m6A Regulator-Mediated Methylation Modification Patterns and Characterisation of Tumour Microenvironment Infiltration in Non-Small Cell Lung Cancer

N6-methyladenosine modification of circMARK2 enhances cytoplasmic export and stabilizes LIN28B, contributing to the progression of Wilms tumor

BACKGROUND

The potential involvement of circular RNAs (circRNAs) and N6-methyladenosine (m6A) modification in the progression of Wilms tumor (WT) has not been fully elucidated. This study investigates the regulatory mechanisms and clinical significance of m6A-modified circMARK2 and its role in WT progression.

METHODS

We identified dysregulated circRNAs through deep sequencing and validated their expression by qRT-PCR in WT tissues. The biological functions of circMARK2 were assessed using clone formation, transwell migration, and orthotopic animal models. To dissect the underlying mechanisms, we employed RNA immunoprecipitation, RNA pull-down, dual-luciferase reporter assays, Western blotting, and immunofluorescence and immunohistochemical staining.

RESULTS

CircMARK2, upregulated in WT tissues, was found to be m6A-modified and promoted cytoplasmic export. It facilitated WT progression by stabilizing LIN28B mRNA through the circMARK2/IGF2BP2 interaction. In vitro and in vivo studies demonstrated that circMARK2 enhances the malignant behavior of WT cells. Clinically, higher circMARK2 levels in tumor tissues of WT patients were linked to increased tumor aggressiveness and reduced survival rates.

CONCLUSIONS

Our study provides the first comprehensive evidence that m6A-modified circMARK2 contributes to WT progression by enhancing LIN28B mRNA stability, promoting cellular aggressiveness. CircMARK2 emerges as a potential biomarker for prognosis and a promising target for therapeutic intervention in WT, underscoring the clinical relevance of m6A modification in pediatric renal cancer.

Targeting METTL3 reprograms the tumor microenvironment to improve cancer immunotherapy

The tumor microenvironment (TME) is a heterogeneous ecosystem containing cancer cells, immune cells, stromal cells, cytokines, and chemokines which together govern tumor progression and response to immunotherapies. Methyltransferase-like 3 (METTL3), a core catalytic subunit for RNA N6-methyladenosine (m6A) modification, plays a crucial role in regulating various physiological and pathological processes. Whether and how METTL3 regulates the TME and anti-tumor immunity in non-small-cell lung cancer (NSCLC) remain poorly understood. Here, we report that METTL3 elevates expression of pro-tumorigenic chemokines including CXCL1, CXCL5, and CCL20, and destabilizes PD-L1 mRNA in an m6A-dependent manner, thereby shaping a non-inflamed TME. Thus, inhibiting METTL3 reprograms a more inflamed TME that renders anti-PD-1 therapy more effective in several murine lung tumor models. Clinically, NSCLC patients who exhibit low-METTL3 expression have a better prognosis when receiving anti-PD-1 therapy. Collectively, our study highlights targeting METTL3 as a promising strategy to improve immunotherapy in NSCLC patients.

Integrated analysis of m6A regulator-mediated RNA methylation modification patterns and immune characteristics in Sjögren's syndrome

The epigenetic modifier N6-methyladenosine (m6A), recognized as the most prevalent internal modification in messenger RNA (mRNA), has recently emerged as a pivotal player in immune regulation. Its dysregulation has been implicated in the pathogenesis of various autoimmune conditions. However, the implications of m6A modification within the immune microenvironment of Sjögren's syndrome (SS), a chronic autoimmune disorder characterized by exocrine gland dysfunction, remain unexplored. Herein, we leverage an integrative analysis combining public database resources and novel sequencing data to investigate the expression profiles of m6A regulatory genes in SS. Our cohort comprised 220 patients diagnosed with SS and 62 healthy individuals, enabling a comprehensive evaluation of peripheral blood at the transcriptomic level. We report a significant association between SS and altered expression of key m6A regulators, with these changes closely tied to the activation of CD4+ T cells. Employing a random forest (RF) algorithm, we identified crucial genes contributing to the disease phenotype, which facilitated the development of a robust diagnostic model via multivariate logistic regression analysis. Further, unsupervised clustering revealed two distinct m6A modification patterns, which were significantly associated with variations in immunocyte infiltration, immune response activity, and biological function enrichment in SS. Subsequently, we proceeded with a screening process aimed at identifying genes that were differentially expressed (DEGs) between the two groups distinguished by m6A modification. Leveraging these DEGs, we employed weight gene co-expression network analysis (WGCNA) to uncover sets of genes that exhibited strong co-variance and hub genes that were closely linked to m6A modification. Through rigorous analysis, we identified three critical m6A regulators - METTL3, ALKBH5, and YTHDF1 - alongside two m6A-related hub genes, COMMD8 and SRP9. These elements collectively underscore a complex but discernible pattern of m6A modification that appears to be integrally linked with SS's pathogenesis. Our findings not only illuminate the significant correlation between m6A modification and the immune microenvironment in SS but also lay the groundwork for a deeper understanding of m6A regulatory mechanisms. More importantly, the identification of these key regulators and hub genes opens new avenues for the diagnosis and treatment of SS, presenting potential targets for therapeutic intervention.

Identification of the expression patterns and potential prognostic role of m6A-RNA methylation regulators in Wilms Tumor

BACKGROUND

To explore the potential role of m6A methylation modification in Wilms Tumor (WT) by m6A-RNA Methylation (m6A) regulators.

METHODOLOGY

The association of m6A modification patterns with immune and prognostic characteristics of tumors was systematically evaluated using 19 m6A regulators extracted from Wilms Tumor's samples in public databases. A comprehensive model of "m6Ascore" was constructed using principal component analysis, and its prognostic value was evaluated.

RESULTS

Almost all m6A regulators were differentially expressed between WT and normal tissues. Unsupervised clustering identified three distinct m6A clusters that differed in both immune cell infiltration and biological pathways. The m6Ascore was constructed to quantify m6A modifications in individual patients. Our analysis suggests that m6Ascore is an independent prognostic factor for WT and can be used as a novel predictor of WT prognosis.

CONCLUSIONS

This study comprehensively explored and systematically characterized m6A modifications in WT. m6A modification patterns play a critical role in the tumor immune microenvironment (TIME) and WT prognosis. m6Ascore provides a more comprehensive understanding of m6A modifications in WT and offers a practical tool for predicting WT prognosis. This study will help clinicians to identify valid indicators of WT to improve the poor prognosis of this disease.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at https://www.aliyundrive.com/drive/folder/64be739cd6956a741fb24670baeea53422be6024 .

GR-m6A: Prediction of N6-methyladenosine sites in mammals with molecular graph and residual network

RNA N6-methyladenine (m6A), which is produced by the methylation of the N6 position of eukaryotic adenine, is a relatively common post-transcriptional modification on the surface of the molecule, which frequently plays a crucial role in biological processes. Biological experimental methods to identify m6A have been studied and implemented in recent years, but they cannot be promoted widely due to drawbacks such as the time and cost of reagents and equipment. Therefore, researchers have proposed computational strategies for identifying m6A sites, but these strategies do not account for the mechanism of methylation occurrence or the structure of RNA molecules. This study, therefore, proposed a novel deep learning model for predicting m6A sites, GR-m6A, which predicts m6A sites by extracting features from the physicochemical properties and spatial structure of molecules via residual networks. In GR-m6A, each RNA base string is represented by SMILES as two matrices comprising topology structural information and node attributes with molecular physicochemical characteristics. The feature encoding matrix was then obtained by fusing the topology matrix and the node matrix in accordance with the graphical convolutional network principle. Correspondingly, the more discriminative features were extracted from the encoding matrix using the residual neural network and predicted using a multilayer perceptron. As evident from the 5-fold cross-validation and independent validation, the GR-m6A model outperformed other existing methods. Thus, we hope that GR-m6A can aid researchers in predicting mammalian m6A loci. The source code and database are available at https://github.com/YingLiangjxau/GR-m6A.

The critical roles of m6A RNA methylation in lung cancer: from mechanism to prognosis and therapy

Lung cancer, a highly malignant disease, greatly affects patients' quality of life. N6-methyladenosine (m6A) is one of the most common posttranscriptional modifications of various RNAs, including mRNAs and ncRNAs. Emerging studies have demonstrated that m6A participates in normal physiological processes and that its dysregulation is involved in many diseases, especially pulmonary tumorigenesis and progression. Among these, regulators including m6A writers, readers and erasers mediate m6A modification of lung cancer-related molecular RNAs to regulate their expression. Furthermore, the imbalance of this regulatory effect adversely affects signalling pathways related to lung cancer cell proliferation, invasion, metastasis and other biological behaviours. Based on the close association between m6A and lung cancer, various prognostic risk models have been established and novel drugs have been developed. Overall, this review comprehensively elaborates the mechanism of m6A regulation in the development of lung cancer, suggesting its potential for clinical application in the therapy and prognostic assessment of lung cancer.

Comprehensive Analysis and Functional Characteristics of Differential Expression of N6-Methyladenosine Methylation Modification in the Whole Transcriptome of Rheumatoid Arthritis

N6-methyladenosine (m6A) modification is the most prevalent chemical modification in eukaryotic mRNA and is associated with the development of various immune diseases. However, the role of m6A methylation in rheumatoid arthritis (RA) development is unclear. We preliminarily explored the role of m6A methylation-related mRNAs in RA for its clinical application. The discovery of m6A methylation-modifying genes in this study may provide a fresh perspective on the development of drugs for RA treatment. High-throughput sequencing combined with methylated RNA immunoprecipitation (MeRIP-seq) and RNA sequencing were used to assess whole-transcriptome m6A modifications in the synovium of patients with RA. The relationship between m6A-modified target genes and RA inflammation and macrophages was determined. The expression of the m6A-modified significant transcript-enriched inflammatory signaling pathway was assessed through animal experiments. Differentially expressed m6A genes were correlated with macrophage activation involved in immune response, vascular endothelium, MAPK signaling pathway, PI3K - Akt signaling pathway, and other inflammatory processes. Furthermore, combined analysis with m6A-seq and RNA-seq revealed 120 genes with significant changes in both m6A modification and mRNA expression. We selected the top 3 candidate mRNAs that were upregulated and downregulated simultaneously. The expression of phosphatase and tensin homolog deleted on chromosome ten (PTEN) mRNA and protein in RA patients was lower than that in healthy control (HC). SHC-binding protein 1 (SHCBP1) and neurexophilin-3 (NXPH3) mRNA expressions were increased in RA patients. The expression of M1 macrophages was increased in RA patients. RA markers are such as rheumatoid factor (RF) and peptide containing citrulline (CCP). Further animal experiments showed that the expression of synovial MAPK, PI3K, and Akt1 proteins in the RA model was increased, and the PTEN, p-PTEN protein expression was decreased. PI3K, Akt1, PTEN, and p-PTEN were correlated to RA joint inflammation. This study revealed a unique pattern of differential m6A methylation modifications in RA and concluded that m6A modification is related to the occurrence of RA synovial inflammation.

Gene signature of m6A RNA regulators in diagnosis, prognosis, treatment, and immune microenvironment for cervical cancer

Continuing studies imply that m⁶A RNA modification is involved in the development of cervical cancer (CC), but lack strong support on recurrence and diagnosis prediction. In this research, a comprehensive analysis of 33 m⁶A regulators was performed to fulfill them. Here, we performed diagnostic and prognosis models and identified key regulators, respectively. Then the CC patients were separated into two clusters in accordance with 33 regulators, and participants in the cluster 1 had a worse prognosis. Subsequently, the m⁶AScore was calculated to quantify the m⁶A modification pattern based on regulators and we found that patients in cluster 1 had higher m⁶AScore. Afterwards, immune microenvironment, cell infiltration, escape analyses and tumor burden mutation analyses were executed, and results showed that m⁶AScore was correlated with them, but to a limited extent. Interestingly, HLAs and immune checkpoint expression, and immunophenoscore in patients with high-m⁶AScores were significantly lower than those in the low-m⁶AScore group. These suggested the m⁶AScores might be used to predict the feasibility of immunotherapy in patients. Results provided a distinctive perspective on m⁶A modification and theoretical basis for CC diagnosis, prognosis, clinical treatment strategies, and potential mechanism exploration.

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.

PLXDC1 Can Be a Biomarker for Poor Prognosis and Immune Evasion in Gastric Cancer

Background

Research has revealed that Plexin domain containing 1 (PLXDC1) is correlated with the prognosis of a variety of tumors, but its role in the tumor microenvironment (TME) of gastric cancer has not been reported.

Methods

In this study, we analyzed PLXDC1 expression in gastric cancer using the Oncomine and the Cancer Genome Atlas (TCGA) databases and immunohistochemical staining experiments, and performed prognostic assessment with data from the TCGA and Kaplan–Meier Plotter databases. The immunomodulatory role of PLXDC1 in the gastric cancer TME was analyzed by signaling pathway enrichment, immune cell correlation analysis, immunomodulator risk model construction and immunohistochemical staining experiments of immune cells.

Results

The results indicated that PLXDC1 was overexpressed in gastric cancer and that its overexpression was associated with poor prognosis. Multivariate Cox analysis revealed that PLXDC1 could be an independent biomarker of the risk of gastric cancer. Signaling pathway enrichment revealed that high PLXDC1 expression was involved in signaling pathways related to immune activation and stromal activation, and Tumor Immune Dysfunction and Exclusion (TIDE) assessment indicated that high PLXDC1 expression was associated with a significantly higher risk of immune evasion than low PLXDC1 expression. A Cox risk model based on PLXDC1-associated immunomodulators also presented poor prognosis, and immune evasion was significantly higher in the high-risk group than in the low-risk group. In addition, immunohistochemical staining of CD8/CD3/CD4⁺ T cells in the high and low PLXDC1 expression groups also observed immune cell distribution characteristics of immune evasion.

Conclusion

This study analyzed PLXDC1 from multiple biological perspectives and revealed that PLXDC1 can be a biomarker for poor prognosis and immune evasion in gastric cancer.

Role of WTAP in Cancer: From Mechanisms to the Therapeutic Potential

Wilms' tumor 1-associating protein (WTAP) is required for N⁶-methyladenosine (m⁶A) RNA methylation modifications, which regulate biological processes such as RNA splicing, cell proliferation, cell cycle, and embryonic development. m⁶A is the predominant form of mRNA modification in eukaryotes. WTAP exerts m⁶A modification by binding to methyltransferase-like 3 (METTL3) in the nucleus to form the METTL3-methyltransferase-like 14 (METTL14)-WTAP (MMW) complex, a core component of the methyltransferase complex (MTC), and localizing to the nuclear patches. Studies have demonstrated that WTAP plays a critical role in various cancers, both dependent and independent of its role in m⁶A modification of methyltransferases. Here, we describe the recent findings on the structural features of WTAP, the mechanisms by which WTAP regulates the biological functions, and the molecular mechanisms of its functions in various cancers. By summarizing the latest WTAP research, we expect to provide new directions and insights for oncology research and discover new targets for cancer treatment.

CD69 and SBK1 as potential predictors of responses to PD-1/PD-L1 blockade cancer immunotherapy in lung cancer and melanoma

Background

PD-1/PD-L1 blockade is a promising immunotherapeutic strategy with the potential to improve the outcomes of various cancers. However, there is a critically unmet need for effective biomarkers of response to PD-1/PD-L1 blockade.

Materials and methods

Potential biomarkers of response to PD-1/PD-L1 blockade were obtained from the Cancer Treatment Response gene signature Database (CTR-DB). A comprehensive pan-cancer analysis was done on The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) datasets. Correlations between gene expression and infiltration by immune cells were assessed using TIMER, EPIC, MCPcounter, xCell, CIBERSORT, and quanTIseq. Immunophenoscore (IPS) was used to assess the potential application of the biomarkers to all TCGA tumors.

Results

Analysis of CTR-DB data identified CD69 and SBK1 as potential biomarkers of response to PD-1/PD-L1 blockade. Correlation analysis revealed that in various TCGA cancer datasets, CD69 expression level correlated positively with most immune checkpoints and tumor-infiltrating immune cells, while SBK1 expression level correlated negatively with infiltrating immune cells. IPS analysis demonstrated the ability of CD69 and SBK1 to predict PD-1/PD-L1 blockade responses in various cancers.

Conclusion

CD69 and SBK1 are potential predictors of response to cancer immunotherapy using PD-1/PD-L1 blockade. These biomarkers may guide treatment decisions, leading to precise treatment and minimizing the waste of medical resources.