eIF4E3 acts as a tumor suppressor by utilizing an atypical mode of methyl-7-guanosine cap recognition

eIF4E orchestrates mRNA processing, RNA export and translation to modify specific protein production

The eukaryotic translation initiation factor eIF4E acts as a multifunctional factor that simultaneously influences mRNA processing, export, and translation in many organisms. Its multifactorial effects are derived from its capacity to bind to the methyl-7-guanosine cap on the 5'end of mRNAs and thus can act as a cap chaperone for transcripts in the nucleus and cytoplasm. In this review, we describe the multifactorial roles of eIF4E in major mRNA-processing events including capping, splicing, cleavage and polyadenylation, nuclear export and translation. We discuss the evidence that eIF4E acts at two levels to generate widescale changes to processing, export and ultimately the protein produced. First, eIF4E alters the production of components of the mRNA processing machinery, supporting a widescale reprogramming of multiple mRNA processing events. In this way, eIF4E can modulate mRNA processing without physically interacting with target transcripts. Second, eIF4E also physically interacts with both capped mRNAs and components of the RNA processing or translation machineries. Further, specific mRNAs are sensitive to eIF4E only in particular mRNA processing events. This selectivity is governed by the presence of cis-acting elements within mRNAs known as USER codes that recruit relevant co-factors engaging the appropriate machinery. In all, we describe the molecular bases for eIF4E's multifactorial function and relevant regulatory pathways, discuss the basis for selectivity, present a compendium of ~80 eIF4E-interacting factors which play roles in these activities and provide an overview of the relevance of its functions to its oncogenic potential. Finally, we summarize early-stage clinical studies targeting eIF4E in cancer.

CircVDAC3 sequesters microRNA-592 and elevates EIF4E3 expression to inhibit the progression of gastric cancer

BACKGROUND

Accumulating evidence has shown that circular RNAs (circRNAs) are involved in gastric cancer (GC) tumorigenesis. However, specific functional circRNAs in GC remain to be discovered, and their underlying mechanisms remain to be elucidated.

METHODS

CircRNAs that were differentially expressed between GC tissues and controls were analyzed using a circRNA microarray dataset. The expression of circVDAC3 in GC was determined using quantitative real-time PCR (qRT-PCR), and the structural features of circVDAC3 were validated. Cell function assays and animal experiments were conducted to explore the effects of circVDAC3 on GC. Finally, bioinformatics analysis, fluorescent in situ hybridization, and dual luciferase assays were used to analyze the downstream mechanisms of circVDAC3.

RESULTS

Our results showed that circVDAC3 was downregulated in GC and inhibited the proliferation and metastasis of GC cells. Mechanistically, circVDAC3 acts as a competing endogenous RNA (ceRNA) of miR-592 and deregulates the repression of EIF4E3 by miR-592. EIF4E3 is downregulated in GC and overexpression of miR-592 or knockdown of EIF4E3 in circVDAC3-overexpressing cells weakens the anticancer effect of circVDAC3.

CONCLUSION

Our study provides evidence that circVDAC3 affects the growth and metastasis of GC cells via the circVDAC3/miR-592/EIF4E3 axis. Our findings offer valuable insights into the mechanisms underlying GC tumorigenesis and suggest novel therapeutic strategies.

RNA modification gene WDR4 facilitates tumor progression and immunotherapy resistance in breast cancer

INTRODUCTION

Growing interest toward RNA modification in cancer has inspired the exploration of datasets related to multiple RNA modifications. However, a comprehensive elucidation of the clinical value of various RNA modifications in breast cancer is still lacking.

OBJECTIVES

This study aimed to provide a strategy based on RNA modification-related genes for predicting therapy response and survival outcomes in breast cancer patients.

METHODS

Genes related to thirteen RNA modification patterns were integrated for establishing a nine-gene-containing signature-RMscore. Alterations of tumor immune microenvironment and therapy response featured by different RMscore levels were assessed by bulk transcriptome, single-cell transcriptome and genomics analyses. The biological function of key RMscore-related molecules was investigated by cellular experiments in vitro and in vivo, using flow cytometry, immunohistochemistry and immunofluorescence staining.

RESULTS

This study has raised an effective therapy strategy for breast cancer patients after a well-rounded investigation of RNA modification-related genes. With a great performance of predicting patient prognosis, high levels of the RMscore proposed in this study represented suppressive immune microenvironment and therapy resistance, including adjuvant chemotherapy and PD-L1 blockade treatment. As the key contributor of the RMscore, inhibition of WDR4 impaired breast cancer progression significantly in vitro and in vivo, as well as participated in regulating cell cycle and mTORC1 signaling pathway via m7G modification.

CONCLUSION

Briefly, this study has developed promising and effective tactics to achieve the prediction of survival probabilities and treatment response in breast cancer patients.

Dual role of GRHL3 in bladder carcinogenesis depending on histological subtypes

The effect of grainyhead-like transcription factor 3 (GRHL3) on cancer development depends on the cancer subtypes as shown in tumor entities such as colorectal or oral squamous cell carcinomas. Here, we analyzed the subtype-specific role of GRHL3 in bladder carcinogenesis, comparing common urothelial carcinoma (UC) with squamous bladder cancer (sq-BLCA). We examined GRHL3 mRNA and protein expression in cohorts of patient samples, its prognostic role and its functional impact on tumorigeneses in different molecular and histopathological subtypes of bladder cancer. We showed for GRHL3 a reverse expression in squamous and urothelial bladder cancer subtypes. Stably GRHL3-overexpressing EJ28, J82, and SCaBER in vitro models revealed a tumor-suppressive function in squamous and an oncogenic role in the urothelial cancer cells affecting cell and colony growth, and migratory and invasive capacities. Transcriptomic profiling demonstrated highly subtype-specific GRHL3-regulated expression networks coined by the enrichment of genes involved in integrin-mediated pathways. In SCaBER, loss of ras homolog family member A (RHOA) GTPase activity was demonstrated to be associated with co-regulation of eukaryotic translation initiation factor 4E family member 3 (EIF4E3), a potential tumor suppressor gene. Thus, our data provide for the first time a detailed insight into the role of the transcription factor GRHL3 in different histopathological subtypes of bladder cancer.

Non-canonical mRNA translation initiation in cell stress and cancer

The now well described canonical mRNA translation initiation mechanism of m7G 'cap' recognition by cap-binding protein eIF4E and assembly of the canonical pre-initiation complex consisting of scaffolding protein eIF4G and RNA helicase eIF4A has historically been thought to describe all cellular mRNA translation. However, the past decade has seen the discovery of alternative mechanisms to canonical eIF4E mediated mRNA translation initiation. Studies have shown that non-canonical alternate mechanisms of cellular mRNA translation initiation, whether cap-dependent or independent, serve to provide selective translation of mRNAs under cell physiological and pathological stress conditions. These conditions typically involve the global downregulation of canonical eIF4E1/cap-mediated mRNA translation, and selective translational reprogramming of the cell proteome, as occurs in tumor development and malignant progression. Cancer cells must be able to maintain physiological plasticity to acquire a migratory phenotype, invade tissues, metastasize, survive and adapt to severe microenvironmental stress conditions that involve inhibition of canonical mRNA translation initiation. In this review we describe the emerging, important role of non-canonical, alternate mechanisms of mRNA translation initiation in cancer, particularly in adaptation to stresses and the phenotypic cell fate changes involved in malignant progression and metastasis. These alternate translation initiation mechanisms provide new targets for oncology therapeutics development.

Advances in prognostic models for osteosarcoma risk

The risk prognosis model is a statistical model that uses a set of features to predict whether an individual will develop a specific disease or clinical outcome. It can be used in clinical practice to stratify disease severity and assess risk or prognosis. With the advancement of large-scale second-generation sequencing technology, along Prognosis models for osteosarcoma are increasingly being developed as large-scale second-generation sequencing technology advances and clinical and biological data becomes more abundant. This expansion greatly increases the number of prognostic models and candidate genes suitable for clinical use. This article will present the predictive effects and reliability of various prognosis models, serving as a reference for their evaluation and application.

eIF4E1b is a non-canonical eIF4E protecting maternal dormant mRNAs

Maternal mRNAs are essential for protein synthesis during oogenesis and early embryogenesis. To adapt translation to specific needs during development, maternal mRNAs are translationally repressed by shortening the polyA tails. While mRNA deadenylation is associated with decapping and degradation in somatic cells, maternal mRNAs with short polyA tails are stable. Here we report that the germline-specific eIF4E paralog, eIF4E1b, is essential for zebrafish oogenesis. eIF4E1b localizes to P-bodies in zebrafish embryos and binds to mRNAs with reported short or no polyA tails, including histone mRNAs. Loss of eIF4E1b results in reduced histone mRNA levels in early gonads, consistent with a role in mRNA storage. Using mouse and human eIF4E1Bs (in vitro) and zebrafish eIF4E1b (in vivo), we show that unlike canonical eIF4Es, eIF4E1b does not interact with eIF4G to initiate translation. Instead, eIF4E1b interacts with the translational repressor eIF4ENIF1, which is required for eIF4E1b localization to P-bodies. Our study is consistent with an important role of eIF4E1b in regulating mRNA dormancy and provides new insights into fundamental post-transcriptional regulatory principles governing early vertebrate development.

Identification and validation of N7 -methylguanosine-associated gene NCBP1 as prognostic and immune-associated biomarkers in breast cancer patients

We intend to evaluate the importance of N7 -methylguanosine (m7G) for the prognosis of breast cancer (BC). We gained 29 m7G-related genes from the published literature and among them, 16 m7G-related genes were found to have differential expression. Five differentially expressed genes (CYFIP1, EIF4E, EIF4E3, NCBP1 and WDR4) were linked to overall survival. This suggests that m7G-related genes might be prognostic or therapeutic targets for BC patients. We put the five genes to LASSO regression analysis to create a four-gene signature, including EIF4E, EIF4E3, WDR4 and NCBP1, that divides samples into two risky groups. Survival was drastically worsened in a high-risk group (p < 0.001). The signature's predictive capacity was demonstrated using ROC (10-year AUC 0.689; 10-year AUC 0.615; 3-year AUC 0.602). We found that immune status was significantly different between the two risk groups. In particular, NCBP1 also has a poor prognosis, with higher diagnostic value in ROC. NCBP1 also has different immune states according to its high or low expression. Meanwhile, knockdown of NCBP1 suppresses BC malignancy in vitro. Therefore, m7G RNA regulators are crucial participants in BC and four-gene mRNA levels are important predictors of prognosis. NCBP1 plays a critical target of m7G mechanism in BC.

A methylation-related signature for predicting prognosis and sensitivity to first-line therapies in gastric cancer

Background

Methylation modification patterns play a crucial role in human cancer progression, especially in gastrointestinal cancers. We aimed to use methylation regulators to classify patients with gastric adenocarcinoma and build a model to predict prognosis, promoting the application of precision medicine.

Methods

We obtained RNA sequencing data and clinical data from The Cancer Genome Atlas (TCGA) database (n=335) and Gene Expression Omnibus (GEO) database (n=865). Unsupervised consensus clustering was used to identify subtypes of gastric adenocarcinoma. We performed functional enrichment analysis, immune infiltration analysis, drug sensitivity analysis, and molecular feature analysis to determine the clinical application for different subtypes. The univariate Cox regression analysis and the LASSO regression analysis were subsequently used to identify prognosis-related methylation regulators and construct a risk model.

Results

Through unsupervised consensus clustering, patients were divided into two subtypes (cluster A and cluster B) with different clinical outcomes. Cluster B included patients with a better prognosis outcome and who were more likely to respond to immunotherapy. We then successfully built a predictive model and found five methylation-related genes (CHAF1A, CPNE8, PHLDA3, SPARC, and EHF) potentially significant to the prognosis of patients. The 1-, 3-, and 5-year areas under the curve of the risk model were 0.712, 0.696, and 0.759, respectively. The risk score was an independent prognostic factor and had the highest concordance index among common clinical indicators. Meanwhile, the tumor microenvironment, sensitivity of chemotherapeutic drugs, molecular features, and oncogenic dedifferentiation differed significantly across the risk groups and subtypes.

Conclusions

We classified patients with gastric adenocarcinoma based on methylation regulators, which has positive implications for first-line clinical treatment. The prognostic model could predict the prognosis of patients and help to promote the development of precision medicine.

eIF4E as a molecular wildcard in metazoans RNA metabolism

The evolutionary origin of eukaryotes spurred the transition from prokaryotic-like translation to a more sophisticated, eukaryotic translation. During this process, successive gene duplication of a single, primordial eIF4E gene encoding the mRNA cap-binding protein eukaryotic translation initiation factor 4E (eIF4E) gave rise to a plethora of paralog genes across eukaryotes that underwent further functional diversification in RNA metabolism. The ability to take different roles is due to eIF4E promiscuity in binding many partner proteins, rendering eIF4E a highly versatile and multifunctional player that functions as a molecular wildcard. Thus, in metazoans, eIF4E paralogs are involved in various processes, including messenger RNA (mRNA) processing, export, translation, storage, and decay. Moreover, some paralogs display differential expression in tissues and developmental stages and show variable biochemical properties. In this review, we discuss recent advances shedding light on the functional diversification of eIF4E in metazoans. We emphasise humans and two phylogenetically distant species which have become paradigms for studies on development, namely the fruit fly Drosophila melanogaster and the roundworm Caenorhabditis elegans.

m7G-related genes-NCBP2 and EIF4E3 determine immune contexture in head and neck squamous cell carcinoma by regulating CCL4/CCL5 expression

Aberrant N7 -methylguanosine (m7G) levels closely correlate with tumor genesis and progression. NCBP2 and EIF4E3 are two important m7G-related cap-binding genes. This study aimed to identify the relationship between the EIF4E3/NCBP2 function and immunological characteristics of head and neck squamous cell carcinoma (HNSCC). Hierarchical clustering was employed in classifying HNSCC patients into two groups based on the expressions of NCBP2 and EIF4E3. The differentially expressed genes were identified between the two groups, and GO functional enrichment was subsequently performed. Weighted gene co-expression network analysis was conducted to identify the hub genes related to EIF4E3/NCBP2 expression and immunity. The differential infiltration of immune cells and the response to immunotherapy were compared between the two groups. Single-cell sequence and trajectory analyses were performed to predict cell differentiation and display the expression of EIF4E3/NCBP2 in each state. In addition, quantitative real-time PCR, spatial transcriptome analysis, transwell assay, and western blotting were conducted to verify the biological function of EIF4E3/NCBP2. Here, group A showed a higher EIF4E3 expression and a lower NCBP2 expression, which had higher immune scores, proportion of most immune cells, immune activities, expression of immunomodulatory targets, and a better response to cancer immunotherapy. Besides, 56 hub molecules with notable immune regulation significance were identified. A risk model containing 17 hub genes and a prognostic nomogram was successfully established. Moreover, HNSCC tissues had a lower EIF4E3 expression and a higher NCBP2 expression than normal tissues. NCBP2 and EIF4E3 played a vital role in the differentiation of monocytes. Furthermore, the expression of CCL4/CCL5 can be regulated via EIF4E3 overexpression and NCBP2 knockdown. Collectively, NCBP2 and EIF4E3 can affect downstream gene expression, as well as immune contexture and response to immunotherapy, which could induce "cold-to-hot" tumor transformation in HNSCC patients.

Analysis of m7G-Related signatures in the tumour immune microenvironment and identification of clinical prognostic regulators in breast cancer

BACKGROUND

Breast cancer is a malignant tumour that seriously threatens women's life and health and exhibits high inter-individual heterogeneity, emphasising the need for more in-depth research on its pathogenesis. While internal 7-methylguanosine (m7G) modifications affect RNA processing and function and are believed to be involved in human diseases, little is currently known about the role of m7G modification in breast cancer.

METHODS AND RESULTS

We elucidated the expression, copy number variation incidence and prognostic value of 24 m7G-related genes (m7GRGs) in breast cancer. Subsequently, based on the expression of these 24 m7GRGs, consensus clustering was used to divide tumour samples from the TCGA-BRCA dataset into four subtypes based on significant differences in their immune cell infiltration and stromal scores. Differentially expressed genes between subtypes were mainly enriched in immune-related pathways such as 'Ribosome', 'TNF signalling pathway' and 'Salmonella infection'. Support vector machines and multivariate Cox regression analysis were applied based on these 24 m7GRGs, and four m7GRGs-AGO2, EIF4E3, DPCS and EIF4E-were identified for constructing the prediction model. An ROC curve indicated that a nomogram model based on the risk model and clinical factors had strong ability to predict the prognosis of breast cancer. The prognoses of patients in the high- and low-TMB groups were significantly different (p = 0.03). Moreover, the four-gene signature was able to predict the response to chemotherapy.

CONCLUSIONS

In conclusion, we identified four different subtypes of breast cancer with significant differences in the immune microenvironment and pathways. We elucidated prognostic biomarkers associated with breast cancer and constructed a prognostic model involving four m7GRGs. In addition, we predicted the candidate drugs related to breast cancer based on the prognosis model.

Comprehensive multi-omics analysis reveals m7G-related signature for evaluating prognosis and immunotherapy efficacy in osteosarcoma

Background

Osteosarcoma is one of the most prevalent bone malignancies with a poor prognosis. The N7-methylguanosine (m7G) modification facilitates the modification of RNA structure and function tightly associated with cancer. Nonetheless, there is a lack of joint exploration of the relationship between m7G methylation and immune status in osteosarcoma.

Methods

With the support of TARGET and GEO databases, we performed consensus clustering to characterize molecular subtypes based on m7G regulators in all osteosarcoma patients. The least absolute shrinkage and selection operator (LASSO) method, Cox regression, and receiver operating characteristic (ROC) curves were employed to construct and validate m7G-related prognostic features and derived risk scores. In addition, GSVA, ssGSEA, CIBERSORT, ESTIMATE, and gene set enrichment analysis were conducted to characterize biological pathways and immune landscapes. We explored the relationship between risk scores and drug sensitivity, immune checkpoints, and human leukocyte antigens by correlation analysis. Finally, the roles of EIF4E3 in cell function were verified through external experiments.

Results

Two molecular isoforms based on regulator genes were identified, which presented significant discrepancies in terms of survival and activated pathways. Moreover, the six m7G regulators most associated with prognosis in osteosarcoma patients were identified as independent predictors for the construction of prognostic signature. The model was well stabilized and outperformed traditional clinicopathological features to reliably predict 3-year (AUC = 0.787) and 5-year (AUC = 0.790) survival in osteosarcoma cohorts. Patients with increased risk scores had a poorer prognosis, higher tumor purity, lower checkpoint gene expression, and were in an immunosuppressive microenvironment. Furthermore, enhanced expression of EIF4E3 indicated a favorable prognosis and affected the biological behavior of osteosarcoma cells.

Conclusions

We identified six prognostic relevant m7G modulators that may provide valuable indicators for the estimation of overall survival and the corresponding immune landscape in patients with osteosarcoma.

Comparative Transcriptome Analyses of Leg Muscle during Early Growth between Geese (Anser cygnoides) Breeds Differing in Body Size Characteristics

Goose is an important poultry commonly raised for meat. The early growth performance of geese significantly influences their market weight and slaughter weight, affecting the poultry industry's economic benefits. To identify the growth surge between the Shitou goose and the Wuzong goose, we collected the early growth body traits from 0 to 12 weeks. In addition, we investigated the transcriptomic changes in leg muscles at the high growth speed period to reveal the difference between the two geese breeds. We also estimated the growth curve parameters under three models, including the logistic, von Bertalanffy, and Gompertz models. The results showed that except for body length and keel length, the best-fitting model between the body weight and body size of the Shitou and Wuzong was the logistic model. The growth turning points of Shitou and Wuzong were 5.954 and 4.944 weeks, respectively, and the turning point of their body weight was 1459.01 g and 478.54 g, respectively. Growth surge occurred at 2-9 weeks in Shitou goose and at 1-7 weeks in Wuzong goose. The body size traits of the Shitou goose and Wuzong goose showed a trend of rapid growth in the early stage and slow growth in the later stage, and the Shitou goose growth was higher than the Wuzong goose. For transcriptome sequencing, a total of 87 differentially expressed genes (DEGs) were identified with a fold change ≥ 2 and a false discovery rate < 0.05. Many DEGs have a potential function for growth, such as CXCL12, SSTR4, FABP5, SLC2A1, MYLK4, and EIF4E3. KEGG pathway analysis identified that some DEGs were significantly enriched in the calcium signaling pathway, which may promote muscle growth. The gene-gene interaction network of DEGs was mainly related to the transmission of cell signals and substances, hematological system development, and functions. This study can provide theoretical guidance for the production and breeding management of the Shitou goose and Wuzong goose and help reveal the genetic mechanisms underlying diverse body sizes between two goose breeds.

Regulation and function of poised mRNAs in lymphocytes

Pre-existing but untranslated or 'poised' mRNA exists as a means to rapidly induce the production of specific proteins in response to stimuli and as a safeguard to limit the actions of these proteins. The translation of poised mRNA enables immune cells to express quickly genes that enhance immune responses. The molecular mechanisms that repress the translation of poised mRNA and, upon stimulation, enable translation have yet to be elucidated. They likely reflect intrinsic properties of the mRNAs and their interactions with trans-acting factors that direct poised mRNAs away from or into the ribosome. Here, I discuss mechanisms by which this might be regulated.

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

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.

Therapeutic targeting of eukaryotic initiation factor (eIF) 4E

Fundamental studies unraveled the role of eukaryotic initiation factor (eIF) 4E in mRNA translation and its control. Under physiological conditions, regulation of translation by eIF4E is essential to cellular homeostasis. Under stress, gene flow information is parsed by eIF4E to support adaptive mechanisms that favor cell survival. Dysregulated eIF4E activity fuels tumor formation and progression and modulates response to therapy. Thus, there has been heightened interest in understanding eIF4E function in controlling gene expression as well as developing strategies to block its activity to treat disease.

The prognostic index of m7G-related genes in CRC correlates with immune infiltration

N7-methyladenosine (m⁷G) modifications have been the subject of growing research interest with respect to their relationship with the progression and treatment of various cancers. This analysis was designed to examine the association between m⁷G-related gene expression and colorectal cancer (CRC) patient outcomes. Initial training analyses were performed using the TCGA dataset, with the GSE28722 dataset then being used to validate these results. Univariate Cox analyses were initially conducted to screen out prognostic m⁷G-related genes, after which a LASSO approach was used to construct an m⁷G risk score (MRS) model. Kaplan-Meier curves, ROC curves, and Cox analyses were subsequently used to validate the prognostic utility of this model in CRC patients. The R maftools package was further employed to assess mutational characteristics in CRC patients in different MRS subgroups, while the ESTIMATE, CIBERSORT, and ssGSEA tools were used to conduct immune infiltration analyses. A WGCNA was then performed to identify key immune-associated hub genes. The EIF4E3, GEMIN5, and NCBP2 genes were used to establish the MRS model. Patients with high MRS scores exhibited worse overall survival than patients with low scores. In Cox analyses, MRS scores were independently associated with CRC patient prognosis. Patients with low MRS scores exhibited a higher tumor mutational burden and higher levels of microsatellite instability. In immune infiltration analyses, higher immune checkpoint expression and greater immune cell infiltration were also observed in patients with low MRS scores. WGCNA analyses further identified 25 CD8+ T cell infiltration-associated genes. These findings suggest that MRS values represent a useful biomarker capable of differentiating among CRC patients with different immunological features and prognostic outcomes, offering an opportunity to better determine which patients are likely to benefit from immune checkpoint inhibitor treatment.

N7-methylguanosine methylation-related regulator genes as biological markers in predicting prognosis for melanoma

The aim of this study is to find those N7-methylguanosine (m7G) methylation-related regulator genes (m7GMRRGs) which were associated with melanoma prognosis and use them to develop a prognostic prediction model. Clinical information was retrieved online from The Cancer Gene Atlas (TCGA) and the Gene Expression Omnibus (GEO). R software was used to extract m⁷GMRRGs by differential expression analysis. To create a prognostic risk model, univariate and multivariate Cox regression analyses were employed for the evaluation of the prognostic significance of m⁷G methylation modifiers. Internal validation using cohort from TCGA (training set) and external validation using cohort from GEO (validation set) of the model were carried out. The model's predictive performance was confirmed by using the Kaplan-Meier, univariate, and multivariate Cox regression, and receiver operating characteristic curve (ROC) by constructing column line plots incorporating clinical factor characteristics. Immune infiltration analyses were performed to assess the immune function of m⁷GMRRGs. Drug sensitivity analysis was conducted to study chemotherapeutic drug treatment cues. Prognostic models using four m⁷GMRRGs (EIF4E3, LARP1, NCBP3, and IFIT5) showed good prognostic power in training and validation sets. The area under the curve (AUC) at 1, 3, and 5 years for GEO-melanoma were 0.689, 0.704, and 0.726, respectively. The prediction model could distinctly classify patients with melanoma into different risk subgroups (P < 0.001 for TCGA-melanoma and P < 0.05 for GEO-melanoma). Clinical characteristics were taken into account in Cox regression and AUC analysis, which highlighted that the risk score served as an independent risk factor determining the prognosis of patients with melanoma. Immuno-infiltration analysis showed that m⁷GMRRGs could potentially regulate CD8⁺ T cells as well as regulatory T cells (Treg cells). Results of our study indicate a association between m⁷GMRRGs and melanoma prognosis, and the prognostic prediction model using m⁷GMRRGs may predict the prognosis of patients with melanoma well. Nevertheless, these results may provide a clue for potential better options of melanoma treatment but need further validation in futural studies.

Integrated analysis from multi-center studies identities m7G-derived modification pattern and risk stratification system in skin cutaneous melanoma

The m7G modification has been proven to play an important role in RNA post-transcriptional modification and protein translation. However, the potential role of m7G modification patterns in assessing the prognosis of Skin cutaneous melanoma (SKCM) and tumor microenvironment (TME) has not been well studied. In this study, we investigated and finally identified 21 available m7G-related genes. We used hierarchical clustering (K-means) to classify 743 SKCM patients into three m7G-modified subtypes named m7G/gene cluster-A, B, C. We found that both m7G cluster B and gene cluster B exhibited higher prognosis and higher immune cell infiltration in TME compared to other subtypes. EIF4E3 and IFIT5, two m7G related genes, were both markedly elevated in Cluster B. Then, we constructed an m7G score system utilizing principal component analysis (PCA) in order to evaluate the patients' prognosis. High m7G score subtype was associated with better survival prognosis and active immune response. Overall, this article revealed that m7G modification patterns were involved in the development of the tumor microenvironment. Evaluating patients' m7G modification patterns will enhance our understanding of TME characteristics and help to guide personal treatment in clinics in the future.

A Novel m7G-Related Genes-Based Signature with Prognostic Value and Predictive Ability to Select Patients Responsive to Personalized Treatment Strategies in Bladder Cancer

Although N7-methylguanosine (m7G) modification serves as a tumor promoter in bladder cancer (BLCA), the comprehensive role of m7G-related characterization in BLCA remains unclear. In this study, we systematically evaluated the m7G-related clusters of 760 BLCA patients through consensus unsupervised clustering analysis. Next, we investigated the underlying m7G-related genes among these m7G-related clusters. Univariate Cox and LASSO regressions were used for screening out prognostic genes and for reducing the dimension, respectively. Finally, we developed a novel m7G-related scoring system via the GSVA algorithm. The correlation between tumor microenvironment, prediction of personalized therapies and this m7G-related signature was gradually revealed. We first identified three m7G-related clusters and 1108 differentially expressed genes relevant to the three clusters. Based on the profile of 1108 genes, we divided BLCA patients into two clusters, which were quantified by our established m7G-related scoring system. Patients with higher m7G-related scores tended to have a better OS and more chances to benefit from immunotherapy. A significantly negative connection between sensitivity to classic chemotherapeutic drugs and m7G-related signature was uncovered. In summary, our data show that m7G-related characterization of BLCA patients can be of value for prognostic stratification and for patient-oriented therapeutic options, designing personalized treatment strategies in the preclinical setting.

m7G regulator-mediated molecular subtypes and tumor microenvironment in kidney renal clear cell carcinoma

Background: RNA methylation modification plays an important role in immune regulation. m7G RNA methylation is an emerging research hotspot in the RNA methylation field. However, its role in the tumor immune microenvironment of kidney renal clear cell carcinoma (KIRC) is still unclear.

Methods: We analyzed the expression profiles of 29 m7G regulators in KIRC, integrated multiple datasets to identify a novel m7G regulator-mediated molecular subtype, and developed the m7G score. We evaluated the immune tumor microenvironments in m7G clusters and analyzed the correlation of the m7G score with immune cells and drug sensitivity. We tested the predictive power of the m7G score for prognosis of patients with KIRC and verified the predictive accuracy of the m7G score by using the GSE40912 and E-MTAB-1980 datasets. The genes used to develop the m7G score were verified by qRT-PCR. Finally, we experimentally analyzed the effects of WDR4 knockdown on KIRC proliferation, migration, invasion, and drug sensitivity.

Results: We identified three m7G clusters. The expression of m7G regulators was higher in cluster C than in other clusters. m7G cluster C was related to immune activation, low tumor purity, good prognosis, and low m7G score. Cluster B was related to drug metabolism, high tumor purity, poor survival, and high m7G score. Cluster A was related to purine metabolism. The m7G score can well-predict the prognosis of patients with KIRC, and its prediction accuracy based on the m7G score nomogram was very high. Patients with high m7G scores were more sensitive to rapamycin, gefitinib, sunitinib, and vinblastine than other patients. Knocking down WDR4 can inhibit the proliferation, migration, and invasion of 786-0 and Caki-1 cells and increase sensitivity to sorafenib and sunitinib.

Conclusion: We proposed a novel molecular subtype related to m7G modification and revealed the immune cell infiltration characteristics of different subtypes. The developed m7G score can well-predict the prognosis of patients with KIRC, and our research provides a basis for personalized treatment of patients with KIRC.

The pattern of expression and prognostic value of key regulators for m7G RNA methylation in hepatocellular carcinoma

N7-methylguanosine (m7G) modification on internal RNA positions plays a vital role in several biological processes. Recent research shows m7G modification is associated with multiple cancers. However, in hepatocellular carcinoma (HCC), its implications remain to be determined. In this place, we need to interrogate the mRNA patterns for 29 key regulators of m7G RNA modification and assess their prognostic value in HCC. Initial, the details from The Cancer Genome Atlas (TCGA) database concerning transcribed gene data and clinical information of HCC patients were inspected systematically. Second, according to the mRNA profiles of 29 m7G RNA methylation regulators, two clusters (named 1 and 2, respectively) were identified by consensus clustering. Furthermore, robust risk signature for seven m7G RNA modification regulators was constructed. Last, we used the Gene Expression Omnibus (GEO) dataset to validate the prognostic associations of the seven-gene risk signature. We figured out that 24/29 key regulators of m7G RNA modification varied remarkably in their grades of expression between the HCC and the adjacent tumor control tissues. Cluster one compared with cluster two had a substandard prognosis and was also positively correlated with T classification (T), pathological stage, and vital status (fustat) significantly. Consensus clustering results suggested the expression pattern of m7G RNA modification regulators was correlated with the malignancy of HCC strongly. In addition, cluster one was extensively enriched in metabolic-related pathways. Seven optimal genes (METTL1, WDR4, NSUN2, EIF4E, EIF4E2, NCBP1, and NCBP2) were selected to establish the risk model for HCC. Indicating by further analyses and validation, the prognostic model has fine anticipating command and this probability signature might be a self supporting presage factor for HCC. Finally, a new prognostic nomogram based on age, gender, pathological stage, histological grade, and prospects were established to forecast the prognosis of HCC patients accurately. In essence, we detected association of HCC severity and expression levels of m7G RNA modification regulators, and developed a risk score model for predicting prognosis of HCC patients’ progression.

Moonlighting translation factors: multifunctionality drives diverse gene regulation

Translation factors have traditionally been viewed as proteins that drive ribosome function and ensure accurate mRNA translation. Recent discoveries have highlighted that these factors can also moonlight in gene regulation, but through functions distinct from their canonical roles in protein synthesis. Notably, the additional functions that translation factors encode are diverse, ranging from transcriptional control and extracellular signaling to RNA binding, and are highly regulated in response to external cues and the intrinsic cellular state. Thus, this multifunctionality of translation factors provides an additional mechanism for exquisite control of gene expression.

Prognostic Signature and Tumor Immune Landscape of N7-Methylguanosine-Related lncRNAs in Hepatocellular Carcinoma

Despite great advances in the treatment of liver hepatocellular carcinoma (LIHC), such as immunotherapy, the prognosis remains extremely poor, and there is an urgent need to develop novel diagnostic and prognostic markers. Recently, RNA methylation-related long non-coding RNAs (lncRNAs) have been demonstrated to be novel potential biomarkers for tumor diagnosis and prognosis as well as immunotherapy response, such as N6-methyladenine (m6A) and 5-methylcytosine (m5C). N7-Methylguanosine (m7G) is a widespread RNA modification in eukaryotes, but the relationship between m7G-related lncRNAs and prognosis of LIHC patients as well as tumor immunotherapy response is still unknown. In this study, based on the LIHC patients’ clinical and transcriptomic data from TCGA database, a total of 992 m7G-related lncRNAs that co-expressed with 22 m7G regulatory genes were identified using Pearson correlation analysis. Univariate regression analysis was used to screen prognostic m7G-related lncRNAs, and the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were applied to construct a 9-m7G-related-lncRNA risk model. The m7G-related lncRNA risk model was validated to exhibit good prognostic performance through Kaplan–Meier analysis and ROC analysis. Together with the clinicopathological features, the m7G-related lncRNA risk score was found to be an independent prognostic factor for LIHC. Furthermore, the high-risk group of LIHC patients was unveiled to have a higher tumor mutation burden (TMB), and their tumor microenvironment was more prone to the immunosuppressive state and exhibited a lower response rate to immunotherapy. In addition, 47 anti-cancer drugs were identified to exhibit a difference in drug sensitivity between the high-risk and low-risk groups. Taken together, the m7G-related lncRNA risk model might display potential value in predicting prognosis, immunotherapy response, and drug sensitivity in LIHC patients.

Risk Model and Immune Signature of m7G-Related lncRNA Based on Lung Adenocarcinoma

Lung cancer is a major cause of cancer-related deaths globally, with a dismal prognosis. N7-methylguanosine (m7G) is essential for the transcriptional phenotypic modification of messenger RNA (mRNA) and long noncoding RNA (lncRNA). However, research on m7G-related lncRNAs involved in lung adenocarcinoma (LUAD) regulation is still limited. Herein, we aim to establish a prognostic model of m7G-related lncRNAs and investigate their immune properties. Eight prognostic m7G-related lncRNAs were identified using univariate Cox analysis. Six m7G-related lncRNAs were identified using LASSO-Cox regression analysis to construct risk models, and all LUAD patients in The Cancer Genome Atlas (TCGA) cohort was divided into low-risk and high-risk subgroups. The accuracy of the model was verified by Kaplan-Meier analysis, time-dependent receiver operating characteristic, principal component analysis, independent prognostic analysis, nomogram, and calibration curve. Further studies were conducted on the gene set enrichment and disease ontology enrichment analyses. The gene set enrichment analysis (GSEA) revealed that the high-risk group enriched for cancer proliferation pathways, and the enrichment analysis of disease ontology (DO) revealed that lung disease was enriched, rationally explaining the superiority of the risk model. Finally, we found that the low-risk group had higher immune infiltration and checkpoint expression. It can be speculated that the low-risk group has a better effect on immunotherapy. Susceptibility to antitumor drugs in different risk subgroups was assessed, and it found that the high-risk group showed high sensitivity to first-line treatment drugs for non-small cell lung cancer. In conclusion, a risk model based on 6 m7G-related lncRNAs can not only predict the overall survival (OS) rate of LUAD patients but also guide individualized treatment for these patients.

Anomalous HIV-1 RNA, How Cap-Methylation Segregates Viral Transcripts by Form and Function

The acquisition of m7G-cap-binding proteins is now recognized as a major variable driving the form and function of host RNAs. This manuscript compares the 5'-cap-RNA binding proteins that engage HIV-1 precursor RNAs, host mRNAs, small nuclear (sn)- and small nucleolar (sno) RNAs and sort into disparate RNA-fate pathways. Before completion of the transcription cycle, the transcription start site of nascent class II RNAs is appended to a non-templated guanosine that is methylated (m7G-cap) and bound by hetero-dimeric CBP80-CBP20 cap binding complex (CBC). The CBC is a nexus for the co-transcriptional processing of precursor RNAs to mRNAs and the snRNA and snoRNA of spliceosomal and ribosomal ribonucleoproteins (RNPs). Just as sn/sno-RNAs experience hyper-methylation of m7G-cap to trimethylguanosine (TMG)-cap, so do select HIV RNAs and an emerging cohort of mRNAs. TMG-cap is blocked from Watson:Crick base pairing and disqualified from participating in secondary structure. The HIV TMG-cap has been shown to license select viral transcripts for specialized cap-dependent translation initiation without eIF4E that is dependent upon CBP80/NCBP3. The exceptional activity of HIV precursor RNAs secures their access to maturation pathways of sn/snoRNAs, canonical and non-canonical host mRNAs in proper stoichiometry to execute the retroviral replication cycle.

RNA m6A methylation regulates the dissemination of cancer cells via modulating expression and membrane localization of β-catenin

N6-methyladenosine (m⁶A) methylation, which is modified by METTL3/METTL14 complex, is a dominant internal modification in mammalian RNA and tightly links to cancer progression. Here, we reveal that METTL3-promoted cell migration, invasion and epithelial to mesenchymal transition (EMT) are associated with the expression and membrane localization of β-catenin (encoded by CTNNB1), as opposed to Wnt signaling activation in various types of cancer cells, including cervical, lung, and liver cancers. Specifically, METTL3 regulates the transcription, mRNA decay, translation and sub-cellular localization of β-catenin. For CTNNB1 expression, METTL3 indirectly suppresses CTNNB1 transcription via stabilizing its transcription suppressor E2F1 mRNA; deposition of 5'UTR m⁶A in CTNNB1 promotes its decay in a content-dependent manner via YTHDF2 recognition; 5'UTR m⁶A in CTNNB1 suppresses its translation efficiency, while global METTL3 level controls the canonical and non-canonical translation of CTNNB1, which is probably associated with the interaction between YTHDF1 and eIF4E1/eIF4E3. For β-catenin translocation, METTL3 represses membrane localization of β-catenin and its interaction with E-Cadherin by downregulating c-Met kinase, leading to the inhibition of cell motility. In vitro, in vivo and clinical analysis confirm the essential roles of β-catenin and its expression regulators in cancer cell dissemination. The findings not only expand our understanding of m⁶A modification and its roles in gene expression and subcellular localization of targets, but also suggest that METTL3/β-catenin axis might be a potential target to inhibit cancer metastasis.

Development and Validation of Ten-RNA Binding Protein Signature Predicts Overall Survival in Osteosarcoma

Osteosarcoma is a malignant tumor that originates in the bones with the characteristics of high malignancy, predisposition to metastasis, and poor prognosis. RNA binding proteins (RBPs) are closely related to various tumors, but their relationship with osteosarcoma remains unclear. Based on GTEx and TARGET RNA sequencing data, we applied differential analysis to obtain RBP genes that are differentially expressed in osteosarcoma, and analyzed the functions of these RBPs. After applying univariate and LASSO Cox regression analysis, 10 key prognostic RBPs (TDRD6, TLR8, NXT2, EIF4E3, RPS27L, CPEB3, RBM34, TERT, RPS29, and ZC3HAV1) were screened, and an RBP prognostic risk assessment model for patients with osteosarcoma was established. The independent cohort GSE21257 was used for external verification, and the results showed that the signature has an excellent ability to predict prognosis. In addition, a nomogram that can be used for clinical evaluation was constructed. Finally, the expression levels of 10 prognostic RBPs in osteosarcoma cells and tissues were confirmed through experiments. Our study identified a ten-gene prognostic marker related to RBP, which is of great significance for adjusting the treatment strategy of patients with osteosarcoma and exploring prognostic markers.

Deep computational analysis details dysregulation of eukaryotic translation initiation complex eIF4F in human cancers

eIF4F plays diverse roles in human cancers, which complicate the development of an overarching understanding of its functional and regulatory impacts across tumor types. Typically, eIF4F drives initiation from the mRNA 5' end (cap) and is composed of eIF4G1, eIF4A1, and cap-binding eIF4E. Cap-independent initiation is possible without eIF4E, from internal ribosomal entry sites (IRESs). By analyzing large public datasets, we found that cancers selectively overexpress EIF4G1 more than EIF4E. That expression imbalance supports EIF4G1 as a prognostic indicator in patients with cancer. It also attenuates "housekeeping" pathways that are usually regulated in a tissue-specific manner via cap-dependent initiation in healthy tissues and reinforce regulation of cancer-preferred pathways in cap-independent contexts. Cap-independent initiation is mechanistically attributable to eIF4G1 hyperphosphorylation that promotes binding to eIF4A1 and reduced eIF4E availability. Collectively, these findings reveal a novel model of dysregulated eIF4F function and highlight the clinical relevance of cap-(in)dependent initiation in cancer.

eIF4E3 forms an active eIF4F complex during stresses (eIF4FS) targeting mTOR and re-programs the translatome

The eIF4E are a family of initiation factors that bind the mRNA 5′ cap, regulating the proteome and the cellular phenotype. eIF4E1 mediates global translation and its activity is controlled via the PI3K/AKT/mTOR pathway. mTOR down-regulation results in eIF4E1 sequestration into an inactive complex with the 4E binding proteins (4EBPs). The second member, eIF4E2, regulates the translatome during hypoxia. However, the exact function of the third member, eIF4E3, has remained elusive. We have dissected its function using a range of techniques. Starting from the observation that it does not interact with 4EBP1, we demonstrate that eIF4E3 recruitment into an eIF4F complex occurs when Torin1 inhibits the mTOR pathway. Ribo-seq studies demonstrate that this complex (eIF4F^S) is translationally active during stress and that it selects specific mRNA populations based on 5′ TL (UTR) length. The interactome reveals that it associates with cellular proteins beyond the cognate initiation factors, suggesting that it may have ‘moon-lighting’ functions. Finally, we provide evidence that cellular metabolism is altered in an eIF4E3 KO background but only upon Torin1 treatment. We propose that eIF4E3 acts as a second branch of the integrated stress response, re-programming the translatome to promote ‘stress resistance’ and adaptation.

Multifaceted control of mRNA translation machinery in cancer

The mRNA translation machinery is tightly regulated through several, at times overlapping, mechanisms that modulate its efficiency and accuracy. Due to their fast rate of growth and metabolism, cancer cells require an excessive amount of mRNA translation and protein synthesis. However, unfavorable conditions, such as hypoxia, amino acid starvation, and oxidative stress, which are abundant in cancer, as well as many anti-cancer treatments inhibit mRNA translation. Cancer cells adapt to the various internal and environmental stresses by employing specialised transcript-specific translation to survive and gain a proliferative advantage. We will highlight the major signaling pathways and mechanisms of translation that regulate the global or mRNA-specific translation in response to the intra- or extra-cellular signals and stresses that are key components in the process of tumourigenesis.

Translational remodeling by RNA-binding proteins and noncoding RNAs

Responsible for generating the proteome that controls phenotype, translation is the ultimate convergence point for myriad upstream signals that influence gene expression. System-wide adaptive translational reprogramming has recently emerged as a pillar of cellular adaptation. As classic regulators of mRNA stability and translation efficiency, foundational studies established the concept of collaboration and competition between RNA-binding proteins (RBPs) and noncoding RNAs (ncRNAs) on individual mRNAs. Fresh conceptual innovations now highlight stress-activated, evolutionarily conserved RBP networks and ncRNAs that increase the translation efficiency of populations of transcripts encoding proteins that participate in a common cellular process. The discovery of post-transcriptional functions for long noncoding RNAs (lncRNAs) was particularly intriguing given their cell-type-specificity and historical definition as nuclear-functioning epigenetic regulators. The convergence of RBPs, lncRNAs, and microRNAs on functionally related mRNAs to enable adaptive protein synthesis is a newer biological paradigm that highlights their role as "translatome (protein output) remodelers" and reinvigorates the paradigm of "RNA operons." Together, these concepts modernize our understanding of cellular stress adaptation and strategies for therapeutic development. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications Translation > Translation Regulation Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

The multifaceted eukaryotic cap structure

The 5' cap structure is added onto RNA polymerase II transcripts soon after initiation of transcription and modulates several post-transcriptional regulatory events involved in RNA maturation. It is also required for stimulating translation initiation of many cytoplasmic mRNAs and serves to protect mRNAs from degradation. These functional properties of the cap are mediated by several cap binding proteins (CBPs) involved in nuclear and cytoplasmic gene expression steps. The role that CBPs play in gene regulation, as well as the biophysical nature by which they recognize the cap, is quite intricate. Differences in mechanisms of capping as well as nuances in cap recognition speak to the potential of targeting these processes for drug development. In this review, we focus on recent findings concerning the cap epitranscriptome, our understanding of cap binding by different CBPs, and explore therapeutic targeting of CBP-cap interaction. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Processing > Capping and 5' End Modifications Translation > Translation Mechanisms.

Translational control in the naked mole-rat as a model highly resistant to cancer

Dysregulation of mRNA translation is involved in the onset and progression of different types of cancer. To gain insight into novel genetic strategies to avoid this malady, we reviewed the available genomic, transcriptomic, and proteomic data about the translational machinery from the naked-mole rat (NMR) Heterocephalus glaber, a new model of study that exhibits high resistance to cancer. The principal features that might confer cancer resistance are 28S rRNA fragmentation, RPL26 and eIF4G overexpression, global downregulation of mTOR pathway, specific amino acid residues in RAPTOR (P908) and RICTOR (V1695), and the absence of 4E-BP3. These features are not only associated with cancer but also might couple longevity and adaptation to hypoxia. We propose that the regulation of translation is among the strategies endowing NMR cancer resistance.

RNA-tethering assay and eIF4G:eIF4A obligate dimer design uncovers multiple eIF4F functional complexes

Eukaryotic cellular mRNAs possess a 5′ cap structure (m⁷GpppN) which plays a critical role in translation initiation mediated by eukaryotic initiation factor (eIF) 4F. The heterotrimeric eIF4F complex possesses several activities imparted by its subunits that include cap recognition (by eIF4E), RNA unwinding (eIF4A), and factor/ribosome recruitment (eIF4G). Mammalian cells have paralogs of all three eIF4F subunits and it remains an open question as to whether these all can participate in the process of ribosome recruitment. To query the activities of the eIF4F subunits in translation initiation, we adopted an RNA-tethering assay in which select subunits are recruited to a specific address on a reporter mRNA template. We find that all eIF4F subunits can participate in the initiation process. Based on eIF4G:eIF4A structural information, we also designed obligate dimer pairs to probe the activity of all combinations of eIF4G and eIF4A paralogs. We demonstrate that both eIF4GI and eIF4GII can associate with either eIF4A1 or eIF4A2 to recruit ribosomes to mRNA templates. In combination with eIF4E and eIF4E3, our results indicate the presence of up to eight eIF4F complexes that can operate in translation initiation.

The Effect of MicroRNA-101 on Angiogenesis of Human Umbilical Vein Endothelial Cells during Hypoxia and in Mice with Myocardial Infarction

Background

Previous studies showed that recanalization and angiogenesis within the infarct region are of vital importance to the survival of myocardial cells during the treatment of acute myocardial infarction (AMI).

Methods

In this study, EdU cell proliferation assay, Transwell assay, scratch wound assay, and tube formation assay were used. Twelve bioinformatics analysis packages were used to predict the target genes of miR-101. Target genes were verified by luciferase reporter generation and assay, fluorescent quantitative PCR, and western blotting. Animal model and treatments were detected by M-mode echocardiography and immunofluorescent staining of CD31, Ki67, and α-SMA.

Results

AgomiR-101 significantly enhanced HUVEC proliferation, migration, and tube formation. A double-luciferase reporter assay revealed that the hsa-miR-101 mimic attenuated the activity of the EIF4E3′-UTR-wt type plasmid by 36%. The expression levels of HIF-1α and VEGF-A in the scrambled RNA group were significantly lower than those in the EIF4E3 siRNA and agomiR-101 groups. The left ventricular ejection fraction of the AMI+Adv-miR-101 group was significantly higher than that of the AMI+Adv-null and Sham+Adv-null groups. The proliferation of vessel cells in the peripheral infarcted myocardium was higher in the AMI+Adv-miR-101 group than that in the AMI+Adv-null and Sham+Adv-null groups.

Conclusion

MiR-101 can promote angiogenesis in the region surrounding the myocardial infarction.

The Organizing Principles of Eukaryotic Ribosome Recruitment

The stage at which ribosomes are recruited to messenger RNAs (mRNAs) is an elaborate and highly regulated phase of protein synthesis. Upon completion of this step, a ribosome is positioned at an appropriate initiation codon and primed to synthesize the encoded polypeptide product. In most circumstances, this step commits the ribosome to translate the mRNA. We summarize the knowledge regarding the initiation factors implicated in this activity as well as review different mechanisms by which this process is conducted.

The diversity, plasticity, and adaptability of cap-dependent translation initiation and the associated machinery

Translation initiation is a critical facet of gene expression with important impacts that underlie cellular responses to stresses and environmental cues. Its dysregulation in many diseases position this process as an important area for the development of new therapeutics. The gateway translation factor eIF4E is typically considered responsible for ‘global’ or ‘canonical’ m⁷G cap-dependent translation. However, eIF4E impacts translation of specific transcripts rather than the entire translatome. There are many alternative cap-dependent translation mechanisms that also contribute to the translation capacity of the cell. We review the diversity of these, juxtaposing more recently identified mechanisms with eIF4E-dependent modalities. We also explore the multiplicity of functions played by translation factors, both within and outside protein synthesis, and discuss how these differentially contribute to their ultimate physiological impacts. For comparison, we discuss some modalities for cap-independent translation. In all, this review highlights the diverse mechanisms that engage and control translation in eukaryotes.

The RALF1-FERONIA Complex Phosphorylates eIF4E1 to Promote Protein Synthesis and Polar Root Hair Growth

The molecular links between extracellular signals and the regulation of localized protein synthesis in plant cells are poorly understood. Here, we show that in Arabidopsis thaliana, the extracellular peptide RALF1 and its receptor, the FERONIA receptor kinase, promote root hair (RH) tip growth by modulating protein synthesis. We found that RALF1 promotes FERONIA-mediated phosphorylation of eIF4E1, a eukaryotic translation initiation factor that plays a crucial role in the control of mRNA translation rate. Phosphorylated eIF4E1 increases mRNA affinity and modulates mRNA translation and, thus, protein synthesis. The mRNAs targeted by the RALF1-FERONIA-eIF4E1 module include ROP2 and RSL4, which are important regulators of RH cell polarity and growth. RALF1 and FERONIA are expressed in a polar manner in RHs, which facilitate eIF4E1 polar localization and thus may control local ROP2 translation. Moreover, we demonstrated that high-level accumulation of RSL4 exerts negative-feedback regulation of RALF1 expression by directly binding the RALF1 gene promoter, determining the final RH size. Our study reveals that the link between RALF1-FERONIA signaling and protein synthesis constitutes a novel component regulating cell expansion in these polar growing cells.

Crystal structure of the Trypanosoma cruzi EIF4E5 translation factor homologue in complex with mRNA cap-4

Association of the initiation factor eIF4E with the mRNA cap structure is a key step for translation. Trypanosomatids present six eIF4E homologues, showing a low conservation and also differing significantly from the IF4Es of multicellular eukaryotes. On the mRNA side, while in most eukaryotes the mRNA contains cap-0 (7-methyl-GTP), the trypanosomatid mRNA features a cap-4, which is formed by a cap-0, followed by the AACU sequence containing 2′-O-ribose methylations and base methylations on nucleotides 1 and 4. The studies on eIF4E-cap-4 interaction have been hindered by the difficulty to synthesize this rather elaborated cap-4 sequence. To overcome this problem, we applied a liquid-phase oligonucleotide synthesis strategy and describe for the first time the crystal structure of a trypanosomatid eIF4E (T. cruzi EIF4E5) in complex with cap-4.

The TcEIF4E5-cap-4 structure allowed a detailed description of the binding mechanism, revealing the interaction mode for the AACU sequence, with the bases packed in a parallel stacking conformation and involved, together with the methyl groups, in hydrophobic contacts with the protein. This binding mechanism evidences a distinct cap interaction mode in comparison with previously described eIF4E structures and may account for the difference of TcEIF4E5-cap-4 dissociation constant in comparison with other eIF4E homologues.

DNA methylation changes in infants between 6 and 52 weeks

Infants undergo extensive developments during their first year of life. Although the biological mechanisms involved are not yet fully understood, changes in the DNA methylation in mammals are believed to play a key role. This study was designed to investigate changes in infant DNA methylation that occurs between 6 and 52 weeks. A total of 214 infant saliva samples from 6 or 52 weeks were assessed using principal component analyses and t-distributed stochastic neighbor-embedding algorithms. Between the two time points, there were clear differences in DNA methylation. To further investigate these findings, paired two-sided student’s t-tests were performed. Differently methylated regions were defined as at least two consecutive probes that showed significant differences, with a q-value < 0.01 and a mean difference > 0.2. After correcting for false discovery rates, changes in the DNA methylation levels were found in 42 genes. Of these, 36 genes showed increased and six decreased DNA methylation. The overall DNA methylation changes indicated decreased gene expression. This was surprising because infants undergo such profound developments during their first year of life. The results were evaluated by taking into consideration the extensive development that occurs during pregnancy. During the first year of life, infants have an overall three-fold increase in weight, while the fetus develops from a single cell into a viable infant in 9 months, with an 875-million-fold increase in weight. It is possible that the findings represent a biological slowing mechanism in response to extensive fetal development. In conclusion, our study provides evidence of DNA methylation changes during the first year of life, representing a possible biological slowing mechanism. We encourage future studies of DNA methylation changes in infants to replicate the findings by using a repeated measures model and less stringent criteria to see if the same genes can be found, as well as investigating whether other genes are involved in development during this period.

LeishIF4E1 Deletion Affects the Promastigote Proteome, Morphology, and Infectivity

Leishmania parasites are the causative agents of a broad spectrum of diseases. The parasites migrate between sand-fly vectors and mammalian hosts, adapting to changing environments by driving a regulated program of gene expression, with translation regulation playing a key role. The leishmanias encode six different paralogs of eIF4E, the cap-binding translation initiation factor. Since these vary in function, expression profile, and assemblage, it is assumed that each is assigned a specific role throughout the life cycle. Using the CRISPR-Cas9 system for Leishmania, we generated a null mutant of LeishIF4E1, eliminating both alleles. Although the mutant cells were viable, their morphology was altered and their ability to synthesize the flagellum was impaired. Elimination of LeishIF4E1 affected their protein expression profile and decreased their ability to infect cultured macrophages. Restoring LeishIF4E1 expression restored the affected features. This study highlights the importance of LeishIF4E1 in diverse cellular events during the life cycle of Leishmania.

Leishmania parasites cycle between sand-fly vectors and mammalian hosts, adapting to changing environmental conditions by driving a stage-specific program of gene expression, which is tightly regulated by translation processes. Leishmania encodes six eIF4E orthologs (LeishIF4Es) and five eIF4G candidates, forming different cap-binding complexes with potentially varying functions. Most LeishIF4E paralogs display temperature sensitivity in their cap-binding activity, except for LeishIF4E1, which maintains its cap-binding activity under all conditions. We used the CRISPR-Cas9 system to successfully generate a null mutant of LeishIF4E1 and examine how its elimination affected parasite physiology. Although the LeishIF4E1^–/– null mutant was viable, its growth was impaired, in line with a reduction in global translation. As a result of the mutation, the null LeishIF4E1^–/– mutant had a defective morphology, as the cells were round and unable to grow a normal flagellum. This was further emphasized when the LeishIF4E1^–/– cells failed to develop the promastigote morphology once they shifted from conditions that generate axenic amastigotes (33°C, pH 5.5) back to neutral pH and 25°C, and they maintained their short flagellum and circular structure. Finally, the LeishIF4E1^–/– null mutant displayed difficulty in infecting cultured macrophages. The morphological changes and reduced infectivity of the mutant may be related to differences in the proteomic profile of LeishIF4E1^–/– cells from that of controls. All defects monitored in the LeishIF4E1^–/– null mutant were reversed in the add-back strain, in which expression of LeishIF4E1 was reconstituted, establishing a strong link between the cellular defects and the absence of LeishIF4E1 expression.

IMPORTANCELeishmania parasites are the causative agents of a broad spectrum of diseases. The parasites migrate between sand-fly vectors and mammalian hosts, adapting to changing environments by driving a regulated program of gene expression, with translation regulation playing a key role. The leishmanias encode six different paralogs of eIF4E, the cap-binding translation initiation factor. Since these vary in function, expression profile, and assemblage, it is assumed that each is assigned a specific role throughout the life cycle. Using the CRISPR-Cas9 system for Leishmania, we generated a null mutant of LeishIF4E1, eliminating both alleles. Although the mutant cells were viable, their morphology was altered and their ability to synthesize the flagellum was impaired. Elimination of LeishIF4E1 affected their protein expression profile and decreased their ability to infect cultured macrophages. Restoring LeishIF4E1 expression restored the affected features. This study highlights the importance of LeishIF4E1 in diverse cellular events during the life cycle of Leishmania.

Structural studies of the eIF4E-VPg complex reveal a direct competition for capped RNA: Implications for translation

Viruses have transformed our understanding of mammalian RNA processing, including facilitating the discovery of the methyl-7-guanosine (m⁷G) cap on the 5' end of RNAs. The m⁷G cap is required for RNAs to bind the eukaryotic translation initiation factor eIF4E and associate with the translation machinery across plant and animal kingdoms. The potyvirus-derived viral genome-linked protein (VPg) is covalently bound to the 5' end of viral genomic RNA (gRNA) and associates with host eIF4E for successful infection. Divergent models to explain these observations proposed either an unknown mode of eIF4E engagement or a competition of VPg for the m⁷G cap-binding site. To dissect these possibilities, we resolved the structure of VPg, revealing a previously unknown 3-dimensional (3D) fold, and characterized the VPg-eIF4E complex using NMR and biophysical techniques. VPg directly bound the cap-binding site of eIF4E and competed for m⁷G cap analog binding. In human cells, VPg inhibited eIF4E-dependent RNA export, translation, and oncogenic transformation. Moreover, VPg formed trimeric complexes with eIF4E-eIF4G, eIF4E bound VPg-luciferase RNA conjugates, and these VPg-RNA conjugates were templates for translation. Informatic analyses revealed structural similarities between VPg and the human kinesin EG5. Consistently, EG5 directly bound eIF4E in a similar manner to VPg, demonstrating that this form of engagement is relevant beyond potyviruses. In all, we revealed an unprecedented modality for control and engagement of eIF4E and show that VPg-RNA conjugates functionally engage eIF4E. As such, potyvirus VPg provides a unique model system to interrogate eIF4E.

Cell Fate Control by Translation: mRNA Translation Initiation as a Therapeutic Target for Cancer Development and Stem Cell Fate Control

Translation of mRNA is an important process that controls cell behavior and gene regulation because proteins are the functional molecules that determine cell types and function. Cancer develops as a result of genetic mutations, which lead to the production of abnormal proteins and the dysregulation of translation, which in turn, leads to aberrant protein synthesis. In addition, the machinery that is involved in protein synthesis plays critical roles in stem cell fate determination. In the current review, recent advances in the understanding of translational control, especially translational initiation in cancer development and stem cell fate control, are described. Therapeutic targets of mRNA translation such as eIF4E, 4EBP, and eIF2, for cancer treatment or stem cell fate regulation are reviewed. Upstream signaling pathways that regulate and affect translation initiation were introduced. It is important to regulate the expression of protein for normal cell behavior and development. mRNA translation initiation is a key step to regulate protein synthesis, therefore, identifying and targeting molecules that are critical for protein synthesis is necessary and beneficial to develop cancer therapeutics and stem cells fate regulation.

Heterogeneity and specialized functions of translation machinery: from genes to organisms

Regulation of mRNA translation offers the opportunity to diversify the expression and abundance of proteins made from individual gene products in cells, tissues and organisms. Emerging evidence has highlighted variation in the composition and activity of several large, highly conserved translation complexes as a means to differentially control gene expression. Heterogeneity and specialized functions of individual components of the ribosome and of the translation initiation factor complexes eIF3 and eIF4F, which are required for recruitment of the ribosome to the mRNA 5' untranslated region, have been identified. In this Review, we summarize the evidence for selective mRNA translation by components of these macromolecular complexes as a means to dynamically control the translation of the proteome in time and space. We further discuss the implications of this form of gene expression regulation for a growing number of human genetic disorders associated with mutations in the translation machinery.

Integrated Bioinformatics Analysis the Function of RNA Binding Proteins (RBPs) and Their Prognostic Value in Breast Cancer

Background and Purpose: Breast cancer is one of the leading causes of death among women. RNA binding proteins (RBPs) play a vital role in the progression of many cancers. Functional investigation of RBPs may contribute to elucidating the mechanisms underlying tumor initiation, progression, and invasion, therefore providing novel insights into future diagnosis, treatment, and prognosis.

Methods: We downloaded RNA sequencing data from the cancer genome atlas (TCGA) by UCSC Xena and identified relevant RBPs through an integrated bioinformatics analysis. We then analyzed biological processes of differentially expressed genes (DEGs) by DAVID, and established their interaction networks and performed pathway analysis through the STRING database to uncover potential biological effects of these RBPs. We also explored the relationship between these RBPs and the prognosis of breast cancer patients.

Results: In the present study, we obtained 1092 breast tumor samples and 113 normal controls. After data analysis, we identified 90 upregulated and 115 downregulated RBPs in breast cancer. GO and KEGG pathway analysis indicated that these significantly changed genes were mainly involved in RNA processing, splicing, localization and RNA silencing, DNA transposition regulation and methylation, alkylation, mitochondrial gene expression, and transcription regulation. In addition, some RBPs were related to histone H3K27 methylation, estrogen response, inflammatory mediators, and translation regulation. Our study also identified five RBPs associated with breast cancer prognosis. Survival analysis found that overexpression of DCAF13, EZR, and MRPL13 showed worse survival, but overexpression of APOBEC3C and EIF4E3 showed better survival.

Conclusion: In conclusion, we identified key RBPs of breast cancer through comprehensive bioinformatics analysis. These RBPs were involved in a variety of biological and molecular pathways in breast cancer. Furthermore, we identified five RBPs as a potential prognostic biomarker of breast cancer. Our study provided novel insights to understand breast cancer at a molecular level.

Translational Control of Canonical and Non-Canonical Translation Initiation Factors at the Sea Urchin Egg to Embryo Transition

Sea urchin early development is a powerful model to study translational regulation under physiological conditions. Fertilization triggers an activation of the translation machinery responsible for the increase of protein synthesis necessary for the completion of the first embryonic cell cycles. The cap-binding protein eIF4E, the helicase eIF4A and the large scaffolding protein eIF4G are assembled upon fertilization to form an initiation complex on mRNAs involved in cap-dependent translation initiation. The presence of these proteins in unfertilized and fertilized eggs has already been demonstrated, however data concerning the translational status of translation factors are still scarce. Using polysome fractionation, we analyzed the impact of fertilization on the recruitment of mRNAs encoding initiation factors. Strikingly, whereas the mRNAs coding eIF4E, eIF4A, and eIF4G were not recruited into polysomes at 1 h post-fertilization, mRNAs for eIF4B and for non-canonical initiation factors such as DAP5, eIF4E2, eIF4E3, or hnRNP Q, are recruited and are differentially sensitive to the activation state of the mechanistic target of rapamycin (mTOR) pathway. We discuss our results suggesting alternative translation initiation in the context of the early development of sea urchins.