m6A RNA Methylation Regulators Research Articles

N6-Methyladenosine Regulators Promote Malignant Progression of Gastric Adenocarcinoma.

N6-methyladenosine (m6A) RNA methylation is dynamically and reversibly regulated by methyltransferases, binding proteins, and demethylases. The restoration of m6A to adenosine could result in demethylation modifications. Abnormalities in m6A epigenetic modifications in cancer are of increasing interest in recent years. According to the progression and prognostic performance of m6A epigenetic modifications in gastric adenocarcinoma (STAD), this study comprehensively analyzed the m6A modification patterns of gastric adenocarcinoma specimens in The Cancer Genome Atlas (TCGA) database based on 20 m6A regulators. Here, we found that 20 m6A RNA methylation regulators were high-expressed in gastric adenocarcinoma. m6A RNA methylation regulators were closely associated with pT staging of gastric cancer. Based on such findings, we developed a prognostic model using four m6A RNA methylation regulators (IGF2BP1, RBM15, FTO, ALKBH5), and the FTO was confirmed as an independent prognostic marker.

Downregulation of Methyltransferase-Like 14 Promotes Ovarian Cancer Cell Proliferation Through Stabilizing TROAP mRNA.

Altered expression levels of the proteins that regulate N6-methyladenosine (m6A) RNA methylation, including methyltransferase-like 14 (METTL14), are associated with cancer development. Based on our analysis of m6A methylation regulators using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets, we focused on the regulatory role of METTL14 in ovarian cancer. We performed bioinformatics and survival analyses with these datasets and also used METTL14-overexpressing SKOV-3 ovarian cancer cells for in vitro studies. Trophinin associated protein (TROAP) siRNA and treatment with or without actinomycin D was used in the cells for qRT-PCR, western blot, cDNA microarray, cell viability, colony formation, luciferase gene reporter, methylated RNA immunoprecipitation (MeRIP)-qPCR, total RNA methylation, and RNA stability assays. Additionally, ovarian cancer and normal tissue samples were analyzed by immunohistochemistry, qRT-PCR, and western blot assays. The TCGA and GEO data confirmed copy number variations (CNVs) of these m6A RNA methylation regulators in ovarian cancer tissues. Furthermore, reduced METTL14 expression was associated with alterations in CNVs as well as poor patient survival in ovarian cancer. Moreover, the METTL14 and m6A RNA methylation levels were both significantly reduced in ovarian cancer tissues than in normal tissues. Restoration of METTL14 expression suppresses ovarian cancer cell proliferation by inhibition of TROAP expression. Further in vivo and in vitro experiments confirmed that METTL14 is a negative regulator of ovarian cancer cell proliferation via TROAP expression and that m6A RNA methylation regulates TROAP mRNA stability. In conclusion, METTL14 overexpression decreased ovarian cancer proliferation by inhibition of TROAP expression via an m6A RNA methylation-dependent mechanism.

29 m6A-RNA Methylation (Epitranscriptomic) Regulators Are Regulated in 41 Diseases including Atherosclerosis and Tumors Potentially via ROS Regulation - 102 Transcriptomic Dataset Analyses.

We performed a database mining on 102 transcriptomic datasets for the expressions of 29 m6A-RNA methylation (epitranscriptomic) regulators (m6A-RMRs) in 41 diseases and cancers and made significant findings: (1) a few m6A-RMRs were upregulated; and most m6A-RMRs were downregulated in sepsis, acute respiratory distress syndrome, shock, and trauma; (2) half of 29 m6A-RMRs were downregulated in atherosclerosis; (3) inflammatory bowel disease and rheumatoid arthritis modulated m6A-RMRs more than lupus and psoriasis; (4) some organ failures shared eight upregulated m6A-RMRs; end-stage renal failure (ESRF) downregulated 85% of m6A-RMRs; (5) Middle-East respiratory syndrome coronavirus infections modulated m6A-RMRs the most among viral infections; (6) proinflammatory oxPAPC modulated m6A-RMRs more than DAMP stimulation including LPS and oxLDL; (7) upregulated m6A-RMRs were more than downregulated m6A-RMRs in cancer types; five types of cancers upregulated ≥10 m6A-RMRs; (8) proinflammatory M1 macrophages upregulated seven m6A-RMRs; (9) 86% of m6A-RMRs were differentially expressed in the six clusters of CD4+Foxp3+ immunosuppressive Treg, and 8 out of 12 Treg signatures regulated m6A-RMRs; (10) immune checkpoint receptors TIM3, TIGIT, PD-L2, and CTLA4 modulated m6A-RMRs, and inhibition of CD40 upregulated m6A-RMRs; (11) cytokines and interferons modulated m6A-RMRs; (12) NF-κB and JAK/STAT pathways upregulated more than downregulated m6A-RMRs whereas TP53, PTEN, and APC did the opposite; (13) methionine-homocysteine-methyl cycle enzyme Mthfd1 downregulated more than upregulated m6A-RMRs; (14) m6A writer RBM15 and one m6A eraser FTO, H3K4 methyltransferase MLL1, and DNA methyltransferase, DNMT1, regulated m6A-RMRs; and (15) 40 out of 165 ROS regulators were modulated by m6A eraser FTO and two m6A writers METTL3 and WTAP. Our findings shed new light on the functions of upregulated m6A-RMRs in 41 diseases and cancers, nine cellular and molecular mechanisms, novel therapeutic targets for inflammatory disorders, metabolic cardiovascular diseases, autoimmune diseases, organ failures, and cancers.

Integrative Analysis of m6A RNA Methylation Regulators and the Tumor Immune Microenvironment in Non-Small-Cell Lung Cancer.

Background Non-small-cell lung cancer (NSCLC) is a major component of lung cancer and is significantly correlated with poor prognosis. N6-methyladenosine (m6A) RNA methylation is closely related to the occurrence, progression, and prognosis of cancer. The potential biological functions and mechanisms of m6A RNA methylation in the immune microenvironment are still unclear. Methods We assessed m6A RNA methylation modification patterns in 1326 NSCLC patient samples based on 20 m6A regulators, linking these clusters to the tumor microenvironment and immune cell infiltration. The m6Ascore was created to quantify the m6A modification patterns of individual tumors. We then assessed the value of NSCLC patients in terms of clinical prognosis and immunotherapy response. Results According to different mRNA expression levels, two different m6A clusters were identified. m6A aggregation was significantly associated with clinical prognostic characteristics, the tumor microenvironment, and immune-related biological processes. Fifteen differential genes were screened based on these two m6A clusters, and to further investigate the mechanisms of action of these differential genes, they were subjected to unsupervised clustering analysis, which classified them into four different genomic isoforms. Prognostic analysis indicated that the survival advantage of the m6A gene cluster A modification mode was significantly prominent. We continued to construct the m6Ascore, which was used as a scoring tool to evaluate tumor typing, immunity, and prognosis. Patients with a low m6Ascore showed a significant survival advantage, and the group with a low m6Ascore had a better prognosis predicted by immunotherapy. The anti-PD-1/L1 immunotherapy cohort showed that a lower m6Ascore was associated with higher efficacy of immunotherapy. Conclusions The results suggest that m6A RNA methylation regulators make an important difference in the tumor immune microenvironment of patients with NSCLC. m6A gene characterization and the construction of the m6Ascore provide us with a richer understanding of m6A RNA methylation modification patterns in NSCLC patients and help to predict clinical prognosis and immunotherapeutic response.

Diagnostic, Therapeutic, and Prognostic Value of the m6A Writer Complex in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) has poor prognosis and is usually diagnosed only at an advanced stage. Identification of novel biomarkers is critical to early diagnosis and better prognosis for HCC patients. N6-methyladenosine (m6A) RNA methylation regulators play important roles in the development of many tumors. However, the m6A writer complex, a key executor of m6A methylation modification, has not been independently investigated, and its specific bioinformatics analysis has not yet been performed in HCC. In this study, we used multiple public databases to evaluate the diagnostic, therapeutic, and prognostic value of the m6A writers in HCC. The results showed that expression levels of METTL3, VIRMA and CBLL1 were significantly increased, while expression levels of METTL14 and ZC3H13 were significantly decreased in HCC, which was closely related to clinicopathological factors, such as tumor stage and prognosis. Bioinformatics further explored the possible underlying mechanisms by which the m6A writer complex are involved in activation of tumor-promoting pathways and/or inhibition of tumor-suppressing pathways, including apoptosis, cell cycle, DNA damage response and EMT. Furthermore, we showed that the m6A writer complex is correlated with immune cell infiltration and immunoregulator expression in HCC. In conclusion, the m6A writer complex may represent a promising biomarker and target that can guide targeted therapy or immunotherapy for HCC patients.

Construction of a risk prediction model using m6A RNA methylation regulators in prostate cancer: comprehensive bioinformatic analysis and histological validation

BackgroundEpigenetic reprogramming reportedly has a crucial role in prostate cancer (PCa) progression. RNA modification is a hot topic in epigenetics, and N6-methyladenosine (m6A) accounts for approximately 60% of RNA chemical modifications. The aim of this study was to evaluate the m6A modification patterns in PCa patients and construct a risk prediction model using m6A RNA regulators.Materials and methodsAnalyses were based on the levels of 25 m6A regulators in The Cancer Genome Atlas (TCGA). Differentially expressed gene (DEG) and survival analyses were performed according to TCGA-PRAD clinicopathologic and follow-up information. To detect the influences of m6A regulators and their DEGs, consensus clustering analysis was performed, and tumor mutational burden (TMB) estimation and tumor microenvironment (TME) cell infiltration were assessed. mRNA levels of representative genes were verified using clinical PCa data.ResultsDiverse expression patterns of m6A regulators between tumor and normal (TN) tissues were detected regarding Gleason score (GS), pathological T stage (pT), TP53 mutation, and survival comparisons, with HNRNPA2B1 and IGFBP3 being intersecting genes. HNRNPA2B1 was upregulated in advanced stages (GS > 7, pT3, HR > 1, and TP53 mutation), as verified using clinical PCa tissue. Three distinct m6A modification patterns were identified through consensus clustering analysis, but no significant difference was found among these groups in recurrence-free survival (RFS) analysis. Six DEGs of m6A clusters (m6Aclusters) were screened through univariate Cox regression analysis. MMAB and PAIAP2 were intersecting genes for the five clinical factors. MMAB, which was upregulated in PCa compared with TN, was verified using clinical PCa samples. Three distinct subgroups were established according to the 6 DEGs. Cluster A involved the most advanced stages and had the poorest RFS. The m6A score (m6Ascore) was calculated based on the 6 genes, and the low m6Ascore group showed poor RFS with a negative association with infiltration for 16 of 23 immune-related cells.ConclusionWe screened DEGs of m6Aclusters and identified 6 genes (BAIAP2, TEX264, MMAB, JAGN1, TIMM8AP1, and IMP3), with which we constructed a highly predictive model with prognostic value by dividing TCGA-PRAD into three distinct subgroups and performing m6Ascore analysis. This study helps to elucidate the integral effects of m6A modification patterns on PCa progression.

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

Astrocytoma (AS) is the most ubiquitous primary malignancy of the central nervous system (CNS). The vital involvement of the N6-methyladenosine (m6A) RNA modification in the growth of multiple human tumors is known. This study entailed probing m6A regulators with AS prognosis to construct a risk prediction model (RS) for potential clinical use. A total of 579 AS patients' (of the Chinese Glioma Genome Atlas,CGGA) data and the expression of 12 published m6A-related genes were included in this study. Cox and selection operator (LASSO) regression analyses for independent prognostic factors and multifactor Cox analysis established an R.S. model to predict the AS patient prognosis. This was subject to verification employing 331 samples from the TCGA data set followed by gene ontology and pathway enrichment study with gene set enrichment analysis (GSEA). The R.S. constructed with three m6A genes inclusive of WTAP, RBM15, and YTHDF2 emerged as independent prognostic factors in AS patients with vital involvement in the advancement and development of the malignancy. In a nutshell, this work reported an m6A-related gene risk model to predict the prognosis of AS patients to pave the way for discerning diagnostic and prognostic biomarkers. Further corroboration employing relevant wet-lab assays of this model is warranted.

The methylation modification of m6A regulators contributes to the prognosis of ovarian cancer.

BackgroundOvarian cancer (OV) is the leading cause of death in gynecological cancer. The dysregulation of N6-methyladenosine (m6A) modification is commonly found in cancers. However, there is a lack of research into m6A RNA methylation regulators in OV.MethodsThe RNA-Seq of 379 OV tissues and 88 healthy ovarian tissues was downloaded from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases, respectively. A Gene Ontology (GO) functional analysis was performed to verify the function of m6A RNA methylation regulators. Kaplan-Meier (K-M) curves and the log-rank (Mantel-Cox) test were used for the survival analysis. A Cox regression analysis was used to identify the genes related to overall survival (OS) and build the prediction model.Resultsm6A RNA methylation regulators were dysregulated in OV tissues compared with normal tissues (P<0.05), and patients with a high expression of KIAA1429 and YTHDC2 had a poor prognosis (P<0.05). A prognostic model was constructed based on the m6A RNA methylation regulators. Based on the risk signature, the patients were classified into high- and low-risk groups. The low-risk group’s OS rate was significantly better than that of the high-risk group. The validity and accuracy of the prognostic model were verified by using TCGA and Gene Expression Omnibus (GEO) datasets, and the risk score from the prognostic model acted as an independent prognostic indicator in predicting the survival of OV patients.Conclusionsm6A RNA methylation regulators were dysregulated in OV tissues. More importantly, the prognostic model comprising the five selected m6A RNA methylation regulators could be a valuable tool for predicting the prognosis of OV patients.

Four m6A RNA Methylation Gene Signatures and Their Prognostic Values in Lung Adenocarcinoma.

Introduction: Evidence demonstrates that N6-methyladenosine (m6A) modification plays an increasingly important role in the development of tumors. The aim of this study is to explore the expression of m6A-related regulators in lung adenocarcinoma, identify the effect of altered key factors modified by m6A on the prognosis of patients with lung adenocarcinoma. Methods: A comprehensive analysis of m6A-related gene expressions in patients with lung adenocarcinoma based on The Cancer Genome Atlas database (TCGA) and the CBioPortal database. A prognostic risk score was established based on a linear combination of 4 key gene expression levels using the regression coefficients of the multivariate Cox regression models. Immunohistochemical staining analysis was performed to validate the relationship between the protein expression level of m6A regulators and the prognosis of patients retrospectively. The possible mechanism and prospective therapeutic targets of these key m6A molecules were explored by the M6A2Target database and the CMAP database. Results: Mutation pattern analysis revealed that 32% of 656 patients had genetic alterations. Four genes (writer: methyltransferase like 3 [METTL3] and three readers: insulin like growth factor 2 mRNA binding protein 2 [IGF2BP2], heterogeneous nuclear ribonucleoprotein C [HNRNPC], and heterogeneous nuclear ribonucleoprotein A2/B1 [HNRNPA2B1]) were selected to construct a survival risk prediction model and the results of immunohistochemical staining showed that the expression of these four m6A genes was significantly different between lung adenocarcinoma tissues and normal lung tissues (p < .01). The possible downstream genes and prospective therapeutic targets of these four m6A key molecules were discovered. Conclusion: These four m6A RNA methylation regulators may be effective prognostic and diagnostic factors which can provide auxiliary diagnosis and prognosis of lung adenocarcinoma.

The expression of m6A regulators correlated with the immune microenvironment plays an important role in the prognosis of pancreatic ductal adenocarcinoma.

The relationship between N6-methyladenosine (m6A) RNA methylation regulators and the tumor immune microenvironment has been extensively studied. Nevertheless, the potential function of m6A regulators in the tumor immune landscape of pancreatic ductal adenocarcinoma (PDAC) remains to be fully elucidated. Here, we systematically evaluated the expression of 19 m6A regulators in PDAC patients from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Utilizing consensus clustering, the PDAC patients were segmented into two subgroups according to the expression of 19 m6A regulators. A prognostic risk signature of 5 m6A methylation regulators (ALKBH5, IGF2BP2, IGF2BP3, LRPPRC, and KIAA1429) was then built, and the PDAC patients were divided into high-risk and low-risk groups. Subsequently, differences in independent prognostic parameters, risk score distribution, survival, and cluster analysis between high-risk and low-risk groups were analyzed. We found two subgroups with dramatically different immune landscapes and prognoses. Subsequently, differences in independent prognostic parameters, risk score distribution, survival, and cluster analysis between the high-risk and low-risk groups were found. Moreover, these gene signatures displayed good discriminative performances in the GEO datasets. We also found that the risk score was positively correlated with the tumor mutation burden (TMB), and the TMB value was higher in the high-risk scoring group. The low-risk scoring group was linked by a stronger response to anti-programmed cell death ligand 1 (anti-PD-L1) immunotherapy and clinical advantages in the immunotherapeutic advanced urothelial cancer (IMvigor210) cohort. Ultimately, we found that these 5 m6A regulators had a fatal regulatory role on the tumor immune microenvironment in PDAC patients. The construction signature based on the m6A regulators may be crucial regulators of the tumor immune microenvironment in PDAC, providing a new approach to improving the immunotherapy strategy for PDAC patients.

Integrated Clinical and Prognostic Analysis of the m6A RNA Methylation Regulator YTHDF3 in Pan-Cancer and its Correlation with Cancer Cell Proliferation.

Background: N6-methyladenosine (m6A) is the most abundant and extensive chemical modification of mammalian RNA molecules. Although numerous studies have investigated m6A methylation-related genes, to the best of our knowledge, none have examined the expression patterns of YTH N6-methyladenosine RNA binding protein 3 (YTHDF3) across cancers. Methods: Using various publicly available datasets, we searched for a potential carcinogenic role of YTHDF3 in 33 tumor types. Furthermore, the clinicopathological parameters, clinical prognostic value, enrichment analysis, mutations, microsatellite instability (MSI), tumor mutation burden (TMB), levels of infiltrating cells, and related immune checkpoint genes were included. Finally, we performed a validation analysis using existing clinical samples and proliferation-related functional experiments. Results: YTHDF3 is highly expressed in most cancer types and associated with patient prognosis in certain tumors. The ROC analysis suggested that YTHDF3 has high diagnostic value in 13 types of cancer. Furthermore, we found that the genes associated with YTHDF3 were enriched for translation initiation and mRNA metabolic processes. The results of the GSEA enrichment suggest that YTHDF3 may be associated with different pathways in cells in various tumor types. We further analyzed the correlations between YTHDF3 expression and MSI, TMB, and immune checkpoint genes. YTHDF3 also possibly exerts important antitumor immunotherapy effects. Additionally, the results of the immune analysis using TIMER showed that high YTHDF3 expression levels in pan-cancer tissues were related to an immunosuppressive microenvironment. Finally, we experimentally demonstrated that both overexpression and downregulation of YTHDF3 can affect cancer cell proliferation rates. Conclusion: YTHDF3 is a promising biomarker for cancer diagnosis. This study provides the first comprehensive pan-cancer report on YTHDF3 and increases our understanding of its oncogenic role in different tumors.

Characterization of m6A RNA Methylation Regulators Predicts Survival and Immunotherapy in Lung Adenocarcinoma.

N6-methyladenosine (m6A) RNA modification is a reversible mechanism that regulates eukaryotic gene expression. Growing evidence has demonstrated an association between m6A modification and tumorigenesis and response to immunotherapy. However, the overall influence of m6A regulators on the tumor microenvironment and their effect on the response to immunotherapy in lung adenocarcinoma remains to be explored. Here, we comprehensively analyzed the m6A modification patterns of 936 lung adenocarcinoma samples based on 24 m6A regulators. First, we described the features of genetic variation in these m6A regulators. Many m6A regulators were aberrantly expressed in tumors and negatively correlated with most tumor-infiltrating immune cell types. Furthermore, we identified three m6A modification patterns using a consensus clustering method. m6A cluster B was preferentially associated with a favorable prognosis and enriched in metabolism-associated pathways. In contrast, m6A cluster A was associated with the worst prognosis and was enriched in the process of DNA repair. m6A cluster C was characterized by activation of the immune system and a higher stromal cell score. Surprisingly, patients who received radiotherapy had a better prognosis than patients without radiotherapy only in the m6A cluster C group. Subsequently, we constructed an m6A score model that qualified the m6A modification level of individual samples by using principal component analysis algorithms. Patients with high m6A score were characterized by enhanced immune cell infiltration and prolonged survival time and were associated with lower tumor mutation burden and PD-1/CTLA4 expression. The combination of the m6A score and tumor mutation burden could accurately predict the prognosis of patients with lung adenocarcinoma. Furthermore, patients with high m6A score exhibited greater prognostic benefits from radiotherapy and immunotherapy. This study demonstrates that m6A modification is significantly associated with tumor microenvironment diversity and prognosis. A comprehensive evaluation of m6A modification patterns in single tumors will expand our understanding of the tumor immune landscape. In addition, our m6A score model demonstrated that the level of immune cell infiltration plays a significant role in cancer immunotherapy and provides a basis to increase the efficiency of current immune therapies and promote the clinical success of immunotherapy.

Analysis and identification of m6A RNA methylation regulators in metastatic osteosarcoma

Osteosarcoma (OS) is characterized by rapid growth and early metastasis. However, its mechanism remains unclear. N6-methyladenosine (m6A) modification and its regulatory factors play essential roles in most cancers, including OS. In this study, we screened out 21 m6A modifiers using the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, followed by the identification of the critical m6A methylation modifiers. The results revealed that the expression levels of three m6A methylation regulators, namely RBM15, METTL3, and LRPPRC, were associated with the low survival rate of patients with OS. We further studied the independent prognostic factors by performing univariate and multivariate Cox analyses and found that metastasis was an independent prognostic factor for patients with OS. Furthermore, we found for the first time that RBM15 was specific for metastatic OS rather than non-metastatic OS. Moreover, the significant overexpression of RBM15 was validated in metastatic OS cell lines and in actual human clinical specimens. We also revealed that RBM15 promoted the invasion, migration, and metastasis of OS cells through loss-functional and gain-functional experiments and an animal metastatic model. In conclusion, RBM15 has a high correlation with OS metastasis formation and the decreased survival rate of patients with OS, and this may serve as a useful biomarker for predicting metastasis and prognosis of patients with OS.

The Regulators Associated With N6-Methyladenosine in Lung Adenocarcinoma and Lung Squamous Cell Carcinoma Reveal New Clinical and Prognostic Markers.

N6-methyladenosine (m6A) methylation is of significant importance in the initiation and progression of tumors, but how specific genes take effect in different lung cancers still needs to be explored. The aim of this study is to analyze the correlation between the m6A RNA methylation regulators and the occurrence and development of lung cancer. The data of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) were obtained through the TCGA database. We systematically analyzed the related pathological characteristics and prognostic factors by applying univariate and multivariate Cox regression, as well as LASSO Cox regression. Some of 23 m6A regulators are identified as having high expression in lung cancer. In addition, risk score has been shown to be an independent prognostic factor in lung cancer. Our research not only fully reveals that m6A regulators and clinical pathological characteristics are potentially useful with respect to survival and prognosis in different lung tumors but also can lay a theoretical root for the treatment for lung cancer—notably, to point out a new direction for the development of treatment.

Analysis and validation of m6A regulatory network: a novel circBACH2/has-miR-944/HNRNPC axis in breast cancer progression

BackgroundN6-methyladenosine (m6A), the most abundant and reversible modification of mRNAs in eukaryotes, plays pivotal role in breast cancer (BC) tumorigenesis and progression. Circular RNAs (circRNAs) can act as tumor promoters or suppressors by microRNA (miRNA) sponges in BC. However, the underlying mechanism of circRNAs in BC progression via regulating m6A modulators remains unclear.MethodsPrognostic m6A RNA methylation regulators were identified in 1065 BC patients from The Cancer Genome Atlas (TCGA) project. Differentially expressed (DE) miRNAs and DE circRNAs were identified between BC and normal samples in TCGA and GSE101123, respectively. MiRNA-mRNA interactive pairs and circRNA-miRNA interactive pairs were verified by MiRDIP and Circular RNA Interactome. GSEA, KEGG, and ssGSEA were executed to explore the potential biological and immune functions between HNRNPC-high and HNRNPC-low expression groups. qRT-PCR and Western blot were used to quantify the expression of HNRNPC and circBACH2 in MCF-7 and MDA-MB-231 cells. The proliferation of BC cells was assessed by CCK-8 and EdU assay.Results2 m6A RNA methylation regulators with prognostic value, including HNRNPC and YTHDF3, were identified in BC patients. Then, the regulatory network of circRNA-miRNA-m6A modulators was constructed, which consisted of 2 DE m6A modulators (HNRNPC and YTHDF3), 12 DE miRNAs, and 11 DE circRNAs. Notably, BC patients with high expression of HNRNPC and low expression of hsa-miR-944 were correlated with late clinical stages and shorter survival times. Besides, the results from the KEGG inferred that the DE HNRNPC was associated with the MAPK signaling pathway in BC. Moreover, the circBACH2 (hsa_circ_0001625) was confirmed to act as hsa-miR-944 sponge to stimulate HNRNPC expression to promote BC cell proliferation via MAPK signaling pathway, thus constructing a circBACH2/hsa-miR-944/HNRNPC axis in BC.ConclusionsOur findings decipher a novel circRNA-based m6A regulatory mechanism involved in BC progression, thus providing attractive diagnostic and therapeutic strategies for combating BC.

The N6-Methyladenosine- (m6A-) Associated Genes Act as Strong Key Biomarkers for the Prognosis of Pancreatic Adenocarcinoma.

Background Pancreatic adenocarcinoma (PAAD) has become the major cause of cancer-related deaths globally. The m6A (N6-methyladenosine) alteration plays a crucial function in carcinogenesis and tumor progression. The role of genes related to m6A and their expression level in pancreatic cancer is not identified yet. The objective of this research analysis is a demonstration of the m6A RNA methylation regulators based as biomarkers for the PAAD diagnosis. Methods About 23 extensively reported m6A RNA methylation regulators were identified through the Cancer Genome Atlas (TCGA) database. This identification was based on consensus clustering analysis, protein-protein integration (PPI) analysis, risk prognostic model, Cox-regression analysis, String Spearman analysis, and LASSO Cox-regression. Results Herein, we conclude that 23 m6A methylation regulators have a strong link with the clinical and molecular characteristics of PAAD. The three subgroups (1/2) of pancreatic adenocarcinoma were identified using the clustering of 23 m6A regulators. Subgroup cluster 2 had a lower survival rate than the subgroup of cluster 1, and the difference in grades between the two groups was substantial. An assessment was performed using the 23 reported m6A methylation regulators. Eight of these can be used as independent PAAD prognostic markers. The consequences of variable IGF2BP3 expression in PAAD were then investigated further. Conclusions The key finding of this study was that the m6A methylation regulator gene has the main role in pancreatic tumors, and it may be used as a biomarker in the prognosis of the PAAD and for therapy purposes.

Comprehensive Analysis of m6A RNA Methylation Regulators and the Immune Microenvironment to Aid Immunotherapy in Pancreatic Cancer.

Pancreatic cancer (PAAD) is one of the most malignant cancers and immune microenvironment has been proved to be involved in pathogenesis of PAAD. m6A modification, related to the expression of m6A regulators, participates in the development of multiple cancers. However, the correlation between m6A regulators and immune microenvironment was largely unknown in PAAD. And because of the small sample size of pancreatic cancer in the TCGA database, it is not enough to draw a convincing conclusion. In the present study, we downloaded seven pancreatic cancer datasets with survival data and removed batch effects among these datasets to be used as the PAAD cohort to analyze the immune landscape of PAAD and the expression pattern of m6A regulators and divided the integrated dataset into cluster 1 and cluster 2 by consensus clustering for m6A regulators. Lower m6A regulators were found to be related to higher immune cell infiltration and a better survival. Moreover, we identified six m6A regulators and constructed the prognostic signature of m6A regulators. Patients with low-risk score had a higher response to immune checkpoint inhibitor and a longer overall survival. To figure out the underlying mechanism, we analyzed the cancer immunity cycle, most altered genes, gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) in risk subtypes. In summary, the present study proved m6A regulators modulated the PAAD immune microenvironment. And risk scores served as predictive indicator for immunotherapy and played a prognostic role for PAAD patients. Our study provided novel therapeutic targets to improve immunotherapy efficacy.

Comprehensive Analysis of m6A RNA Methylation Regulators in the Prognosis and Immune Microenvironment of Multiple Myeloma.

BackgroundN6-methyladenosine is the most abundant RNA modification, which plays a prominent role in various biology processes, including tumorigenesis and immune regulation. Multiple myeloma (MM) is the second most frequent hematological malignancy.Materials and MethodsTwenty-two m6A RNA methylation regulators were analyzed between MM patients and normal samples. Kaplan–Meier survival analysis and least absolute shrinkage and selection operator (LASSO) Cox regression analysis were employed to construct the risk signature model. Receiver operation characteristic (ROC) curves were used to verify the prognostic and diagnostic efficiency. Immune infiltration level was evaluated by ESTIMATE algorithm and immune-related single-sample gene set enrichment analysis (ssGSEA).ResultsHigh expression of HNRNPC, HNRNPA2B1, and YTHDF2 and low expression of ZC3H13 were associated with poor survival. Based on these four genes, a prognostic risk signature model was established. Multivariate Cox regression analysis demonstrated that the risk score was an independent prognostic factor of MM. Enrichment analysis showed that cell cycle, immune response, MYC, proteasome, and unfold protein reaction were enriched in high-risk MM patients. Furthermore, patients with higher risk score exhibited lower immune scores and lower immune infiltration level.ConclusionThe m6A-based prognostic risk score accurately and robustly predicts the survival of MM patients and is associated with the immune infiltration level, which complements current prediction models and enhances our cognition of immune infiltration.

Identification of IGF2BP3 as an Adverse Prognostic Biomarker of Gliomas.

N6-methyladenosine (m6A) RNA modification can alter gene expression and function by regulating RNA splicing, stability, translocation, and translation. It is involved in various types of cancer. However, its role in gliomas is not well known. This study aimed to determine the prognostic value of the m6A RNA methylation regulator in gliomas and investigate the underlying mechanisms of the aberrant expression of m6A-related genes.mRNA expression profiles and clinical information of 448 glioma samples were obtained from The Cancer Genome Atlas and cBioportal. The expression of m6A-related genes in normal controls and low-grade glioma and glioblastoma was obtained from Gene Expression Profiling Interactive Analysis. Further, m6A-related gene expression and its relationship with prognosis were obtained through The Chinese Glioma Genome Atlas (CGGA). Multivariate Cox regression analyses were performed, and a nomogram was built with potential risk factors based on a multivariate Cox analysis to predict survival probability. Online tools such as Gene Set Enrichment Analysis, STRING, Cytoscape, and Molecular Complex Detection were applied for bioinformatics analysis and to investigate the underlying mechanisms of the aberrant expression of m6A-related genes. The multivariate Cox regression analysis found that higher expression levels of YTHDC2 and insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3, also called IMP3) were independent negative and positive prognostic factors for overall survival (OS), respectively. Data from the CGGA database showed that IGF2BP3 expression increased when the tumor grade increased. Receiver operating characteristic (ROC) curve was used to evaluate the predictive specificity and sensitivity. The area under the ROC curve indicated that the OS prediction was 0.92 (1-year) and 0.917 (3-years), indicating that m6A-related genes could predict patient survival. In addition, IGF2BP3 was closely related to the shorter survival period of patients. Copy number variation and DNA methylation, but not somatic mutations, might contribute to the abnormal upregulation of IGF2BP3 in gliomas. Significantly altered genes were identified, and the protein–protein interaction network was constructed. Based on the data presented, our study identified several m6A-related genes, especially IGF2BP3, that could be potential prognostic biomarkers of gliomas. The study unveiled the potential regulatory mechanism of IGF2BP3 in gliomas.

An integrated model of FTO and METTL3 expression that predicts prognosis in lung squamous cell carcinoma patients.

BackgroundLung squamous cell carcinoma (LUSC) approximately accounts for a third of lung cancers. However, the role of N6-methyladenosine (m6A) in LUSC remains largely unknown according to previous studies.MethodsIn this study, we investigated the mutations, copy number variants (CNVs), expression of 20 m6A RNA methylation regulators, and clinical data from The Cancer Genome Atlas-LUSC (TCGA-LUSC). These data were used for the training cohort of screening potential biomarkers. The prognostic model of m6A RNA methylation regulators was constructed. A receiver operating characteristic (ROC) analysis was undertaken to determine the area under the curves (AUCs) (for 3- and 5-year survival) for the model. Additionally, the accuracy of the two-gene model was confirmed with external data verifications. Combined two-gene model and clinincal information were performed to construct a nomogram to predict patient’s prognostic risk assessment.ResultsFat mass- and obesity-associated protein (FTO) and methyltransferase-like 3 (METTL3) were identified as potential prognostic biomarkers to evaluate benign and malignant tumors and prognosticate. The following prognostic model of m6A RNA methylation regulators was constructed: risk score = 0.162 × FTO − 0.069 × METTL3. Patients in low-risk group [median overall survival (mOS), 43.4 months] had longer survival than those with high-risk (mOS, 67.3 months) with P=0.0023. The smoking grade and risk score could be independent prognostic factors (P=0.00098 and P=0.0014, respectively). Ultimately, a nomogram was developed to assist clinicians to predict clinical outcomes.ConclusionsFTO and METTL3 are potential prognostic biomarkers of LUSC. The two-gene model’s use of prognostic risk scores may provide guidance in the selection of therapeutic strategies.