectrometry. Bioinformatic analyses of the putative interactors identified 42 small molecules with the potential to inhibit the host interaction targets, and thus potentially inhibit VEEV. Three inhibitors, tomatidine, citalopram HBr, and Z-VEID-FMK, reduced replication of both the TC-83 strain and the Trinidad donkey (TrD) strain of VEEV by at least 10-fold in astrocytoma, astroglial, and microglial cells. Further, these inhibitors reduced replication of the related New World (NW) alphavirus Eastern equine encephalitis virus (EEEV) in multiple cell types, thus demonstrating broad-spectrum antiviral activity. Time-course assays revealed all three inhibitors reduced both infectious particle production and positive-sense RNA levels post-infection. Further evaluation of the putative host targets for the three inhibitors revealed an interaction of VEEV nsP3 with TFAP2A, but not eIF2S2. Mechanistic studies utilizing siRNA knockdowns demonstrated that eIF2S2, but not TFAP2A, supports both efficient TC-83 replication and genomic RNA synthesis, but not subgenomic RNA translation. Overall, this work reveals the composition of the VEEV nsP3 proteome and the potential to identify host-based, broad spectrum therapeutic approaches to treat new world alphavirus infections.

Prognostic prediction and gene regulation network of EIF2S2 in hepatocellular carcinoma based on data mining.

BACKGROUND: Hepatocellular carcinoma (HCC) is a malignant tumor with a high fatality rate, predicting poor prognosis and therapeutic effect. Screening potential prognostic genes in HCC could be a creative way to advance clinical treatment. Eukaryotic translation initiation factor 2 subunit beta (EIF2S2) has reportedly been linked to several tumors, including liver cancer, but the prognostic predictions remain unknown. Therefore, we aimed to clarify the prognostic role and interaction network of EIF2S2 in HCC using bioinformatics data. METHODS: We screened EIF2S2 using the Oncomine, Ualcan, and TCGA databases. R software was used to analyze the mRNA level and clinicopathological characteristics of hepatocellular carcinoma. Evaluation of the correlations between EIF2S2 and patients' survival was made using the Kaplan-Meier curves and Cox proportional hazards regression model. Then, the influence of EIF2S2 gene mutations on the prognosis of patients was explored by cBioPortal. The protein-protein interaction network of 50 similar genes related to EIF2S2 was implemented by GEPIA2 and Metascape. The LinkedOmics database allowed us to carry out Gene Set Enrichment Analysis. Finally, we constructed the EIF2S2 kinase, miRNA, and transcription factor target networks using GeneMANIA. RESULTS: EIF2S2 mRNA was overexpressed in HCC and was closely associated with clinicopathological features, including gender, age, race, tumor grade, and stage. There was no correlation between EIF2S2 genetic mutations and prognostic survival. Combining Cox proportional hazards regression model analyses, high-expressed EIF2S2 predicted poor prognosis in HCC patients. Additionally, we screened the top three EIF2S2-related genes (PFDN4, HM13, and SNRPD1), the 50 similar genes, and then constructed a 50-similar-gene protein-protein interaction network identified by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways using Metascape. EIF2S2 target networks in HCC were identified in kinase, miRNA, and transcription factor networks, including the mitogen-activated protein kinase 1 (MAPK1), miRNAs (Mir-144), and transcription factors (GGAANCGGAANY_UNKNOWN) using GeneMANIA. CONCLUSIONS: EIF2S2 plays a crucial role in the gene-regulating network of HCC and may be a potential prognostic marker or therapeutic target for HCC patients.