Systematically profiling the expression of eIF3 subunits in glioma reveals the expression of eIF3i has prognostic value in IDH-mutant lower grade glioma

Circ-EIF3I Promotes Hepatocellular Carcinoma Progression Through Modulating miR-361-3p/DUSP2 Axis

Hepatocellular carcinoma (HCC) is one of the most common malignant cancers globally. Circular RNAs (circRNAs) have been implicated in the development of HCC. Previous studies have confirmed that circ-EIF3I plays an important role in the progress of lung cancer. Nevertheless, the biological functions of circ-EIF3I and the underlying mechanisms by which they regulate HCC progression remain unclear. In this study, the regulatory mechanism and targets were studied with bioinformatics analysis, luciferase reporting analysis, transwell migration, Cell Counting Kit-8, and 5-Ethynyl-2'-deoxyuridine analysis. In addition, in vivo tumorigenesis and metastasis assays were employed to evaluate the roles of circ-EIF3I in HCC. The result shows that the circ-EIF3I expression was increased in HCC cell line, which means that circ-EIF3I plays a role in the progression of HCC. Downregulation of circ-EIF3I suppressed HCC cells' proliferation and migration in both in vivo and in vitro experiments. Bioinformatics and luciferase report analysis confirmed that both miR-361-3p and Dual-specificity phosphatase 2 (DUSP2) were the downstream target of circ-EIF3I. The overexpression of DUSP2 or inhibition of miR-361-3p restored HCC cells' proliferation and migration ability after silence circ-EIF3I. Taken together, our study found that downregulation of circ-EIF3I suppressed the progression of HCC through miR-361-3p/DUSP2 Axis.

Emerging Roles and Mechanisms of RNA Modifications in Neurodegenerative Diseases and Glioma

Despite a long history of research, neurodegenerative diseases and malignant brain tumor gliomas are both considered incurable, facing challenges in the development of treatments. Recent evidence suggests that RNA modifications, previously considered as static components of intracellular RNAs, are in fact dynamically regulated across various RNA species in cells and play a critical role in major biological processes in the nervous system. Innovations in next-generation sequencing have enabled the accurate detection of modifications on bases and sugars within various RNA molecules. These RNA modifications influence the stability and transportation of RNA, and crucially affect its translation. This review delves into existing knowledge on RNA modifications to offer a comprehensive inventory of these modifications across different RNA species. The detailed regulatory functions and roles of RNA modifications within the nervous system are discussed with a focus on neurodegenerative diseases and gliomas. This article presents a comprehensive overview of the fundamental mechanisms and emerging roles of RNA modifications in these diseases, which can facilitate the creation of innovative diagnostics and therapeutics for these conditions.

An Integrated Approach of Learning Genetic Networks From Genome-Wide Gene Expression Data Using Gaussian Graphical Model and Monte Carlo Method

Global genetic networks provide additional information for the analysis of human diseases, beyond the traditional analysis that focuses on single genes or local networks. The Gaussian graphical model (GGM) is widely applied to learn genetic networks because it defines an undirected graph decoding the conditional dependence between genes. Many algorithms based on the GGM have been proposed for learning genetic network structures. Because the number of gene variables is typically far more than the number of samples collected, and a real genetic network is typically sparse, the graphical lasso implementation of GGM becomes a popular tool for inferring the conditional interdependence among genes. However, graphical lasso, although showing good performance in low dimensional data sets, is computationally expensive and inefficient or even unable to work directly on genome-wide gene expression data sets. In this study, the method of Monte Carlo Gaussian graphical model (MCGGM) was proposed to learn global genetic networks of genes. This method uses a Monte Carlo approach to sample subnetworks from genome-wide gene expression data and graphical lasso to learn the structures of the subnetworks. The learned subnetworks are then integrated to approximate a global genetic network. The proposed method was evaluated with a relatively small real data set of RNA-seq expression levels. The results indicate the proposed method shows a strong ability of decoding the interactions with high conditional dependences among genes. The method was then applied to genome-wide data sets of RNA-seq expression levels. The gene interactions with high interdependence from the estimated global networks show that most of the predicted gene-gene interactions have been reported in the literatures playing important roles in different human cancers. Also, the results validate the ability and reliability of the proposed method to identify high conditional dependences among genes in large-scale data sets.

Understanding the Epitranscriptome for Avant-Garde Brain Tumour Diagnostics

RNA modifications are diverse, dynamic, and reversible transcript alterations rapidly gaining attention due to their newly defined RNA regulatory roles in cellular pathways and pathogenic mechanisms. The exciting emerging field of 'epitranscriptomics' is predominantly centred on studying the most abundant mRNA modification, N6-methyladenine (m⁶A). The m⁶A mark, similar to many other RNA modifications, is strictly regulated by so-called 'writer', 'reader', and 'eraser' protein species. The abundance of genes coding for the expression of these regulator proteins and m⁶A levels shows great potential as diagnostic and predictive tools across several cancer fields. This review explores our current understanding of RNA modifications in glioma biology and the potential of epitranscriptomics to develop new diagnostic and predictive classification tools that can stratify these highly complex and heterogeneous brain tumours.

Comprehensive Analysis of the Prognostic Value and Molecular Function of CRNDE in Glioma at Bulk and Single-Cell Levels

Colorectal neoplasia differentially expressed (CRNDE) is an oncogenic long noncoding RNA (lncRNA) overexpressed in diverse malignancies. Here, we comprehensively analyze the prognostic value and molecular function of CRNDE in glioma. Bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA), and single-cell RNA-sequencing data from the Tumor Immune Single-Cell Hub (TISCH) were analyzed. Kaplan-Meier survival analysis was applied to verify the prognostic value of CRNDE. Then, a nomogram based on multivariate Cox regression was established for individualized survival prediction. Subsequently, the expression characteristic and biological function of CRNDE were analyzed at the single-cell level. Lastly, the effects of CRNDE on the proliferation and invasion of glioma cell were explored in vitro. We discovered that CRNDE was a powerful marker for risk stratification of glioma patients. Regardless of the status of IDH and 1p/19q, CRNDE could effectively stratify patients' prognosis. The nomogram that incorporated the CRNDE expression was proved to be a reliable tool for survival prediction. In addition, epithelial-mesenchymal transition may be the most important biological process regulated by CRNDE, which was identified at both the bulk and single-cell levels. Moreover, CRNDE knockdown significantly inhibited the proliferation and invasion of glioma cell. Overall, CRNDE is a vital oncogene and may be a valuable supplement to improve the clinical stratification of glioma.

Development of a Hallmark Pathway-Related Gene Signature Associated with Immune Response for Lower Grade Gliomas

Although some biomarkers have been used to predict prognosis of lower-grade gliomas (LGGs), a pathway-related signature associated with immune response has not been developed. A key signaling pathway was determined according to the lowest adjusted p value among 50 hallmark pathways. The least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox analyses were performed to construct a pathway-related gene signature. Somatic mutation, drug sensitivity and prediction of immunotherapy analyses were conducted to reveal the value of this signature in targeted therapies. In this study, an allograft rejection (AR) pathway was considered as a crucial signaling pathway, and we constructed an AR-related five-gene signature, which can independently predict the prognosis of LGGs. High-AR LGG patients had higher tumor mutation burden (TMB), Immunophenscore (IPS), IMmuno-PREdictive Score (IMPRES), T cell-inflamed gene expression profile (GEP) score and MHC I association immunoscore (MIAS) than low-AR patients. Most importantly, our signature can be validated in four immunotherapy cohorts. Furthermore, IC50 values of the six classic chemotherapeutic drugs were significantly elevated in the low-AR group compared with the high-AR group. This signature might be regarded as an underlying biomarker in predicting prognosis for LGGs, possibly providing more therapeutic strategies for future clinical research.

Molecular markers related to patient outcome in patients with IDH-mutant astrocytomas grade 2 to 4: A systematic review

BACKGROUND

Grading and classification of IDH-mutant astrocytomas has shifted from solely histology towards histology combined with molecular diagnostics. In this systematic review, we give an overview of all currently known clinically relevant molecular markers within IDH-mutant astrocytomas grade 2 to 4.

METHODS

A literature search was performed in five electronic databases for English original papers on patient outcome with respect to a molecular marker as determined by DNA/RNA sequencing, micro-arrays, or DNA methylation profiling in IDH-mutant astrocytomas grade 2 to 4. Papers were included if molecular diagnostics were performed on tumour tissue of at least 15 IDH-mutant astrocytoma patients, and if the investigated molecular markers were not limited to the diagnostic markers MGMT, ATRX, TERT, and/or TP53.

RESULTS

The literature search identified 4508 unique articles, published between August 2012 and December 2021, of which ultimately 44 articles were included. Numerous molecular markers from these papers were significantly correlated to patient outcome. The associations between patient outcome and non-canonical IDH mutations, PI3K mutations, high expression of MSH2, high expression of RAD18, homozygous deletion of CDKN2A/B, amplification of PDGFRA, copy number neutral loss of chromosomal arm 17p, loss of chromosomal arm 19q, the G-CIMP-low DNA methylation cluster, high total CNV, and high tumour mutation burden were confirmed in multiple studies.

CONCLUSIONS

Multiple genetic and epigenetic markers are associated with survival in IDH-mutant astrocytoma patients. Commonly affected are the RB signalling pathway, the RTK-PI3K-mTOR signalling pathway, genomic stability markers, and (epigenetic) gene regulation.

Eukaryotic translation initiation factor 3 subunit B promotes head and neck cancer via CEBPB translation

Background

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer type worldwide. Deregulation of mRNA translation is a frequent feature of cancer. Eukaryotic translation initiation factor 3 subunit B (EIF3B) has been reported as an oncogene; however, its role in HNSCC has yet to be fully elucidated.

Methods

In this study, the clinical significance of EIF3B expression was analyzed based on TCGA datasets. Then, EIF3B expression was knocked down and its role in HNSCC was revealed. To explore the molecular mechanisms of EIF3B, we applied RNA sequencing and proteomics and acquired deregulated pathways. RNA immunoprecipitation (RIP) sequencing was conducted to reveal the target mRNAs of EIF3B, and TCGA datasets were used to validate potential targets of EIF3B.

Results

Elevated expression of EIF3B was observed in the HNSCC cancer samples. The expression of EIF3B was significantly correlated with the patient’s sex, age, HPV infection status, T stage, N stage, perineural invasion status and survival status. EIF3B serves as a marker of an unfavorable HNSCC prognosis. EIF3B-silenced Fadu and Cal27 cells exhibited reduced cell numbers, and EIF3B knockdown induced apoptosis in both cell lines. The EIF3B-silenced cells demonstrated decreased invasion and migration capabilities, and the EIF3B knockdown group mice showed significantly decreased tumor volumes. The results show that EIF3B promotes CEBPB translation and activates the MAPK pathway and revealed that IL6R and CCNG2 are targets of EIF3B-regulated CEBPB translation.

Conclusion

In summary, the results indicated that EIF3B is a novel oncogene in HNSCC that promotes CEBPB translation and IL6R expression, and these findings provide a link between the molecular basis and pathogenesis of HNSCC.

Graphical Abstract

EIF3B is a prognostic biomarker for HNSCC risk;

EIF3B promotes HNSCC progression in vitro and in vivo;

EIF3B promotes CEBPB translation and activates the MAPK pathway;

IL6R and CCNG2 are targets of EIF3B-regulated CEBPB translation.

The Roles and Regulation of m6A Modification in Glioblastoma Stem Cells and Tumorigenesis

Glioblastoma is the most common and most lethal primary malignant brain tumor. N6-methyladenosine (m6A) is a widespread and abundant internal messenger RNA (mRNA) modification found in eukaryotes. Accumulated evidence demonstrates that m6A modification is aberrantly activated in human cancers and is critical for tumorigenesis and metastasis. m6A modification is also strongly involved in key signaling pathways and is associated with prognosis in glioblastoma. Here, we briefly outline the functions of m6A and its regulatory proteins, including m6A writers, erasers, and readers of the fate of RNA. We also summarize the latest breakthroughs in this field, describe the underlying molecular mechanisms that contribute to the tumorigenesis and progression, and highlight the inhibitors targeting the factors in m6A modification in glioblastoma. Further studies focusing on the specific pathways of m6A modification could help identify biomarkers and therapeutic targets that might prevent and treat glioblastoma.

CD20 positive CD8 T cells are a unique and transcriptionally-distinct subset of T cells with distinct transmigration properties

The presence of T cells that are dimly positive for the B cell marker CD20 is well-established in autoimmunity and correlates with disease severity in various diseases. Further, we previously identified that the level of CD20-positive T cells was three-fourfold elevated in ascites fluid of ovarian carcinoma patients, together suggesting a role in both autoimmunity and cancer. In this respect, treatment of autoimmune patients with the CD20-targeting antibody Rituximab has also been shown to target and deplete CD20-positive T cells, previously identified as IFN-gamma producing, low proliferative, CD8 cytotoxic T cells with an effector memory (EM) differentiation state. However, the exact phenotype and relevance of CD20-positive T cells remains unclear. Here, we set out to identify the transcriptomic profile of CD20-positive T cells using RNA sequencing. Further, to gain insight into potential functional properties of CD20 expression in T cells, CD20 was ectopically expressed on healthy human T cells and phenotypic, functional, migratory and adhesive properties were determined in vitro and in vivo. Together, these assays revealed a reduced transmigration and an enhanced adhesive profile combined with an enhanced activation status for CD20-positive T cells.

Promoting Prognostic Model Application: A Review Based on Gliomas

Malignant neoplasms are characterized by poor therapeutic efficacy, high recurrence rate, and extensive metastasis, leading to short survival. Previous methods for grouping prognostic risks are based on anatomic, clinical, and pathological features that exhibit lower distinguishing capability compared with genetic signatures. The update of sequencing techniques and machine learning promotes the genetic panels-based prognostic model development, especially the RNA-panel models. Gliomas harbor the most malignant features and the poorest survival among all tumors. Currently, numerous glioma prognostic models have been reported. We systematically reviewed all 138 machine-learning-based genetic models and proposed novel criteria in assessing their quality. Besides, the biological and clinical significance of some highly overlapped glioma markers in these models were discussed. This study screened out markers with strong prognostic potential and 27 models presenting high quality. Conclusively, we comprehensively reviewed 138 prognostic models combined with glioma genetic panels and presented novel criteria for the development and assessment of clinically important prognostic models. This will guide the genetic models in cancers from laboratory-based research studies to clinical applications and improve glioma patient prognostic management.

Promoting Prognostic Model Application: A Review Based on Gliomas

Malignant neoplasms are characterized by poor therapeutic efficacy, high recurrence rate, and extensive metastasis, leading to short survival. Previous methods for grouping prognostic risks are based on anatomic, clinical, and pathological features that exhibit lower distinguishing capability compared with genetic signatures. The update of sequencing techniques and machine learning promotes the genetic panels-based prognostic model development, especially the RNA-panel models. Gliomas harbor the most malignant features and the poorest survival among all tumors. Currently, numerous glioma prognostic models have been reported. We systematically reviewed all 138 machine-learning-based genetic models and proposed novel criteria in assessing their quality. Besides, the biological and clinical significance of some highly overlapped glioma markers in these models were discussed. This study screened out markers with strong prognostic potential and 27 models presenting high quality. Conclusively, we comprehensively reviewed 138 prognostic models combined with glioma genetic panels and presented novel criteria for the development and assessment of clinically important prognostic models. This will guide the genetic models in cancers from laboratory-based research studies to clinical applications and improve glioma patient prognostic management.

A Profound Basic Characterization of eIFs in Gliomas: Identifying eIF3I and 4H as Potential Novel Target Candidates in Glioma Therapy

Simple Summary

Gliomas are brain tumors with currently limited therapy options. Glioma growth and proliferation is regulated by the mTOR pathway together with eukaryotic initiation factors (eIFs). In this work we show a profound basic characterization of eIFs in human gliomas and demonstrate increased mRNA and protein expressions of several eIFs in gliomas compared to healthy control brain tissue. Moreover, increased eIF3I and eIF4H levels seem to have a negative influence on the survival of patients. Our work suggests eIF3I and eIF4H as potential targets for future glioma therapy.

Abstract

Glioblastoma (GBM) is an utterly devastating cerebral neoplasm and current therapies only marginally improve patients’ overall survival (OS). The PI3K/AKT/mTOR pathway participates in gliomagenesis through regulation of cell growth and proliferation. Since it is an upstream regulator of the rate-limiting translation initiation step of protein synthesis, controlled by eukaryotic initiation factors (eIFs), we aimed for a profound basic characterization of 17 eIFs to identify potential novel therapeutic targets for gliomas. Therefore, we retrospectively analyzed expressions of mTOR-related proteins and eIFs in human astrocytoma samples (WHO grades I–IV) and compared them to non-neoplastic cortical control brain tissue (CCBT) using immunoblot analyses and immunohistochemistry. We examined mRNA expression using qRT-PCR and additionally performed in silico analyses to observe the influence of eIFs on patients’ survival. Protein and mRNA expressions of eIF3B, eIF3I, eIF4A1, eIF4H, eIF5 and eIF6 were significantly increased in high grade gliomas compared to CCBT and partially in low grade gliomas. However, short OS was only associated with high eIF3I gene expression in low grade gliomas, but not in GBM. In GBM, high eIF4H gene expression significantly correlated with shorter patient survival. In conclusion, we identified eIF3I and eIF4H as the most promising targets for future therapy for glioma patients.

EIF3B promotes cancer progression in pancreatic cancer

BACKGROUND

This study aimed to analyze the relative expression of Eukaryotic Translation Initiation Factor 3 Subunit B (EIF3B) in pancreatic cancer and elucidate its contribution to this disease.

METHODS

Relative expression of EIF3B in pancreatic cancer was analyzed by immunohistochemistry. Cell viability was determined by the MTT assay and cell proliferation was measured by direct cell counting. Cell apoptosis was detected by Annexin V staining followed by flow cytometry analysis, and cell cycle was analyzed by PI staining. The differential expression gene analysis was performed by microarray. Tumor progression in response to EIF3B deficiency in vivo was investigated using the xenograft tumor model.

RESULTS

We found aberrantly high expression of EIF3B in pancreatic cancer, which associated with unfavorable prognosis. Knockdown of EIF3B greatly compromised cell viability and proliferation in both SW1990 and PANC-1 cells. Furthermore, EIF3B deficiency induced cell cycle arrest and spontaneous apoptosis. In vivo tumor progression was significantly suppressed by EIF3B silencing in the xenograft mouse model. Mechanistically, we characterized down-regulation of CDH1 and IRS1 and up-regulation of DDIT3, PTEN and CDKN1B, in response to EIF3B knockdown, which might mediate the oncogenic effect of EIF3B in pancreatic cancer.

CONCLUSIONS

Our data uncovered the oncogenic role of EIF3B in pancreatic cancer.

EIF3H knockdown inhibits malignant melanoma through regulating cell proliferation, apoptosis and cell cycle

Malignant melanoma (MM) causes 80% of skin cancer-related deaths and becomes the most lethal type of skin cancer. The molecular mechanism of MM is still not clear. This study aimed to reveal the relationship between MM and EIF3H. Clinical specimens were collected to preliminarily explore the role of EIF3H in MM. MM cell lines with EIF3H knockdown were constructed for investigating the effects of EIF3H on cell proliferation, apoptosis, cell cycle and cell motility. Mice xenograft model was constructed for verification in vivo. We found that EIF3H was obviously upregulated in MM tissues compared with normal skin tissues, which was correlated with tumor stage and risk of lymphatic metastasis. The in vitro results indicated that silencing EIF3H in MM cells could significantly suppress cell proliferation, promote cell apoptosis and induce cell cycle arrest. Moreover, EIF3H knockdown significantly restrained cell motility through regulating EMT-related proteins. The effects of EIF3H knockdown were also verified in mice xenograft model, which were represented by slower growth rate, smaller volume and lighter weight of tumors. Therefore, EIF3H was identified as a critical factor in the development and progression of MM which may be used as a novel therapeutic target in the treatment of MM.

eIF3i regulation of protein synthesis, cell proliferation, cell cycle progression, and tumorigenesis

eIF3i, a 36-kDa protein, is a putative subunit of the eIF3 complex important for translation initiation of mRNAs. It is a WD40 domain-containing protein with seven WD40 repeats that forms a β-propeller structure with an important function in pre-initiation complex formation and mRNA translation initiation. In addition to participating in the eIF3 complex formation for global translational control, eIF3i may bind to specific mRNAs and regulate their translation individually. Furthermore, eIF3i has been shown to bind to TGF-β type II receptor and participate in TGF-β signaling. It may also participate in and regulate other signaling pathways including Wnt/β-catenin pathway via translational regulation of COX-2 synthesis. These multiple canonical and noncanonical functions of eIF3i in translational control and in regulating signal transduction pathways may be responsible for its role in cell differentiation, cell cycle regulation, proliferation, and tumorigenesis. In this review, we will critically evaluate recent progresses and assess future prospects in studying eIF3i.

Development of a nomogram for prognostic prediction of lower-grade glioma based on alternative splicing signatures

BACKGROUND

The prognosis of lower-grade glioma (LGG) differs from that of other grades gliomas. Although lots of studies on the prognostic biomarkers of LGG have been reported, few have significant clinical impact. Alternative splicing (AS) events can affect cell function by splicing precursor mRNA. Therefore, a prognostic model for LGG based on AS events are important to establish.

METHODS

RNA sequencing, clinical, and AS event data of 510 LGG patients from the TCGA database were downloaded. Univariate Cox regression analysis was used to screen out prognostic-related AS events and LASSO regression and multivariate Cox regression were used to establish prognostic risk scores for patients in the training set (n = 340). After validation, a nomogram model was established based on the AS signature and clinical information, which was able to predict 1-, 3-, and 5-year survival rates. Finally, considering the regulatory effect of splicing factors (SFs) on AS events, an AS-SF regulatory network was analyzed.

RESULTS

The most common AS event was exon skipping and the least was mutually exclusive exons. All the seven AS events were related to the prognosis of LGG patients, regardless of whether they were separated or considered as a whole event (integrated AS event), and the integrated AS event had the most significant correlation. After further inclusion of clinical indicators, eight factors were screened out: age, new event, KPS, WHO grade, treatment, integrated AS signature, IDH1 and TP53 mutation status, and a nomogram model was established. The study also constructed an AS-SF regulatory network.

CONCLUSION

The AS events and clinical factors that can predict the prognosis of LGG patients were screened, and a prognostic prediction model was established. The results of this study can play an important role in clinical work to better evaluate the prognosis of patients and impact treatment options.

Genetic Profiles Playing Opposite Roles of Pathogenesis in Schizophrenia and Glioma

Background

Patients diagnosed with schizophrenia were found having lower risks to develop cancers, including glioma. Based on this epidemiology, we hypothesized that there were gene profiles playing opposite roles in pathogenesis of schizophrenia and glioma.

Methods

Based on GEO datasets and TCGA, key genes of schizophrenia genes on the opposite development of glioma were screened by different expressed genes (DEGs) screening, weighted gene coexpression network analysis (WGCNA), disease-specific survival (DSS), and glioma grading and verified by gene set enrichment analysis (GSEA).

Results

First, 612 DEGs were screened from schizophrenia and control brain samples. Second, 134 key genes more specific to schizophrenia were left by WGCNA, with 93 key genes having annotations in TCGA. Third, DSS of glioma helped to find 42 key gene expressions of schizophrenia oppositely associated with survival of glioma. Finally, 24 key genes showed opposite expression trends in schizophrenia and different glioma grading, i.e., the upregulated key genes in schizophrenia expressed increasingly in higher grade glioma, and vice versa. CAMK2D and MPC2 were taken as the examples and evaluated by GSEA, which indeed showed opposite trends in the same pathways of schizophrenia and glioma.

Conclusion

This workflow of selecting novel targeted genes which may have opposite roles in pathogenesis of two diseases was firstly and innovatively generated by our team. Some filtered key genes were indeed found by their potential effects in several mechanism studies, indicating our process could be effective to generate novel targeted genes. These 24 key genes may provide potential directions for future biochemical and pharmacotherapeutic research studies.

Eukaryotic translation initiation factor 3 subunit b is a novel oncogenic factor in prostate cancer

Prostate cancer, the second most common cancer among male adults, affects millions globally. We sought to investigate the expression and contribution of Eukaryotic translation initiation factor 3 subunit b (EIF3B) in prostate cancer. Expression of EIF3B was analyzed in both human prostate patient tissues and prostate cancer cell lines. Small interfering RNA (siRNA) knockdown of EIF3B was introduced into prostate cancer cell line PC-3 and LNCaP, followed by examination of cell viability, proliferation and apoptosis using the MTT, cell counting and terminal deoxynucleotidyl transferase dUTP nick end labeling assays, respectively. An in vivo xenograft tumor mouse model was employed to address the role of EIF3B in tumorigenesis as well. Finally, a gene microarray analysis was performed to search for differentially expressed genes upon EIF3B knockdown. EIF3B was upregulated in prostate tumor tissues and prostate cancer cell lines. EIF3B knockdown inhibited viability and proliferation of prostate cancer cells, as well as promoted cell apoptosis. In the in vivo mouse model, inoculation of EIF3B knockdown PC-3 cells displayed inhibited growth of xenograft tumors. In addition, potential signaling pathways that might be involved in EIF3B action in prostate cancer were identified by the gene microarray. EIF3B is a novel oncogenic factor in prostate cancer both in vitro and in vivo, which could be employed as a novel therapeutic target in the treatment against prostate cancer.

Relevance of Translation Initiation in Diffuse Glioma Biology and its Therapeutic Potential

Cancer cells are continually exposed to environmental stressors forcing them to adapt their protein production to survive. The translational machinery can be recruited by malignant cells to synthesize proteins required to promote their survival, even in times of high physiological and pathological stress. This phenomenon has been described in several cancers including in gliomas. Abnormal regulation of translation has encouraged the development of new therapeutics targeting the protein synthesis pathway. This approach could be meaningful for glioma given the fact that the median survival following diagnosis of the highest grade of glioma remains short despite current therapy. The identification of new targets for the development of novel therapeutics is therefore needed in order to improve this devastating overall survival rate. This review discusses current literature on translation in gliomas with a focus on the initiation step covering both the cap-dependent and cap-independent modes of initiation. The different translation initiation protagonists will be described in normal conditions and then in gliomas. In addition, their gene expression in gliomas will systematically be examined using two freely available datasets. Finally, we will discuss different pathways regulating translation initiation and current drugs targeting the translational machinery and their potential for the treatment of gliomas.

A Novel DNA Methylation-Based Signature Can Predict the Responses of MGMT Promoter Unmethylated Glioblastomas to Temozolomide

Glioblastoma (GBM) is the most malignant glioma, with a median overall survival (OS) of 14–16 months. Temozolomide (TMZ) is the first-line chemotherapy drug for glioma, but whether TMZ should be withheld from patients with GBMs that lack O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation is still under debate. DNA methylation profiling holds great promise for further stratifying the responses of MGMT promoter unmethylated GBMs to TMZ. In this study, we studied 147 TMZ-treated MGMT promoter unmethylated GBM, whose methylation information was obtained from the HumanMethylation27 (HM-27K) BeadChips (n = 107) and the HumanMethylation450 (HM-450K) BeadChips (n = 40) for training and validation, respectively. In the training set, we performed univariate Cox regression and identified that 3,565 CpGs were significantly associated with the OS of the TMZ-treated MGMT promoter unmethylated GBMs. Functional analysis indicated that the genes corresponding to these CpGs were enriched in the biological processes or pathways of mitochondrial translation, cell cycle, and DNA repair. Based on these CpGs, we developed a 31-CpGs methylation signature utilizing the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm. In both training and validation datasets, the signature identified the TMZ-sensitive GBMs in the MGMT promoter unmethylated GBMs, and only the patients in the low-risk group appear to benefit from the TMZ treatment. Furthermore, these identified TMZ-sensitive MGMT promoter unmethylated GBMs have a similar OS when compared with the MGMT promoter methylated GBMs after TMZ treatment in both two datasets. Multivariate Cox regression demonstrated the independent prognostic value of the signature in TMZ-treated MGMT promoter unmethylated GBMs. Moreover, we also noticed that the hallmark of epithelial–mesenchymal transition, ECM related biological processes and pathways were highly enriched in the MGMT unmethylated GBMs with the high-risk score, indicating that enhanced ECM activities could be involved in the TMZ-resistance of GBM. In conclusion, our findings promote our understanding of the roles of DNA methylation in MGMT umethylated GBMs and offer a very promising TMZ-sensitivity predictive signature for these GBMs that could be tested prospectively.