METTL1 Promotes let-7 MicroRNA Processing via m7G Methylation

The Repertoire of RNA Modifications Orchestrates a Plethora of Cellular Responses

Although a plethora of DNA modifications have been extensively investigated in the last decade, recent breakthroughs in molecular biology, including high throughput sequencing techniques, have enabled the identification of post-transcriptional marks that decorate RNAs; hence, epitranscriptomics has arisen. This recent scientific field aims to decode the regulatory layer of the transcriptome and set the ground for the detection of modifications in ribose nucleotides. Until now, more than 170 RNA modifications have been reported in diverse types of RNA that contribute to various biological processes, such as RNA biogenesis, stability, and transcriptional and translational accuracy. However, dysfunctions in the RNA-modifying enzymes that regulate their dynamic level can lead to human diseases and cancer. The present review aims to highlight the epitranscriptomic landscape in human RNAs and match the catalytic proteins with the deposition or deletion of a specific mark. In the current review, the most abundant RNA modifications, such as N6-methyladenosine (m⁶A), N5-methylcytosine (m⁵C), pseudouridine (Ψ) and inosine (I), are thoroughly described, their functional and regulatory roles are discussed and their contributions to cellular homeostasis are stated. Ultimately, the involvement of the RNA modifications and their writers, erasers, and readers in human diseases and cancer is also discussed.

Association of RNA m7G Modification Gene Polymorphisms with Pediatric Glioma Risk

Glioma stemming from glial cells of the central nervous system (CNS) is one of the leading causes of cancer death in childhood. The genetic predisposition of glioma is not fully understood. METTL1-WDR4 methyltransferase complex is implicated in tumorigenesis by catalyzing N7-methylguanosine (m⁷G) modification of RNA. This study is aimed at determining the association of glioma risk with three polymorphisms (rs2291617, rs10877013, and rs10877012) in METTL1 and five polymorphisms (rs2156315 rs2156316, rs6586250, rs15736, and rs2248490) in WDR4 gene in children of Chinese Han. We enrolled 314 cases and 380 controls from three independent hospitals. Genotypes of these polymorphisms were determined using the TaqMan assay. We found the WDR4 gene rs15736 was significantly associated with reduced glioma risk (GA/AA vs. GG: adjusted odds ratio = 0.63, 95%confidence interval = 0.42 - 0.94, P = 0.023) out of the eight studied polymorphisms. Stratified analyses showed that the association of rs15736 with the risk of glioma remained significant in children aged 60 months or older, girls, the subgroups with astrocytic tumors, or grade I + II glioma. We also found the combined effects of five WDR4 gene polymorphisms on glioma risk. Finally, expression quantitative trait locus (eQTL) analyses elucidated that the rs15736 polymorphism was related to the expression level of WDR4 and neighboring gene cystathionine-beta-synthase (CBS). Our finding provided evidence of a causal association between WDR4 gene polymorphisms and glioma susceptibility in Chinese Han children.

Expression patterns and prognostic value of key regulators associated with m7G RNA modification based on all gene expression in colon adenocarcinoma

BACKGROUND

N7-methylguanosine (m7G) is present in a wide variety of organisms and has important roles. m7G has been reported to be involved in multiple biological processes, and recent studies have reported that changes in RNA modifications result in tumor cellular transformation and cancer, such as colon adenocarcinoma, lung cancer, and intrahepatic cholangiocarcinoma. However, little is known about the function of the m7G in colon adenocarcinoma.

METHODS

We established two clusters based on the expression of all genes associated with m7G to explore the expression pattern of 31 key regulatory factors of m7G RNA and assess the prognostic value of regulatory factors. Wilcoxon test and differential box line plots were applied for bioinformatics analysis. Receiver Operating and Kaplan‒Meier curves were utilized to evaluate the prognostic value. Finally, four genes' expression in the colon cancer cell line was confirmed by qRT-PCR.

RESULTS

From The Cancer Genome Atlas database, we found that the expression levels of 25 out of the 31 key N7-methylguanosine RNA modification regulators were significantly different in colon adenocarcinoma. According to 25 methylation regulators' expression, we identified two subgroups by consensus clustering, in which the prognosis was worse in Group 2 than in Group 1 and was significantly correlated with age. Cluster 2 was significantly enriched in tumor-associated pathways, and immune cells were highly infiltrated in Cluster 1 but weakly infiltrated in Cluster 2. Further results indicated that this risk profile may serve as a standalone predictive factor for colon adenocarcinoma, and the four genetic risk profiles' prognostic relatedness was successfully verified through Gene Expression Omnibus dataset. At last, A nomogram for prognosis was created according to age, sex, histological grading, clinicopathological staging, and hazard score to accurately predict patient prognosis in colon adenocarcinoma. We successfully validated the differential expression of four genes using qRT-PCR.

CONCLUSIONS

In the present study, we revealed the important contribution of key regulators associated with m7G RNA modifications based on all gene expression in colon adenocarcinoma and developed a signature of risk that serves as a promising prognostic marker for patients with colon adenocarcinoma.

Internal m7G methylation: A novel epitranscriptomic contributor in brain development and diseases

In recent years, N7-methylguanosine (m7G) methylation, originally considered as messenger RNA (mRNA) 5' caps modifications, has been identified at defined internal positions within multiple types of RNAs, including transfer RNAs, ribosomal RNAs, miRNA, and mRNAs. Scientists have put substantial efforts to discover m7G methyltransferases and methylated sites in RNAs to unveil the essential roles of m7G modifications in the regulation of gene expression and determine the association of m7G dysregulation in various diseases, including neurological disorders. Here, we review recent findings regarding the distribution, abundance, biogenesis, modifiers, and functions of m7G modifications. We also provide an up-to-date summary of m7G detection and profile mapping techniques, databases for validated and predicted m7G RNA sites, and web servers for m7G methylation prediction. Furthermore, we discuss the pathological roles of METTL1/WDR-driven m7G methylation in neurological disorders. Last, we outline a roadmap for future directions and trends of m7G modification research, particularly in the central nervous system.

Structure of pre-miR-31 reveals an active role in Dicer processing

As an essential post-transcriptional regulator of gene expression, microRNA (miR) levels must be strictly maintained. The biogenesis of many, but not all, miRs is mediated by trans-acting protein partners through a variety of mechanisms, including remodeling of the RNA structure. miR-31 functions as an oncogene in numerous cancers and interestingly, its biogenesis is not known to be regulated by protein binding partners. Therefore, the intrinsic structural properties of pre-miR-31 can provide a mechanism by which its biogenesis is regulated. We determined the solution structure of the precursor element of miR-31 (pre-miR-31) to investigate the role of distinct structural elements in regulating Dicer processing. We found that the presence or absence of mismatches within the helical stem do not strongly influence Dicer processing of the pre-miR. However, both the apical loop size and structure at the Dicing site are key elements for discrimination by Dicer. Interestingly, our NMR-derived structure reveals the presence of a triplet of base pairs that link the Dicer cleavage site and the apical loop. Mutational analysis in this region suggests that the stability of the junction region strongly influence both Dicer binding and processing. Our results enrich our understanding of the active role that RNA structure plays in regulating Dicer processing which has direct implications for control of gene expression.

Tumor-derived miRNAs as tumor microenvironment regulators for synergistic therapeutic options

MicroRNAs (miRNAs) are a class of non-coding RNAs that perform post-transcriptional gene regulation. This review focuses on the role of tumor cell-derived miRNAs in the regulation of the tumor microenvironment (TME) via receptor cell recoding, including angiogenesis, expression of immunosuppressive molecules, formation of radiation resistance, and chemoresistance. Furthermore, we discuss the potential of these molecules as adjuvant therapies in combination with chemotherapy, radiotherapy, or immunotherapy, as well as their advantages as efficacy predictors for personalized therapy. MiRNA-based therapeutic agents for tumors are currently in clinical trials, and while challenges remain, additional research on tumor-derived miRNAs is warranted, which may provide significant clinical benefits to cancer patients.

Pathological and Therapeutic Advances in Parkinson's Disease: Mitochondria in the Interplay

Parkinson's disease (PD) is the second most common neurodegenerative illness majorly affecting the population between the ages of 55 to 65 years. Progressive dopaminergic neuronal loss and the collective assemblage of misfolded alpha-synuclein in the substantia nigra, remain notable neuro-pathological hallmarks of the disease. Multitudes of mechanistic pathways have been proposed in attempts to unravel the pathogenesis of PD but still, it remains elusive. The convergence of PD pathology is found in organelle dysfunction where mitochondria remain a major contributor. Mitochondrial processes like bioenergetics, mitochondrial dynamics, and mitophagy are under strict regulation by the mitochondrial genome and nuclear genome. These processes aggravate neurodegenerative activities upon alteration through neuroinflammation, oxidative damage, apoptosis, and proteostatic stress. Therefore, the mitochondria have grabbed a central position in the patho-mechanistic exploration of neurodegenerative diseases like PD. The management of PD remains a challenge to physicians to date, due to the variable therapeutic response of patients and the limitation of conventional chemical agents which only offer symptomatic relief with minimal to no disease-modifying effect. This review describes the patho-mechanistic pathways involved in PD not only limited to protein dyshomeostasis and oxidative stress, but explicit attention has been drawn to exploring mechanisms like organelle dysfunction, primarily mitochondria and mitochondrial genome influence, while delineating the newer exploratory targets such as GBA1, GLP, LRRK2, and miRNAs and therapeutic agents targeting them.

RNA methyltransferases in plants: Breakthroughs in function and evolution

Each day it is becoming increasingly difficult not to notice the completely new, fast growing, extremely intricate and challenging world of epitranscriptomics as the understanding of RNA methylation is expanding at a hasty rate. Writers (methyltransferases), erasers (demethylases) and readers (RNA-binding proteins) are responsible for adding, removing and recognising methyl groups on RNA, respectively. Several methyltransferases identified in plants are now being investigated and recent studies have shown a connection between RNA-methyltransferases (RNA-MTases) and stress and development processes. However, compared to their animal and bacteria counterparts, the understanding of RNA methyltransferases is still incipient, particularly those located in organelles. Comparative and systematic analyses allowed the tracing of the evolution of these enzymes suggesting the existence of several methyltransferases yet to be characterised. This review outlines the functions of plant nuclear and organellar RNA-MTases in plant development and stress responses and the comparative and evolutionary discoveries made on RNA-MTases across kingdoms.

Identification and validation of RNA methylation-related alternative splicing gene signature for low-grade glioma to predict survival and immune landscapes

BACKGROUND

Low-grade glioma (LGG) is a crucial pathological type of glioma. The present study aimed to explore multiple RNA methylation regulator-related AS events and investigate their prognostic values in LGG.

METHODS

The prognostic model for low-grade glioma was established using the LASSO regression analysis. To validate prognostic value, we performed Kaplan-Maier survival analysis, ROC curves and nomograms. The ESTIMATE algorithm, the CIBERSORT algorithm and the ssGSEA algorithm were utilized to explore the role of the immune microenvironment in LGG. Subsequently, we then used GO, KEGG and GSEA enrichment analysis to explore the functional roles of these genes. In addition, we employed the GDSC database to screen potential chemotherapeutic agents.

RESULTS

Eight RNA methylation related AS events were involved in construct a survival and prognosis model, which had good ability of independent prediction for patients with LGG. Patients in the high-risk group had shorter life expectancy and higher mortality, while patients in the low-risk group had a better prognosis. We constructed a nomogram which showed an excellent predictive performance for individual OS. The risk score exhibited a close correlation with some immune cells and expression of immune checkpoints. Patients in high-risk group were characterized by immunosuppressive microenvironment and poor response to immunotherapy, and were sensitive to more chemotherapeutic drugs. Pathway and functional enrichment analyses further confirmed that significant differences existed in immune landscape between the two subgroups.

CONCLUSION

The prognostic RNA methylation-related alternative splicing signature constructed could constitute a promising prognostic biomarker, which could serve to optimize treatment regimens.

m7G-quant-seq: Quantitative Detection of RNA Internal N7-Methylguanosine

Methods for the precise detection and quantification of RNA modifications are critical to uncover functional roles of diverse RNA modifications. The internal m⁷G modification in mammalian cytoplasmic tRNAs is known to affect tRNA function and impact embryonic stem cell self-renewal, tumorigenesis, cancer progression, and other cellular processes. Here, we introduce m⁷G-quant-seq, a quantitative method that accurately detects internal m⁷G sites in human cytoplasmic tRNAs at single-base resolution. The efficient chemical reduction and mild depurination can almost completely convert internal m⁷G sites into RNA abasic sites (AP sites). We demonstrate that RNA abasic sites induce a mixed variation pattern during reverse transcription, including G → A or C or T mutations as well as deletions. We calculated the total variation ratio to quantify the m⁷G modification fraction at each methylated site. The calibration curves of all relevant motif contexts allow us to more quantitatively determine the m⁷G methylation level. We detected internal m⁷G sites in 22 human cytoplasmic tRNAs from HeLa and HEK293T cells and successfully estimated the corresponding m⁷G methylation stoichiometry. m⁷G-quant-seq could be applied to monitor the tRNA m⁷G methylation level change in diverse biological processes.

RNA Epigenetics in Chronic Lung Diseases

Chronic lung diseases are highly prevalent worldwide and cause significant mortality. Lung cancer is the end stage of many chronic lung diseases. RNA epigenetics can dynamically modulate gene expression and decide cell fate. Recently, studies have confirmed that RNA epigenetics plays a crucial role in the developing of chronic lung diseases. Further exploration of the underlying mechanisms of RNA epigenetics in chronic lung diseases, including lung cancer, may lead to a better understanding of the diseases and promote the development of new biomarkers and therapeutic strategies. This article reviews basic information on RNA modifications, including N⁶ methylation of adenosine (m⁶A), N¹ methylation of adenosine (m¹A), N⁷-methylguanosine (m⁷G), 5-methylcytosine (m⁵C), 2'O-methylation (2'-O-Me or Nm), pseudouridine (5-ribosyl uracil or Ψ), and adenosine to inosine RNA editing (A-to-I editing). We then show how they relate to different types of lung disease. This paper hopes to summarize the mechanisms of RNA modification in chronic lung disease and finds a new way to develop early diagnosis and treatment of chronic lung disease.

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 Transcriptome Analysis Reveals the Crucial mRNAs and miRNAs Related to Fecundity in the Hypothalamus of Yunshang Black Goats during the Luteal Phase

A normal estrus cycle is essential for the breeding of goats, and the luteal phase accounts for most of the estrus cycle. The corpus luteum (CL) formed during the luteal phase is a transient endocrine gland that is crucial for the reproductive cycle and pregnancy maintenance, and is controlled by many regulatory factors. However, the molecular mechanism of the hypothalamus effect on the reproductive performance of different litter sizes during the luteal phase of goats has not been elucidated. In this study, RNA-sequencing was used to analyze the mRNA and miRNA expression profiles of the hypothalamic tissues with the high-fecundity goats during the luteal phase (LP-HF) and low-fecundity goats during the luteal phase (LP-LF). The RNA-seq results found that there were 1963 differentially expressed genes (DEGs) (890 up-regulated and 1073 down-regulated). The miRNA-seq identified 57 differentially expressed miRNAs (DEMs), including 11 up-regulated and 46 down-regulated, of which 199 DEGs were predicted to be potential target genes of DEMs. Meanwhile, the functional enrichment analysis identified several mRNA-miRNA pairs involved in the regulation of the hypothalamic activity, such as the common target gene MEA1 of novel-miR-972, novel-miR-125 and novel-miR-403, which can play a certain role as a related gene of the reproductive development in the hypothalamic-pituitary-gonadal (HPG) axis and its regulated network, by regulating the androgen secretion. While another target gene ADIPOR2 of the novel-miR-403, is distributed in the hypothalamus and affects the reproductive system through a central role on the HPG axis and a peripheral role in the gonadal tissue. An annotation analysis of the DE miRNA-mRNA pairs identified targets related to biological processes, such as anion binding (GO:0043168) and small molecule binding (GO: 0036094). Subsequently, the KEGG(Kyoto Encyclopedia of Genes and Genomes) pathways were performed to analyze the miRNA-mRNA pairs with negatively correlated miRNAs. We found that the GnRH signaling pathway (ko04912), the estrogen signaling pathway (ko04915), the Fc gamma R-mediated phagocytosis (ko04666), and the IL-17 signaling pathway (ko04657), etc., were directly and indirectly associated with the reproductive process. These targeting interactions may be closely related to the reproductive performance of goats. The results of this study provide a reference for further research on the molecular regulation mechanism for the high fertility in goats.

m7G-related lncRNAs are potential biomarkers for predicting prognosis and immune responses in patients with oral squamous cell carcinoma

Among head and neck cancers, oral squamous cell carcinoma (OSCC) is the most common malignant tumor. N-7-methylguanosine (m7G) and lncRNAs are both related to the development and progression of tumors. Therefore, this study aims to explore and establish the prognostic signal of OSCC based on m7G-related lncRNAs. In this study, RNA sequencing transcriptome data of OSCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Therefore, m7G-related lncRNAs were identified as differentially expressed in OSCC. Then, univariate Cox regression analysis and LASSO regression analysis were conducted to evaluate the prognostic significance of differentially expressed lncRNAs. Consequently, the abovementioned lncRNAs were assigned five OSCC patient risk scores, with high-risk and low-risk patients assigned to each group. Different signaling pathways were significantly enriched between the two groups as determined by set enrichment analysis (GSEA). Multivariate Cox regression analysis confirmed the factors used to construct the nomogram model. Then, the prognosis of the nomogram model was evaluated. Consequently, high-risk individuals had higher immune infiltration levels. According to the results of a study that evaluated the sensitivity of different risk subgroups to antitumour drugs, the high-risk group had a high sensitivity to doxorubicin. By performing real-time polymerase chain reaction (RT‒PCR), we verified the expression of these five m7G lncRNAs. Therefore, the model based on five m7G-related lncRNAs was able to predict the overall survival rates of OSCC patients and guide their treatment. It can also spur new ideas about how to prevent and treat OSCC.

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.

Constructing and validating of m7G-related genes prognostic signature for hepatocellular carcinoma and immune infiltration: potential biomarkers for predicting the overall survival

Background

To investigate the prognostic significance of N7-methylguanosine (m7G) regulators and immune infiltration in liver hepatocellular carcinoma (LIHC).

Methods

The research measured predictive m7G genes in LIHC samples from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. Data on the stemness index based on mRNA expression (mRNAsi), gene mutations, and corresponding clinical characteristics were obtained from TCGA and ICGC. Lasso regression was used to construct the prediction model to assess the m7G prognostic signals in LIHC. Based on these genes, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to identify key biological functions and pathways. The correlation between m7G RNA methylation regulators and the prognosis and immune infiltration of LIHC was evaluated.

Results

There were 21 m7G-related differentially expressed genes (DEGs) in LIHC and healthy tissues, and LIHC patients could be divided into two categories by consensus clustering of these DEGs. A five-gene predictive approach was employed using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Patients in the low-risk group showed a significantly higher survival rate compared with those in the high-risk group (P=0.001). Validations using the ICGC database. Also, univariate and multivariate Cox regression analyses suggested that the risk score produced by the predictive model is an independent predictor for LIHC [hazard ratio (HR): 1.848, 95% confidence interval (CI): 1.286-2.656; HR: 2.597, 95% CI: 1.358-4.965]. The ROC curves of the ICGC cohort revealed that the five-gene prediction model performed well [area under the curve (AUC) =0.642 at 1 year, AUC =0.686 at 2 years, and AUC =0.667 at 3 years]. Immuno-oncology scoring revealed that in the high-risk group, among 16 immune cells, the expressions of neutrophils and natural killer (NK) cells were low and that of regulatory T-cells (Tregs) was high.

Conclusions

LIHC occurrence and progression are linked to m7G-related genes. Corresponding prognostic models help forecast the prognosis of LIHC patients. m7G-related genes and associated immune cell infiltration in the TME may serve as potential therapeutic targets in LIHC, which requires further trials. In addition, the m7G-related gene signature offers a viable alternative to predict LIHC, and these m7G-related genes show a prospective research area for LIHC targeted treatment in the future.

RNA Modifications Meet Tumors

RNA modifications occur through the whole process of gene expression regulation, including transcription, translation, and post-translational processes. They are closely associated with gene expression, RNA stability, and cell cycle. RNA modifications in tumor cells play a vital role in tumor development and metastasis, changes in the tumor microenvironment, drug resistance in tumors, construction of tumor cell-cell "internet", etc. Several types of RNA modifications have been identified to date and have various effects on the biological characteristics of different tumors. In this review, we discussed the function of RNA modifications, including N 6-methyladenine (m6A), 5-methylcytosine (m5C), N 7-methyladenosine (m7G), N 1-methyladenosine (m1A), pseudouridine (Ψ), and adenosine-to-inosine (A-to-I), in the microenvironment and therapy of solid and liquid tumors.

METTL1 drives tumor progression of bladder cancer via degrading ATF3 mRNA in an m7G-modified miR-760-dependent manner

7-methylguanosine (m⁷G) modification is recently found to conservatively exist in RNA internal position besides mRNA caps and mediates the various RNA metabolisms. As the core confirmed transmethylase of m⁷G modification, METTL1 has been reported in certain human cancers. However, the role of internal m⁷G at miRNAs and its core writer METTL1 in bladder cancer (BCa) remains to be elucidated. Here, we demonstrated that METTL1 was indispensable for BCa proliferation and metastasis in vitro and in vivo. By combining miRNA sequencing, m⁷G methylated RNA immunoprecipitation (MeRIP) and RIP, we identified METTL1 promoted the processing of miR-760 in an m⁷G-dependent manner. Transcription sequencing suggested that METTL1 indirectly degrades tumor suppressor ATF3 mRNA mediated by miR-760. Together, we concluded a regulatory axis composed of METTL1/m⁷G/miR-760/ATF3 in regulating BCa progression and provided potential therapeutic targets for BCa.

M7G-related LncRNAs: A comprehensive analysis of the prognosis and immunity in glioma

Today, numerous international researchers have demonstrated that N7-methylguanosine (m7G) related long non-coding RNAs (m7G-related lncRNAs) are closely linked to the happenings and developments of various human beings’ cancers. However, the connection between m7G-related lncRNAs and glioma prognosis has not been investigated. We did this study to look for new potential biomarkers and construct an m7G-related lncRNA prognostic signature for glioma. We identified those lncRNAs associated with DEGs from glioma tissue sequences as m7G-related lncRNAs. First, we used Pearson’s correlation analysis to identify 28 DEGs by glioma and normal brain tissue gene sequences and predicated 657 m7G-related lncRNAs. Then, eight lncRNAs associated with prognosis were obtained and used to construct the m7G risk score model by lasso and Cox regression analysis methods. Furthermore, we used Kaplan-Meier analysis, time-dependent ROC, principal component analysis, clinical variables, independent prognostic analysis, nomograms, calibration curves, and expression levels of lncRNAs to determine the model’s accuracy. Importantly, we validated the model with external and internal validation methods and found it has strong predictive power. Finally, we performed functional enrichment analysis (GSEA, aaGSEA enrichment analyses) and analyzed immune checkpoints, associated pathways, and drug sensitivity based on predictors. In conclusion, we successfully constructed the formula of m7G-related lncRNAs with powerful predictive functions. Our study provides instructional value for analyzing glioma pathogenesis and offers potential research targets for glioma treatment and scientific research.

Gene regulation in animal miRNA biogenesis

miRNAs are a class of noncoding RNAs of approximately 19-22 nucleotides that are widely found in animals, plants, bacteria and even viruses. Dysregulation of the expression profile of miRNAs is importantly linked to the development of diseases. Epigenetic modifications regulate gene expression and control cellular phenotypes. Although miRNAs are used as an epigenetic regulation tool, the biogenesis of miRNAs is also regulated by epigenetic events. Here the authors review the mechanisms and roles of epigenetic modification (DNA methylation, histone modifications), RNA modification and ncRNAs in the biogenesis of miRNAs, aiming to deepen the understanding of the miRNA biogenesis regulatory network.

A Novel m7G-Related Gene Signature Predicts the Prognosis of Colon Cancer

Colon cancer (CC), one of the most common malignancies worldwide, lacks an effective prognostic prediction biomarker. N7-methylguanosine (m7G) methylation is a common RNA modification type and has been proven to influence tumorigenesis. However, the correlation between m7G-related genes and CC remains unclear. The gene expression levels and clinical information of CC patients were downloaded from public databases. Twenty-nine m7G-related genes were obtained from the published literature. Via unsupervised clustering based on the expression levels of m7G-related genes, CC patients were divided into three m7G clusters. Based on differentially expressed genes (DEGs) from the above three groups, CC patients were further divided into three gene clusters. The m7G score, a prognostic model, was established using principal component analysis (PCA) based on 15 prognosis-associated m7G genes. KM curve analysis demonstrated that the overall survival rate was remarkably higher in the high-m7G score group, which was much more significant in advanced CC patients as confirmed by subgroup analysis. Correlation analysis indicated that the m7G score was associated with tumor mutational burden (TMB), PD-L1 expression, immune infiltration, and drug sensitivity. The expression level of prognosis-related m7G genes was further confirmed in human CC cell lines and samples. This study established an m7G gene-based prognostic model (m7G score), which demonstrated the important roles of m7G-related genes during CC initiation and progression. The m7G score could be a practical biomarker to predict immunotherapy response and prognosis in CC patients.

M7G-Related lncRNAs predict prognosis and regulate the immune microenvironment in lung squamous cell carcinoma

Background

N7-Methylguanosine (m7G) and long non-coding RNAs (lncRNAs) have been widely studied in cancer and have been found to be useful for assessing tumor progression. However, the role of m7G-related lncRNAs in lung squamous cell carcinoma (LUSC) remains unclear. Thus, it is crucial to identify m7G-associated lncRNAs with definitive prognostic value. This study aimed to investigate the prognostic value, correlation with tumor mutation burden, and impact on the tumor immune microenvironment of m7G-related lncRNAs in LUSC. 

Methods

LUSC transcriptome data and clinical data were downloaded from The Cancer Genome Atlas, and an m7G-related lncRNA-mRNA co-expression network was constructed using Pearson’s correlation analysis. Cox regression analyses were used to determine a risk model for m7G-associated lncRNAs with prognostic value. The risk signature was verified using the Kaplan–Meier method, receiver operating characteristic curve analysis, and principal component analysis. A nomogram based on risk scores and clinical characteristics was then developed. Gene set enrichment analysis was used for functional annotation to analyze the risk signature. The association among the risk signature, tumor mutational burden, and tumor-infiltrating immune cells was then analyzed. RT-qPCR was used to investigate the expression of 6 m7G-related lncRNAs in LUSC cells. The cytological function of SRP14-AS1 was verified by wound-healing assay and transwell assay.

Results

A total of 293 m7G-related lncRNAs were identifed, 27 candidate m7G-related lncRNAs were signifcantly associated with overall survival (OS). Six of these lncRNAs (CYP4F26P, LINC02178, MIR22HG, SRP14-AS1, TMEM99, PTCSC2) were selected for establishment of the risk model. The OS of patients in the low-risk group was higher than that of patients in the high-risk group (p < 0.001). Multivariate cox regression analysis indicated that the model could be an independent prognostic factor for LUSC (HR = 1.859; 95% CI 1.452–2.380, p < 0.001). The ROC curve analysis revealed that the AUCs for OS in the 3-, and 5-year were 0.682, 0.657, respectively. GSEA analysis revealed that the risk model was closely related to immune-related pathways. Compared with normal lung epithelial cells, four m7G-related lncRNAs were higher expressed in cancer cells and two were lower expressed, among which knockdown of SRP14-AS1 promoted the proliferation and migration of LUSC cells.

Conclusion

A risk model based on six m7G-related lncRNAs with prognostic value may be a promising prognostic tool in LUSC and guide individualized patient treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10232-z.

The snoRNA-like lncRNA LNC-SNO49AB drives leukemia by activating the RNA-editing enzyme ADAR1

Long noncoding RNAs (lncRNAs) are usually 5' capped and 3' polyadenylated, similar to most typical mRNAs. However, recent studies revealed a type of snoRNA-related lncRNA with unique structures, leading to questions on how they are processed and how they work. Here, we identify a novel snoRNA-related lncRNA named LNC-SNO49AB containing two C/D box snoRNA sequences, SNORD49A and SNORD49B; and show that LNC-SNO49AB represents an unreported type of lncRNA with a 5'-end m7G and a 3'-end snoRNA structure. LNC-SNO49AB was found highly expressed in leukemia patient samples, and silencing LNC-SNO49AB dramatically suppressed leukemia progression in vitro and in vivo. Subcellular location indicated that the LNC-SNO49AB is mainly located in nucleolus and interacted with the nucleolar protein fibrillarin. However, we found that LNC-SNO49AB does not play a role in 2'-O-methylation regulation, a classical function of snoRNA; instead, its snoRNA structure affected the lncRNA stability. We further demonstrated that LNC-SNO49AB could directly bind to the adenosine deaminase acting on RNA 1(ADAR1) and promoted its homodimerization followed by a high RNA A-to-I editing activity. Transcriptome profiling shows that LNC-SNO49AB and ADAR1 knockdown respectively share very similar patterns of RNA modification change in downstream signaling pathways, especially in cell cycle pathways. These findings suggest a previously unknown class of snoRNA-related lncRNAs, which function via a manner in nucleolus independently on snoRNA-guide rRNA modification. This is the first report that a lncRNA regulates genome-wide RNA A-to-I editing by enhancing ADAR1 dimerization to facilitate hematopoietic malignancy, suggesting that LNC-SNO49AB may be a novel target in therapy directed to leukemia.

m7G regulator-mediated methylation modification patterns define immune cell infiltration and patient survival

Numerous studies have demonstrated the important roles of epigenetic modifications in tumorigenesis, progression and prognosis. However, in hepatocellular carcinoma, the potential link between N7-methylguanosine (m7G) modification and molecular heterogeneity and tumor microenvironment (TME) remains unclear.

Method

We performed a comprehensive evaluation of m7G modification patterns in 816 hepatocellular carcinoma samples based on 24 m7G regulatory factors, identified different m7G modification patterns, and made a systematic correlation of these modification patterns with the infiltration characteristics of immunocytes. Then, we built and validated a scoring tool called m7G score.

Results

In this study, we revealed the presence of three distinct m7G modification patterns in liver cancer, with remarkable differences in the immunocyte infiltration characteristics of these three subtypes. The m7G scoring system of this study could assess m7G modification patterns in individual hepatocellular carcinoma patients, could predict TME infiltration characteristics, genetic variants and patient prognosis. We also found that the m7G scoring system may be useful in guiding patients’ clinical use of medications.

Conclusions

This study revealed that m7G methylation modifications exerted a significant role in formation of TME in hepatocellular carcinoma. Assessing the m7G modification patterns of single patients would help enhance our perception of TME infiltration characteristics and give significant insights into immunotherapy efficacy.

Detection technologies for RNA modifications

To date, more than 170 chemical modifications have been characterized in RNA, providing a new layer of gene expression regulation termed the 'epitranscriptome'. RNA modification detection methods and tools advance the functional studies of the epitranscriptome. According to the detection throughput and principles, existing RNA modification detection technologies can be categorized into four classes, including quantification methods, locus-specific detection methods, next-generation sequencing-based detection technologies and nanopore direct RNA sequencing-based technologies. In this review, we summarize the current knowledge about these RNA modification detection technologies and discuss the challenges for the existing detection tools, providing information for a comprehensive understanding of the epitranscriptome.

Comprehensive pan-cancer analysis of N7-methylguanosine regulators: Expression features and potential implications in prognosis and immunotherapy

Although immunotherapy has made great strides in cancer therapy, its effectiveness varies widely among individual patients as well as tumor types, and there is an urgent need to develop biomarkers for effectively assessing immunotherapy response. In recent years, RNA methylation regulators have demonstrated to be novel potential biomarkers for prognosis as well as immunotherapy of cancers, such as N6-methyladenine (m6A) and 5-methylcytosine (m5C). N7-methylguanosine (m7G) is a prevalent RNA modification in eukaryotes, but the relationship between m7G regulators and prognosis as well as tumor immune microenvironment is still unclear. In this study, a pan-cancer analysis of 26 m7G regulators across 17 cancer types was conducted based on the bioinformatics approach. On the one hand, a comprehensive analysis of expression features, genetic variations and epigenetic regulation of m7G regulators was carried out, and we found that the expression tendency of m7G regulators were different among tumors and their aberrant expression in cancers could be affected by single nucleotide variation (SNV), copy number variation (CNV), DNA methylation and microRNA (miRNA) separately or simultaneously. On the other hand, the m7Gscore was modeled based on single sample gene set enrichment analysis (ssGSEA) for evaluating the relationships between m7G regulators and cancer clinical features, hallmark pathways, tumor immune microenvironment, immunotherapy response as well as pharmacotherapy sensitivity, and we illustrated that the m7Gscore exhibited tight correlations with prognosis, several immune features, immunotherapy response and drug sensitivity in most cancers. In conclusion, our pan-cancer analysis revealed that m7G regulators may exert critical roles in the tumor progression and immune microenvironment, and have the potential as biomarkers for predicting prognosis, immunotherapy response as well as candidate drug compounds for cancer patients.

Establishment of m7G-related gene pair signature to predict overall survival in colorectal cancer

Background: N7-methylguanosine (m7G) is an emerging research hotspot in the field of RNA methylation, and its role in tumor regulation is becoming increasingly recognized. However, its role in colorectal cancer (CRC) remains unclear. Hence, our study explored the role of m7G in CRC.

Methods: The mRNA expression data and the corresponding clinical information of the patients with CRC were obtained from The Cancer Genome Atlas (TCGA). A m7G-related gene pair signature was established using the Cox and LASSO regression analyses. A series of in silico analyses based on the signature included analysis of prognosis, correlation analysis, immune-related analysis, and estimation of tumor mutational burden (TMB), microsatellite instability (MSI), and response to immunotherapy. A nomogram prediction model was then constructed.

Results: In total, 2156 m7G-related gene pairs were screened based on 152 m7G-related genes. Then, a prognostic signature of seven gene pairs was constructed, and the patients were stratified into high- or low-risk groups. Better overall survival (OS), left-sided tumor, early stage, immune activity, and low proportion of MSI-low and MSI-high were all associated with a low risk score. High-risk patients had a higher TMB, and patients with a high TMB had a poor OS. Furthermore, the risk score was linked to immune checkpoint expression (including PD-L1), the tumor immune dysfunction and exclusion (TIDE) score, and chemotherapy sensitivity. We also created an accurate nomogram to increase the clinical applicability of the risk score.

Conclusion: We identified an m7G pair-based prognostic signature associated with prognosis, immune landscape, immunotherapy, and chemotherapy in CRC. These findings could help us to better understand the role of m7G in CRC, as well as pave the path for novel methods to assess prognosis and design more effective individualized therapeutic strategies.

A novel prognostic signature based on N7-methylguanosine-related long non-coding RNAs in breast cancer

Long non-coding RNA (lncRNA) are closely associated with the occurrence and progression of tumors. However, research on N7-methylguanosine (m7G)-related lncRNA in breast cancer is lacking. Therefore, the present study explored the prognostic value, gene expression characteristics, and effects of m7G-related lncRNA on tumor immune cell infiltration and tumor mutational burden (TMB) in breast cancer. lncRNA expression matrices and clinical follow-up data of patients with breast cancer were obtained from The Cancer Genome Atlas, revealing eight significantly differentially expressed and prognostically relevant m7G-related lncRNAs in breast cancer tissues: BAIAP2-DT, COL4A2-AS1, FARP1-AS1, RERE-AS1, NDUFA6-DT, TFAP2A-AS1, LINC00115, and MIR302CHG. A breast cancer prognostic signature was created based on these m7G-related lncRNAs according to least absolute shrinkage and selection operator Cox regression. The prognostic signature combined with potential prognostic factors showed independent prognostic value, reliability, and specificity. Meanwhile, we constructed a risk score-based nomogram to assist clinical decision-making. Gene set enrichment analysis revealed that low- and high-risk group were associated with metabolism-related pathways. Our study demonstrated the association between tumor immune cell infiltration based on analyses with the CIBERSORT algorithm and prognostic signature. We also assessed the correlation between prognostic signature and TMB. Lastly, quantitative real-time polymerase chain reaction analysis was performed to validate differentially expressed lncRNAs. The effective prognostic signature based on m7G-related lncRNAs has the potential to predict the survival prognosis of patients with breast cancer. The eight m7G-related lncRNAs identified in this study might represent potential biomarkers and therapeutic targets of breast cancer.

Dynamic Protein-RNA recognition in primary MicroRNA processing

MicroRNAs are prevalent regulators of gene expression, controlling most of the proteome in multicellular organisms. To generate the functional small RNAs, precise processing steps are required. In animals, microRNA biogenesis is initiated by Microprocessor that minimally consists of the Drosha enzyme and its partner, DGCR8. This first step is critical for selecting primary microRNAs, and many RNA-binding proteins and regulatory pathways target both the accuracy and efficiency of microRNA maturation. Structures of Drosha and DGCR8 in complex with primary microRNAs elucidate how RNA structural features rather than sequence provide the framework for substrate recognition. Comparing multiple states of Microprocessor and the closely related Dicer homologs shed light on the dynamic protein-RNA complex assembly and disassembly required to recognize RNAs with diverse sequences via common structural features.

Role of N7-methylguanosine (m7G) in cancer

N7-methylguanosine (m7G) is a significant RNA modification occurring during epigenetic regulation. An increasing number of investigations have proved that the effect of m7G in suppressing cancer deserves more attention. Herein, we explore potential valuable targets based on present studies of m7G-related cancer to improve disease therapy and prognoses.

RNA modifications in aging-associated cardiovascular diseases

Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide that bears an enormous healthcare burden and aging is a major contributing factor to CVDs. Functional gene expression network during aging is regulated by mRNAs transcriptionally and by non-coding RNAs epi-transcriptionally. RNA modifications alter the stability and function of both mRNAs and non-coding RNAs and are involved in differentiation, development, and diseases. Here we review major chemical RNA modifications on mRNAs and non-coding RNAs, including N6-adenosine methylation, N1-adenosine methylation, 5-methylcytidine, pseudouridylation, 2′ -O-ribose-methylation, and N7-methylguanosine, in the aging process with an emphasis on cardiovascular aging. We also summarize the currently available methods to detect RNA modifications and the bioinformatic tools to study RNA modifications. More importantly, we discussed the specific implication of the RNA modifications on mRNAs and non-coding RNAs in the pathogenesis of aging-associated CVDs, including atherosclerosis, hypertension, coronary heart diseases, congestive heart failure, atrial fibrillation, peripheral artery disease, venous insufficiency, and stroke.

Integrative pan-cancer analysis and clinical characterization of the N7-methylguanosine (m7G) RNA modification regulators in human cancers

Background: RNA modification is one of the epigenetic mechanisms that regulates post-transcriptional gene expression, and abnormal RNA modifications have been reported to play important roles in tumorigenesis. N7-methylguanosine (m7G) is an essential modification at the 5′ cap of human mRNA. However, a systematic and pan-cancer analysis of the clinical relevance of m7G related regulatory genes is still lacking.

Methods: We used univariate Cox model and Kaplan-Meier analysis to generate the forest plot of OS, PFI, DSS and identified the correlation between the altered expression of m7G regulators and patient survival in 33 cancer types from the TCGA and GTEx databases. Then, the “estimate” R-package, ssGSEA and CIBERSORT were used to depict the pan-cancer immune landscape. Through Spearman’s correlation test, we analyzed the correlation between m7G regulators and the tumor microenvironment (TME), immune subtype, and drug sensitivity of the tumors, which was further validated in NSCLC. We also assessed the changes in the expression of m7G related regulatory genes in NSCLC with regards to the genetic and transcriptional aspects and evaluated the correlation of METTL1 and WDR4 expression with TMB, MSI and immunotherapy in pan-cancer.

Results: High expression of most of the m7G regulators was significantly associated with worse prognosis. Correlation analyses revealed that the expression of majority of the m7G regulators was correlated with tumor immune infiltration and tumor stem cell scores. Drug sensitivity analysis showed that the expression of CYFP1,2 was closely related to drug sensitivity for various anticancer agents (p &lt; 0.001). Analysis of the pan-cancer immune subtype revealed significant differences in the expression of m7G regulators between different immune subtypes (p &lt; 0.001). Additionally, the types and proportions of mutations in METTL1 and WDR4 and their relevance to immunotherapy were further described.

Conclusion: Our study is the first to evaluate the correlation between the altered expression of m7G regulators and patient survival, the degree of immune infiltration, TME and drug sensitivity in pan-cancer datasets.

Identification of Six N7-Methylguanosine-Related miRNA Signatures to Predict the Overall Survival and Immune Landscape of Triple-Negative Breast Cancer through In Silico Analysis

Triple-negative breast cancer (TNBC) is a widely prevalent breast cancer, with a mortality rate of up to 25%. TNBC has a lower survival rate, and the significance of N7-methylguanosine (m7G) modification in TNBC remains unclear. Thus, this study is aimed at investigating m7G-related miRNAs in TNBC patients through in silico analysis. In our research, RNA sequencing and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. The miRNAs targeting typical m7G modification regulators Methyltransferase-like 1 (METTL1) and WD repeat domain 4 (WDR4) were predicted on the TargetScan website. A miRNA risk model was built, and its prognostic value was evaluated by R soft packages. Single-sample gene set enrichment analysis was used to assess immune infiltration, and further expression of immune checkpoints was investigated. As a result, miR-421, miR-5001-3p, miR-4326, miR-1915-3p, miR-3177-5p, and miR-4505 were identified to create the risk model. A nomogram consisting of the stage N and risk model predicted overall survival effectively among TNBC patients. Treg and TIL were shown to be strongly linked to the risk model, and the high-risk group had higher levels of four immune checkpoints expression (CD28, CTLA-4, ICOS, and TNFRSF9). A risk model consisting of m7G-related miRNAs was constructed. The findings of the current study could be used as a prognostic biomarker and can provide a novel immunotherapy insight for TNBC patients.

RNA modifications: importance in immune cell biology and related diseases

RNA modifications have become hot topics recently. By influencing RNA processes, including generation, transportation, function, and metabolization, they act as critical regulators of cell biology. The immune cell abnormality in human diseases is also a research focus and progressing rapidly these years. Studies have demonstrated that RNA modifications participate in the multiple biological processes of immune cells, including development, differentiation, activation, migration, and polarization, thereby modulating the immune responses and are involved in some immune related diseases. In this review, we present existing knowledge of the biological functions and underlying mechanisms of RNA modifications, including N⁶-methyladenosine (m⁶A), 5-methylcytosine (m⁵C), N¹-methyladenosine (m¹A), N⁷-methylguanosine (m⁷G), N⁴-acetylcytosine (ac⁴C), pseudouridine (Ψ), uridylation, and adenosine-to-inosine (A-to-I) RNA editing, and summarize their critical roles in immune cell biology. Via regulating the biological processes of immune cells, RNA modifications can participate in the pathogenesis of immune related diseases, such as cancers, infection, inflammatory and autoimmune diseases. We further highlight the challenges and future directions based on the existing knowledge. All in all, this review will provide helpful knowledge as well as novel ideas for the researchers in this area.

Novel roles of METTL1/WDR4 in tumor via m7G methylation

As one of the prevalent posttranscriptional modifications of RNA, N⁷-methylguanosine (m⁷G) plays essential roles in RNA processing, metabolism, and function, mainly regulated by the methyltransferase-like 1 (METTL1) and WD repeat domain 4 (WDR4) complex. Emerging evidence suggests that the METTL1/WDR4 complex promoted or inhibited the processes of many tumors, including head and neck, lung, liver, colon, bladder cancer, and teratoma, dependent on close m⁷G methylation modification of tRNA or microRNA (miRNA). Therefore, METTL1 and m⁷G modification can be used as biomarkers or potential intervention targets, providing new possibilities for early diagnosis and treatment of tumors. This review will mainly focus on the mechanisms of METTL1/WDR4 via m⁷G in tumorigenesis and the corresponding detection methods.

N7-methylguanosine-related lncRNAs: Distinction between hot and cold tumors and construction of predictive models in colon adenocarcinoma

Colon adenocarcinoma (COAD) is a prevalent malignant tumor that severely threatens human health across the globe. Immunotherapy is an essential need for patients with COAD. N7-methylguanosine (m7G) has been associated with human diseases, and non-coding RNAs (lncRNAs) regulate various tumor-related biological processes. Nonetheless, the m7G-related lncRNAs involved in COAD regulation are limited. This study aims to construct the clustering features and prognostic model of m7G-related lncRNAs in COAD. First, The Cancer Genome Atlas (TCGA) database was used to identify m7G-related differentially expressed lncRNAs (DELs), based on which COAD cases could be classified into two subtypes. Subsequently, univariate Cox analysis was used to identify 9 prognostic m7G-related lncRNAs. Further, Five candidates were screened by LASSO-Cox regression to develop new models. The patients were divided into high-risk and low-risk groups based on the median risk score. Consequently, the Kaplan-Meier survival curve demonstrated a statistically significant overall survival (OS) between the high- and low-risk groups (P&lt;0.001). Multivariate Cox regression analysis revealed that risk score is an independent prognostic factor in COAD patients (P&lt;0.001). This confirms the clinical applicability of the model. Additionally, we performed Gene Set Enrichment Analysis (GSEA), which uncovered the biological and functional differences between risk subgroups, i.e., enrichment of immune-related diseases in the high-risk group and enrichment of metabolic-related pathways in the low-risk group. In a drug sensitivity analysis, high-risk group were more sensitive to some chemotherapeutics and targeted drugs than low-risk group. Eventually, the stability of the model was confirmed by qRT-PCR. Our study unraveled the features of different immune states of COAD and established a prognostic model, including five m7G-related lncRNAs for COAD patients. These results will bolster clinical treatment and survival prediction of COAD.

Identification and construction of a prognostic risk model based on multi-RNA methylation regulators in cervical cancer

AIM

Cervical cancer is one of the most aggressive female cancers. RNA methylation is a necessary epigenetic modification in biological process. This study aimed to construct an RNA methylation regulator-based risk model for predicting the prognosis of cervical cancer patients.

METHODS

The transcriptome profiles of cervical cancer data were obtained from The Cancer Genome Atlas (TCGA) and GSE44001. An RNA methylation-related risk model was constructed and assessed by the Least absolute shrinkage and selection operator (Lasso)-penalized Cox regression model and receiver operating characteristic (ROC). Kaplan-Meier and Cox regression analyses were used to evaluate the prognostic effect of the risk model and calculated scores. The immune infiltration difference was further analyzed between the subgroups with a single-sample gene set enrichment analysis (ssGSEA).

RESULTS

A total of 63 methylation modulators were included in this study, and 618 cervical cancer patients were identified from TCGA and GSE44001. Differential expression genes profiling RNA methylation regulators between normal and tumor samples were distinct. A four-gene signature panel was constructed to predict the prognostic risk. The predictive ability was satisfactory. Cervical cancer patients were classified into high- or low-risk subgroups according to the median risk score. Moreover, the immune infiltration patterns between them differed.

CONCLUSIONS

A risk model including four RNA methylation regulators was constructed, which will provide new perspectives for further investigation of the relationship between RNA methylation and cervical cancer.

The role of RNA modification in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a highly mortal type of primary liver cancer. Abnormal epigenetic modifications are present in HCC, and RNA modification is dynamic and reversible and is a key post-transcriptional regulator. With the in-depth study of post-transcriptional modifications, RNA modifications are aberrantly expressed in human cancers. Moreover, the regulators of RNA modifications can be used as potential targets for cancer therapy. In RNA modifications, N6-methyladenosine (m6A), N7-methylguanosine (m7G), and 5-methylcytosine (m5C) and their regulators have important regulatory roles in HCC progression and represent potential novel biomarkers for the confirmation of diagnosis and treatment of HCC. This review focuses on RNA modifications in HCC and the roles and mechanisms of m6A, m7G, m5C, N1-methyladenosine (m1A), N3-methylcytosine (m3C), and pseudouridine (ψ) on its development and maintenance. The potential therapeutic strategies of RNA modifications are elaborated for HCC.

CD47 interactions with exportin-1 limit the targeting of m7G-modified RNAs to extracellular vesicles

CD47 is a marker of self and a signaling receptor for thrombospondin-1 that is also a component of extracellular vesicles (EVs) released by various cell types. Previous studies identified CD47-dependent functional effects of T cell EVs on target cells, mediated by delivery of their RNA contents, and enrichment of specific subsets of coding and noncoding RNAs in CD47+ EVs. Mass spectrometry was employed here to identify potential mechanisms by which CD47 regulates the trafficking of specific RNAs to EVs. Specific interactions of CD47 and its cytoplasmic adapter ubiquilin-1 with components of the exportin-1/Ran nuclear export complex were identified and confirmed by coimmunoprecipitation. Exportin-1 is known to regulate nuclear to cytoplasmic trafficking of 5'-7-methylguanosine (m7G)-modified microRNAs and mRNAs that interact with its cargo protein EIF4E. Interaction with CD47 was inhibited following alkylation of exportin-1 at Cys528 by its covalent inhibitor leptomycin B. Leptomycin B increased levels of m7G-modified RNAs, and their association with exportin-1 in EVs released from wild type but not CD47-deficient cells. In addition to perturbing nuclear to cytoplasmic transport, transcriptomic analyses of EVs released by wild type and CD47-deficient Jurkat T cells revealed a global CD47-dependent enrichment of m7G-modified microRNAs and mRNAs in EVs released by CD47-deficient cells. Correspondingly, decreasing CD47 expression in wild type cells or treatment with thrombospondin-1 enhanced levels of specific m7G-modified RNAs released in EVs, and re-expressing CD47 in CD47-deficient T cells decreased their levels. Therefore, CD47 signaling limits the trafficking of m7G-modified RNAs to EVs through physical interactions with the exportin-1/Ran transport complex.

Identification of N7-methylguanosine-related IncRNA signature as a potential predictive biomarker for colon adenocarcinoma

N⁷-Methylguanosine (m7G) is an RNA modification serving as a key part of colon cancer development. Thus, a comprehensive analysis was executed to explore prognostic roles and associations with the immune status of the m7G-related lncRNA (m7G-RNAs) in colon adenocarcinoma (COAD). Identification of m7G-RNAs was achieved via Pearson’s correlation analysis of lncRNAs in the TCGA-COAD dataset and m7G regulators. A prognostic signature was developed via LASSO analyses. ESTIMATE, CIBERSORT, and ssGSEA algorithms were utilized to assess immune infiltration between different risk groups. Survival analysis suggested the high-risk group possesses poor outcomes compared with the low-risk group. According to the ROC curves, the m7G-RNAs signature exhibited a reliable capability of prediction (AUCs at 1, 3, and 5 years were 0.770, 0.766, and 0.849, respectively). Multivariate hazard analysis proved that the signature was an independent predictive indicator for OS. Moreover, the risk score was related to infiltration levels of naïve B cells, CD4⁺ memory T cells, and resting NK cells. The result revealed the prognostic value of m7G modification in COAD and provided a novel perspective on personalized immunotherapy strategies.

Molecular characterization, clinical relevance and immune feature of m7G regulator genes across 33 cancer types

Over 170 RNA modifications have been identified after transcriptions, involving in regulation of RNA splicing, processing, translation and decay. Growing evidence has unmasked the crucial role of N6-methyladenosine (m6A) in cancer development and progression, while, as a relative newly found RNA modification, N7-methylguanosine (m7G) is also certified to participate in tumorigenesis via different catalytic machinery from that of m6A. However, system analysis on m7G RNA modification-related regulator genes is lack. In this study, we first investigated the genetic alteration of m7G related regulator genes in 33 cancers, and found mRNA expression levels of most regulator genes were positively correlated with copy number variation (CNV) and negatively correlated with methylation in most cancers. We built a m7G RNA modification model based on the enrichment of the regulator gene scores to evaluate the m7G modification levels in 33 cancers, and investigated the connections of m7G scores to clinical outcomes. Furthermore, we paid close attention to the role of m7G in immunology due to the widely used immune checkpoint blockade therapy. Our results showed the higher m7G scores related to immunosuppression of tumor cells. Further confirmation with phase 3 clinical data with application of anti-PDL1/PDL indicated the impact of m7G modification level on immunotherapy effect. Relevance of m7G regulator genes and drug sensitivity was also evaluated to provide a better treatment choice when treating cancers. In summary, our study uncovered the profile of m7G RNA modification through various cancers, and figured out the connection of m7G modification levels with therapeutical outcomes, providing potential better options of cancer treatment.

Astrocytic IGF-1 and IGF-1R Orchestrate Mitophagy in Traumatic Brain Injury via Exosomal miR-let-7e

Defective brain hormonal signaling and autophagy have been associated with neurodegeneration after brain insults, characterized by neuronal loss and cognitive dysfunction. However, few studies have linked them in the context of brain injury. Insulin-like growth factor-1 (IGF-1) is an important hormone that contributes to growth, cell proliferation, and autophagy and is also expressed in the brain. Here, we assessed the clinical data from TBI patients and performed both in vitro and in vivo experiments with proteomic and gene-chip analysis to assess the functions of IGF-1 in mitophagy following TBI. We show that reduced plasma IGF-1 is correlated with cognition in TBI patients. Overexpression of astrocytic IGF-1 improves cognitive dysfunction and mitophagy in TBI mice. Mechanically, proteomics data show that the IGF-1-related NF-κB pathway transcriptionally regulates decapping mRNA2 (Dcp2) and miR-let-7, together with IGF-1R to orchestrate mitophagy in TBI. Finally, we demonstrate that brain injury induces impaired mitophagy at the chronic stage and that IGF-1 treatment could facilitate the mitophagy markers via exosomal miR-let-7e. By showing that IGF-1 is an important mediator of the beneficial effect of the neural-endocrine network in TBI models, our findings place IGF-1/IGF-1R as a potential target capable of noncoding RNAs and opposing mitophagy failure and cognitive impairment in TBI.

METTL1 gene polymorphisms synergistically confer hepatoblastoma susceptibility

INTRODUCTION

Hepatoblastoma is a rare but devastating pediatric liver malignancy. Overexpressed methyltransferase-like 1 (METTL1) is a methyltransferase that catalyzes essential N7-methylguanosine (m7G) modification of eukaryotic mRNA. Accumulating evidence has revealed the oncogenic potential of METTL1. However, whether METTL1 gene polymorphisms confer susceptibility to hepatoblastoma has not been reported. This study aimed to identify causal relationships between genetic variants of this gene and susceptibility to hepatoblastoma.

MATERIALS AND METHODS

Using the TaqMan assay, we genotyped three METTL1 polymorphisms (rs2291617 G > T, rs10877013 T > C, rs10877012 T > G) in germline DNA samples from 1759 Chinese children of Han ethnicity (313 cases vs. 1446 controls).

RESULTS

None of these polymorphisms were associated with hepatoblastoma risk. However, combination analysis showed that children with 1 to 3 risk genotypes were associated with increased hepatoblastoma risk (adjusted odds ratio = 1.47, 95% confidence interval  1.07-2.02; P = 0.018). Stratified analyses revealed significant effects of combined polymorphisms mainly among young children (< 17 months of age), boys, and those with advanced hepatoblastoma.

CONCLUSION

We identified some potential functional METTL1 gene polymorphisms that work together to increase the risk of hepatoblastoma among Chinese Han children; single polymorphism showed only weak effects. These METTL1 polymorphisms may be promising biomarkers for screening high-risk individuals for hepatoblastoma. These findings are inspiring and deserve to be validated among individuals of different ethnicities.

A novel prognostic 7-methylguanosine signature reflects immune microenvironment and alternative splicing in glioma based on multi-omics analysis

Glioma is the most common type of central nervous system tumor with increasing incidence. 7-methylguanosine (m7G) is one of the diverse RNA modifications that is known to regulate RNA metabolism and its dysregulation was associated with various cancers. However, the expression pattern of m7G regulators and their roles in regulating tumor immune microenvironments (TIMEs) as well as alternative splicing events (ASEs) in glioma has not been reported. In this study, we showed that m7G regulators displayed a close correlation with each other and most of them were differentially expressed between normal and glioma tissues. Two m7G signatures were then constructed to predict the overall survival of both GBM and LGG patients with moderate predictive performance. The risk score calculated from the regression coefficient and expression level of signature genes was proved to be an independent prognostic factor for patients with LGG, thus, a nomogram was established on the risk score and other independent clinical parameters to predict the survival probability of LGG patients. We also investigated the correlation of m7G signatures with TIMEs in terms of immune scores, expression levels of HLA and immune checkpoint genes, immune cell composition, and immune-related functions. While exploring the correlation between signature genes and the ASEs in glioma, we found that EIF4E1B was a key regulator and might play dual roles depending on glioma grade. By incorporating spatial transcriptomic data, we found a cluster of cells featured by high expression of PTN exhibited the highest m7G score and may communicate with adjacent cancer cells via SPP1 and PTN signaling pathways. In conclusion, our work brought novel insights into the roles of m7G modification in TIMEs and ASEs in glioma, suggesting that evaluation of m7G in glioma could predict prognosis. Moreover, our data suggested that blocking SPP1 and PTN pathways might be a strategy for combating glioma.

Let-7 as a Promising Target in Aging and Aging-Related Diseases: A Promise or a Pledge

The abnormal regulation and expression of microRNA (miRNA) are closely related to the aging process and the occurrence and development of aging-related diseases. Lethal-7 (let-7) was discovered in Caenorhabditis elegans (C. elegans) and plays an important role in development by regulating cell fate regulators. Accumulating evidence has shown that let-7 is elevated in aging tissues and participates in multiple pathways that regulate the aging process, including affecting tissue stem cell function, body metabolism, and various aging-related diseases (ARDs). Moreover, recent studies have found that let-7 plays an important role in the senescence of B cells, suggesting that let-7 may also participate in the aging process by regulating immune function. Therefore, these studies show the diversity and complexity of let-7 expression and regulatory functions during aging. In this review, we provide a detailed overview of let-7 expression regulation as well as its role in different tissue aging and aging-related diseases, which may provide new ideas for enriching the complex expression regulation mechanism and pathobiological function of let-7 in aging and related diseases and ultimately provide help for the development of new therapeutic strategies.

Change of Heart: the Epitranscriptome of Small Non-coding RNAs in Heart Failure

Purpose of Review

Small non-coding RNAs regulate gene expression and are highly implicated in heart failure. Recently, an additional level of post-transcriptional regulation has been identified, referred to as the epitranscriptome, which encompasses the body of post-transcriptional modifications that are placed on RNA molecules. In this review, we summarize the current knowledge on the small non-coding RNA epitranscriptome in heart failure.

Recent Findings

With the rise of new methods to study RNA modifications, epitranscriptome research has begun to take flight. Over the past 3 years, the number of publications on the epitranscriptome in heart failure has significantly increased, and we expect many more highly relevant publications to come out over the next few years.

Summary

Currently, at least six modifications on small non-coding RNAs have been investigated in heart failure-relevant studies, namely N6-adenosine, N5-cytosine and N7-guanosine methylation, 2’-O-ribose-methylation, adenosine-to-inosine editing, and isomiRs. Their potential role in heart failure is discussed.

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.

N7-methylguanosine-related lncRNAs: Predicting the prognosis and diagnosis of colorectal cancer in the cold and hot tumors

Background: 7-Methylguanosine(m7G) contributes greatly to its pathogenesis and progression in colorectal cancer. We proposed building a prognostic model of m7G-related LncRNAs. Our prognostic model was used to identify differences between hot and cold tumors.

Methods: The study included 647 colorectal cancer patients (51 cancer-free patients and 647 cancer patients) from The Cancer Genome Atlas (TCGA). We identified m7G-related prognostic lncRNAs by employing the univariate Cox regression method. Assessments were conducted using univariate Cox regression, multivariate Cox regression, receiver operating characteristics (ROC), nomogram, calibration curves, and Kaplan-Meier analysis. All of these procedures were used with the aim of confirming the validity and stability of the model. Besides these two analyses, we also conducted half-maximal inhibitory concentration (IC50), immune analysis, principal component analysis (PCA), and gene set enrichment analysis (GSEA). The entire set of m7G-related (lncRNAs) with respect to cold and hot tumors has been divided into two clusters for further discussion of immunotherapy.

Results: The risk model was constructed with 17 m7G-related lncRNAs. A good correlation was found between the calibration plots and the prognosis prediction in the model. By assessing IC50 in a significant way across risk groups, systemic treatment can be guided. By using clusters, it may be possible to distinguish hot and cold tumors effectively and to aid in specific therapeutic interventions. Cluster 1 was identified as having the highest response to immunotherapy drugs and thus was identified as the hot tumor.

Conclusion: This study shows that 17 m7G-related lncRNA can be used in clinical settings to predict prognosis and use them to determine whether a tumor is cold or hot in colorectal cancer and improve the individualization of treatment.

Comprehensive analysis of the prognosis and immune infiltration landscape of RNA methylation-related subtypes in pancreatic cancer

Background

RNA methylation refers to a form of methyl modification in RNA that modulates various epigenetic alterations. Mounting studies have focused on its potential mechanisms in cancer initiation and progression. However, the prognostic value and potential role of RNA methylation in the immune microenvironment of pancreatic cancer remain unclear.

Methods

Comprehensive bioinformatics analysis was performed to illuminate the expression profiles of RNA methylation modulators. In addition, the ConsensusClusterPlus algorithm was utilized to identify two remarkably different subtypes, and a feasible risk stratification method was established to accurately estimate prognosis. In addition, we validated our signature at the cytology and histology levels and conducted functional experiments to explore the biological functions of our key genes.

Results

Two subtypes with remarkable survival differences were identified by the consensus clustering algorithm. Cluster 2 tended to have higher expression levels of RNA methylation regulators and to be the high RNA methylation group. In addition, cluster 1 exhibited a significantly higher abundance of almost all immune cells and increased immune checkpoint expression compared to cluster 2. Chemotherapeutic sensitivity analysis indicated that there were significant differences in the sensitivity of four of the six drugs between different subgroups. Mutation investigation revealed a higher mutation burden and a higher number of mutations in cluster 2. An accurate and feasible risk stratification method was established based on the expression of key genes of each subtype. Patients with low risk scores exhibited longer survival times in one training (TCGA) and two validation cohorts (ICGC, GSE57495), with p values of 0.001, 0.0081, and 0.0042, respectively. In addition, our signature was further validated in a cohort from Fudan University Shanghai Cancer Center. The low-risk group exhibited higher immune cell abundance and immune checkpoint levels than the high-risk group. The characteristics of the low-risk group were consistent with those of cluster 1: higher stromal score, estimate score, and immune score and lower tumor purity. Additionally, cell function investigations suggested that knockdown of CDKN3 remarkably inhibited the proliferation and migration of pancreatic cancer cells.

Conclusions

RNA methylation has a close correlation with prognosis, immune infiltration and therapy in pancreatic cancer. Our subtypes and risk stratification method can accurately predict prognosis and the efficacy of immune therapy and chemotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09863-z.