Recruitment of the m6A/m6Am demethylase FTO to target RNAs by the telomeric zinc finger protein ZBTB48.

BACKGROUND: N6-methyladenosine (m6A), the most abundant internal modification on eukaryotic mRNA, and N6, 2'-O-dimethyladenosine (m6Am), are epitranscriptomic marks that function in multiple aspects of posttranscriptional regulation. Fat mass and obesity-associated protein (FTO) can remove both m6A and m6Am; however, little is known about how FTO achieves its substrate selectivity. RESULTS: Here, we demonstrate that ZBTB48, a C2H2-zinc finger protein that functions in telomere maintenance, associates with FTO and binds both mRNA and the telomere-associated regulatory RNA TERRA to regulate the functional interactions of FTO with target transcripts. Specifically, depletion of ZBTB48 affects targeting of FTO to sites of m6A/m6Am modification, changes cellular m6A/m6Am levels and, consequently, alters decay rates of target RNAs. ZBTB48 ablation also accelerates growth of HCT-116 colorectal cancer cells and modulates FTO-dependent regulation of Metastasis-associated protein 1 (MTA1) transcripts by controlling the binding to MTA1 mRNA of the m6A reader IGF2BP2. CONCLUSIONS: Our findings thus uncover a previously unknown mechanism of posttranscriptional regulation in which ZBTB48 co-ordinates RNA-binding of the m6A/m6Am demethylase FTO to control expression of its target RNAs.

A novel m6A/m5C/m1A/m7G-related classification and risk signature predicts prognosis and reveals immunotherapy inclination in gastric cancer.

Background: Gastric cancer (GC) is characterized by high morbidity and mortality rates, and the prognosis is not optimistic. Therefore, the search for new biomarkers is crucial. Methylation modifications in RNA modifications play a crucial role in tumors. However, the role of methylation modification of integrated m6A/m5C/m1A/m7G, in GC and its related analysis have not been reported. It still needs to be studied in depth. Our study aims to deepen our understanding of m6A/m5C/m1A/m7G methylation and potentially provide new strategies for GC treatment. Methods: We used TCGA-STAD (The Cancer Genome Atlas-Stomach Adenocarcinoma) as a training set and GSE84433 as a validation set to analyze and determine potential associations between m6A/m5C/m1A/m7G-related genes and clinical risk of GC. In addition, we explored the prognostic value and potential biological mechanisms of m6A/m5C/m1A/m7G-related genes in GC through consistent clustering, differential expression gene identification, enrichment analysis, and immune infiltration analysis. Finally, we constructed m6A/m5C/m1A/m7G-related risk signature (MRRS) to evaluate the correlation between risk grade and survival prognosis, drug sensitivity, and immune infiltration, and validated the validity by immunohistochemical staining. Results: We identified subgroups of C1, C2, and C3 patients by consensus clustering using data from 45 m6A/m5C/m1A/m7G-related genes. The three groups showed significant differences in survival, immune scores, and immune cell infiltration. We then constructed MRRS using least absolute shrinkage and selection operator (LASSO) regression analysis, including SLC5A6, FKBP10, GPC3, and GGH, which could accurately differentiate between high-/low-risk populations. Its accuracy was further validated in the validation set and immunohistochemical staining. These results suggest that m6A/m5C/m1A/m7G are closely related to the GC tumor immune microenvironment, and MRRS has good performance in predicting the survival of GC patients. Conclusions: In this study, we highlighted the association of m6A/m5C/m1A/m7G subtypes with changes in the GC immunotumor microenvironment. We constructed and validated MRRS, which is valuable in predicting survival, immune infiltration and drug sensitivity in GC patients. This helps to deepen our understanding of m6A/m5C/m1A/m7G methylation and potentially provides new strategies for GC treatment.

Cap-related modifications of RNA regulate binding to IFIT proteins.

All cells in our body are equipped with receptors to recognize pathogens and trigger a rapid defense response. As a result, foreign molecules are blocked, and cells are alerted to the danger. Among the many molecules produced in response to viral infection are interferon-induced proteins with tetratricopeptide repeats (IFITs). Their role is to recognize foreign mRNA and eliminate it from the translational pool of transcripts. In the present study, we used biophysical methods to characterize the interactions between the IFIT1 protein and its partners IFIT2 and IFIT3. IFIT1 interacts with IFIT3 with nanomolar binding affinity, which did not change significantly in the presence of the preformed IFIT2/3 complex. The interactions between IFIT2 and IFIT3 and IFIT1 and IFIT2 were one order of magnitude weaker. We also present kinetic data of the interactions between the IFIT protein complex and short RNA bearing various modifications at the 5' end. We show kinetic parameters for interaction between the IFIT complex and RNA with m6Am modification. The results show that the cap-adjacent m6Am modification is a stronger signature than cap1 alone. It blocks the formation of a complex between IFIT proteins and m7Gpppm6Am-RNA much more effectively than other cap modifications. In contrast, m6A in the 5'UTR is not recognized by IFIT proteins and does not contribute to translation repression by IFIT proteins. The data obtained are important for understanding the regulation of expression of genetic information. They indicate that 2'-O and m6Am modifications modulate the availability of mRNA molecules for proteins of innate immune response.

Development of m6A/m5C/m1A regulated lncRNA signature for prognostic prediction, personalized immune intervention and drug selection in LUAD.

Research indicates that there are links between m6A, m5C and m1A modifications and the development of different types of tumours. However, it is not yet clear if these modifications are involved in the prognosis of LUAD. The TCGA-LUAD dataset was used as for signature training, while the validation cohort was created by amalgamating publicly accessible GEO datasets including GSE29013, GSE30219, GSE31210, GSE37745 and GSE50081. The study focused on 33 genes that are regulated by m6A, m5C or m1A (mRG), which were used to form mRGs clusters and clusters of mRG differentially expressed genes clusters (mRG-DEG clusters). Our subsequent LASSO regression analysis trained the signature of m6A/m5C/m1A-related lncRNA (mRLncSig) using lncRNAs that exhibited differential expression among mRG-DEG clusters and had prognostic value. The model's accuracy underwent validation via Kaplan-Meier analysis, Cox regression, ROC analysis, tAUC evaluation, PCA examination and nomogram predictor validation. In evaluating the immunotherapeutic potential of the signature, we employed multiple bioinformatics algorithms and concepts through various analyses. These included seven newly developed immunoinformatic algorithms, as well as evaluations of TMB, TIDE and immune checkpoints. Additionally, we identified and validated promising agents that target the high-risk mRLncSig in LUAD. To validate the real-world expression pattern of mRLncSig, real-time PCR was carried out on human LUAD tissues. The signature's ability to perform in pan-cancer settings was also evaluated. The study created a 10-lncRNA signature, mRLncSig, which was validated to have prognostic power in the validation cohort. Real-time PCR was applied to verify the actual manifestation of each gene in the signature in the real world. Our immunotherapy analysis revealed an association between mRLncSig and immune status. mRLncSig was found to be closely linked to several checkpoints, such as IL10, IL2, CD40LG, SELP, BTLA and CD28, which could be appropriate immunotherapy targets for LUAD. Among the high-risk patients, our study identified 12 candidate drugs and verified gemcitabine as the most significant one that could target our signature and be effective in treating LUAD. Additionally, we discovered that some of the lncRNAs in mRLncSig could play a crucial role in certain cancer types, and thus, may require further attention in future studies. According to the findings of this study, the use of mRLncSig has the potential to aid in forecasting the prognosis of LUAD and could serve as a potential target for immunotherapy. Moreover, our signature may assist in identifying targets and therapeutic agents more effectively.

Regulation of m6Am RNA modification and its implications in human diseases.

N 6,2'-O-dimethyladenosine (m6Am) is a prevalent modification frequently found at the 5' cap-adjacent adenosine of messenger RNAs (mRNAs) and small nuclear RNAs (snRNAs) and the internal adenosine of snRNAs. This dynamic and reversible modification is under the regulation of methyltransferases phosphorylated CTD interacting factor 1 and methyltransferase-like protein 4, along with the demethylase fat mass and obesity-associated protein. m6Am RNA modification plays a crucial role in the regulation of pre-mRNA splicing, mRNA stability, and translation, thereby influencing gene expression. In recent years, there has been growing interest in exploring the functions of m6Am and its relevance to human diseases. In this review, we provide a comprehensive overview of the current knowledge concerning m6Am, with a focus on m6Am-modifying enzymes, sequencing approaches for its detection, and its impacts on pre-mRNA splicing, mRNA stability, and translation regulation. Furthermore, we highlight the roles of m6Am in the context of obesity, viral infections, and cancers, unravelling its underlying regulatory mechanisms.

Epitranscriptomic regulation in fasting hearts: implications for cardiac health.

Cardiac tolerance to ischaemia can be increased by dietary interventions such as fasting, which is associated with significant changes in myocardial gene expression. Among the possible mechanisms of how gene expression may be altered are epigenetic modifications of RNA - epitranscriptomics. N6-methyladenosine (m6A) and N6,2'-O-dimethyladenosine (m6Am) are two of the most prevalent modifications in mRNA. These methylations are reversible and regulated by proteins called writers, erasers, readers, and m6A-repelled proteins. We analysed 33 of these epitranscriptomic regulators in rat hearts after cardioprotective 3-day fasting using RT-qPCR, Western blot, and targeted proteomic analysis. We found that the most of these regulators were changed on mRNA or protein levels in fasting hearts, including up-regulation of both demethylases - FTO and ALKBH5. In accordance, decreased methylation (m6A+m6Am) levels were detected in cardiac total RNA after fasting. We also identified altered methylation levels in Nox4 and Hdac1 transcripts, both of which play a role in the cytoprotective action of ketone bodies produced during fasting. Furthermore, we investigated the impact of inhibiting demethylases ALKBH5 and FTO in adult rat primary cardiomyocytes (AVCMs). Our findings indicate that inhibiting these demethylases reduced the hypoxic tolerance of AVCMs isolated from fasting rats. This study showed that the complex epitranscriptomic machinery around m6A and m6Am modifications is regulated in the fasting hearts and might play an important role in cardiac adaptation to fasting, a well-known cardioprotective intervention.

Construction of a prognostic model for lung adenocarcinoma based on m6A/m5C/m1A genes.

BACKGROUND: Developing a prognostic model for lung adenocarcinoma (LUAD) that utilizes m6A/m5C/m1A genes holds immense importance in providing precise prognosis predictions for individuals. METHODS: This study mined m6A/m5C/m1A-related differential genes in LUAD based on public databases, identified LUAD tumor subtypes based on these genes, and further built a risk prognostic model grounded in differential genes between subtypes. The immune status between high- and low-risk groups was investigated, and the distribution of feature genes in tumor immune cells was analyzed using single-cell analysis. Based on the expression levels of feature genes, a projection of chemotherapeutic and targeted drugs was made for individuals identified as high-risk. Ultimately, cell experiments were further verified. RESULTS: The 6-gene risk prognosis model based on differential genes between tumor subtypes had good predictive performance. Individuals classified as low-risk exhibited a higher (P < 0.05) abundance of infiltrating immune cells. Feature genes were mainly distributed in tumor immune cells like CD4+T cells, CD8+T cells, and regulatory T cells. Four drugs with relatively low IC50 values were found in the high-risk group: Elesclomol, Pyrimethamine, Saracatinib, and Temsirolimus. In addition, four drugs with significant positive correlation (P < 0.001) between IC50 values and feature gene expression were found, including Alectinib, Estramustine, Brigatinib, and Elesclomol. The low expression of key gene NTSR1 reduced the IC50 value of irinotecan. CONCLUSION: Based on the m6A/m5C/m1A-related genes in LUAD, LUAD patients were divided into 2 subtypes, and a m6A/m5C/m1A-related LUAD prognostic model was constructed to provide a reference for the prognosis prediction of LUAD.

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.

EMDL_m6Am: identifying N6,2'-O-dimethyladenosine sites based on stacking ensemble deep learning.

BACKGROUND: N6, 2'-O-dimethyladenosine (m6Am) is an abundant RNA methylation modification on vertebrate mRNAs and is present in the transcription initiation region of mRNAs. It has recently been experimentally shown to be associated with several human disorders, including obesity genes, and stomach cancer, among others. As a result, N6,2'-O-dimethyladenosine (m6Am) site will play a crucial part in the regulation of RNA if it can be correctly identified. RESULTS: This study proposes a novel deep learning-based m6Am prediction model, EMDL_m6Am, which employs one-hot encoding to expressthe feature map of the RNA sequence and recognizes m6Am sites by integrating different CNN models via stacking. Including DenseNet, Inflated Convolutional Network (DCNN) and Deep Multiscale Residual Network (MSRN), the sensitivity (Sn), specificity (Sp), accuracy (ACC), Mathews correlation coefficient (MCC) and area under the curve (AUC) of our model on the training data set reach 86.62%, 88.94%, 87.78%, 0.7590 and 0.8778, respectively, and the prediction results on the independent test set are as high as 82.25%, 79.72%, 80.98%, 0.6199, and 0.8211. CONCLUSIONS: In conclusion, the experimental results demonstrated that EMDL_m6Am greatly improved the predictive performance of the m6Am sites and could provide a valuable reference for the next part of the study. The source code and experimental data are available at: https://github.com/13133989982/EMDL-m6Am .

A novel m6A/m5C/m1A score signature to evaluate prognosis and its immunotherapy value in colon cancer patients.

BACKGROUND: Colon cancer features strong heterogeneity and invasiveness, with high incidence and mortality rates. Recently, RNA modifications involving m6A, m5C, and m1A play a vital part in tumorigenesis and immune cell infiltration. However, integrated analysis among various RNA modifications in colon cancer has not been performed. METHODS: RNA-seq profiling, clinical data and mutation data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus. We first explored the mutation status and expression levels of m6A/m5C/m1A regulators in colon cancer. Then, different m6A/m5C/m1A clusters and gene clusters were identified by consensus clustering analysis. We further constructed and validated a scoring system, which could be utilized to accurately assess the risk of individuals and guide personalized immunotherapy. Finally, m6A/m5C/m1A regulators were validated by immunohistochemical staining and RT-qPCR. RESULTS: In our study, three m6A/m5C/m1A clusters and gene clusters were identified. Most importantly, we constructed a m6A/m5C/m1A scoring system to assess the clinical risk of the individuals. Besides, the prognostic value of the score was validated with three independent cohorts. Moreover, the level of the immunophenoscore of the low m6A/m5C/m1A score group increased significantly with CTLA-4/PD-1 immunotherapy. Finally, we validated that the mRNA and protein expression of VIRMA and DNMT3B increased in colon cancer tissues. CONCLUSIONS: We constructed and validated a stable and powerful m6A/m5C/m1A score signature to assess the survival outcomes and immune infiltration characteristics of colon cancer patients, which further guides optimization of personalized treatment, making it valuable for clinical translation and implementation.

The role of m6A and m6Am RNA modifications in the pathogenesis of diabetes mellitus.

The rapidly developing research field of epitranscriptomics has recently emerged into the spotlight of researchers due to its vast regulatory effects on gene expression and thereby cellular physiology and pathophysiology. N6-methyladenosine (m6A) and N6,2'-O-dimethyladenosine (m6Am) are among the most prevalent and well-characterized modified nucleosides in eukaryotic RNA. Both of these modifications are dynamically regulated by a complex set of epitranscriptomic regulators called writers, readers, and erasers. Altered levels of m6A and also several regulatory proteins were already associated with diabetic tissues. This review summarizes the current knowledge and gaps about m6A and m6Am modifications and their respective regulators in the pathophysiology of diabetes mellitus. It focuses mainly on the more prevalent type 2 diabetes mellitus (T2DM) and its treatment by metformin, the first-line antidiabetic agent. A better understanding of epitranscriptomic modifications in this highly prevalent disease deserves further investigation and might reveal clinically relevant discoveries in the future.

RNA modification m6Am: the role in cardiac biology.

Epitranscriptomic modifications have recently emerged into the spotlight of researchers due to their vast regulatory effects on gene expression and thereby cellular physiology and pathophysiology. N6,2'-O-dimethyladenosine (m6Am) is one of the most prevalent chemical marks on RNA and is dynamically regulated by writers (PCIF1, METTL4) and erasers (FTO). The presence or absence of m6Am in RNA affects mRNA stability, regulates transcription, and modulates pre-mRNA splicing. Nevertheless, its functions in the heart are poorly known. This review summarizes the current knowledge and gaps about m6Am modification and its regulators in cardiac biology. It also points out technical challenges and lists the currently available techniques to measure m6Am. A better understanding of epitranscriptomic modifications is needed to improve our knowledge of the molecular regulations in the heart which may lead to novel cardioprotective strategies.

m6Aminer: Predicting the m6Am Sites on mRNA by Fusing Multiple Sequence-Derived Features into a CatBoost-Based Classifier.

As one of the most important post-transcriptional modifications, m6Am plays a fairly important role in conferring mRNA stability and in the progression of cancers. The accurate identification of the m6Am sites is critical for explaining its biological significance and developing its application in the medical field. However, conventional experimental approaches are time-consuming and expensive, making them unsuitable for the large-scale identification of the m6Am sites. To address this challenge, we exploit a CatBoost-based method, m6Aminer, to identify the m6Am sites on mRNA. For feature extraction, nine different feature-encoding schemes (pseudo electron-ion interaction potential, hash decimal conversion method, dinucleotide binary encoding, nucleotide chemical properties, pseudo k-tuple composition, dinucleotide numerical mapping, K monomeric units, series correlation pseudo trinucleotide composition, and K-spaced nucleotide pair frequency) were utilized to form the initial feature space. To obtain the optimized feature subset, the ExtraTreesClassifier algorithm was adopted to perform feature importance ranking, and the top 300 features were selected as the optimal feature subset. With different performance assessment methods, 10-fold cross-validation and independent test, m6Aminer achieved average AUC of 0.913 and 0.754, demonstrating a competitive performance with the state-of-the-art models m6AmPred (0.905 and 0.735) and DLm6Am (0.897 and 0.730). The prediction model developed in this study can be used to identify the m6Am sites in the whole transcriptome, laying a foundation for the functional research of m6Am.

Breast cancer prognosis and immunological characteristics are predicted using the m6A/m5C/m1A/m7G-related long noncoding RNA signature.

According to statistics, breast cancer (BC) has replaced lung cancer as the most common cancer in the world. Therefore, specific detection markers and therapeutic targets need to be explored as a way to improve the survival rate of BC patients. We first identified m6A/m5C/m1A/m7G-related long noncoding RNAs (MRlncRNAs) and developed a model of 16 MRlncRNAs. Kaplan-Meier survival analysis was applied to assess the prognostic power of the model, while univariate Cox analysis and multivariate Cox analysis were used to assess the prognostic value of the constructed model. Then, we constructed a nomogram to illustrate whether the predicted results were in good agreement with the actual outcomes. We tried to use the model to distinguish the difference in sensitivity to immunotherapy between the two groups and performed some analyses such as immune infiltration analysis, ssGSEA and IC50 prediction. To explore the novel anti-tumor drug response, we reclassified the patients into two clusters. Next, we assessed their response to clinical treatment by the R package pRRophetic, which is determined by the IC50 of each BC patient. We finally identified 11 MRlncRNAs and based on them, a risk model was constructed. In this model, we found good agreement between calibration plots and prognosis prediction. The AUC of ROC curves was 0.751, 0.734, and 0.769 for 1-year, 2-year, and 3-year overall survival (OS), respectively. The results showed that the IC50 was significantly different between the risk groups, suggesting that the risk groups can be used as a guide for systemic treatment. We regrouped patients into two clusters based on 11 MRlncRNAs expression. Next, we conducted immune scores for 2 clusters, which showed that cluster 1 had higher stromal scores, immune scores and higher estimated (microenvironment) scores, demonstrating that TME of cluster 1 was different from cluster 2. The results of this study support that MRlncRNAs can predict tumor prognosis and help differentiate patients with different sensitivities to immunotherapy as a basis for individualized treatment for BC patients.

The abdominal aortic aneurysm-related disease model based on machine learning predicts immunity and m1A/m5C/m6A/m7G epigenetic regulation.

Introduction: Abdominal aortic aneurysms (AAA) are among the most lethal non-cancerous diseases. A comprehensive analysis of the AAA-related disease model has yet to be conducted. Methods: Weighted correlation network analysis (WGCNA) was performed for the AAA-related genes. Machine learning random forest and LASSO regression analysis were performed to develop the AAA-related score. Immune characteristics and epigenetic characteristics of the AAA-related score were explored. Results: Our study developed a reliable AAA-related disease model for predicting immunity and m1A/m5C/m6A/m7G epigenetic regulation. Discussion: The pathogenic roles of four model genes, UBE2K, TMEM230, VAMP7, and PUM2, in AAA, need further validation by in vitro and in vivo experiments.

The catalytic-dead Pcif1 regulates gene expression and fertility in Drosophila.

Eukaryotic mRNAs are modified at the 5' end with a methylated guanosine (m7G) that is attached to the transcription start site (TSS) nucleotide. The TSS nucleotide is 2'-O-methylated (Nm) by CMTR1 in organisms ranging from insects to human. In mammals, the TSS adenosine can be further N 6 -methylated by RNA polymerase II phosphorylated CTD-interacting factor 1 (PCIF1) to create m6Am. Curiously, the fly ortholog of mammalian PCIF1 is demonstrated to be catalytic-dead, and its functions are not known. Here, we show that Pcif1 mutant flies display a reduced fertility which is particularly marked in females. Deep sequencing analysis of Pcif1 mutant ovaries revealed transcriptome changes with a notable increase in expression of genes belonging to the mitochondrial ATP synthetase complex. Furthermore, the Pcif1 protein is distributed along euchromatic regions of polytene chromosomes, and the Pcif1 mutation behaved as a modifier of position-effect-variegation (PEV) suppressing the heterochromatin-dependent silencing of the white gene. Similar or stronger changes in the transcriptome and PEV phenotype were observed in flies that expressed a cytosolic version of Pcif1. These results point to a nuclear cotranscriptional gene regulatory role for the catalytic-dead fly Pcif1 that is probably based on its conserved ability to interact with the RNA polymerase II carboxy-terminal domain.

RNA m6A methylation across the transcriptome.

Since the early days of foundational studies of nucleic acids, many chemical moieties have been discovered to decorate RNA and DNA in diverse organisms. In mammalian cells, one of these chemical modifications, N6-methyl adenosine (m6A), is unique in a way that it is highly abundant not only on RNA polymerase II (RNAPII) transcribed, protein-coding transcripts but also on non-coding RNAs, such as ribosomal RNAs and snRNAs, mediated by distinct, evolutionarily conserved enzymes. Here, we review RNA m6A modification in the light of the recent appreciation of nuclear roles for m6A in regulating chromatin states and gene expression, as well as the recent discoveries of the evolutionarily conserved methyltransferases, which catalyze methylation of adenosine on diverse sets of RNAs. Considering that the substrates of these enzymes are involved in many important biological processes, this modification warrants further research to understand the molecular mechanisms and functions of m6A in health and disease.

Regulation of Gene Expression by m6Am RNA Modification.

The field of RNA modification, also referred to as "epitranscriptomics," is gaining more and more interest from the scientific community. More than 160 chemical modifications have been identified in RNA molecules, but the functional significance of most of them still needs to be clarified. In this review, we discuss the role of N6,2'-O-dimethyladenosine (m6Am) in gene expression regulation. m6Am is present in the first transcribed nucleotide close to the cap in many mRNAs and snRNAs in mammals and as internal modification in the snRNA U2. The writer and eraser proteins for these modifications have been recently identified and their deletions have been utilized to understand their contributions in gene expression regulation. While the role of U2 snRNA-m6Am in splicing regulation has been reported by different independent studies, conflicting data were found for the role of cap-associated m6Am in mRNA stability and translation. However, despite the open debate on the role of m6Am in mRNA expression, the modulation of regulators produced promising results in cancer cells. We believe that the investigation on m6Am will continue to yield relevant results in the future.

Enhancer RNA promotes resistance to radiotherapy in bone-metastatic prostate cancer by m6A modification.

Rationale: Prostate cancer metastasizes to the bone with the highest frequency and exhibits high resistance to 177Lu-prostate-specific membrane antigen (PSMA) radioligand therapy. Little is known about bone metastatic prostate cancer (mPCa) resistance to radiation. Methods: We filtered the metastatic eRNA using RNA-seq, MeRIP-seq, RT-qPCR and bioinformation. Western blot, RT-qPCR, CLIP, co-IP and RNA pull-down assays were used for RNA/protein interaction, RNA or protein expression examination. MTS assay was used to determine cell viability in vitro, xenograft assay was used to examine the tumor growth in mice. Results: In this study, we screened and identified bone-specific N6 adenosine methylation (m6A) on enhancer RNA (eRNA) that played a post-transcriptional functional role in bone mPCa and was correlated with radiotherapy (RT) resistance. Further data demonstrated that RNA-binding protein KHSRP recognized both m6A at eRNA and m6Am at 5'-UTR of mRNA to block RNA degradation from exoribonuclease XRN2. Depletion of the MLXIPe/KHSRP/PSMD9 regulatory complex inhibited tumor growth and RT sensitization of bone mPCa xenograft in vitro and in vivo. Conclusions: Our findings indicate that a bone-specific m6A-modified eRNA plays a vital role in regulating mPCa progression and RT resistance and might be a novel specific predictor for cancer RT.

PCIF1-mediated deposition of 5'-cap N6,2'-O-dimethyladenosine in ACE2 and TMPRSS2 mRNA regulates susceptibility to SARS-CoV-2 infection.

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to be a major health problem worldwide. Due to the fast emergence of SARS-CoV-2 variants, understanding the molecular mechanisms of viral pathogenesis and developing novel inhibitors are essential and urgent. Here, we investigated the potential roles of N6,2'-O-dimethyladenosine (m6Am), one of the most abundant modifications of eukaryotic messenger ribonucleic acid (mRNAs), in SARS-CoV-2 infection of human cells. Using genome-wide m6Am-exo-seq, RNA sequencing analysis, and Clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 genome editing, we demonstrate that phosphorylated C-terminal domain (CTD)-interacting factor 1 (PCIF1), a cap-specific adenine N6-methyltransferase, plays a major role in facilitating infection of primary human lung epithelial cells and cell lines by SARS-CoV-2, variants of concern, and other coronaviruses. We show that PCIF1 promotes infection by sustaining expression of the coronavirus receptors angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) via m6Am-dependent mRNA stabilization. In PCIF1-depleted cells, both ACE2/TMPRSS2 expression and viral infection are rescued by re-expression of wild-type, but not catalytically inactive, PCIF1. These findings suggest a role for PCIF1 and cap m6Am in regulating SARS-CoV-2 susceptibility and identify a potential therapeutic target for prevention of infection.