7-Methylguanosine Modifications in Transfer RNA (tRNA)

Exploring the role of m7G modification in Cancer: Mechanisms, regulatory proteins, and biomarker potential

The dysregulation of N(7)-methylguanosine (m7G) modification is increasingly recognized as a key factor in the pathogenesis of cancers. Aberrant expression of these regulatory proteins in various cancers, including lung, liver, and bladder cancers, suggests a universal role in tumorigenesis. Studies have established a strong correlation between the expression levels of m7G regulatory proteins, such as Methyltransferase like 1 (METTL1) and WD repeat domain 4 (WDR4), and clinical parameters including tumor stage, grade, and patient prognosis. For example, in hepatocellular carcinoma, high METTL1 expression is associated with advanced tumor stage and poor prognosis. Similarly, WDR4 overexpression in colorectal cancer correlates with increased tumor invasiveness and reduced patient survival. This correlation underscores the potential of these proteins as valuable biomarkers for cancer diagnosis and prognosis. Additionally, m7G modification regulatory proteins influence cancer progression by modulating the expression of target genes involved in critical biological processes, including cell proliferation, apoptosis, migration, and invasion. Their ability to regulate these processes highlights their significance in the intricate network of molecular interactions driving tumor development and metastasis. Given their pivotal role in cancer biology, m7G modification regulatory proteins are emerging as promising therapeutic targets. Targeting these proteins could offer a novel approach to disrupt the malignant behavior of cancer cells and enhance treatment outcomes. Furthermore, their diagnostic and prognostic value could aid in the early detection of cancer and the selection of appropriate therapeutic strategies, ultimately enhancing patient management and survival rates. This review aims to explore the mechanisms of action of RNA m7G modification regulatory proteins in tumors and their potential applications in cancer progression and treatment. By delving into the roles of these regulatory proteins, we intend to provide a theoretical foundation for the development of novel cancer treatment strategies.

Moss-m7G: A Motif-Based Interpretable Deep Learning Method for RNA N7-Methlguanosine Site Prediction

N-7methylguanosine (m7G) modification plays a crucial role in various biological processes and is closely associated with the development and progression of many cancers. Accurate identification of m7G modification sites is essential for understanding their regulatory mechanisms and advancing cancer therapy. Previous studies often suffered from insufficient research data, underutilization of motif information, and lack of interpretability. In this work, we designed a novel motif-based interpretable method for m7G modification site prediction, called Moss-m7G. This approach enables the analysis of RNA sequences from a motif-centric perspective. Our proposed word-detection module and motif-embedding module within Moss-m7G extract motif information from sequences, transforming the raw sequences from base-level into motif-level and generating embeddings for these motif sequences. Compared with base sequences, motif sequences contain richer contextual information, which is further analyzed and integrated through the Transformer model. We constructed a comprehensive m7G data set to implement the training and testing process to address the data insufficiency noted in prior research. Our experimental results affirm the effectiveness and superiority of Moss-m7G in predicting m7G modification sites. Moreover, the introduction of the word-detection module enhances the interpretability of the model, providing insights into the predictive mechanisms.

Dysregulation of tRNA methylation in cancer: Mechanisms and targeting therapeutic strategies

tRNA is the RNA type that undergoes the most modifications among known RNA, and in recent years, tRNA methylation has emerged as a crucial process in regulating gene translation. Dysregulation of tRNA abundance occurs in cancer cells, along with increased expression and activity of tRNA methyltransferases to raise the level of tRNA modification and stability. This leads to hijacking of translation and synthesis of multiple proteins associated with tumor proliferation, metastasis, invasion, autophagy, chemotherapy resistance, and metabolic reprogramming. In this review, we provide an overview of current research on tRNA methylation in cancer to clarify its involvement in human malignancies and establish a theoretical framework for future therapeutic interventions targeting tRNA methylation processes.

Development of a prognostic risk model of uveal melanoma based on N7-methylguanosine-related regulators

BACKGROUND

Uveal melanoma (UVM) stands as the predominant type of primary intraocular malignancy among adults. The clinical significance of N7-methylguanosine (m7G), a prevalent RNA modifications, in UVM remains unclear.

METHODS

Primary information from 80 UVM patients were analyzed as the training set, incorporating clinical information, mutation annotations and mRNA expression obtained from The Cancer Genome Atlas (TCGA) website. The validation set was carried out using Gene Expression Omnibus (GEO) database GSE22138 and GSE84976. Kaplan-Meier and Cox regression of univariate analyses were subjected to identify m7G-related regulators as prognostic genes.

RESULT

A prognostic risk model comprising EIF4E2, NUDT16, SNUPN and WDR4 was established through Cox regression of LASSO. Evaluation of the model's predictability for UVM patients' prognosis by Receiver Operating Characteristic (ROC) curves in the training set, demonstrated excellent performance Area Under the Curve (AUC) > 0.75. The high-risk prognosis within the TCGA cohort exhibit a notable worse outcome. Additionally, an independent correlation between the risk score and overall survival (OS) among UVM patients were identified. External validation of this model was carried out using the validation sets (GSE22138 and GSE84976). Immune-related analysis revealed that patients with high score of m7G-related risk model exhibited elevated level of immune infiltration and immune checkpoint gene expression.

CONCLUSION

We have developed a risk prediction model based on four m7G-related regulators, facilitating effective estimate UVM patients' survival by clinicians. Our findings shed novel light on essential role of m7G-related regulators in UVM and suggest potential novel targets for the diagnosis, prognosis and therapy of UVM.

Pan-Cancer Analysis Links Altered RNA m7G Methyltransferase Expression to Oncogenic Pathways, Immune Cell Infiltrations and Overall Survival

BACKGROUND

N7-methylguanosine (m7G) modification is one of the most prevalent RNA modifications in humans. Dysregulated m7G modifications caused by aberrant expression of m7G writers contribute to cancer progression and result in worse patient survival in several human cancers. However, studies that systematically assess the frequency and clinical relevance of aberrant m7G writer expression in a pan-cancer cohort remain to be performed.

AIMS

This study aims to systematically investigate the molecular alteration and clinical relevance of m7G methyltransferase in human cancers.

METHODS

We analysed genome, transcriptome and clinical data from the Cancer Genome Atlas Research Network spanning 33 types of human cancers for aberrant changes in genes encoding m7G writers.

RESULT

We demonstrate that m7G writers are dysregulated in human cancers and are associated predominantly with poorer survival. By dividing patients into those with high and low m7G scores, we show that a lower m7G score is generally associated with immune infiltration and better response to immunotherapy.

CONCLUSION

Our analyses indicate the genetic alterations, expression patterns and clinical relevance of m7G writers across various cancers. This study provides insights into the potential utility of m7G writer expression as a cancer biomarker and proposes the possibility of targeting m7G writers for cancer therapy.

Methylation modifications in tRNA and associated disorders: Current research and potential therapeutic targets

High-throughput sequencing has sparked increased research interest in RNA modifications, particularly tRNA methylation, and its connection to various diseases. However, the precise mechanisms underpinning the development of these diseases remain largely elusive. This review sheds light on the roles of several tRNA methylations (m1A, m3C, m5C, m1G, m2G, m7G, m5U, and Nm) in diverse biological functions, including metabolic processing, stability, protein interactions, and mitochondrial activities. It further outlines diseases linked to aberrant tRNA modifications, related enzymes, and potential underlying mechanisms. Moreover, disruptions in tRNA regulation and abnormalities in tRNA-derived small RNAs (tsRNAs) contribute to disease pathogenesis, highlighting their potential as biomarkers for disease diagnosis. The review also delves into the exploration of drugs development targeting tRNA methylation enzymes, emphasizing the therapeutic prospects of modulating these processes. Continued research is imperative for a comprehensive comprehension and integration of these molecular mechanisms in disease diagnosis and treatment.

Regulations of m6A and other RNA modifications and their roles in cancer

RNA modification is an essential component of the epitranscriptome, regulating RNA metabolism and cellular functions. Several types of RNA modifications have been identified to date; they include N6-methyladenosine (m6A), N1-methyladenosine (m1A), 5-methylcytosine (m5C), N7-methylguanosine (m7G), N6,2'-O-dimethyladenosine (m6Am), N4-acetylcytidine (ac4C), etc. RNA modifications, mediated by regulators including writers, erasers, and readers, are associated with carcinogenesis, tumor microenvironment, metabolic reprogramming, immunosuppression, immunotherapy, chemotherapy, etc. A novel perspective indicates that regulatory subunits and post-translational modifications (PTMs) are involved in the regulation of writer, eraser, and reader functions in mediating RNA modifications, tumorigenesis, and anticancer therapy. In this review, we summarize the advances made in the knowledge of different RNA modifications (especially m6A) and focus on RNA modification regulators with functions modulated by a series of factors in cancer, including regulatory subunits (proteins, noncoding RNA or peptides encoded by long noncoding RNA) and PTMs (acetylation, SUMOylation, lactylation, phosphorylation, etc.). We also delineate the relationship between RNA modification regulator functions and carcinogenesis or cancer progression. Additionally, inhibitors that target RNA modification regulators for anticancer therapy and their synergistic effect combined with immunotherapy or chemotherapy are discussed.

The role of RNA methylation in tumor immunity and its potential in immunotherapy

RNA methylation, a prevalent post-transcriptional modification, has garnered considerable attention in research circles. It exerts regulatory control over diverse biological functions by modulating RNA splicing, translation, transport, and stability. Notably, studies have illuminated the substantial impact of RNA methylation on tumor immunity. The primary types of RNA methylation encompass N6-methyladenosine (m6A), 5-methylcytosine (m5C), N1-methyladenosine (m1A), and N7-methylguanosine (m7G), and 3-methylcytidine (m3C). Compelling evidence underscores the involvement of RNA methylation in regulating the tumor microenvironment (TME). By affecting RNA translation and stability through the "writers", "erasers" and "readers", RNA methylation exerts influence over the dysregulation of immune cells and immune factors. Consequently, RNA methylation plays a pivotal role in modulating tumor immunity and mediating various biological behaviors, encompassing proliferation, invasion, metastasis, etc. In this review, we discussed the mechanisms and functions of several RNA methylations, providing a comprehensive overview of their biological roles and underlying mechanisms within the tumor microenvironment and among immunocytes. By exploring how these RNA modifications mediate tumor immune evasion, we also examine their potential applications in immunotherapy. This review aims to provide novel insights and strategies for identifying novel targets in RNA methylation and advancing cancer immunotherapy efficacy.

Prognostic signature and immune efficacy of m1A-, m5C-, m6A-, m7G-, and DNA methylation-related regulators in hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is the main type of primary liver cancer, and its related death ranks third worldwide. The curative methods and progress prediction markers of HCC are not sufficient enough. Nevertheless, little progress has been made in the signature of m1A-, m5C-, m6A-, m7G-, and DNA methylation of HCC. Results: We calibrated a risk gene signature model that can be used to categorize HCC patients based on univariate, multivariate, and LASSO Cox regression analysis. This gene signature classified the patients into high- and low-risk subgroups. Patients in the high-risk group showed significantly reduced overall survival (OS) compared with patients in the low-risk group. The gene set variation analysis (GSVA), immune infiltration, and immunotherapy response were analyzed. The results demonstrated that an immunosuppressive environment was exited and the high-risk group had higher sensitivity to 5-fluorouracil, cisplatin, sorafenib, tamoxifen, and epirubicin. These results indicated personalized therapy should be taken into consideration. Conclusions: Our findings enriched our understanding of the molecular heterogeneity, tumor microenvironment (TME), and drug susceptibility of HCC. m1A-, m5C-, m6A-, m7G-, and DNA methylation-related regulators may be promising biomarkers for future research.

Comprehensive review on lipid metabolism and RNA methylation: Biological mechanisms, perspectives and challenges

Adipose tissue plays a crucial role in maintaining energy balance, regulating hormones, and promoting metabolic health. To address disorders related to obesity and develop effective therapies, it is essential to have a deep understanding of adipose tissue biology. In recent years, RNA methylation has emerged as a significant epigenetic modification involved in various cellular functions and metabolic pathways. Particularly in the realm of adipogenesis and lipid metabolism, extensive research is ongoing to uncover the mechanisms and functional importance of RNA methylation. Increasing evidence suggests that RNA methylation plays a regulatory role in adipocyte development, metabolism, and lipid utilization across different organs. This comprehensive review aims to provide an overview of common RNA methylation modifications, their occurrences, and regulatory mechanisms, focusing specifically on their intricate connections to fat metabolism. Additionally, we discuss the research methodologies used in studying RNA methylation and highlight relevant databases that can aid researchers in this rapidly advancing field.

WDR4 promotes HCC pathogenesis through N7-methylguanosine by regulating and interacting with METTL1

BACKGROUND

The N7-methylguanosine (m7G), a modification at defined internal positions within tRNAs and rRNAs, is correlated with tumor progression. Methyltransferase like 1 (METTL1)/ WD repeat domain 4 (WDR4) mediated tRNA m7G modification, which could alter many oncogenic mRNAs translation to promote progress of multiple cancer types. However, whether and how the internal mRNA m7G modification is involved in tumorigenesis remains unclear.

METHODS

The immunohistochemistry assay was conducted to detect the expression of WDR4 and METTL1 in hepatocellular carcinoma (HCC) and the expression of both genes whether contributes to the prognosis of the survival rate of HCC patients. Then, CCK8, colony formation assays and tumor xenograft models were conducted to determine the effects of WDR4 on HCC cells in vitro and vivo. Besides, dot blot assay, m7G-MeRIP-seq and RNA-seq analysis were conducted to determine whether WDR4 contributes to m7G modification and underlying mechanism in HCC cells. Finally, rescue and CO-IP assay were conducted to explore whether WDR4 and METTL1 proteins form a complex in Huh7 cells.

RESULTS

WDR4 modulates m7G modification at the internal sites of tumor-promoting mRNAs by forming the WDR4-METTL1 complex. WDR4 knockdown downregulated the expression of mRNA and protein levels of METTL1 gene and thus further modulate the formation of WDR4-METTL1 complex indirectly. METTL1 expression was markedly correlated with WDR4 expression in HCC tissues. HCC patients with high expression of both genes had a poor prognosis.

CONCLUSIONS

WDR4 may contribute to HCC pathogenesis by interacting with and regulating the expression of METTL1 to synergistically modulate the m7G modification of target mRNAs in tumor cells.

Dynamic RNA methylation modifications and their regulatory role in mammalian development and diseases

Among over 170 different types of chemical modifications on RNA nucleobases identified so far, RNA methylation is the major type of epitranscriptomic modifications existing on almost all types of RNAs, and has been demonstrated to participate in the entire process of RNA metabolism, including transcription, pre-mRNA alternative splicing and maturation, mRNA nucleus export, mRNA degradation and stabilization, mRNA translation. Attributing to the development of high-throughput detection technologies and the identification of both dynamic regulators and recognition proteins, mechanisms of RNA methylation modification in regulating the normal development of the organism as well as various disease occurrence and developmental abnormalities upon RNA methylation dysregulation have become increasingly clear. Here, we particularly focus on three types of RNA methylations: N6-methylcytosine (m6A), 5-methylcytosine (m5C), and N7-methyladenosine (m7G). We summarize the elements related to their dynamic installment and removal, specific binding proteins, and the development of high-throughput detection technologies. Then, for a comprehensive understanding of their biological significance, we also overview the latest knowledge on the underlying mechanisms and key roles of these three mRNA methylation modifications in gametogenesis, embryonic development, immune system development, as well as disease and tumor progression.

RNA modifications in pulmonary diseases

Threatening public health, pulmonary disease (PD) encompasses diverse lung injuries like chronic obstructive PD, pulmonary fibrosis, asthma, pulmonary infections due to pathogen invasion, and fatal lung cancer. The crucial involvement of RNA epigenetic modifications in PD pathogenesis is underscored by robust evidence. These modifications not only shape cell fates but also finely modulate the expression of genes linked to disease progression, suggesting their utility as biomarkers and targets for therapeutic strategies. The critical RNA modifications implicated in PDs are summarized in this review, including N6-methylation of adenosine, N1-methylation of adenosine, 5-methylcytosine, pseudouridine (5-ribosyl uracil), 7-methylguanosine, and adenosine to inosine editing, along with relevant regulatory mechanisms. By shedding light on the pathology of PDs, these summaries could spur the identification of new biomarkers and therapeutic strategies, ultimately paving the way for early PD diagnosis and treatment innovation.

Identification of N7-methylguanosine-related miRNAs as potential biomarkers for prognosis and drug response in breast cancer

Objectives

The impact of N7-methylguanosine (m7G) on tumor progression and the regulatory role of microRNAs (miRNAs) in immune function significantly influence breast cancer (BC) prognosis. Investigating the interplay between m7G modification and miRNAs provides novel insights for assessing prognostics and drug responses in BC.

Materials and methods

RNA sequences (miRNA and mRNA profiles) and clinical data for BC were acquired from the Cancer Genome Atlas (TCGA) database. A miRNA signature associated with 15 m7G in this cohort was identified using Cox regression and LASSO. The risk score model was evaluated using Kaplan-Meier and time-dependent ROC analysis, categorizing patients into high-risk and low-risk groups. Functional enrichment analyses were conducted to explore potential pathways. The immune system, including scores, cell infiltration, function, and drug sensitivity, was examined and compared between high-risk and low-risk groups. A nomogram that combines risk scores and clinical factors was developed and validated. Single-sample gene set enrichment analysis (ssGSEA) was employed to explore m7G-related miRNA signatures and immune cell relationships in the tumor microenvironment. Additionally, drug susceptibility was compared between risk groups.

Results

Fifteen m7G-related miRNAs were independently correlated with overall survival (OS) in BC patients. Time-dependent ROC analysis yielded area under the curve (AUC) values of 0.742, 0.726, and 0.712 for predicting 3-, 5-, and 10-year survival rates, respectively. The Kaplan-Meier analysis revealed a significant disparity in OS between the high-risk and low-risk groups (p = 1.3e-6). Multiple regression identified the risk score as a significant independent prognostic factor. An excellent calibration nomogram with a C-index of 0.785 (95 % CI: 0.728-0.843) was constructed. In immune analysis, low-risk patients exhibited heightened immune function and increased responsiveness to immunotherapy and chemotherapy compared to high-risk patients.

Conclusion

This study systematically analyzed m7G-related miRNAs and revealed their regulatory mechanisms concerning the tumor microenvironment (TME), pathology, and the prognosis of BC patient. Based on these miRNAs, a prognostic model and nomogram were developed for BC patients, facilitating prognostic assessments. These findings can also assist in predicting treatment responses and guiding medication selection.

Small-Molecule Inhibitors of the m7G-RNA Writer METTL1

We discovered the first inhibitors of the m7G-RNA writer METTL1 by high-throughput docking and an enzymatic assay based on luminescence. Eleven compounds, which belong to three different chemotypes, show inhibitory activity in the range 40-300 μM. Two adenine derivatives identified by docking have very favorable ligand efficiency of 0.34 and 0.31 kcal/mol per non-hydrogen atom, respectively. Molecular dynamics simulations provide evidence that the inhibitors compete with the binding of the cosubstrate S-adenosyl methionine to METTL1. We also present a soakable crystal form that was used to determine the structure of the complex of METTL1 with sinefungin at a resolution of 1.85 Å.

Beyond the Anticodon: tRNA Core Modifications and Their Impact on Structure, Translation and Stress Adaptation

Transfer RNAs (tRNAs) are heavily decorated with post-transcriptional chemical modifications. Approximately 100 different modifications have been identified in tRNAs, and each tRNA typically contains 5-15 modifications that are incorporated at specific sites along the tRNA sequence. These modifications may be classified into two groups according to their position in the three-dimensional tRNA structure, i.e., modifications in the tRNA core and modifications in the anticodon-loop (ACL) region. Since many modified nucleotides in the tRNA core are involved in the formation of tertiary interactions implicated in tRNA folding, these modifications are key to tRNA stability and resistance to RNA decay pathways. In comparison to the extensively studied ACL modifications, tRNA core modifications have generally received less attention, although they have been shown to play important roles beyond tRNA stability. Here, we review and place in perspective selected data on tRNA core modifications. We present their impact on tRNA structure and stability and report how these changes manifest themselves at the functional level in translation, fitness and stress adaptation.

Oral squamous cell carcinoma gene patterns connected with RNA methylation for prognostic prediction

OBJECTIVES

To determine whether m6A/m1A/m5C/m7G/m6Am/Ψ-related genes influence the prognosis of a patient with oral squamous cell carcinoma.

MATERIALS AND METHODS

We investigated the changes in regulatory genes using publicly available data from The Cancer Genome Atlas. Consensus clustering by RNA methylation-related regulators was used to describe oral squamous cell carcinomas (OSCCs). Then, we developed the prediction model. The tumor microenvironment was investigated using ESTIMATE. Gene set enrichment analysis was used to determine whether pathways or cell types were enriched in different groups. The association between the model and immune-related risk scores was investigated using correlation analysis.

RESULTS

We found 22 gene signatures in this analysis and then developed a predictive model that reveals the genes that are highly connected to the overall survival of OSCC patients. The survival and death rates were substantially different in the two groups (high and low risk) classified by the risk scores. The validation cohort verified the phenotypic diversity and prognostic effects of these genes.

CONCLUSION

Our data reveal that immune cell infiltration, genetic mutation, and survival potential in OSCC patients are linked to m6A/m1A/m5C/m7G/m6Am/Ψ-related genes, and we constructed a dependable prognostic model for OSCC patients.

METTL1 mediated tRNA m7G modification promotes leukaemogenesis of AML via tRNA regulated translational control

BACKGROUND

RNA modifications have been proven to play fundamental roles in regulating cellular biology process. Recently, maladjusted N7-methylguanosine (m7G) modification and its modifiers METTL1/WDR4 have been confirmed an oncogene role in multiple cancers. However, the functions and molecular mechanisms of METTL1/WDR4 in acute myeloid leukemia (AML) remain to be determined.

METHODS

METTL1/WDR4 expression levels were quantified using qRT-PCR, western blot analysis on AML clinical samples, and bioinformatics analysis on publicly available AML datasets. CCK-8 assays and cell count assays were performed to determine cell proliferation. Flow cytometry assays were conducted to assess cell cycle and apoptosis rates. Multiple techniques were used for mechanism studies in vitro assays, such as northern blotting, liquid chromatography-coupled mass spectrometry (LC-MS/MS), tRNA stability analysis, transcriptome sequencing, small non-coding RNA sequencing, quantitative proteomics, and protein synthesis measurements.

RESULTS

METTL1/WDR4 are significantly elevated in AML patients and associated with poor prognosis. METTL1 knockdown resulted in reduced cell proliferation and increased apoptosis in AML cells. Mechanically, METTL1 knockdown leads to significant decrease of m7G modification abundance on tRNA, which further destabilizes tRNAs and facilitates the biogenesis of tsRNAs in AML cells. In addition, profiling of nascent proteins revealed that METTL1 knockdown and transfection of total tRNAs that were isolated from METTL1 knockdown AML cells decreased global translation efficiency in AML cells.

CONCLUSIONS

Taken together, our study demonstrates the important role of METTL1/WDR4 in AML leukaemogenesis, which provides a promising target candidate for AML therapy.

Transfer RNA modifications and cellular thermotolerance

RNA molecules are modified post-transcriptionally to acquire their diverse functions. Transfer RNA (tRNA) has the widest variety and largest numbers of RNA modifications. tRNA modifications are pivotal for decoding the genetic code and stabilizing the tertiary structure of tRNA molecules. Alternation of tRNA modifications directly modulates the structure and function of tRNAs and regulates gene expression. Notably, thermophilic organisms exhibit characteristic tRNA modifications that are dynamically regulated in response to varying growth temperatures, thereby bolstering fitness in extreme environments. Here, we review the history and latest findings regarding the functions and biogenesis of several tRNA modifications that contribute to the cellular thermotolerance of thermophiles.

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.

Three molecular subtypes and a five-gene signature for hepatocellular carcinoma based on m7G-related classification

BACKGROUND

The current research investigated the heterogeneity of hepatocellular carcinoma (HCC) based on the expression of N7-methylguanosine (m7G)-related genes as a classification model and developed a risk model predictive of HCC prognosis, key pathological behaviors and molecular events of HCC.

METHODS

The RNA sequencing data of HCC were extracted from The Cancer Genome Atlas (TCGA)-live cancer (LIHC) database, hepatocellular carcinoman database (HCCDB) and Gene Expression Omnibus database, respectively. According to the expression level of 29 m7G-related genes, a consensus clustering analysis was conducted. The least absolute shrinkage and selection operator (LASSO) regression analysis and COX regression algorithm were applied to create a risk prediction model based on normalized expression of five characteristic genes weighted by coefficients. Tumor microenvironment (TME) analysis was performed using the MCP-Counter, TIMER, CIBERSORT and ESTIMATE algorithms. The Tumor Immune Dysfunction and Exclusion algorithm was applied to assess the responses to immunotherapy in different clusters and risk groups. In addition, patient sensitivity to common chemotherapeutic drugs was determined by the biochemical half-maximal inhibitory concentration using the R package pRRophetic.

RESULTS

Three molecular subtypes of HCC were defined based on the expression level of m7G-associated genes, each of which had its specific survival rate, genomic variation status, TME status and immunotherapy response. In addition, drug sensitivity analysis showed that the C1 subtype was more sensitive to a number of conventional oncolytic drugs (including paclitaxel, imatinib, CGP-082996, pyrimethamine, salubrinal and vinorelbine). The current five-gene risk prediction model accurately predicted HCC prognosis and revealed the degree of somatic mutations, immune microenvironment status and specific biological events.

CONCLUSION

In this study, three heterogeneous molecular subtypes of HCC were defined based on m7G-related genes as a classification model, and a five-gene risk prediction model was created for predicting HCC prognosis, providing a potential assessment tool for understanding the genomic variation, immune microenvironment status and key pathological mechanisms during HCC development.

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.

Diagnostic Values of METTL1-Related Genes and Immune Characteristics in Systemic Lupus Erythematosus

Purpose

Methyltransferase like 1 (METTL1) regulates epitranscriptomes via the m7G modification in mammalian mRNA and microRNA. Systemic lupus erythematosus (SLE) is caused by abnormal immune reactivity and has diverse clinical manifestations. RNA methylation as a mechanism to regulate gene expression is widely implicated in immune regulation. However, the role of m7G in immune response of SLE has not been extensively studied.

Patients and Methods

Expression of METTL1 was identified in the public dataset GSE122459 and validated in an independent cohort of SLE patients. We investigated the association between METTL1-expression and clinical manifestations of SLE. Subsequently, differentially expressed genes (DEG) that were correlated with METTL1-expression in GSE122459 were used for functional enrichment analysis. The correlation between infiltrating immune cells and METTL1, as well as candidate biomarkers identified to be correlated with either METTL1 or immune cell infiltration were assessed by single-sample GSEA. Potential mechanisms were explored with Gene ontology and KEGG pathway enrichment. Diagnostic performances of candidate biomarkers in SLE were analyzed.

Results

The mRNA and protein expression of METTL1 in SLE patients were significantly decreased in both datasets. METTL1-coexpressed DEGs were enriched in several key immune-related pathways. Activated CD8 T cells, activated CD4 T cells, memory B cells and type 2 helper T cells were different between patients with high and low METTL1 expression. Further, activated CD8 T-cells, activated CD4 T-cells, memory B-cells were correlated with METTL1. The genes of LAMP3, CD83, PDCD1LG2, IGKVD3D-20, IGKV5-2, IGKV2D-30, IGLV3-19 and IGLV4-60 were identified as candidate targets that were correlated with immune cell proportion. Moreover, LAMP3, CD83, and PDCD1LG2 expression were of diagnostic value in SLE as indicated by ROC analysis.

Conclusion

Our findings suggested that METTL1 and its candidate targets LAMP3, CD83, PDCD1LG2 may be used for diagnosing SLE and could be explored for developing targeted molecular therapy for SLE.

Selection of M7G-related lncRNAs in kidney renal clear cell carcinoma and their putative diagnostic and prognostic role

BACKGROUND

Kidney renal clear cell carcinoma (KIRC) is a common malignant tumor of the urinary system. This study aims to develop new biomarkers for KIRC and explore the impact of biomarkers on the immunotherapeutic efficacy for KIRC, providing a theoretical basis for the treatment of KIRC patients.

METHODS

Transcriptome data for KIRC was obtained from the The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Weighted gene co-expression network analysis identified KIRC-related modules of long noncoding RNAs (lncRNAs). Intersection analysis was performed differentially expressed lncRNAs between KIRC and normal control samples, and lncRNAs associated with N(7)-methylguanosine (m7G), resulting in differentially expressed m7G-associated lncRNAs in KIRC patients (DE-m7G-lncRNAs). Machine Learning was employed to select biomarkers for KIRC. The prognostic value of biomarkers and clinical features was evaluated using Kaplan-Meier (K-M) survival analysis, univariate and multivariate Cox regression analysis. A nomogram was constructed based on biomarkers and clinical features, and its efficacy was evaluated using calibration curves and decision curves. Functional enrichment analysis was performed to investigate the functional enrichment of biomarkers. Correlation analysis was conducted to explore the relationship between biomarkers and immune cell infiltration levels and common immune checkpoint in KIRC samples.

RESULTS

By intersecting 575 KIRC-related module lncRNAs, 1773 differentially expressed lncRNAs, and 62 m7G-related lncRNAs, we identified 42 DE-m7G-lncRNAs. Using XGBoost and Boruta algorithms, 8 biomarkers for KIRC were selected. Kaplan-Meier survival analysis showed significant survival differences in KIRC patients with high and low expression of the PTCSC3 and RP11-321G12.1. Univariate and multivariate Cox regression analyses showed that AP000696.2, PTCSC3 and clinical characteristics were independent prognostic factors for patients with KIRC. A nomogram based on these prognostic factors accurately predicted the prognosis of KIRC patients. The biomarkers showed associations with clinical features of KIRC patients, mainly localized in the cytoplasm and related to cytokine-mediated immune response. Furthermore, immune feature analysis demonstrated a significant decrease in immune cell infiltration levels in KIRC samples compared to normal samples, with a negative correlation observed between the biomarkers and most differentially infiltrating immune cells and common immune checkpoints.

CONCLUSION

In summary, this study discovered eight prognostic biomarkers associated with KIRC patients. These biomarkers showed significant correlations with clinical features, immune cell infiltration, and immune checkpoint expression in KIRC patients, laying a theoretical foundation for the diagnosis and treatment of KIRC.

Establishment of a new molecular subtyping and prognostic signature with m6A/m5C/m1A/m7G regulatory genes for hepatocellular carcinoma

Background

RNA modification, including m6A, m5C, m1A, and m7G, participated in tumor progress. Therefore, the purpose of the present study was to explore the role of m6A/m5C/m1A/m7G regulatory genes in the prognosis and tumor microenvironment (TME) for hepatocellular carcinoma (HCC).

Methods

71 m6A/m5C/m1A/m7G regulatory genes expression for HCC was detected, differentially expressed genes were screened, and molecular forms were classified by unsupervised consensus clustering. Cox regression and the Least Absolute Shrinkage and Selection Operator (LASSO) analysis were applied to establish a prognostic signature. Time-dependent receiver operating characteristic (ROC) curves were evaluated for clinical effectiveness and accuracy of the prognostic hazard model. In cluster subtypes and risk models, the differences in prognosis, immune cell infiltration, immune checkpoint, immunotherapy, and drug sensitivity between different subtypes were evaluated.

Results

HCC patients were classified into two clusters (cluster 1 and cluster 2) according to the expression of 71 m6A/m5C/m1A/m7G regulatory genes. Cluster 1 had a poor prognosis and different immune cell infiltration. Cluster 1 had higher immune checkpoint expression and TIDE score than cluster 2. Subsequently, we construct a five-gene prognostic model of m6A/m5C/m1A/m7G regulatory genes (YTHDF2, YTHDF1,YBX1, TRMT61A, TRMT10C). The Kaplan-Meier and ROC curve analysis showed that the prognostic signature exhibited good predictability. The risk score was considered an independent poor prognostic index. The high-risk group had higher immune checkpoint expression and higher TIDE scores. 5-Fluorouracil, docetaxel, doxorubicin, etoposide, gemcitabine, paclitaxel, sorafenib, and vinblastine were more suitable for high-risk patients. ECM receptor interaction, cell cycle, and Leishmania infection were enriched in the high-risk group.

Conclusion

The clustering subgroups and prognostic model of m6A/m5C/m1A/m7G regulatory genes were linked with bad prognosis and TME for HCC, and had the potential to be a novel tool to evaluate the outcomes of HCC patients.

The tRNA methyltransferase TrmB is critical for Acinetobacter baumannii stress responses and pulmonary infection

IMPORTANCE

As deficiencies in tRNA modifications have been linked to human diseases such as cancer and diabetes, much research has focused on the modifications' impacts on translational regulation in eukaryotes. However, the significance of tRNA modifications in bacterial physiology remains largely unexplored. In this paper, we demonstrate that the m7G tRNA methyltransferase TrmB is crucial for a top-priority pathogen, Acinetobacter baumannii, to respond to stressors encountered during infection, including oxidative stress, low pH, and iron deprivation. We show that loss of TrmB dramatically attenuates a murine pulmonary infection. Given the current efforts to use another tRNA methyltransferase, TrmD, as an antimicrobial therapeutic target, we propose that TrmB, and other tRNA methyltransferases, may also be viable options for drug development to combat multidrug-resistant A. baumannii.

Establishment of a prognostic model toward lung squamous cell carcinoma based on m7G-related genes in the cancer genome atlas

Lung squamous cell carcinoma (LUSC) is a non-small cell lung cancer with a poor prognosis owing to late diagnosis. New molecular markers are urgently needed to improve the diagnosis and prognosis of LUSC. 7-Methylguanosine (m7G) modifications, a tRNA modification, are common in eubacteria, eukaryotes, and a few archaea. These modifications promote the turnover and stability of some mRNAs to prevent mRNA decay, improve translation efficiency, and reduce ribosomal pausing but are associated with poor survival in human cancer cells. However, expression of m7G-related genes in LUSC and their association with prognosis remain unclear. In the present study, we identified nine differentially expressed genes related to prognosis by comparing the expression profiles of tumor tissues (502 LUSC reports) with normal tissues (49 adjacent nontumor lung tissue reports). The genes included six upregulated genes (KLK7, LCE3E, AREG, KLK6, ZBED2, and MAPK4) and three downregulated genes (ADH1C, NTS, and ERLIN2). Based on these nine genes, patients with LUSC were classified into low- and high-risk groups to analyze the trends in prognosis. We found that the nine m7G-related genes play important roles in immune regulation, hormone regulation, and drug sensitivity through pathways including antigen processing and presentation, adherent plaques, extracellular matrix receptor interactions, drug metabolism of cytochrome P-450, and metabolism of cytochrome P-450 to xenobiotics; the functions of these genes are likely accomplished in part by m6A modifications. The effect of m7G-related genes on the diagnosis and prognosis of LUSC was further indicated by population analysis.NEW & NOTEWORTHY Based on the differential expression of 7-methylguanosine (m7G) modification-associated genes between normal and lung squamous cell carcinoma (LUSC) tissues, and considering the performance of our m7G-related gene risk profiles as independent risk factors in predicting overall survival, we conclude that m7G modification is closely linked to the development of LUSC. In addition, this study offers a new genetic marker for predicting the prognosis of patients with LUSC and presents a crucial theoretical foundation for future investigations on the relationship between m7G modification-related genes, immunity, and drug sensitivity in LUSC.

Multi-omics analysis and validation of the tumor microenvironment of hepatocellular carcinoma under RNA modification patterns

BACKGROUND

Multiple types of RNA modifications are associated with the prognosis of hepatocellular carcinoma (HCC) patients. However, the overall mediating effect of RNA modifications on the tumor microenvironment (TME) and the prognosis of patients with HCC is unclear.

METHODS

Thoroughly analyze the TME, biological processes, immune infiltration and patient prognosis based on RNA modification patterns and gene patterns. Construct a prognostic model (RNA modification score, RNAM-S) to predict the overall survival (OS) in HCC patients. Analyze the immune status, cancer stem cell (CSC), mutations and drug sensitivity of HCC patients in both the high and low RNAM-S groups. Verify the expression levels of the four characteristic genes of the prognostic RNAM-S using in vitro cell experiments.

RESULTS

Two modification patterns and two gene patterns were identified in this study. Both the high-expression modification pattern and the gene pattern exhibited worse OS. A prognostic RNAM-S model was constructed based on four featured genes (KIF20A, NR1I2, NR2F1 and PLOD2). Cellular experiments suggested significant dysregulation of the expression levels of these four genes. In addition, validation of the RNAM-S model using each data set showed good predictive performance of the model. The two groups of HCC patients (high and low RNAM-S groups) exhibited significant differences in immune status, CSC, mutation and drug sensitivity.

CONCLUSION

The findings of the study demonstrate the clinical value of RNA modifications, which provide new insights into the individualized treatment for patients with HCC.

Biological roles of RNA m7G modification and its implications in cancer

M7G modification, known as one of the common post-transcriptional modifications of RNA, is present in many different types of RNAs. With the accurate identification of m7G modifications within RNAs, their functional roles in the regulation of gene expression and different physiological functions have been revealed. In addition, there is growing evidence that m7G modifications are crucial in the emergence of cancer. Here, we review the most recent findings regarding the detection techniques, distribution, biological functions and Regulators of m7G. We also summarize the connections between m7G modifications and cancer development, drug resistance, and tumor microenvironment as well as we discuss the research's future directions and trends.

The dysregulation of lncRNAs by epigenetic factors in human pathologies

Dysregulation of long noncoding RNAs (lncRNAs) contributes to numerous human diseases, including cancers and autoimmune diseases (ADs). Given the importance of lncRNAs in disease initiation and progression, a deeper understanding of their complex regulatory network is required to facilitate their use as therapeutic targets for ADs. In this review, we summarize how lncRNAs are dysregulated in pathological states by epigenetic factors, including RNA-binding proteins, chemical modifications (N6-methyladenosine, 5-methylcytosine, 7-methylguanosine, adenosine-to-inosine editing, microRNA, alternative splicing, DNA methylation, and histone modification). Moreover, the roles of lncRNA epigenetic regulators in immune response and ADs are discussed, providing new insights into the complicated epigenetic factor-lncRNA network, thus, laying a theoretical foundation for future research and clinical application of lncRNAs.

Regulation of the epigenome through RNA modifications

Chemical modifications of nucleotides expand the complexity and functional properties of genomes and transcriptomes. A handful of modifications in DNA bases are part of the epigenome, wherein DNA methylation regulates chromatin structure, transcription, and co-transcriptional RNA processing. In contrast, more than 150 chemical modifications of RNA constitute the epitranscriptome. Ribonucleoside modifications comprise a diverse repertoire of chemical groups, including methylation, acetylation, deamination, isomerization, and oxidation. Such RNA modifications regulate all steps of RNA metabolism, including folding, processing, stability, transport, translation, and RNA's intermolecular interactions. Initially thought to influence all aspects of the post-transcriptional regulation of gene expression exclusively, recent findings uncovered a crosstalk between the epitranscriptome and the epigenome. In other words, RNA modifications feedback to the epigenome to transcriptionally regulate gene expression. The epitranscriptome achieves this feat by directly or indirectly affecting chromatin structure and nuclear organization. This review highlights how chemical modifications in chromatin-associated RNAs (caRNAs) and messenger RNAs (mRNAs) encoding factors involved in transcription, chromatin structure, histone modifications, and nuclear organization affect gene expression transcriptionally.

Identification and validation of a m7G-related lncRNA signature for predicting the prognosis and therapy response in hepatocellular carcinoma

BACKGROUND

N7-methylguanosine (m7G) is one of the most common RNA posttranscriptional modifications; however, its potential role in hepatocellular carcinoma (HCC) remains unknown. We developed a prediction signature based on m7G-related long noncoding RNAs (lncRNAs) to predict HCC prognosis and provide a reference for immunotherapy and chemotherapy.

METHODS

RNA-seq data from The Cancer Genome Atlas (TCGA) database and relevant clinical data were used. Univariate and multivariate Cox regression analyses were conducted to identify m7G-related lncRNAs with prognostic value to build a predictive signature. We evaluated the prognostic value and clinical relevance of this signature and explored the correlation between the predictive signature and the chemotherapy treatment response of HCC. Moreover, an in vitro study to validate the function of CASC19 was performed.

RESULTS

Six m7G-related lncRNAs were identified to create a signature. This signature was considered an independent risk factor for the prognosis of patients with HCC. TIDE analyses showed that the high-risk group might be more sensitive to immunotherapy. ssGSEA indicated that the predictive signature was strongly related to the immune activities of HCC. HCC in high-risk patients was more sensitive to the common chemotherapy drugs bleomycin, doxorubicin, gemcitabine, and lenalidomide. In vitro knockdown of CASC19 inhibited the proliferation, migration and invasion of HCC cells.

CONCLUSION

We established a 6 m7G-related lncRNA signature that may assist in predicting the prognosis and response to chemotherapy and immunotherapy of HCC.

RNA modifications in cancer

Currently, more than 170 modifications have been identified on RNA. Among these RNA modifications, various methylations account for two-thirds of total cases and exist on almost all RNAs. Roles of RNA modifications in cancer are garnering increasing interest. The research on m6A RNA methylation in cancer is in full swing at present. However, there are still many other popular RNA modifications involved in the regulation of gene expression post-transcriptionally besides m6A RNA methylation. In this review, we focus on several important RNA modifications including m1A, m5C, m7G, 2'-O-Me, Ψ and A-to-I editing in cancer, which will provide a new perspective on tumourigenesis by peeking into the complex regulatory network of epigenetic RNA modifications, transcript processing, and protein translation.

Identification and validation of a novel prognostic model for gastric cancer based on m7G-related genes

Background

The role of N7-methyladenosine (m7G)-related genes in the progression and prognosis of gastric cancer (GC) remains unclear. This study aimed to explore prognostic biomarkers for GC based on m7G methylation regulators and to construct a prognostic risk model.

Methods

RNA sequencing profiles with corresponding clinicopathological information associated with GC of which the histological type was stomach adenocarcinoma (STAD) were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), respectively. A total of 29 m7G regulators were extracted from previous studies. According to the expression similarity of m7G regulators, the GC samples obtained from TCGA were further classified into 2 clusters demonstrating different overall survival (OS) rates and genetic heterogeneity, and the differentially expressed genes (DEGs) between these 2 clusters were defined as m7G-related genes. Univariate regression analysis and regression analysis were then used to obtain the prognostic m7G-related genes. The samples in TCGA and Genotype-Tissue Expression (GTEx) were used to verify the differential expression and prognostic value of these m7G-related genes contained in the prognostic model. Subsequently, the risk score was combined with other prognostic factors to develop a nomogram. The predictive ability of the nomogram was evaluated by the standard receiver operating characteristic (ROC) curve. Gene set enrichment analysis (GSEA) was used to identify activation pathways in both groups. Finally, the association between the prognostic model and the immune characteristics of GC were appraised.

Results

A prognostic model consisting of 11 m7G-related genes was constructed. GC patients in the high-risk group were shown to have a poor prognosis and this result was further demonstrated in each group. The risk model can be applied for patients with different clinical features. The results of GSEA showed that cell adhesion, cell junction, and focal adhesion were highly enriched in the high-risk group. In addition, we found that the expression of programmed cell death ligand 1 (PD-L1) was significantly elevated in the low-risk group, whereas programmed cell death ligand 2 (PD-L2) and tumor necrosis factor receptor superfamily member 4 (TNFRSF4) were overexpressed in the high-risk group.

Conclusions

We successfully built and verified a m7G relevant prognostic model for predicting prognosis and providing a new train of thought for improving the treatment of GC.

TROP2 translation mediated by dual m6A/m7G RNA modifications promotes bladder cancer development

RNA modifications, including adenine methylation (m6A) of mRNA and guanine methylation (m7G) of tRNA, are crucial for the biological function of RNA. However, the mechanism underlying the translation of specific genes synergistically mediated by dual m6A/m7G RNA modifications in bladder cancer (BCa) remains unclear. We demonstrated that m6A methyltransferase METTL3-mediated programmable m6A modification of oncogene trophoblast cell surface protein 2 (TROP2) mRNA promoted its translation during malignant transformation of bladder epithelial cells. m7G methyltransferase METTL1 enhanced TROP2 translation by mediating m7G modification of certain tRNAs. TROP2 protein inhibition decreased the proliferation and invasion of BCa cells in vitro and in vivo. Moreover, synergistical knockout of METTL3/METTL1 inhibited BCa cell proliferation, migration, and invasion; however, TROP2 overexpression partially abrogated its effect. Furthermore, TROP2 expression was significantly positively correlated with the expression levels of METTL3 and METTL1 in BCa patients. Overall, our results revealed that METTL3/METTL1-mediated dual m6A/m7G RNA modifications enhanced TROP2 translation and promoted BCa development, indicating a novel RNA epigenetic mechanism in BCa.

The life and times of a tRNA

The study of eukaryotic tRNA processing has given rise to an explosion of new information and insights in the last several years. We now have unprecedented knowledge of each step in the tRNA processing pathway, revealing unexpected twists in biochemical pathways, multiple new connections with regulatory pathways, and numerous biological effects of defects in processing steps that have profound consequences throughout eukaryotes, leading to growth phenotypes in the yeast Saccharomyces cerevisiae and to neurological and other disorders in humans. This review highlights seminal new results within the pathways that comprise the life of a tRNA, from its birth after transcription until its death by decay. We focus on new findings and revelations in each step of the pathway including the end-processing and splicing steps, many of the numerous modifications throughout the main body and anticodon loop of tRNA that are so crucial for tRNA function, the intricate tRNA trafficking pathways, and the quality control decay pathways, as well as the biogenesis and biology of tRNA-derived fragments. We also describe the many interactions of these pathways with signaling and other pathways in the cell.

Structural Mapping of the Base Stacks Containing Post-transcriptionally Modified Bases in RNA

Post-transcriptionally modified bases play vital roles in many biochemical processes involving RNA. Analysis of the non-covalent interactions associated with these bases in RNA is crucial for providing a more complete understanding of the RNA structure and function; however, the characterization of these interactions remains understudied. To address this limitation, we present a comprehensive analysis of base stacks involving all crystallographic occurrences of the most biologically relevant modified bases in a large dataset of high-resolution RNA crystal structures. This is accompanied by a geometrical classification of the stacking contacts using our established tools. Coupled with quantum chemical calculations and an analysis of the specific structural context of these stacks, this provides a map of the stacking conformations available to modified bases in RNA. Overall, our analysis is expected to facilitate structural research on altered RNA bases.

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.

WDR4/TRIM28 is a novel molecular target linked to lenvatinib resistance that helps retain the stem characteristics in hepatocellular carcinomas

Hepatocellular carcinoma (HCC) is an aggressive malignancy with few effective treatment options. Lenvatinib is the first-line therapy for HCC but has only limited clinical benefit. Here, we explored the role and mechanism of the WD repeat domain 4 (WDR4) in lenvatinib resistance to improve clinical benefit. We found that lenvatinib-resistant HCC tissues/cells exhibited increased the N⁷-methylguanosine (m⁷G) modification and WDR4 expression. By a gain/loss of function experiment, we showed that WDR4 promoted HCC lenvatinib resistance and tumor progress both in vitro and in vivo. By proteomics analysis and RNA immunoprecipitation PCR, we found that tripartite motif protein 28 (trim28) was an important WDR4 target gene. WDR4 promoted TRIM28 expression, further affected target genes expression, and thus increased cell-acquired stemness and lenvatinib resistance. Clinical tissue data showed that TRIM28 expression was correlated with WDR4 levels, and the expression of both was positively correlated with poor prognosis. Our study provides new insight into the role of WDR4, suggesting a potential therapeutic target to enhance the lenvatinib sensitivity of HCC.

Underexplored reciprocity between genome-wide methylation status and long non-coding RNA expression reflected in breast cancer research: potential impacts for the disease management in the framework of 3P medicine

Breast cancer (BC) is the most common female malignancy reaching a pandemic scale worldwide. A comprehensive interplay between genetic alterations and shifted epigenetic regions synergistically leads to disease development and progression into metastatic BC. DNA and histones methylations, as the most studied epigenetic modifications, represent frequent and early events in the process of carcinogenesis. To this end, long non-coding RNAs (lncRNAs) are recognized as potent epigenetic modulators in pathomechanisms of BC by contributing to the regulation of DNA, RNA, and histones' methylation. In turn, the methylation status of DNA, RNA, and histones can affect the level of lncRNAs expression demonstrating the reciprocity of mechanisms involved. Furthermore, lncRNAs might undergo methylation in response to actual medical conditions such as tumor development and treated malignancies. The reciprocity between genome-wide methylation status and long non-coding RNA expression levels in BC remains largely unexplored. Since the bio/medical research in the area is, per evidence, strongly fragmented, the relevance of this reciprocity for BC development and progression has not yet been systematically analyzed. Contextually, the article aims at:consolidating the accumulated knowledge on both-the genome-wide methylation status and corresponding lncRNA expression patterns in BC andhighlighting the potential benefits of this consolidated multi-professional approach for advanced BC management. Based on a big data analysis and machine learning for individualized data interpretation, the proposed approach demonstrates a great potential to promote predictive diagnostics and targeted prevention in the cost-effective primary healthcare (sub-optimal health conditions and protection against the health-to-disease transition) as well as advanced treatment algorithms tailored to the individualized patient profiles in secondary BC care (effective protection against metastatic disease). Clinically relevant examples are provided, including mitochondrial health control and epigenetic regulatory mechanisms involved.

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.

Vital roles of m5C RNA modification in cancer and immune cell biology

RNA modification plays an important role in epigenetics at the posttranscriptional level, and 5-methylcytosine (m5C) has attracted increasing attention in recent years due to the improvement in RNA m5C site detection methods. By influencing transcription, transportation and translation, m5C modification of mRNA, tRNA, rRNA, lncRNA and other RNAs has been proven to affect gene expression and metabolism and is associated with a wide range of diseases, including malignant cancers. RNA m5C modifications also substantially impact the tumor microenvironment (TME) by targeting different groups of immune cells, including B cells, T cells, macrophages, granulocytes, NK cells, dendritic cells and mast cells. Alterations in immune cell expression, infiltration and activation are highly linked to tumor malignancy and patient prognosis. This review provides a novel and holistic examination of m5C-mediated cancer development by examining the exact mechanisms underlying the oncogenicity of m5C RNA modification and summarizing the biological effects of m5C RNA modification on tumor cells as well as immune cells. Understanding methylation-related tumorigenesis can provide useful insights for the diagnosis as well as the treatment of cancer.

Epigenetic regulation in the tumor microenvironment: molecular mechanisms and therapeutic targets

Over decades, researchers have focused on the epigenetic control of DNA-templated processes. Histone modification, DNA methylation, chromatin remodeling, RNA modification, and noncoding RNAs modulate many biological processes that are crucial to the development of cancers. Dysregulation of the epigenome drives aberrant transcriptional programs. A growing body of evidence suggests that the mechanisms of epigenetic modification are dysregulated in human cancers and might be excellent targets for tumor treatment. Epigenetics has also been shown to influence tumor immunogenicity and immune cells involved in antitumor responses. Thus, the development and application of epigenetic therapy and cancer immunotherapy and their combinations may have important implications for cancer treatment. Here, we present an up-to-date and thorough description of how epigenetic modifications in tumor cells influence immune cell responses in the tumor microenvironment (TME) and how epigenetics influence immune cells internally to modify the TME. Additionally, we highlight the therapeutic potential of targeting epigenetic regulators for cancer immunotherapy. Harnessing the complex interplay between epigenetics and cancer immunology to develop therapeutics that combine thereof is challenging but could yield significant benefits. The purpose of this review is to assist researchers in understanding how epigenetics impact immune responses in the TME, so that better cancer immunotherapies can be developed.

WDR4 gene polymorphisms and Wilms tumor susceptibility in Chinese children: A five-center case-control study

Wilms tumor is the most common embryonal renal malignancy in children. WDR4 is an indispensable noncatalytic subunit of the RNA N7-methylguanosine (m7G) methyltransferase complex and plays an essential role in tumorigenesis. However, the relationship between polymorphisms in the WDR4 gene and susceptibility to Wilms tumor remains to be fully investigated. We performed a large case-control study involving 414 patients and 1199 cancer-free controls to investigate whether single nucleotide polymorphisms (SNPs) in the WDR4 gene are associated with Wilms tumor susceptibility. WDR4 gene polymorphisms (rs2156315 C > T, rs2156316 C > G, rs6586250 C > T, rs15736 G > A, and rs2248490 C > G) were genotyped using the TaqMan assay. In addition, unconditioned logistic regression analysis was performed, odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the association between WDR4 gene SNPs and Wilms tumor susceptibility as well as the strength of the associations. We found that only the rs6586250 C>T polymorphism was significantly associated with an increased risk of Wilms tumor (adjusted OR=2.99, 95% CI = 1.28-6.97, P = 0.011 for the rs6586250 TT genotype; adjusted OR=3.08, 95% CI = 1.33-7.17, P = 0.009 for the rs6586250 CC/CT genotype). Furthermore, the stratification analysis revealed that patients with the rs6586250 TT genotype and carriers with 1-5 risk genotypes exhibited statistically significant associations with increased Wilms tumor risk in specific subgroups. However, the rs2156315 CT/TT genotype was identified as having a protective effect against Wilms tumor in the age >18 months subgroup compared with the rs2156315 CC genotype. In brief, our study demonstrated that the rs6586250 C > T polymorphism of the WDR4 gene was significantly associated with Wilms tumor. This finding may contribute to the understanding of the genetic mechanism of Wilms tumor.

An innovative model based on N7-methylguanosine-related lncRNAs for forecasting prognosis and tumor immune landscape in bladder cancer

BACKGROUND

As a novel type of the prevalent post-transcriptional modifications, N7-methylguanosine (m7G) modification is essential in the tumorigenesis, progression, and invasion of many cancers, including bladder cancer (BCa). However, the integrated roles of m7G-related lncRNAs in BCa remain undiscovered. This study aims to develop a prognostic model based on the m7G-related lncRNAs and explore its predictive value of the prognosis and anti-cancer treatment sensitivity.

METHODS

We obtained RNA-seq data and corresponding clinicopathological information from the TCGA database and collected m7G-related genes from previous studies and GSEA. Based on LASSO and Cox regression analysis, we developed a m7G prognostic model. The Kaplan-Meier (K-M) survival analysis and ROC curves were performed to evaluate the predictive power of the model. Gene set enrichment analysis (GSEA) was conducted to explore the molecular mechanisms behind apparent discrepancies between the low- and high-risk groups. We also investigated immune cell infiltration, TIDE score, TMB, the sensitivity of common chemotherapy drugs, and the response to immunotherapy between the two risk groups. Finally, we validated the expression levels of these ten m7G-related lncRNAs in BCa cell lines by qRT-PCR.

RESULTS

We developed a m7G prognostic model (risk score) composed of 10 m7G-related lncRNAs that are significantly associated with the OS of BCa patients. The K-M survival curves revealed that the high-risk group patients had significantly worse OS than those in the low-risk group. The Cox regression analysis confirmed that the risk score was a significant independent prognostic factor for BCa patients. We found that the high-risk group had higher the immune scores and immune cell infiltration. Furthermore, the results of the sensitivity of common anti-BCa drugs showed that the high-risk group was more sensitive to neoadjuvant cisplatin-based chemotherapy and anti-PD1 immunotherapy. Finally, qRT-PCR revealed that AC006058.1, AC073133.2, LINC00677, and LINC01338 were significantly downregulated in BCa cell lines, while the expression levels of AC124312.2 and AL158209.1 were significantly upregulated in BCa cell lines compared with normal cell lines.

CONCLUSION

The m7G prognostic model can be applied to accurately predict the prognosis and provide robust directions for clinicians to develop better individual-based and precise treatment strategies for BCa patients.

A potential biological signature of 7-methylguanosine-related lncRNA to predict the immunotherapy effects in bladder cancer

Background

Bladder urothelial carcinoma (BLCA) is the second prevalent genitourinary carcinoma globally. N7-methylguanosine (m7G) is important for tumorigenesis and progression. This study aimed to build a predictive model for m7G-related long non-coding RNAs (lncRNAs), elucidate their role in the tumor immune microenvironment (TIME), and predict immunotherapy response in BLCA.

Methods

We first used univariate Cox regression and coexpression analyses to identify m7G-related lncRNAs. Next, the prognostic model was built by utilizing LASSO regression analysis. Then, the prognostic significance of the model was examined utilizing Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curves, nomogram, and univariate, multivariate Cox regression. We also analyzed Gene set enrichment analyses (GSEA), immune analysis and principal component analysis (PCA) in risk groups. To further predict immunotherapy effectiveness, we evaluated the predictive ability for immunotherapy in 2 risk groups and clusters using tumor immune dysfunction and exclusion (TIDE) score and Immunophenoscore (IPS).

Results

Seven lncRNAs related to m7G were used to create a model. The calibration plots for the model suggested a strong fit with the prediction of overall survival (OS). The area under the curve (AUC) for first, second, and third years was respectively, 0.722, 0.711, and 0.686. In addition, the risk score had strong correlation with TIME features and genes linked to immune checkpoint blockade (ICB). TIDE scores were dramatically different between two risk groups (p < 0.05), and IPS scores were markedly different between two clusters (p < 0.05).

Conclusion

Our research constructed a novel m7G-related lncRNAs that could be used to predict patient outcomes and the effectiveness of immunotherapy in BLCA. Immunotherapy may be more effective for the low-risk group and cluster 2.

A new prediction model of hepatocellular carcinoma based on N7-methylguanosine modification

PURPOSE

Hepatocellular carcinoma (HCC) is a kind of primary liver cancer. It is a common malignant tumor of digestive system that is difficult to predict the prognosis of patients. As an important epigenetic modification, N7 methyl guanosine (m7G) is indispensable in gene regulation. This regulation may affect the development and occurrence of cancer. However, the prognosis of long non coding RNAs (lncRNAs) in HCC is limited, especially how m7G-related lncRNAs regulate the development of HCC has not been reported.

METHODS

The Cancer Genome Atlas (TCGA) provides us with the expression data and corresponding clinical information of HCC patients we need. We used a series of statistical methods to screen four kinds of m7G-related lncRNAs related to HCC prognosis and through a series of verifications, the results were in line with our expectations. Finally, we also explored the IC50 difference and correlation analysis of various common chemotherapy drugs.

RESULT

Our study identified four differentially expressed m7g-related lncRNAs associated with HCC prognosis. Survival curve analysis showed that high risk lncRNAs would lead to poor prognosis of HCC patients. M7G signature's AUC was 0.789, which shows that the prognosis model we studied has certain significance in predicting the prognosis of HCC patients. Moreover, our study found that different risk groups have different immune and tumor related pathways through gene set enrichment analysis. In addition, many immune cell functions are significantly different among different risk groups, such as T cell functions, including coordination of type I INF response and coordination of type II INF response. The expression of PDCD1, HHLA2, CTLA-4 and many other immune checkpoints in different risk groups is also different. Additionally, we analyzed the differences of IC50 and risk correlation of 15 chemotherapeutic drugs among different risk groups.

CONCLUSION

A novel lncRNAs associated with m7G predicts the prognosis of HCC.

Emerging roles of tRNA in cancer

Transfer RNAs (tRNAs) play pivotal roles in the transmission of genetic information, and abnormality of tRNAs directly leads to translation disorders and causes diseases, including cancer. The complex modifications enable tRNA to execute its delicate biological function. Alteration of appropriate modifications may affect the stability of tRNA, impair its ability to carry amino acids, and disrupt the pairing between anticodons and codons. Studies confirmed that dysregulation of tRNA modifications plays an important role in carcinogenesis. Furthermore, when the stability of tRNA is impaired, tRNAs are cleaved into small tRNA fragments (tRFs) by specific RNases. Though tRFs have been found to play vital regulatory roles in tumorigenesis, its formation process is far from clear. Understanding improper tRNA modifications and abnormal formation of tRFs in cancer is conducive to uncovering the role of metabolic process of tRNA under pathological conditions, which may open up new avenues for cancer prevention and treatment.