m6A regulator-mediated RNA methylation modification patterns are involved in immune microenvironment regulation of periodontitis

Identification of a novel m5C/m6A-related gene signature for predicting prognosis and immunotherapy efficacy in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most prevalent subtype of non-small cell lung cancer (NSCLC) and is associated with high mortality rates. However, effective methods to guide clinical therapeutic strategies for LUAD are still lacking. The goals of this study were to analyze the relationship between an m5C/m6A-related signature and LUAD and construct a novel model for evaluating prognosis and predicting drug resistance and immunotherapy efficacy. We obtained data from LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Based on the differentially expressed m5C/m6A-related genes, we identified distinct m5C/m6A-related modification subtypes in LUAD by unsupervised clustering and compared the differences in functions and pathways between different clusters. In addition, a risk model was constructed using multivariate Cox regression analysis based on prognostic m5C/m6A-related genes to predict prognosis and immunotherapy response. We showed the landscape of 36 m5C/m6A regulators in TCGA-LUAD samples and identified 29 differentially expressed m5C/m6A regulators between the normal and LUAD groups. Two m5C/m6A-related subtypes were identified in 29 genes. Compared to cluster 2, cluster 1 had lower m5C/m6A regulator expression, higher OS (overall survival), higher immune activity, and an abundance of infiltrating immune cells. Four m5C/m6A-related gene signatures consisting of HNRNPA2B1, IGF2BP2, NSUN4, and ALYREF were used to construct a prognostic risk model, and the high-risk group had a worse prognosis, higher immune checkpoint expression, and tumor mutational burden (TMB). In patients treated with immunotherapy, samples with high-risk scores had higher expression of immune checkpoint genes and better immunotherapeutic efficacy than those with low-risk scores. We concluded that the m5C/m6A regulator-related risk model could serve as an effective prognostic biomarker and predict the therapeutic sensitivity of chemotherapy and immunotherapy.

The regulation and potential roles of m6A modifications in early embryonic development and immune tolerance at the maternal-fetal interface

The immune microenvironment at the maternal-fetal interface was determined by the crosstalk between the trophoblast and maternal-derived cells, which dynamically changed during the whole gestation. Trophoblasts act as innate immune cells and dialogue with maternal-derived cells to ensure early embryonic development, depending on the local immune microenvironment. Therefore, dysfunctions in trophoblasts and maternal decidual cells contribute to pregnancy complications, especially recurrent pregnancy loss in early pregnancy. Since many unknown regulatory factors still affect the complex immune status, exploring new potential aspects that could influence early pregnancy is essential. RNA methylation plays an important role in contributing to the transcriptional regulation of various cells. Sufficient studies have shown the crucial roles of N6-methyladenosine (m6A)- and m6A-associated- regulators in embryogenesis during implantation. They are also essential in regulating innate and adaptive immune cells and the immune response and shaping the local and systemic immune microenvironment. However, the function of m6A modifications at the maternal-fetal interface still lacks wide research. This review highlights the critical functions of m6A in early embryonic development, summarizes the reported research on m6A in regulating immune cells and tumor immune microenvironment, and identifies the potential value of m6A modifications in shaping trophoblasts, decidual immune cells, and the microenvironment at the maternal-fetal interface. The m6A modifications are more likely to contribute to embryogenesis, placentation and shape the immune microenvironment at the maternal-fetal interface. Uncovering these crucial regulatory mechanisms could provide novel therapeutic targets for RNA methylation in early pregnancy.

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.

Unveiling the m6A Methylation Regulator Links between Prostate Cancer and Periodontitis by Transcriptomic Analysis

Objective

To identify the N6-methyladenosine (m6A) methylation regulator genes linking prostate adenocarcinoma (PRAD) and periodontitis (PD).

Materials and Methods

PD and TCGA-PRAD GEO datasets were downloaded and analyzed through differential expression analysis to determine the differentially expressed genes (DEGs) deregulated in both conditions. Twenty-three m6A RNA methylation-related genes were downloaded in total. The m6A-related genes that overlapped between PRAD and PD were identified as crosstalk genes. Survival analysis was performed on these genes to determine their prognostic values in the overall survival outcomes of prostate cancer. The KEGG pathways were the most significantly enriched by m6A-related crosstalk genes. We also performed lasso regression analysis and univariate survival analysis to identify the most important m6A-related crosstalk genes, and a protein-protein interaction (PPI) network was built from these genes.

Results

Twenty-three m6A methylation-related regulator genes were differentially expressed and deregulated in PRAD and PD. Among these, seven (i.e., ALKBH5, FMR1, IGFBP3, RBM15B, YTHDF1, YTHDF2, and ZC3H13) were identified as m6A-related cross-talk genes. Survival analysis showed that only the FMR1 gene was a prognostic indicator for PRAD. All other genes had no significant influence on the overall survival of patients with PRAD. Lasso regression analysis and univariate survival analysis identified four m6A-related cross-talk genes (i.e., ALKBH5, IGFBP3, RBM15B, and FMR1) that influenced risk levels. A PPI network was constructed from these genes, and 183 genes from this network were significantly enriched in pathogenic Escherichia coli infection, p53 signaling pathway, nucleocytoplasmic transport, and ubiquitin-mediated proteolysis.

Conclusion

Seven m6A methylation-related genes (ALKBH5, FMR1, IGFBP3, RBM15B, YTHDF1, YTHDF2, and ZC3H13) were identified as cross-talk genes between prostate cancer and PD.

m6A regulator-mediated RNA methylation modification patterns are involved in immune microenvironment regulation of coronary heart disease

Background

Although the roles of m6A modification in the immune responses to human diseases have been increasingly revealed, their roles in immune microenvironment regulation in coronary heart disease (CHD) are poorly understood.

Methods

The GSE20680 and GSE20681 datasets related to CHD were acquired from the Gene Expression Omnibus (GEO) database. A total of 30 m6A regulators were used to perform LASSO regression to identify the significant genes involved in CHD. Unsupervised clustering analysis was conducted using the m6A regulators to distinguish the m6A RNA methylation patterns in patients with CHD. The differentially expressed genes (DEGs) and biological characteristics, including GO and KEGG enrichment results, were assessed for the different m6A patterns to analyse the impacts of m6A regulators on CHD. Hub genes were identified, and subsequent microRNAs-mRNAs (miRNAs–mRNAs) and mRNAs-transcriptional factors (mRNA-TFs) interaction networks were constructed by the protein and protein interaction (PPI) network method using Cytoscape software. The infiltrating proportion of immune cells was assessed by ssGSEA and the CIBERSORT algorithm. Quantitative real-time PCR (qRT-PCR) was performed to detect the expression of the significant m6A regulators and hub genes.

Results

Four of 30 m6A regulators (HNRNPC, YTHDC2, YTHDF3, and ZC3H13) were identified to be significant in the development of CHD. Two m6A RNA methylation clusters were distinguished by unsupervised clustering analysis based on the expression of the 30 m6A regulators. A total of 491 genes were identified as DEGs between the two clusters. A PPI network including 308 mRNAs corresponding to proteins was constructed, and 30 genes were identified as hub genes that were enriched in the bioprocesses of peptide cross-linking, keratinocyte differentiation. Twenty-seven hub genes were found to be related to miRNAs, and seven hub genes were found to be related to TFs. Moreover, among the 30 hub genes, eight genes were found to be upregulated in CHD, and three were found to be downregulated in CHD compared to the normal people. The high m6A modification pattern was associated with a higher infiltrated abundance of immune cells.

Conclusion

Our findings demonstrated that m6A modification plays crucial roles in the diversity and complexity of the immune microenvironment in CHD.

m5C Regulator-mediated methylation modification clusters contribute to the immune microenvironment regulation of multiple myeloma

Background: Multiple myeloma (MM) is a hematological malignancy in which plasma cells proliferate abnormally. 5-methylcytosine (m5C) methylation modification is the primary epigenetic modification and is involved in regulating the occurrence, development, invasion, and metastasis of various tumors; however, its immunological functions have not been systematically described in MM. Thus, this study aimed to clarify the significance of m5C modifications and how the immune microenvironment is linked to m5C methylation in MM.

Method: A total of 483 samples (60 healthy samples, 423 MM samples) from the Gene Expression Omnibus dataset were acquired to assess the expression of m5C regulators. A nomogram model was established to predict the occurrence of MM. We investigated the impact of m5C modification on immune microenvironment characteristics, such as the infiltration of immunocytes and immune response reactions. We then systematically evaluated three different m5C expression patterns to assess immune characteristics and metabolic functional pathways and established m5C-related differentially expressed genes (DEGs). In addition, biological process analysis was performed and an m5C score was constructed to identify potentially significant immunological functions in MM.

Result: Differential expressions of m5C regulators were identified between healthy and MM samples. The nomogram revealed that m5C regulators could predict higher disease occurrence of MM. We identified three distinct m5C clusters with unique immunological and metabolic characteristics. Among the three different m5C clusters, cluster C had more immune characteristics and more metabolism-related pathways than clusters A and B. We analyzed 256 m5C-related DEGs and classified the samples into three different m5C gene clusters. Based on the m5C and m5C gene clusters, we calculated m5C scores and classified each patient into high- and low-m5C score groups.

Conclusion: Our study demonstrated that m5C modification is involved in and contributes to the diversity and complexity of the immune microenvironment, which offers promise for the development of accurate therapeutic strategies.

Identification of pyroptosis-related subtypes and establishment of prognostic model and immune characteristics in asthma

Background

Although studies have shown that cell pyroptosis is involved in the progression of asthma, a systematic analysis of the clinical significance of pyroptosis-related genes (PRGs) cooperating with immune cells in asthma patients is still lacking.

Methods

Transcriptome sequencing datasets from patients with different disease courses were used to screen pyroptosis-related differentially expressed genes and perform biological function analysis. Clustering based on K-means unsupervised clustering method is performed to identify pyroptosis-related subtypes in asthma and explore biological functional characteristics of poorly controlled subtypes. Diagnostic markers between subtypes were screened and validated using an asthma mouse model. The infiltration of immune cells in airway epithelium was evaluated based on CIBERSORT, and the correlation between diagnostic markers and immune cells was analyzed. Finally, a risk prediction model was established and experimentally verified using differentially expressed genes between pyroptosis subtypes in combination with asthma control. The cMAP database and molecular docking were utilized to predict potential therapeutic drugs.

Results

Nineteen differentially expressed PRGs and two subtypes were identified between patients with mild-to-moderate and severe asthma conditions. Significant differences were observed in asthma control and FEV1 reversibility between the two subtypes. Poor control subtypes were closely related to glucocorticoid resistance and airway remodeling. BNIP3 was identified as a diagnostic marker and associated with immune cell infiltration such as, M2 macrophages. The risk prediction model containing four genes has accurate classification efficiency and prediction value. Small molecules obtained from the cMAP database that may have therapeutic effects on asthma are mainly DPP4 inhibitors.

Conclusion

Pyroptosis and its mediated immune phenotype are crucial in the occurrence, development, and prognosis of asthma. The predictive models and drugs developed on the basis of PRGs may provide new solutions for the management of asthma.

METTL3 inhibits inflammation of retinal pigment epithelium cells by regulating NR2F1 in an m6A-dependent manner

N6-metyladenosine (m6A) RNA methylation has been proven to be involved in diverse biological processes, but its potential roles in the development of lipopolysaccharide (LPS) induced retinal pigment epithelium (RPE) inflammation have not been revealed. In this study, we explored the effects and underlying mechanisms of methyltransferase-like 3 (METTL3) in LPS stimulated RPE cells. Proliferation of METTL3-silenced RPE cells was examined by Cell counting kit-8 (CCK8) and 5-Ethynyl-2´-Deoxyuridine (Edu). Expression of tight junction proteins ZO-1 and Occludin, and secretion of inflammatory factors interleukins (IL)-1, 6 and 8 were detected by Western blotting or Enzyme-linked immunosorbent assay (ELISA). RNA sequencing and methylated RNA immunoprecipitation (MeRIP) sequencing were used to analyze the target gene nuclear receptor subfamily 2 group F member 1 (NR2F1) of METTL3. Our results showed that both human RPE (hRPE) cells and ARPE19 cells exhibited inhibited proliferation, tight junction protein expression, and increased inflammatory factor secretion after METTL3 silencing. Mechanistically, we found that NR2F1, as a METTL3-methylated target gene, inhibits Occludin level and promotes IL-6 secretion of RPE cells in an m6A-dependent manner. Interestingly, NR2F1 deficiency reversed the decreased Occludin expression and increased IL-6 secretion in METTL3-defective RPE cells. In conclusion, our study revealed that METTL3 attenuates RPE cell inflammation by methylating NR2F1, suggesting the critical role of METTL3 in RPE cells.

Autophagy-Related Genes Are Involved in the Progression and Prognosis of Asthma and Regulate the Immune Microenvironment

Background

Autophagy has been proven to play an important role in the pathogenesis of asthma and the regulation of the airway epithelial immune microenvironment. However, a systematic analysis of the clinical importance of autophagy-related genes (ARGs) regulating the immune microenvironment in patients with asthma remains lacking.

Methods

Clustering based on the k-means unsupervised clustering method was performed to identify autophagy-related subtypes in asthma. ARG-related diagnostic markers in low-autophagy subtypes were screened, the infiltration of immune cells in the airway epithelium was evaluated by the CIBERSORT, and the correlation between diagnostic markers and infiltrating immune cells was analyzed. On the basis of the expression of ARGs and combined with asthma control, a risk prediction model was established and verified by experiments.

Results

A total of 66 differentially expressed ARGs and 2 subtypes were identified between mild to moderate and severe asthma. Significant differences were observed in asthma control and FEV1 reversibility between the two subtypes, and the low-autophagy subtype was closely associated with severe asthma, energy metabolism, and hormone metabolism. The autophagy gene SERPINB10 was identified as a diagnostic marker and was related to the infiltration of immune cells, such as activated mast cells and neutrophils. Combined with asthma control, a risk prediction model was constructed, the expression of five risk genes was supported by animal experiments, was established for ARGs related to the prediction model.

Conclusion

Autophagy plays a crucial role in the diversity and complexity of the asthma immune microenvironment and has clinical value in treatment response and prognosis.

Comprehensive Analysis of N6-Methyladenosine Regulators in the Subcluster Classification and Drug Candidates Prediction of Severe Obstructive Sleep Apnea

Background: Obstructive sleep apnea (OSA) is the most common type of sleep apnea that impacts the development or progression of many other disorders. Abnormal expression of N6-methyladenosine (m6A) RNA modification regulators have been found relating to a variety of human diseases. However, it is not yet known if m6A regulators are involved in the occurrence and development of OSA. Herein, we aim to explore the impact of m6A modification in severe OSA.

Methods: We detected the differentially expressed m6A regulators in severe OSA microarray dataset GSE135917. The least absolute shrinkage and selection operator (LASSO) and support vector machines (SVM) were used to identify the severe OSA-related m6A regulators. Receiver operating characteristic (ROC) curves were performed to screen and verify the diagnostic markers. Consensus clustering algorithm was used to identify m6A patterns. And then, we explored the character of immune microenvironment, molecular functionals, protein-protein interaction networks and miRNA-TF coregulatory networks for each subcluster. Finally, the Connectivity Map (CMap) tools were used to tailor customized treatment strategies for different severe OSA subclusters. An independent dataset GSE38792 was used for validation.

Results: We found that HNRNPA2B1, KIAA1429, ALKBH5, YTHDF2, FMR1, IGF2BP1 and IGF2BP3 were dysregulated in severe OSA patients. Among them, IGF2BP3 has a high diagnostic value in both independent datasets. Furthermore, severe OSA patients can be accurately classified into three m6A patterns (subcluster1, subcluster2, subcluster3). The immune response in subcluster3 was more active because it has high M0 Macrophages and M2 Macrophages infiltration and up-regulated human leukocyte antigens (HLAs) expression. Functional analysis showed that representative genes for each subcluster in severe OSA were assigned to histone methyltransferase, ATP synthesis coupled electron transport, virus replication, RNA catabolic, multiple neurodegeneration diseases pathway, et al. Moreover, our finding demonstrated cyclooxygenase inhibitors, several of adrenergic receptor antagonists and histamine receptor antagonists might have a therapeutic effect on severe OSA.

Conclusion: Our study presents an overview of the expression pattern and crucial role of m6A regulators in severe OSA, which may provide critical insights for future research and help guide appropriate prevention and treatment options.

Gene model-related m6A expression levels predict the risk of preeclampsia

Background

This is the first study to explore the potential functions and expression patterns of RNA N6-methyladenosine (m6A) and potential related genes in preeclampsia.

Methods

We identified two m6A modification patterns through unsupervised cluster analysis and validated them by principal component analysis. We quantified the relative abundance of specific infiltrating immunocytes using single-sample gene set enrichment analysis (ssGSEA) and the Wilcoxon test. To screen hub genes related to m6A regulators, we performed weighted gene coexpression network analysis. Functional enrichment analysis was conducted for differential signalling pathways and cellular processes. Preeclampsia patients were grouped by consensus clustering based on differentially expressed hub genes and the relationship between different gene-mediated classifications and clinical features.

Results

Two m6A clusters in preeclampsia, cluster A and cluster B, were determined based on the expression of 17 m6A modification regulators; ssGSEA revealed seven significantly different immune cell subtypes between the two clusters. A total of 1393 DEGs and nine potential m6A-modified hub genes were screened. We divided the patients into two groups based on the expression of these nine genes. We found that almost all the patients in m6A cluster A were classified into hub gene cluster 1 and that a lower gestational age may be associated with more m6A-associated events.

Conclusions

This study revealed that hub gene-mediated classification is consistent with m6A modification clusters for predicting the clinical characteristics of patients with preeclampsia. Our results provide new insights into the molecular mechanisms of preeclampsia.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01254-4.

Emerging role of epigenetic regulations in periodontitis: a literature review

Periodontitis is mainly initiated by periodontal pathogens including Porphyromonas gingivalis, and bad living habits such as smoking aggravate its incidence and severity. The development of periodontitis is closely related to the host's immune responses and the secretion of various cytokine networks. Moreover, periodontitis has an important connection with the development of systemic diseases. Recently, epigenetics which is a fast-developing hot research area has provided new insights into the research of various diseases including periodontitis. Epigenetics is an important supplement to the regulation of gene expression. The study of epigenetics is about causing heritable gene expression or cell phenotype changes through certain mechanisms without changing the DNA sequence. It mainly includes histone modification, DNA methylation, non-coding RNA and the latest research hotspot m6A RNA methylation. In the review, we comprehensively summarize the latest literature on the potential epigenetic regulations in various aspects of periodontitis.

m6A Regulator-Mediated RNA Methylation Modification Patterns are Involved in the Pathogenesis and Immune Microenvironment of Depression

Depression is a genetical disease characterized by neuroinflammatory symptoms and is difficult to diagnose and treat effectively. Recently, modification of N6-methyladenosine (m6A) at the gene level was shown to be closely related to immune regulation. This study was conducted to explore the effect of m6A modifications on the occurrence of depression and composition of the immune microenvironment. We downloaded gene expression profile data of healthy and depressed rats from the Gene Expression Omnibus. We described the overall expression of m6A regulators in animal models of depression and constructed risk and clinical prediction models using training and validation sets. Bioinformatics analysis was performed using gene ontology functions, gene set enrichment analysis, gene set variation analysis, weighted gene co-expression network analysis, and protein-protein interaction networks. We used CIBERSORT to identify immune-infiltrating cells in depression and perform correlation analysis. We then constructed two molecular subtypes of depression and assessed the correlation between the key genes and molecular subtypes. Through differential gene analysis of m6A regulators in depressed rats, we identified seven m6A regulators that were significantly upregulated in depressed rats and successfully constructed a clinical prediction model. Gene Ontology functional annotation showed that the m6A regulators enriched differentially expressed genes in biological processes, such as the regulation of mRNA metabolic processes. Further, 12 hub genes were selected from the protein-protein interaction network. Immune cell infiltration analysis showed that levels of inflammatory cells, such as CD4 T cells, were significantly increased in depressed rats and were significantly correlated with the depression hub genes. Depression was divided into two subtypes, and the correlation between hub genes and these two subtypes was clarified. We described the effect of m6A modification on the pathogenesis of depression, focusing on the role of inflammatory infiltration.

Methylation Pattern Mediated by m6A Regulator and Tumor Microenvironment Invasion in Lung Adenocarcinoma

BACKGROUND

Recent research has established the existence of epigenetic modulation of the immune response. The possible involvement of RNA-n6-methyladenosine (m⁶A) alteration in tumor microenvironment (TME) cell invasion, on the other hand, is unknown.

METHODS

Based on 23 m⁶A regulators, we examined the alteration patterns of m⁶A in 629 LUAD tissues and comprehensively connected these modification patterns with TME cell invasion characteristics. The m⁶A score was calculated, and the m⁶A modification pattern of a single tumor was quantified using principal component analysis. Then, we further verified the expression of m⁶A related enzymes and the role hub gene (NOL10) closely related to survival in lung cancer cell lines.

RESULTS

Three separate m⁶A alteration modes have been discovered. TME cell invasion characteristics in the three modes were very similar to the three immunological phenotypes of tumors: immunological rejection, immunological inflammation, and immunological desert. We show that assessing the m⁶A modification pattern in a single tumor may help predict tumor inflammatory stage, subtype, TME interstitial activity, and prognosis. TME phenotypic inflammation is indicated by a high m⁶A score, which is characterized by elevated mutation load and immunological activation. The low m⁶A subtype showed matrix activation and ineffective immune infiltration, indicating that the TME phenotype of noninflammation and immunological rejection had a poor survival probability. Increased neoantigen burden was also linked to a high m⁶A score. Patients with a higher m⁶A score saw substantial therapeutic and clinical improvements. And reducing hub gene NOL10 expression substantially inhibited lung cancer cell growth and migration.

CONCLUSIONS

This research shows that m⁶A alteration is critical in the creation of TME variety and complexity. The analysis of a single tumor's m⁶A alteration pattern will aid in improving our knowledge of TME invasion features and guiding more effective immunotherapy tactics.

m6A Regulator-Mediated RNA Methylation Modification Patterns Regulate the Immune Microenvironment in Osteoarthritis

Epigenetic regulation, particularly RNA n6 methyl adenosine (m6A) modification, plays an important role in the immune response. However, the regulatory role of m6A in the immune microenvironment in osteoarthritis (OA) remains unclear. Accordingly, we systematically studied RNA modification patterns mediated by 23 m6A regulators in 38 samples and discussed the characteristics of the immune microenvironment modified by m6A. Next, we constructed a novel OA m6A nomogram, an m6A-transcription factor-miRNA network, and a drug network. Healthy and OA samples showed distinct m6A regulatory factor expression patterns. YTHDF3 expression was upregulated in OA samples and positively correlated with type II helper cells and TGFb family member receptors. Furthermore, three different RNA modification patterns were mediated by 23 m6A regulatory factors; in Mode 3, the expression levels of YTHDF3, type II T helper cells, and TGFb family member receptors were upregulated. Pathways related to endoplasmic reticulum oxidative stress and mitochondrial autophagy showed a strong correlation with the regulatory factors associated with Mode 3 and 23 m6A regulatory factors. Through RT-qPCR we validated that SREBF2 and EGR1 as transcription factors of YTHDF3 and IGF2BP3 are closely associated with the development of OA, hsa-miR-340 as a miRNA for YTHDF3 and IGF2BP3 was involved in the development of OA, we also detected the protein expression levels of IGF2BP3, YTHDF3, EGR1 and SREBF2 by western blotting, and the results were consistent with PCR. Overall, the constructed nomogram can facilitate the prediction of OA risk.

Comprehensive Analysis of N6-Methyladenosine (m6A) Methylation in Neuromyelitis Optica Spectrum Disorders

Background: N⁶-Methyladenosine (m⁶A) methylation is the most prevalent internal posttranscriptional modification on mammalian mRNA. But its role in neuromyelitis optica spectrum disorders (NMOSD) is not known. Aims: To explore the mechanism of m⁶A in NMOSD patients. Methods: This study assessed the m⁶A methylation levels in blood from two groups: NMOSD patients and healthy controls. Methylated RNA immunoprecipitation Sequencing (MeRIP-seq) and RNA-seq were performed to assess differences in m⁶A methylation between NMOSD patients and healthy controls. Ultra-high performance liquid chromatography coupled with triple quadruple mass spectrometry (UPLC-QQQ-MS) method was performed to check m⁶A level. Differential m⁶A methylation genes were validated by MeRIP-qPCR. Results: Compared with that in the control group, the total m6A level was decreased in the NMOSD group. Genes with upregulated methylation were primarily enriched in processes associated with RNA splicing, mRNA processing, and innate immune response, while genes with downregulated methylation were enriched in processes associated with the regulation of transcription, DNA-templating, and the positive regulation of I-kappa B kinase/NF-kappa B signalling. Conclusion: These findings demonstrate that differential m⁶A methylation may act on functional genes to regulate immune homeostasis in NMOSD.

Development and Validation of a Prognostic N6-Methyladenosine-Related Immune Gene Signature for Lung Adenocarcinoma

Purpose

The prognostic value of an N6-methyladenosine (m6A) methylation-related immune gene signature for lung adenocarcinoma (LUAD) was investigated.

Patients and Methods

Gene expression and clinical phenotype data of LUAD patients were downloaded from The Cancer Genome Atlas database. A list of immune-related genes was retrieved from the InnateDB database. Correlation analysis, survival analysis, and univariate and multivariate Cox regression analyses were performed. After allocating patients into a high-risk or a low-risk group, the corresponding survival rates, immune microenvironment, expression of immune checkpoint genes, and modulation of Kyoto Encyclopedia of Genes and Genomes pathways were examined. Finally, the expression levels of prognostic biomarkers were assessed in the GSE126044 dataset.

Results

Seven m6A-related immune prognostic genes were identified. High expression of PSMD10P1, DIDO1, ABCA5, and CIITA was associated with high survival rates, while that of PRC1, ZWILCH, and ANLN was associated with low survival rates. The high- and low-risk groups showed significant differences in terms of the abundance of six tumor-infiltrating immune cell types and expression of 12 immune checkpoint genes. The risk group acted as an independent prognostic factor (hazard ratio = 0.398, 95% confidence interval = 0.217–0.729, P = 0.003). Finally, the developed nomogram could predict most efficiently the 1-, 2-, and 3-year survival probability of LUAD patients with a C-index of 0.833.

Conclusion

A seven-gene risk signature, associated with the immune microenvironment in LUAD, showed independent prognostic value.

Identification of N6-Methyladenosine-Related LncRNAs for Predicting Overall Survival and Clustering of a Potentially Novel Molecular Subtype of Breast Cancer

We aimed to identify a signature comprising N6-methyladenosine (m6A)-related long non-coding RNAs (lncRNAs) and molecular subtypes associated with breast cancer (BRCA). We obtained data of BRCA samples from The Cancer Genome Atlas database. The m6A-related lncRNA prognostic signature (m6A-LPS) included 10 lncRNAs previously identified as prognostic m6A-related lncRNAs and was constructed using integrated bioinformatics analysis and validated. Accordingly, a risk score based on the m6A-LPS signature was established and shown to confirm differences in survival between high-risk and low-risk groups. Three distinct genotypes were identified, whose characteristics included features of the tumor immune microenvironment in each subtype. Our results indicated that patients in Cluster 2 might have a worse prognostic outcome than those in other clusters. The three genotypes and risk subgroups were enriched in different biological processes and pathways, respectively. We then constructed a competing endogenous RNA network based on the prognostic m6A-related lncRNAs. Finally, we validated the expression levels of target lncRNAs in 72 clinical samples. In summary, the m6A-LPS and the potentially novel genotype may provide a theoretical basis for further study of the molecular mechanism of BRCA and may provide novel insights into precision medicine.

Elevated N6-Methyladenosine RNA Levels in Peripheral Blood Immune Cells: A Novel Predictive Biomarker and Therapeutic Target for Colorectal Cancer

Effective biomarkers for the diagnosis of colorectal cancer (CRC) are essential for improving prognosis. Imbalance in regulation of N6-methyladenosine (m⁶A) RNA has been associated with a variety of cancers. However, whether the m⁶A RNA levels of peripheral blood can serve as a diagnostic biomarker for CRC is still unclear. In this research, we found that the m⁶A RNA levels of peripheral blood immune cells were apparently elevated in the CRC group compared with those in the normal controls (NCs) group. Furthermore, the m⁶A levels arose as CRC progressed and metastasized, while these levels decreased after treatment. The area under the curve (AUC) of the m⁶A levels was 0.946, which was significantly higher than the AUCs for carcinoembryonic antigen (CEA; 0.817), carbohydrate antigen 125 (CA125; 0.732), and carbohydrate antigen 19-9 (CA19-9; 0.771). Moreover, the combination of CEA, CA125, and CA19-9 with m⁶A levels improved the AUC to 0.977. Bioinformatics and qRT-PCR analysis further confirmed that the expression of m⁶A modifying regulator IGF2BP2 was markedly elevated in peripheral blood of CRC patients. Gene set variation analysis (GSVA) implied that monocyte was the most abundant m⁶A-modified immune cell type in CRC patients' peripheral blood. Additionally, m⁶A modifications were negatively related to the immune response of monocytes. In conclusion, our results revealed that m⁶A RNA of peripheral blood immune cells was a prospective non-invasive diagnostic biomarker for CRC patients and might provide a valuable therapeutic target.

Identification of Immune Subtypes for Predicting the Prognosis of Patients in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a common malignancy with poor prognosis and immune response, which plays an important role in tumor progression. Recently, immunotherapies have revolutionized the therapeutic means of malignancies including HNSCC. However, the relationship between immunophenotypes of HNSCC and its clinical response to immune-checkpoint inhibitors remains unclear. We aim to identify molecular subtyping related to distinct immunophenotypes in HNSCC. Consensus clustering algorithm was conducted for subtyping. Immunophenotypes between subtypes were compared according to infiltrating immunocytes, immune reactions, major histocompatibility complex (MHC) family, immunoinhibitory, immunostimulatory and immune scores. The relationship between immunophenotype and genotype was investigated from gene mutation and tumor mutation burden. The potential response of Immune-checkpoint blockade (ICB) therapy was estimated with TIDE and ImmuCellAI algorithms, and immune-checkpoint genes. The immune characteristics were also investigated. Biological functions were annotated by the gene-set enrichment analysis (GSEA) algorithm. Two distinct immune subtypes of HNSCC with different survival outcomes, biological characteristics, immunophenotype, and ICB response were identified. The subtype-1 was featured with better prognosis, more infiltrated immunocytes, stronger immune reaction, higher immune-related gene expression, higher immune-checkpoint gene expression (PD-1, PD-L1, and CTLA-4), and better ICB response. A higher immune response in subtype-1 was also revealed by GSEA. Subtype-1 possessed a higher immune response and more sensitivity to ICB therapy leading to a better prognosis. These findings may shed promising light on the immunotherapy strategy in HNSCC

m6A regulator-mediated RNA methylation modification patterns and immune microenvironment infiltration characterization in severe asthma

N6‐methyladenosine (m6A) modification is one of the most prevalent RNA modification forms of eukaryotic mRNA and is an important post‐transcriptional mechanism for regulating genes. However, the role of m6A modification in the regulation of severe asthma has never been reported. Thus, we aimed to investigate the m6A regulator‐mediated RNA methylation modification patterns and immune microenvironment infiltration characterization in severe asthma. In this study, 87 healthy controls and 344 severe asthma cases from the U‐BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) programme were used to systematically evaluate the m6A modification patterns mediated by 27 m6A regulators and to investigate the effects of m6A modification on immune microenvironment characteristics. We found that 16 m6A regulators were abnormal and identified two key m6A regulators (YTHDF3 and YTHDC1) and three m6A modification patterns. The study of infiltration characteristics of immune microenvironment found that pattern 2 had more infiltrating immune cells and more active immune response. Besides, it was found that the eosinophils which are very important for severe asthma were affected by YTHDF3 and EIF3B. We also verified key m6A regulators with merip‐seq and found that they were mainly distributed in exons and enriched in 3′UTR. In conclusion, our findings suggested that m6A modification plays a key role in severe asthma, and may be able to guide the future strategy of immunotherapy.

Crosstalk between RNA-Binding Proteins and Immune Microenvironment Revealed Two RBP Regulatory Patterns with Distinct Immunophenotypes in Periodontitis

Periodontitis is an inflammatory disease whose pathogenesis is closely related with immunology. RNA-binding proteins (RBPs) were found to play crucial roles in immunity. Therefore, we aimed to investigate the potential impact of RBPs in the immune microenvironment in periodontitis. The differential expressions of RBPs in periodontitis and healthy samples were determined and were used to construct an RBP-based classifier for periodontitis using logistic regression. The correlations between RBPs and immune characteristics were investigated by the Spearman correlation. Unsupervised clustering was conducted to identify the RBP regulatory patterns. RBP-related genes were identified by WGCNA, while biological distinctions were revealed by GSVA and GO. 24 dysregulated RBPs were identified, from which a 12-RBP classifier was established to distinguish periodontitis with AUC of 0.942. Close protein-protein interactions and expression correlations were observed especially between SPATS2 and ISG20. ISG20 and ESRP1 were found to be highly correlated with immunocyte infiltration, immune signaling activation, and HLA expressions in periodontitis. Two distinct RBP regulatory patterns were identified with different immune and other biological characteristics in periodontitis. Our findings indicate a significant impact of RBPs in shaping the immune microenvironment in periodontitis, which might bring new insights into the understanding of immune mechanisms in the pathogenesis of periodontitis.

m6A regulator-mediated RNA methylation modification patterns are involved in immune microenvironment regulation of periodontitis

The role of epigenetic regulation in immunity is emerging, especially for RNA N6‐methyladenosine (m6A) modification. However, little is known about the role of m6A in the regulation of the immune microenvironment of periodontitis. Thus, we aim to investigate the impact of m6A modification in periodontitis immune microenvironment. The RNA modification patterns mediated by 23 m6A‐regulators were systematically evaluated in 310 periodontitis samples. The impact of m6A modification on immune microenvironment characteristics was explored, including infiltrating immunocytes, immune reaction gene‐sets and HLAs (human leukocyte antigen) gene. m6A phenotype‐related immune genes were also identified. 17 m6A regulators were dysregulated and a 15‐m6A regulator signature can well distinguish periodontitis and control samples. ALKBH5 and FMR1 are closely related to infiltrating monocyte abundance. ELAVL1 and CBLL1 are significant regulators in immune reaction of TNF_Family_Members_Receptors and Cytokine. The expression of HLA‐B and HLA‐DOA is affected by ALKBH5 and LRPPRC. 3 distinct RNA modification patterns mediated by 23 m6A regulators were identified. They differ from immunocyte abundance, immune reaction and HLA gene. 1631 m6A phenotype‐related genes and 70 m6A‐mediated immune genes were identified, and the biological functions of these were explored. Our finding demonstrated the m6A modification plays a crucial role in the diversity and complexity of the immune microenvironment of periodontitis.