m6A RNA Methylation Regulators Research Articles

The predictive significance of a 5-m6A RNA methylation regulator signature in colorectal cancer

Colorectal cancer attacks the colon or rectum, with increasing morbidity and mortality globally. The RNA modification 6-methyladenine (m6A) is related to RNA modifications, playing a critical role in colorectal cancer. We aimed to identify prognostic signatures for colorectal cancer using risk prediction algorithms, and to validate these signatures using independent datasets and clinical samples. In this study, 175 cases in GSE17536 were assigned into two clusters using consistent clustering and PCA analysis. A multivariate Cox risk regression model revealed that among 21 m6A RNA methylation regulators, RBM15B, FTO, IGF2BP2, ZCCHC4, and KIAA1429 were remarkably associated with colorectal cancer patients' overall survival (OS); however, Kaplan–Meier (KM) survival assessment showed no significant association between these five regulators and colorectal cancer patients' prognosis. A 5-m6A RNA methylation regulator signature was established using LASSO algorithm. Risk scores of cases in GSE17536, GSE17537 and GSE75500 were calculated, and lower risk scores were associated with better DSS/OS. receiver operating characteristic (ROC) curve and the nomogram revealed the satisfactory predictive efficiency of the risk score model. The risk score could distinguish cases in Cluster1 and Cluster2 and normal and tumor tissues based on GSE37182. The prognostic variables for colorectal cancer patients were assessed using both univariate and multivariate Cox's proportional hazard regression models, which revealed that the stage and risk score were significant risk factors. In this study, a comprehensive set of integrative bioinformatics analyses was conducted to investigate the prognostic and diagnostic potential of a panel of 5 m6A RNA methylated regulators in colorectal cancer patients. The conducted studies included the use of several statistical methods, such as the LASSO regression model, KM survival evaluation, ROC curve, and univariate and multivariate Cox's proportional hazard regression analyses. The findings from these analyses collectively established the prognostic marker, highlighting its significance in predicting patient outcomes and diagnosing colorectal cancer.

Genes associated with N6-methyladenosine regulators provide insight into the prognosis and immune response to renal clear cell carcinoma.

As one of the most common messenger ribonucleic acid modifications in eukaryotic organisms, N6-methyladenosine (m6A) is involved in a wide variety of biological functions. The imbalance of m6A RNA modification may be linked to cancer and other disorders, according to a growing body of studies. Its effects on clear cell renal cell carcinoma (KIRC) have not been well discussed, though. Here, we acquired the expression patterns of 23 important regulators of m6A RNA modification and assess how they might fare in KIRC. We observed that 17 major m6A RNA modification regulatory factors had a substantial predictive influence on KIRC. Using the "ConsensusCluster" program, we defined two groupings (Cluster 1 and Cluster 2) depending on the expression of the aforementioned 17 key m6A RNA methylation regulators. The Cluster 2 has a less favorable outcome and is strongly related with a lesser immune microenvironment, according to the findings. We also developed a strong risk profile for three m6A RNA modifiers (METTL14, YTHDF1, and LRPPRC) using multivariate Cox regression analysis. According to further research, the aforementioned risk profile could serve as an independent predicting factor for KIRC, and the chemotherapy response sensitivity was analyzed between two risk groups. Moreover, to effectively forecast the future outlook of KIRC clients, we established a novel prognostic approach according to gender, age, histopathological level, clinical stage, and risk score. Finally, the function of hub gene METTL14 was validated by cell proliferation and subcutaneous graft tumor in mice. In conclusion, we discovered that m6A RNA modifiers play an important role in controlling KIRC and created a viable risk profile as a marker of prediction for KIRC clients.

SETD2 controls m6A modification of transcriptome and regulates the molecular oncogenesis of glioma.

SETD2 is known for its epigenetic regulatory function and a frequently mutated gene in multiple cancers. Recently, it has been inferred that SETD2 regulates m6A mRNA methylation (epitranscriptome) via H3K36me3. The m6A RNA methylation is vital for tumor maintenance, self-renewal, and tumorigenesis. RNA modifications are executed by writers, readers, and erasers. m6A modifiers work along with the molecular cues, H3K36me3, laid down by SETD2. A positive correlation observed between SETD2 and RNA modifiers signifies their direct role in epitranscriptomics. Hence, understanding the epitranscriptomics will provide a new facet for molecular oncogenesis. Glioma is a common, malignant grade IV tumor with limited therapeutic alternatives and a poor prognosis. Yet, its function in glioma is not fully defined.Inthe present study, thorough investigations were done in the m6A RNA methylation regulators expression, the molecular pathways leading to tumor progression, and their respective outcomes in SETD2-mediated RNA methylation. In vitro analysis reveals that SETD2 knockdown positively affected the oncogenic properties of the glioma cell line and a global reduction in m6A levels in the transcriptome. The reduction of m6A in the transcriptome can be attributed to the decreased expression of METTL3 and METTL14. Therefore, we conclude that SETD2-mediated m6A modifications are crucial for glioma oncogenesis.

Identification of the relationship between single-cell N6-methyladenosine regulators and the infiltrating immune cells in esophageal carcinoma

BackgroundN6-methyladenosine (m6A) RNA methylation plays a crucial role in important genomic processes in a variety of malignancies. However, the characterization of m6A with infiltrating immune cells in the tumor microenvironment (TME) in esophageal squamous carcinoma (ESCC) remains unknown. MethodsThe single-cell transcriptome data from five ESCC patients in our hospital were analyzed, and TME clusters associated with prognosis and immune checkpoint genes were investigated. Cell isolation and qPCR were conducted to validate the gene characterization in different cells. ResultsAccording to distinct biological processes and marker genes, macrophages, T cells, and B cells clustered into three to four different subgroups. In addition, we demonstrated that m6A RNA methylation regulators were strongly related to the clinical and biological features of ESCC. Analysis of transcriptome data revealed that m6A-mediated TME cell subsets had high predictive value and showed a close relationship with immune checkpoint genes. The validation results from qPCR demonstrated the characteristics of essential genes. CellChat analysis revealed that RNA from TME cells m6A methylation-associated cell subtypes had substantial and diversified interactions with cancer cells. Further investigation revealed that MIF- (CD74+CXCR4) and MIF- (CD74+CD44) ligand-receptor pairings facilitated communication between m6A-associated subtypes of TME cells and cancer cells. ConclusionOverall, our study demonstrated for the first time the function of m6A methylation-mediated intercellular communication in the microenvironment of tumors in controlling tumor development and anti-tumor immune regulation in ESCC.

Expression of m6A RNA Methylation Regulators and Their Clinical Predictive Value in Intrahepatic Cholangiocarcinoma.

N6-methyladenosine (m6A) RNA methylation regulators have been implicated in the carcinogenesis and progress of a variety of cancers. Until now, the effects of them on intrahepatic cholangiocarcinoma (ICC) have been poorly understood. We used the GEO databases to systematically evaluate the expression profiles of 36 m6A RNA methylation regulators in ICC patients and produced a signature to assess its prognostic values. In vitro experiments were implemented to confirm the expression level. Compared to normal intrahepatic bile duct tissues, more than half of these 36 genes showed different levels of expression in ICC tissues. Two groups emerged from the consensus cluster analysis of these 36 genes. The two cluster of patients had significantly different clinical outcomes. In addition, we created a m6A-related prognostic signature that performed exceptionally well in the prognostic categorization of ICC patients, based on the ROC curves, Kaplan-Meier curves, and univariate and multivariate Cox regression analyses. Further research showed that there was a significant association between the m6A-related signature and the manifestations of tumor immune microenvironment in ICC. The expression level and biological effect of METTL16, one of the two m6A RNA methylation regulators incorporated in the signature, were confirmed and explored by using in vitro experiments. This analysis revealed the predictive roles of m6A RNA methylation regulators in ICC.

Mettl3 Mediated m6A Methylation Involved in Epithelial-Mesenchymal Transition by Targeting SOCS3/STAT3/SNAI1 in Cigarette Smoking-Induced COPD.

Persistent inflammation and epithelial-mesenchymal transition are essential pathophysiological processes in chronic obstructive pulmonary disease (COPD) and involve airway remodeling. m6A methylation modification was discovered to play an important role in various diseases. Nevertheless, the regulatory role of m6A methylation has not yet been investigated in cigarette smoking-induced COPD. The study aims to explore the regulatory role of m6A methylation in cigarette smoking-induced COPD. In this study, two Gene Expression Omnibus (GEO) datasets were first utilized to analyze the expression profiles of m6A RNA methylation regulators in COPD. We then established a cell model of COPD by exposing human bronchial epithelial cells (HBECs) to cigarette smoke extract (CSE) in vitro and detected the expression of m6A writer Mettl3 and EMT phenotype markers. RNA interference, cycloleucine, RT-qPCR, western blot, MeRIP-sequencing, and cell migration assay were performed to investigate the potential effect of Mettl3 on the EMT process in CSE-induced HBECs. Our results showed that Mettl3 expression was significantly elevated in cigarette smoking-induced COPD patients and in a cellular model of COPD. Furthermore, Mettl3 silence and cycloleucine treatment inhibited the EMT process of HBECs caused by CSE. Mechanically, Mettl3 silence weakens the m6A methylation of SOCS3 mRNA to enhance the protein expression of SOCS3, inhibiting CSE-induced SOCS3/STAT3/SNAI1 signaling and EMT processes in HBECs. Our study inferred that Mettl3-mediated m6A RNA methylation modification modulates CSE-induced EMT by targeting SOCS3 mRNA and ultimately serves as a crucial regulator in the emergence of COPD. This conclusion reinforces the regulatory role of m6A methylation in COPD.

U-shaped association between serum IGF2BP3 and T2DM: A cross-sectional study in Chinese population.

To clarify the expression of N6-methyladenosine (m6 A) modulators involved in the pathogenesis of type 2 diabetes mellitus (T2DM). We further explored the association of serum insulin-like growth factor 2 mRNA-binding proteins 3 (IGF2BP3) levels and odds of T2DM in a high-risk population. The gene expression data set GSE25724 was obtained from the Gene Expression Omnibus, and a cluster heatmap was generated by using the R package ComplexHeatmap. Differential expression analysis for 13 m6 A RNA methylation regulators between nondiabetic controls and T2DM subjects was performed using an unpaired t test. A cross-sectional design, including 393 subjects (131 patients with newly diagnosed T2DM, 131 age- and sex-matched subjects with prediabetes, and 131 healthy controls), was carried out. The associations between serum IGF2BP3 concentrations and T2DM were modeled by restricted cubic spline and logistic regression models. Two upregulated (IGF2BP2 and IGF2BP3) and 5 downregulated (methyltransferase-like 3 [METTL3], alkylation repair homolog protein 1 [ALKBH1], YTH domain family 2 [YTHDF2], YTHDF3, and heterogeneous nuclear ribonucleoprotein [HNRNPC]) m6 A-related genes were found in islet samples of T2DM patients. A U-shaped association existed between serum IGF2BP3 levels and odds of T2DM according to cubic natural spline analysis models, after adjustment for body mass index, waist circumference, diastolic blood pressure, total cholesterol, and triglyeride. Multivariate logistic regression showed that progressively higher odds of T2DM were observed when serum IGF2BP3 levels were below 0.62 ng/mL (odds ratio 3.03 [95% confidence interval 1.23-7.47]) in model 4. Seven significantly altered m6 A RNA methylation genes were identified in T2DM. There was a U-shaped association between serum IGF2BP3 levels and odds of T2DM in the general Chinese adult population. This study provides important evidence for further examination of the role of m6 A RNA methylation, especially serum IGF2BP3 in T2DM risk assessment.

Thyroid cancer risk prediction model using m6A RNA methylation regulators: integrated bioinformatics analysis and histological validation.

Epigenetic reprogramming has been reported to play a critical role in the progression of thyroid cancer. RNA methylation accounts for more than 60% of all RNA modifications, and N6-methyladenosine (m6A) is the most common modification of RNAs in higher organisms. The purpose of this study was to explore the related modification mode of m6A regulators construction and its evaluation on the clinical prognosis and therapeutic effect of thyroid cancer. The levels of 23 m6A regulators in The Cancer Genome Atlas (TCGA) were analyzed. Differentially expressed genes (DEGs) and survival analysis were performed based on TCGA-THCA clinicopathological and follow-up information, and the mRNA levels of representative genes were verified using clinical thyroid cancer data. In order to detect the effects of m6A regulators and their DEGs, consensus cluster analysis was carried out, and the expression of different m6A scores in Tumor Mutation Burden (TMB) and immune double antibodies (PD-1 antibody and CTLA4 antibody) were evaluated to predict the correlation between m6A score and thyroid cancer tumor immunotherapy response. Different expression patterns of m6A regulatory factors were detected in thyroid cancer tumors and normal tissues, and several prognoses related m6A genes were obtained. Two different m6A modification patterns were determined by consensus cluster analysis. Two different subgroups were established by screening overlapping DEGs between two m6A clusters, with cluster A having the best prognosis. According to the m6A score extracted from DEGs, thyroid cancer patients can be divided into high and low score subgroups. Patients with lower m6A score have longer survival time and better clinical features. The relationship between m6A score and Tumor Mutation Burden (TMB) and its correlation with the expression of PD-1 antibody and CTLA4 antibody proved that m6A score could be used as a potential predictor of the efficacy of immunotherapy in thyroid cancer patients. We screened DEGs from cluster m6A and constructed a highly predictive model with prognostic value by dividing TCGA-THCA into two different clusters and performing m6A score analysis. This study will help clarify the overall impact of m6A modification patterns on thyroid cancer progression and formulate more effective immunotherapy strategies.

Genes related to N6-methyladenosine in the diagnosis and prognosis of idiopathic pulmonary fibrosis.

Introduction: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive pulmonary fibrotic disease with unknown etiology and poor outcomes. It severely affects the quality of life. In this study, we comprehensively analyzed the expression of N6-methyladenosine (m6A) RNA methylation regulators using gene expression data from various tissue sources in IPF patients and healthy volunteers. Methods: The gene expression matrix and clinical characteristics of IPF patients were retrieved from the Gene Expression Omnibus database. A random forest model was used to construct diagnosis signature m6A regulators. Regression analysis and correlation analysis were used to identify prognosis m6A regulators. Consensus cluster analysis was used to construct different m6A prognosis risk groups, then functional enrichment, immune infiltration and drug sensitivity analysis were performed. Result: Five candidate m6A genes from lung tissue were used to predict the incidence, and the incidence was validated using datasets from bronchoalveolar lavage fluid (BALF) and peripheral blood mononuclear cells. Subsequently, the BALF dataset containing outcomes data was used for the prognosis analysis of m6A regulators. METTL14, G3BP2, and ZC3H13 were independent protective factors. Using correlation analysis with lung function in the lung tissue-derived dataset, METTL14 was a protective factor in IPF. Based on METTL14 and G3BP2, a consensus cluster analysis was applied to distinguish the prognostic m6A regulation patterns. The low-risk group's prognosis was significantly better than the high-risk group. Biological processes regulated by various risk groups included fibrogenesis and cell adhesion. Analysis of immune cell infiltration showed upregulation of neutrophils in the m6A high-risk group. Subsequently, five m6A high-risk group sensitive drugs and one m6A low-risk group sensitive drug were identified. Discussion: These findings suggest that m6A regulators are involved in the diagnosis and prognosis of IPF, and m6A patterns are a method to identify IPF outcomes.

N6-methyladenosine-related genes contribute to malignant progression, have clinical prognostic and neoadjuvant treatments response impact for breast cancer

N6-methyladenosine (m6A) methylation dysregulation contributes to tumorigenesis and breast cancer development. This study intends to conduct a comprehensive analysis for determining the clinical significance of m6A-related genes and establishing m6A-related gene-based risk signature to predict the clinical outcomes and neoadjuvant treatments response for breast cancer patients. The m6Avar database was utilized for downloading the m6A-regulated genes. The Cancer Genome Atlas (TCGA) database was utilized for downloading breast cancer patients’ RNA-Seq data and clinicopathological information. For determining the differentially expressed m6A-related gene, a one-way analysis of variance (ANOVA) was conducted. The interaction and correlation of m6A-related genes were evaluated using search tool for the retrieval of interacting genes/proteins (STRING) and Spearmen test. For determining clusters of breast cancer patients with different clinical outcomes, a consensus clustering analysis was conducted. We screened differentially expressed genes and functional enrichment pathways between subgroups utilizing gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG). We constructed and verified a prognostic signature utilizing Cox regression analysis as well as a least absolute shrinkage and selection operator (LASSO) regression model. 286 genes were detected as significantly differentially expressed in different stages, including 3 m6A RNA methylation regulators, Wilms tumor 1-associating protein (WTAP), YT521-B homology (YTH) domain containing 2 (YTHDC2), and YTH domain family 2 (YTHDF2). A 13-gene prognostic signature was constructed and could predict the overall survival and the neoadjuvant treatments response in breast cancer patients. We categorized breast cancer patients into four groups based on m6A-associated RNAs expression. Significant differences were found in the overall survivals among the four clusters of patients. The biological processes and the key signaling pathways closely related to breast cancer have a close connection to the four clusters. This study confirmed that the m6A-related genes expression levels were highly associated with prognosis and neoadjuvant treatment response in breast cancer and constructed an effective m6A-related gene-based risk signature for predicting the prognosis of patients with breast cancer.

Retracted: m6A RNA Methylation Regulators Contribute to Predict and as a Therapy Target of Pulmonary Fibrosis

Retracted: m6A RNA Methylation Regulators Contribute to Predict and as a Therapy Target of Pulmonary Fibrosis

Retracted: Identification of an m6A RNA Methylation Regulator Risk Score Model for Prediction of Clinical Prognosis in Astrocytoma

Retracted: Identification of an m6A RNA Methylation Regulator Risk Score Model for Prediction of Clinical Prognosis in Astrocytoma

M6A RNA methylation regulator-based signature for prognostic prediction and its potential immunological role in uterine corpus endometrial carcinoma

BackgroundUterine corpus endometrial carcinoma (UCEC) is the most common female pelvic malignancy worldwide. N6-methyladenosine (m6A) plays an important role in various cellular responses, especially in cancer progression. However, the correlation between prognostic UCEC and m6A RNA methylation regulators remains unclear.MethodsWe used The Cancer Genome Atlas (TCGA) to provide a gene signature that could improve the prognostic evaluation of UCEC patients according to the distinct genetic trait of m6A RNA methylation regulators from a bioinformatics perspective. After comparing UCEC subgroups with different genetic profiles of m6A regulators, we identified 71 differentially expressed genes associated with overall survival (OS) and generated a nine-gene signature through least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Finally, we used in vitro and in vivo tumor cell experiments as well as the immune correlation analysis to verify the function of each gene in the proposed gene signature.ResultsTime-dependent receiver operating characteristic (ROC) curves revealed that the proposed gene signature could predict the outcome of UCEC patients accurately. We found that CDKN2A mainly acted from the perspective of tumor cells, while COL4A4, PXDN, TIGIT, CHODL, LMO3, KCNJ12, L1CAM, and EPHB1 might play a role in UCEC from an immunological point of view.ConclusionsFrom an epigenetics perspective, the m6A RNA methylation regulator-based gene signature can predict the prognosis of UCEC patients and immune therapeutic efficacy.

M6A RNA methylation regulators predict prognosis and indicate characteristics of tumour microenvironment infiltration in acute myeloid leukaemia

ABSTRACT Patients with acute myeloid leukaemia (AML) have poor prognoses and low overall survival (OS) rates owing to its heterogeneity and the complexity of its tumour microenvironment (TME). N6-methyladenosine (m6A) modification plays a key role in the initiation and progression of haematopoietic malignancies. However, the underlying function of m6A regulators in AML remains elusive. This study thoroughly analysed the m6A modification features of 177 AML patients based on 22 m6A regulators. Utilizing unsupervised clustering, we determined three distinct m6A modification patterns related to different biological functions, TME cell-infiltrating characteristics and clinical outcomes. Additionally, a risk score was constructed based on six m6A regulators-associated prognostic signatures and was validated as an independent and valuable prognostic factor for AML. Patients with a low-risk score exhibited better survival than those with a high-risk score. Many m6A regulators were aberrantly expressed in AML, among which METTL14, YTHDC2, ZC3H13 and RBM15 were observed to be associated with the OS of AML. In addition, these four m6A regulators were found to be noticeably related to the immune checkpoint inhibitor (ICI) treatments. Finally, we verified the expression levels of these four m6A regulators in AML and healthy samples and three groups of AML patients with different risk categories. Collectively, our study indicates that the m6A modification pattern is involved in TME immune-infiltrating characteristics and prognosis in AML. A better understanding of the m6A modification pattern will help enhance our knowledge of the molecular mechanisms of AML and develop potential prognosis prediction indicators and more effective immunotherapeutic strategies.

Bioinformatics analysis of the correlation between m6A RNA methylation regulators and the immune infiltration and prognosis of bladder cancer.

To analyze the effect of N6-methyladenosine (m6A) RNA methylation regulators on the immune infiltration and prognosis of bladder cancer (BC). We explored the related signaling pathways and prognosis-related genes to provide candidate targets for the treatment and prognostic evaluation of BC. After downloading BC data from The Cancer Genome Atlas (TCGA) database, the expressions of m6A-related genes were obtained. We then performed correlation and sample cluster analysis of the m6A methylation regulator genes as well as difference comparison and survival analysis for the clustered patients using R software. Gene set enrichment analysis (GSEA) was carried out on cluster-grouped samples. Finally, the prognosis-related genes of BC among the m6A methylation regulators were screened. Genomic alterations in the m6A regulators were linked to a poor BC prognosis. HNRNPA2B1, HNRNPC, IGF2BP2, RBM15, YTHDF1, and YTHDF2 were found to be associated with advanced clinical stages of BC. Furthermore, the current study revealed that the levels of the m6A regulators were related to the expression levels and immune infiltration levels of immune regulators [immunosuppressive factors, immunostimulators, and major histocompatibility complex (MHC) molecules] in BC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses suggested that in addition to the relevant immune responses, m6A regulators were involved in the poor prognosis of BC via their participation in blood vessels through regulatory RNA binding, telomeric DNA binding, microRNA (miRNA) binding, negative regulation of messenger RNA (mRNA) processing, negative regulation of DNA biosynthesis, branches of morphogenesis, positive regulation of the Notch receptor target gene transcription, etc. The expression of m6A RNA methylation regulators is closely linked to immune infiltration and prognosis in BC. Thus, it can be utilized as a potential molecular target for the treatment and prognostic assessment of BC.

Expression of m6A Methylation Regulator in Osteoarthritis and Its Prognostic Markers.

Osteoarthritis (OA) is a multifactorial disorder, in which genetic factors are strongly associated with its development. However, the pathogenesis of OA is still unclear, and recently it has been observed that epigenetic modifications are also involved in the pathogenesis of OA. This study aims to study the potential role of m6A-related genes in the occurrence and development of OA. We downloaded the OA expression profile data (GSE55235) from the Gene Expression Omnibus database. First, function enrichment analysis of 17 representative m6A methylation regulatory factors was performed using the DAVID database and Metascape online tool. Then, we analyzed the expression of 17 m6A methylation regulatory factors in OA and the correlation between regulatory factors using Perl software. Finally, receiver operating characteristic (ROC) curve analysis and the area under the ROC curve were used to evaluate the diagnostic effectiveness of m6A-related genes for discriminating patients with OA and healthy. We first identified that 12 of the 17 genes were differentially expressed in OA. ALKBH1, EIF3, IGF2BP3, WTAP, and YTHDC1 were associated with early diagnosis and prognosis of OA. m6A RNA methylation regulator factors are key players in the progression of OA and have potential role in the stratification of prognosis and the formulation of treatment strategies.

Comprehensive Analysis of N6-Methyladenosine (m6A) RNA Methylation Regulators and Tumour Microenvironment Cell Infiltration Involving Prognosis and Immunotherapy in Gastroesophageal Adenocarcinomas.

Gastroesophageal adenocarcinoma (GEA) is a high deadly and heterogeneous cancer. RNA N6-methyladenosine (m6A) modification plays a non-negligible role in shaping individual tumour microenvironment (TME) characterizations. However, the landscape and relationship of m6A modification patterns and TME cell infiltration features remain unknown in GEA. In this study, we examined the TME of GEA using assessments of the RNA-sequencing data focusing on the distinct m6A modification patterns from the public databases. Intrinsic patterns of m6A modification were evaluated for associations with clinicopathological characteristics, underlying biological pathways, tumour immune cell infiltration, oncological outcomes, and treatment responses. The expression of key m6A regulators and module genes was validated by qRT-PCR analysis. We identified two distinct m6A modification patterns of GEA (cluster 1/2 subgroup), and correlated two subgroups with TME cell-infiltrating characteristics. Cluster 2 subgroup correlates with a poorer prognosis, downregulated PD-1 expression, higher risk scores, and distinct immune cell infiltration. In addition, PPI and WGCNA network analysis were integrated to identify key module genes closely related to immune infiltration of GEA to find immunotherapy markers. COL4A1 and COL5A2 in the brown module were significantly correlated to the prognosis, PD-1/L1 and CTLA-4 expression of GEA patients. Finally, a prognostic risk score was constructed using m6A regulator-associated signatures that represented an independent prognosis factor for GEA. Interestingly, COL5A2 expression was linked to the response to anti-PD-1 immunotherapy, m6A regulator expression, and risk score. Our work identified m6A RNA methylation regulators as an important class of players in the malignant progression of GEA and were associated with the complexity of the TME. COL5A2 may be the potential biomarker which contributes to predicting the response to anti-PD-1 immunotherapy and patients' prognosis.

Characterization of m6A-related lncRNA signature in neuroblastoma.

N6-methyladenosine (m6A) constitutes one of the most common modifications in mRNA, rRNA, tRNA, microRNA, and long-chain noncoding RNA. The influence of modifications of m6A on the stability of RNA depends upon the expression of methyltransferase ("writer") and demethylase ("eraser") and m6A binding protein ("reader"). In this study, we identified a set of m6A-related lncRNA expression profiles in neuroblastoma (NBL) based on the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) program. Thereupon, we identified two subgroups of neuroblastoma (high-risk group and low-risk group) by applying consensus clustering to m6A RNA methylation regulators ("Readers,", "Writer," and "Erase"). Relative to the low-risk group, the high-risk group correlates with a poorer prognosis. Moreover, the present study also revealed that the high-risk group proves to be significantly positively enriched in the tumor-related signaling pathways, including the P53 signaling pathway, cell cycle, and DNA repair. This finding indicates that these molecular prognostic markers may also be potentially valuable in early diagnosis, which provides a new research direction for the study of molecular mechanisms underlying the development of NBL. In conclusion, this study constructed a new model of NBL prognosis based on m6a-associated lncRNAs. Ultimately, this model is helpful for stratification of prognosis and development of treatment strategies.

Cluster classification and clinical prognostic modeling based on m6A RNA methylation regulators in liver cancer

Objective: Cluster classification based on m6A methylation regulators and construct prognostic evaluation model. Methods: Utilizing consensus cluster to classify the liver cancer samples form TCGA based on the expression of 13 m6A methylation regulators, and verify the function and prognostic significance of the clustered subtypes. Marker genes were further screened to construct a risk prediction model for evaluating the prognosis of liver cancer patients. Results: The two clustered subtypes based on m6A methylation regulators showed significant differences in the prognosis value of liver cancer patients (P=0.048), and 38 prognostic markers related to m6A methylation in liver cancer were screened from the subgroup with poor prognosis. Two m6A regulatory genes, YTHDF1 and YTHDF2, are proved with adverse prognosis by univariate cox analysis (P<0.05, Hazard ratio>1). We used Lasso regression method to build risk assessment model and effectively predicted the prognosis status of liver cancer patients within 4 years (4-year AUC=0.685, 3-year AUC=0.669). Moreover, the assessment model was validated in another dataset of Asia liver cancer patients. Conclusion: The study provided ideas for studying m6A methylation in liver cancer, and the risk prediction model can be used to evaluate the short-term prognosis of liver cancer patients.

Alterations of m6A RNA methylation regulators contribute to autophagy and immune infiltration in primary Sjögren's syndrome.

N6-methyladenosine (m6A) RNA modification is a new epigenetic regulation mechanism on eukaryotic mRNA. Few autoimmune diseases focused on the role of m6A in their pathogenies, and m6A modulation in the pathological process of primary Sjögren’s syndrome (pSS) is still unknown. In this work, three microarray datasets of pSS patients were downloaded from the GEO database: datasets #1 and #2 from the whole peripheral blood (PB) samples, dataset #3 from the labial salivary gland tissue samples, as well as a PB cohort collected from our hospital. Six differentially expressed m6A regulators were identified by comparing the PB dataset #1 of pSS and healthy controls using the Wilcox test and logistic regression analysis. Among them, four (ALKBH5, RBMX, RBM15B, and YTHDF1) were confirmed as down-regulated in PB dataset #2 and in our PB cohort by RT-PCR, and four (ALKBH5, METTL3, RBM15B, and YTHDF1) were confirmed as down-regulated in the dataset #3 of the labial gland tissue. In addition, discrepantly expressed m6A regulators accompanied by diverse immunocytes, including dendritic cells (DCs), T cells, and CD56dim natural killer cells, and among the regulators, ALKBH5 and METTL3 were comprehensively linked with the infiltrated immune cells. Notably, the most enriched autophagy mechanism mediated by m6A was observed in pSS using functional annotation analysis. Ten hub genes were identified using a protein-protein interaction network, and their expression in PB dataset #2 and the expression of three genes (PIK3CA, STAT1, and MAPK3) in the labial gland tissue dataset #3 were confirmed. Our study provides evidence that m6A methylation is widely involved in the immune infiltration and autophagy of pSS, thus contributing to the pathogenesis of this disease and potentially representing a novel therapeutic target.