Expression profile of translation initiation factor eIF2B5 in diffuse large B-cell lymphoma and its correlation to clinical outcome

EIF2B5 promotes malignant progression of hepatocellular carcinoma by activating the PI3K/AKT signaling pathway through targeting RPL6

Hepatocellular carcinoma (HCC) is a highly aggressive malignancy with limited treatment options and poor prognosis. In this study, we demonstrated the critical role of EIF2B5 in driving HCC progression. We found EIF2B5 expression is significantly upregulated in HCC tumor tissues in several bioinformatics datasets, including The Cancer Genome Atlas, and that high expression of EIF2B5 predicts poor prognosis for HCC patients. Through a series of in vitro cell biology experiments, we found that EIF2B5 knockdown significantly attenuated Hep3B and HepG2 proliferation, migration, and invasion and increased cell cycle arrest, whereas EIF2B5 overexpression promoted HCC progression. Through mass spectrometry and immunoprecipitation validation, we found that EIF2B5 directly interacted with RPL6 and that when EIF2B5 was overexpressed in HCC cells, it promoted the expression of the downstream protein RPL6, which was able to activate the phosphatidylinositol kinase (PI3K)/serine-threonine kinase (AKT)/mammalian target of rapamycin (mTOR) pathway and thereby increase the proliferation and invasion ability of HCC cell lines, as verified by second-generation sequencing analysis and western blot. We further verified these findings using the mouse ectopic tumor assay, and the results showed that EIF2B5 knockdown significantly inhibited tumor progression in HCC mice. The present study suggests that EIF2B5 promotes malignant progression of HCC by interacting with RPL6 and activating the PI3K/AKT/mTOR signaling pathway and may serve as a potential target for the treatment of HCC.

LncRNA KCNQ1OT1 promotes the metastasis of ovarian cancer by increasing the methylation of EIF2B5 promoter

Background

Long non-coding RNAs (lncRNAs) have emerged as regulators of human malignancies, including ovarian cancer (OC). LncRNA KCNQ1OT1 could promote OC progression, and EIF2B5 was associated with development of several tumors. This project was aimed to explore the role of lncRNA KCNQ1OT1 in OC development, as well as the involving action mechanism.

Methods

Reverse transcription quantitative polymerase chain reaction (RT-qPCR) or Western blotting was employed to determine the expression levels of KCNQ1OT1 and EIF2B5. OC cell proliferation was evaluated by MTT and colony formation assays, and wound healing and Transwell assays were implemented to monitor cell migration and invasion, respectively. The methylation status of EIF2B5 promoter was examined by MS-PCR, to clarify whether the expression of EIF2B5 was decreased. The binding activity of KCNQ1OT1 to methyltransferases DNMT1, DNMT3A and DNMT3B was determined by dual luciferase reporter assay or RIP assay, to explore the potential of KCNQ1OT1 alters the expression of its downstream gene. ChIP assay was carried out to verify the combination between EIF2B5 promoter and above three methyltransferases.

Results

Expression of lncRNA KCNQ1OT1 was increased in OC tissues and cells. EIF2B5 expression was downregulated in OC, which was inversely correlated with KCNQ1OT1. Knockdown of KCNQ1OT1 inhibited OC cell proliferation and metastasis. KCNQ1OT1 could downregulate EIF2B5 expression by recruiting DNA methyltransferases into EIF2B5 promoter. Furthermore, interference of EIF2B5 expression rescued KCNQ1OT1 depletion-induced inhibitory impact on OC cell proliferation and metastasis.

Conclusion

Our findings evidenced that lncRNA KCNQ1OT1 aggravated ovarian cancer metastasis by decreasing EIF2B5 expression level, and provided a novel therapeutic strategy for OC.

LncRNA KCNQ1OT1 is upregulated, while EIF2B5 is downregulated in OC tissues and cells.

Knockdown of KCNQ1OT1 represses OC cell proliferation and metastasis.

KCNQ1OT1 decreases EIF2B5 expression by recruiting DNA methyltransferases into EIF2B5 promoter, thereby promoting OC progression.

Targeted inhibition of mRNA translation initiation factors as a novel therapeutic strategy for mature B-cell neoplasms

Cancer development is frequently associated with dysregulation of mRNA translation to enhance both increased global protein synthesis and translation of specific mRNAs encoding oncoproteins. Thus, targeted inhibition of mRNA translation is viewed as a promising new approach for cancer therapy. In this article we review current progress in investigating dysregulation of mRNA translation initiation in mature B-cell neoplasms, focusing on chronic lymphocytic leukemia, follicular lymphoma and diffuse large B-cell lymphoma. We discuss mechanisms and regulation of mRNA translation, potential pathways by which genetic alterations and the tumor microenvironment alters mRNA translation in malignant B cells, preclinical evaluation of drugs targeted against specific eukaryotic initiation factors and current progress towards clinical development. Overall, inhibition of mRNA translation initiation factors is an exciting and promising area for development of novel targeted anti-tumor drugs.

OSdlbcl: An online consensus survival analysis web server based on gene expression profiles of diffuse large B-cell lymphoma

Diffuse large B‐cell lymphoma (DLBCL) is the most common subtype of non‐Hodgkin lymphoma (NHL) and is a clinical, pathological, and molecular heterogeneous disease with highly variable clinical outcomes. Currently, valid prognostic biomarkers in DLBCL are still lacking. To optimize targeted therapy and improve the prognosis of DLBCL, the performance of proposed biomarkers needs to be evaluated in multiple cohorts, and new biomarkers need to be investigated in large datasets. Here, we developed a consensus Online Survival analysis web server for Diffuse Large B‐Cell Lymphoma, abbreviated OSdlbcl, to assess the prognostic value of individual gene. To build OSdlbcl, we collected 1100 samples with gene expression profiles and clinical follow‐up information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. In addition, DNA mutation data were also collected from the TCGA database. Overall survival (OS), progression‐free survival (PFS), disease‐specific survival (DSS), disease‐free interval (DFI), and progression‐free interval (PFI) are important endpoints to reflect the survival rate in OSdlbcl. Moreover, clinical features were integrated into OSdlbcl to allow data stratifications according to the user's special needs. By inputting an official gene symbol and selecting desired criteria, the survival analysis results can be graphically presented by the Kaplan‐Meier (KM) plot with hazard ratio (HR) and log‐rank p value. As a proof‐of‐concept demonstration, the prognostic value of 23 previously reported survival associated biomarkers, such as transcription factors FOXP1 and BCL2, was evaluated in OSdlbcl and found to be significantly associated with survival as reported (HR = 1.73, P < .01; HR = 1.47, P = .03, respectively). In conclusion, OSdlbcl is a new web server that integrates public gene expression, gene mutation data, and clinical follow‐up information to provide prognosis evaluations for biomarker development for DLBCL. The OSdlbcl web server is available at https://bioinfo.henu.edu.cn/DLBCL/DLBCLList.jsp.