m6A RNA Methylation Regulators Research Articles

A Risk Score Model Incorporating Three m6A RNA Methylation Regulators and a Related Network of miRNAs-m6A Regulators-m6A Target Genes to Predict the Prognosis of Patients With Ovarian Cancer.

Ovarian cancer (OC) is the leading cause of cancer-related death among all gynecological tumors. N6-methyladenosine (m6A)-related regulators play essential roles in various tumors, including OC. However, the expression of m6A RNA methylation regulators and the related regulatory network in OC and their correlations with prognosis remain largely unknown. In the current study, we obtained the genome datasets of OC from GDC and GTEx database and analyzed the mRNA levels of 21 key m6A regulators in OC and normal human ovarian tissues. The expression levels of 7 m6A regulators were lower in both the OC tissues and the high-stage group. Notably, the 5-year survival rate of patients with OC presenting low VIRMA expression or high HNRNPA2B1 expression was higher than that of the controls. Next, a risk score model based on the three selected m6A regulators (VIRMA, IGF2BP1, and HNRNPA2B1) was built by performing a LASSO regression analysis, and the moderate accuracy of the risk score model to predict the prognosis of patients with OC was examined by performing ROC curve, nomogram, and univariate and multivariate Cox regression analyses. In addition, a regulatory network of miRNAs-m6A regulators-m6A target genes, including 2 miRNAs, 3 m6A regulators, and 47 mRNAs, was constructed, and one of the pathways, namely, miR-196b-5p-IGF2BP1-PTEN, was initially validated based on bioinformatic analysis and assay verification. These results demonstrated that the risk score model composed of three m6A RNA methylation regulators and the related network of miRNAs-m6A regulators-m6A target genes is valuable for predicting the prognosis of patients with OC, and these molecules may serve as potential biomarkers or therapeutic targets in the future.

Identification of the Role and Clinical Prognostic Value of Target Genes of m6A RNA Methylation Regulators in Glioma.

m6A RNA methylation regulators can regulate the growth, progression, and invasion of glioma cells by regulating their target genes, which provides a reliable support for the m6A regulator–target axes as the novel therapeutic targets and clinical prognostic signature in glioma. This study aimed to explore the role and prognostic value of m6A RNA methylation regulators and their targets. Expression profiles and clinicopathological data were obtained from the Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Clinical Proteome Tumor Analysis Consortium (CPTAC) datasets. Differential expression and correlation analyses were performed between normal and glioma tissues at mRNA and protein levels. Univariate Cox regression, survival, and Lasso Cox regression analyses were conducted to identify and establish the prognostic gene signature. Kaplan–Meier curve, multivariate Cox regression analysis, and ROC were utilized to evaluate the prognostic capacity of the prognostic gene signature. The correlation analysis, systematic bioinformatics analysis, and cell experiment were performed to further understand the potential underlying molecular mechanisms and drug sensitivity. Our results suggested that IGF2BP2, KIAA1429, METTL16, and METTL3, as well as 208 targets are involved in the occurrence of glioma, GBM, and LGG. YTHDF1 and 78 targets involved the occurrence of glioma and GBM, not LGG, among which 181 genes were associated with overall survival. From other findings and our cell experiment results, we demonstrated that METTL3 can activate Notch pathway and facilitate glioma occurrence through regulating its direct targets NOTCH3, DLL3, and HES1, and Notch pathway genes may serve as the potential treatment targets for glioma. Our study established and validated a seven-gene signature comprising METTL3, COL18A1, NASP, PHLPP2, TIMP1, U2AF2, and VEGFA, with a good capability for predicting glioma survival, which may guide therapeutic customization and clinical decision-making. These genes were identified to influence 81 anticancer drug responses, which further contributes to the early phase clinical trials of drug development.

Integrative Analysis of Biomarkers Through Machine Learning Identifies Stemness Features in Colorectal Cancer

Background: Cancer stem cells (CSCs), which are characterized by self-renewal and plasticity, are highly correlated with tumor metastasis and drug resistance. To fully understand the role of CSCs in colorectal cancer (CRC), we evaluated the stemness traits and prognostic value of stemness-related genes in CRC.Methods: In this study, the data from 616 CRC patients from The Cancer Genome Atlas (TCGA) were assessed and subtyped based on the mRNA expression-based stemness index (mRNAsi). The correlations of cancer stemness with the immune microenvironment, tumor mutational burden (TMB), and N6-methyladenosine (m6A) RNA methylation regulators were analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to identify the crucial stemness-related genes and modules. Furthermore, a prognostic expression signature was constructed using the Lasso-penalized Cox regression analysis. The signature was validated via multiplex immunofluorescence staining of tissue samples in an independent cohort of 48 CRC patients.Results: This study suggests that high-mRNAsi scores are associated with poor overall survival in stage IV CRC patients. Moreover, the levels of TMB and m6A RNA methylation regulators were positively correlated with mRNAsi scores, and low-mRNAsi scores were characterized by increased immune activity in CRC. The analysis identified 34 key genes as candidate prognosis biomarkers. Finally, a three-gene prognostic signature (PARPBP, KNSTRN, and KIF2C) was explored together with specific clinical features to construct a nomogram, which was successfully validated in an external cohort.Conclusion: There is a unique correlation between CSCs and the prognosis of CRC patients, and the novel biomarkers related to cell stemness could accurately predict the clinical outcomes of these patients.

Expression pattern and prognostic value of N6-methyladenosine RNA methylation key regulators in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is still one of the most common malignancies worldwide. The accuracy of biomarkers for predicting the prognosis of HCC and the therapeutic effect is not satisfactory. N6-methyladenosine (m6A) methylation regulators play a crucial role in various tumours. Our research aims further to determine the predictive value of m6A methylation regulators and establish a prognostic model for HCC. In this study, the data of HCC from The Cancer Genome Atlas (TCGA) database was obtained, and the expression level of 15 genes and survival was examined. Then we identified two clusters of HCC with different clinical factors, constructed prognostic markers and analysed gene set enrichment, proteins’ interaction and gene co-expression. Three subgroups by consensus clustering according to the expression of the 13 genes were identified. The risk score generated by five genes divided HCC patients into high-risk and low-risk groups. In addition, we developed a prognostic marker that can identify high-risk HCC. Finally, a novel prognostic nomogram was developed to accurately predict HCC patients’ prognosis. The expression levels of 13 m6A RNA methylation regulators were significantly upregulated in HCC samples. The prognosis of cluster 1 and cluster 3 was worse. Patients in the high-risk group show a poor prognosis. Moreover, the risk score was an independent prognostic factor for HCC patients. In conclusion, we reveal the critical role of m6A RNA methylation modification in HCC and develop a predictive model based on the m6A RNA methylation regulators, which can accurately predict HCC patients’ prognosis and provide meaningful guidance for clinical treatment.

Construction and Analysis of a Colorectal Cancer Prognostic Model Based on N6-Methyladenosine-Related lncRNAs.

Given the relatively poor understanding of the expression and functional effects of the N6-methyladenosine (m6A) RNA methylation on colorectal cancer (CRC), we attempted to measure its prognostic value and clinical significance. We comprehensively screened 37 m6A-related prognostic long non-coding RNAs (lncRNAs) with significant differences in expression based on 21 acknowledged regulators of m6A modification and data on 473 colorectal cancer tissues and 41 para-cancer tissues obtained from the TCGA database. Accordingly, we classified 473 CRC patients into two clusters by consensus clustering on the basis of significantly different survival outcomes. We also found a potential correlation between m6A-related prognostic lncRNAs and BRAF-KRAS expression, as well as immune cell infiltration. Then, we established a prognostic model by selecting 16 m6A-related prognostic lncRNAs via LASSO Cox analysis and grouped the CRC patients into low- and high-risk groups to calculate risk scores. Then, we performed stratified sampling to validate and confirm our model by categorising the 473 samples into a training group (N = 208) and a testing group (N = 205) in a 1:1 ratio. The survival curve showed a distinct clinical outcome in the low- and high-risk subgroups. We reconfirmed the reliability and independence of the prognostic model through various measures: risk curve, heat map and univariate and multivariate Cox analyses. To ensure that the outcomes were applicable to clinical settings, we performed stratified analyses on different clinical features, such as age, lymph node status and clinical stage. CRC patients with downregulated m6A-related gene expression, lower immune score, distant metastasis, lymph node metastasis or more advanced clinical staging had higher risk scores, indicating less-desirable outcomes. Moreover, we explored the immunology of colorectal cancer cells. The risk score showed positive correlations with eosinophils, M2 macrophages and neutrophils. In summary, our effort revealed the significance of m6A RNA methylation regulators in colorectal cancer, and the prognostic model we constructed may be used as an essential reference for predicting the outcome of CRC patients.

Gene Signatures and Prognostic Values of N6-Methyladenosine Related Genes in Ovarian Cancer.

N6-Methyladenosine (m6A) is one of the most prominent modification regulating RNA processing and metabolism. Increasing studies have illuminated the vital role of m6A methylation in carcinogenesis. However, little is known about the interaction between m6A-related genes and survival of ovarian cancer (OC) patients. The purpose of this study was to obtain more reliable m6A-related genes that could be used as prognostic markers of OC using bioinformatics analysis performed on the RNA-seq data of OC. Gene expression datasets of all m6A-related genes as well as corresponding clinical data were obtained from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases. We detected differential expressed m6A-related candidate genes as well as their relationship and interaction. m6A RNA methylation regulator ALKBH5 and 35 m6A-related genes are dysregulated in OC. A gene set that could be used as a potential independent prognostic risk feature was further screened including NEBL, PDGFRA, WDR91, and ZBTB4. The results of mRNA expression analysis by PCR were consistent with those of bioinformatics analysis. We applied consensus clustering analysis on the expression of the four prognostic genes and obtained four OC subgroups TM1-TM4. There were significant differences in age, stage and grade among the subgroups, and the overall survival (OS) as well as Disease-free survival (DFS) of TM2 group were shorter than those of the other three groups. Further GO and KEGG enrichment analysis indicated that these differential genes were closely related to biological processes and key signaling pathways involved in OC. In summary, our study has indicated that m6A-related genes are key factors in the progression of OC and have potential effects on the prognostic stratification of OC and the development of treatment strategies.

N6-methyladenosine (m6A) RNA methylation regulator SNRPC is a prognostic biomarker and is correlated with immunotherapy in hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is one of the most common malignancies in the world, and due to its complex pathogenic factors, its prognosis is poor. N6-methyladenosine (m6A) RNA methylation plays an important role in the tumorigenesis, progression, and prognosis of many tumors. The m6A RNA methylation regulator small nuclear ribonucleoprotein polypeptide C (SNRPC), which encodes one of the specific protein components of the U1 small nuclear ribonucleoprotein (snRNP) particle, has been proven to be related to the prognosis of patients with HCC. However, the effect of SNRPC on the tumor microenvironment and immunotherapy in HCC remains unclear.Case presentationThe HCC RNA-seq profiles in The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases, including 421 LIHC and 440 LIRI-JP samples, respectively, were used in this study. Both the expression of SNRPC in HCC was upregulated in the TCGA and ICGC databases compared to normal tissues. Next, the expression of SNRPC was validated as a risk factor for prognosis by Kaplan-Meier analysis and employed to establish a nomogram with T pathologic stage. By gene set variation (GSVA) analysis and gene set enrichment (GSEA) analysis, we found that SNRPC was mainly related to protein metabolism and the immune process. Furthermore, the estimation of stromal and immune cells in malignant tumor tissues using expression (ESTIMATE), microenvironment cell population counter (MCP-counter), and single sample GSEA (ssGSEA) algorithms revealed that the high-SNRPC group had a lower stromal score, lower abundance of endothelial cells and fibroblasts, and lower immune infiltration. Ultimately, a tumor immune dysfunction and exclusion (TIDE) analysis revealed that patients in the low-SNRPC group may be more sensitive to immune checkpoint inhibitor therapy.ConclusionSNRPC could serve as a promising prognostic and immunotherapeutic marker in HCC and might contribute to new directions and strategies for HCC treatment.

M6A RNA Methylation Regulator YTHDF1 Correlated With Immune Microenvironment Predicts Clinical Outcomes and Therapeutic Efficacy in Breast Cancer.

Objective: Increasing evidence highlights the roles of N6-methyladenosine (m6A) and its regulators in oncogenesis. Herein, this study observed the associations of m6A regulators with breast cancer.Methods: RNA-seq profiles of breast cancer were retrieved from the Cancer Genome Atlas (TCGA) database. The expression of m6A regulators was analyzed in tumor and normal tissues. Their expression correlations were analyzed by Spearson test. Overall survival (OS) analysis of these regulators was then presented. Gene set enrichment analysis (GSEA) was performed in high and low YTHDF1 expression groups. The correlations of YTHDF1 expression with immune cells and tumor mutation burden (TMB) were calculated in breast cancer samples. Somatic variation was assessed in high and low YTHDF1 expression groups.Results: Most of m6A regulators were abnormally expressed in breast cancer compared to normal tissues. At the mRNA levels, there were closely relationships between them. Among them, YTHDF1 up-regulation was significantly related to undesirable prognosis (p = 0.025). GSEA results showed that high YTHDF1 expression was associated with cancer-related pathways. Furthermore, YTHDF1 expression was significantly correlated with T cells CD4 memory activated, NK cells activated, monocytes, and macrophages. There were higher TMB scores in YTHDF1 up-regulation group than its down-regulation group. Missense mutation and non-sense mutation were the most frequent mutation types.Conclusion: Our findings suggested that dysregulated m6A regulator YTHDF1 was predictive of survival outcomes as well as response to immunotherapy of breast cancer, and were closely related to immune microenvironment.

Establishment and validation of prognosis predictive model using m6A RNA methylation regulators in children acute myeloid leukemia

Objective: To figure out the association between the expression of m6A RNA methylation regulators and the prognosis of children AML, and provide genetic markers for monitoring the progression and recurrence of AML. Methods: Twenty two m6A RNA methylation regulators were firstly analyzed using the data from Therapeutically Applicable Research To Generate Effective Treatments(TARGET) database and The Genotype-Tissue Expression(GTEx) database, Wilcoxon rank test was performed to analyze the differentially expression of m6A RNA methylation regulators between the AML and normal tissue, 296 AML children were divided into training cohort and validation cohort by simple random sampling method, Lasso regression was used to screen out the risk factors and the multivariate Cox regression was applied for establishing prognosis predicting model in training cohort. Kaplan-Meier survival curve, time-dependent ROC curve and multivariate Cox regression were used to estimate the efficiency of risk score calculated by predictive model in validation cohort. Results: Twenty one m6A genes were up regulated in AML compared to Normal patients. Five m6A RNA methylation regulators(ZC3H13, YTHDC2, HNRNPA2B1, METTL3, METTL5) were included in final predicting model. Risk score could independently predict the survival of AML patients in training cohort(HR:2.72, 95%CI: 1.54-4.81, P=0.000 6) and validation cohort(HR:2.01, 95%CI:1.14-3.50, P=0.016). Low-risk patients had better prognoses than high-risk patients both in training cohort(P=0.001 9) and validation cohort(P=0.023). Conclusion: This prognosis predicting model constructed by m6A RNA methylation regulators could independently predict the survival prognosis in AML children, and should be helpful for clinical therapy.

Landscape of Prognostic m6A RNA Methylation Regulators in Hepatocellular Carcinoma to Aid Immunotherapy.

Background: Hepatocellular carcinoma (HCC) is the sixth most common malignancy with a high mortality worldwide. N6-methyladenosine (m6A) may participate extensively in tumor progression.Methods: To reveal the landscape of tumor immune microenvironment (TIME), ESTIMATE analysis, ssGSEA algorithm, and the CIBERSORT method were used. Taking advantage of consensus clustering, two different HCC categories were screened. We analyzed the correlation of clustering results with TIME and immunotherapy. Then, we yielded a risk signature by systematical bioinformatics analyses. Immunophenoscore (IPS) was implemented to estimate the immunotherapeutic significance of risk signature.Results: The m6A-based clusters were significantly correlated with overall survival (OS), immune score, immunological signature, immune infiltrating, and ICB-associated genes. Risk signature possessed robust prognostic validity and significantly correlated with TIME context. IPS was employed as a surrogate of immunotherapeutic outcome, and patients with low-risk scores showed significantly higher immunophenoscores.Conclusion: Collectively, m6A-based clustering subtype and signature was a robust prognostic indicator and correlated with TIME and immunotherapy, providing novel insight into antitumor management and prognostic prediction in HCC.

Effects of m6A RNA methylation regulators on endometrial cancer.

BackgroundThe modification 6‐methyladenine (m6A) is the most common type in RNA methylation. Our study aims to explore the bioinformatic analysis of m6A in endometrial cancer.MethodsThe expression of 23 m6A RNA methylation regulators was compared through The Cancer Genome Atlas (TCGA) database among 406 endometrial tissue and 19 normal tissue samples. The Wilcoxon test was applied to compare the relationship between the clinicopathological characteristics and expression. Cox regressions were performed to identify the prognostic factors associated with overall survival. Gene ontology (GO) and Gene Set Enrichment Analysis (GSEA) were performed to evaluate the potential pathways.ResultsYTHDF2, HNRNPA2B1, HDRNPA2B1, YTHDF1, FMR1, IGF2BP3, METTL13, RBM15B, IGF2BP1, YTHDF3, YTHDC1, ZC3H13 IGF2BP2, KIAA1429, METTL14, RBMX, FTO, ALKBH5, and METTL16 were significantly abnormally expressed in endometrial cancer tissue samples. Both univariate and multivariate Cox regression analyses indicated that age, grade, and risk score were independent risk factors. High expression of FTO was associated with worse overall survival.ConclusionM6A RNA methylation regulators play vital role in endometrial cancer.

The methylation modification of m6A regulators contributes to the prognosis of head and neck squamous cell carcinoma.

BackgroundN6-methyladenosine (m6A) regulation is a common type of messenger ribonucleic acid (mRNA) modification, and has been proven to contribute to the malignant behavior of tumors. However, the expression pattern and the prognostic role of m6A RNA methylation regulators in head and neck squamous cell carcinoma (HNSCC) remains unclear.MethodsWe downloaded the data of 422 patients from The Cancer Genome Atlas (TCGA) database. The relationship between the expression level of m6A RNA methylation regulators and clinicopathological variables in HNSCC was analyzed by R language.ResultsThe m6A gene alteration was significantly correlated with tumor grade and tumor stage. Next, a least absolute shrinkage and selection operator (LASSO) Cox regression model was used to identify three m6A RNA methylation regulators [i.e., methyltransferase-like 14 (METTL14), methyltransferase-like 3 (METTL3), and heterogeneous nuclear ribonucleoproteins C1/C2 (HNRNPC)] to construct a risk signature. Based on the risk signature, the patients were classified into high- and low-risk groups. The overall survival (OS) rate of the low-risk group was significantly higher than that of the high-risk group. Additionally, the risk panel was an independent prognostic marker in HNSCC patients.ConclusionsThe m6A RNA methylation regulators are involved in HNSCC cancer progression. Further and more importantly, the risk signature comprising the three selected m6A RNA methylation regulators could serve as a potential marker to predict HNSCC patient outcomes.

Identification of an N6-methyladenosine (m6A)-related signature associated with clinical prognosis, immune response, and chemotherapy in primary glioblastomas.

BackgroundN6-methyladenosine (m6A) RNA methylation regulators play crucial role in tumorigenicity and progression. However, their biological significance in primary glioblastomas (GBM) has not been fully elucidated.MethodsIn the present study, we evaluated the 22 m6A RNA regulators using the integrated data of primary GBM samples from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. The different m6A modification patterns and m6A-related gene signature in primary GBM were distinguished by using principal component analysis. Single-sample gene set enrichment analysis was introduced to assess the relative level of immune infiltration. Gene set variation analysis was performed to calculate the enrichment score of the signaling pathways for different clusters. An m6A scoring scheme was established to evaluate the m6A modification pattern in individual tumors in order to predict prognosis and evaluate tumor microenvironment (TME) cell infiltration, immune response, and chemotherapy effect in primary GBM.ResultsTwo distinct m6A modification subgroups associated with different clinical features and biological pathways were identified among the 371 primary GBM. Based on 132 prognostic m6A phenotype-related differentially expressed genes (DEGs) between 2 m6A cluster subgroups, an m6A scoring model was constructed to assess the m6A modification pattern in individual tumors. The high-m6A score group was associated with better prognosis and immune response and worse chemotherapy effect.ConclusionsThe findings of the present study indicate the potential role of m6A modification in primary GBM, which will help enhance our understanding of TME characteristics, predict clinical prognosis, and provide important insight into effective immunotherapy and chemotherapy.

N6-Methyladenosine-Related RNA Signature Predicting the Prognosis of Ovarian Cancer.

N6-Methyladenosine (m6A) RNA methylation is the most universal mRNA modification in eukaryotic cells. M6A mRNA modification affects almost every phases of RNA processing, including splicing, decay, export, translation and expression. Several patents have reported the application of m6A mRNA modification in cancer diagnosis and treatment. Ovarian cancer is the leading cause of death among all gynecological cancers. It is urgent to identify new biomarkers for early diagnosis and prognosis of ovarian cancer. In the current study, we aimed to evaluate the m6A RNA methylation regulators and m6A related genes and establish a new gene signature panel for the prognosis of ovarian cancer. We downloaded the mutations data, FPKM data and corresponding clinical information of 373 patients with Ovarian Cancer (OC) from the TCGA database. We performed LASSO regression analysis and multivariate cox regression analysis to develop a risk-identifying gene signature panel. A total of 317 candidate m6A RNA methylation related genes were obtained. Finally, 12 - genes (WTAP, LGR6, ZC2HC1A, SLC4A8, AP2A1, NRAS, CUX1, HDAC1, CD79A, ACE2, FLG2 and LRFN1) were selected to establish the signature panel. We analyzed the genetic alterations of the selected 12 -genes in OC using cBioPortal database. Among the 373 patients, 368 patients have mutations. The results showed that all queried genes were altered in 137 of 368 cases (37.23%). The 12-gene signature panel was confirmed as an independent prognostic indicator (P =2.29E-18, HR = 1.699, 95% CI = 1.508-1.913). We established an effective m6A-related gene signature panel consisted of 12 -genes, which can predict the outcome of patients with OC. The high risk score indicates unfavorable survival. Our study provided novel insights into the relationship between m6A and OC. This gene signature panel will be helpful in identifying poor prognostic patients with OC and could be a promising prognostic indicator in clinical practice.

N6-Methyladenosine Regulators and Related LncRNAs Are Potential to be Prognostic Markers for Uveal Melanoma and Indicators of Tumor Microenvironment Remodeling.

Uveal melanoma (UM) is one of the most common malignant intraocular tumors in adults. Few studies have investigated the effect of N6-methyladenosine (m6A) RNA methylation regulators and related long noncoding RNAs (lncRNAs) on the tumor microenvironment (TME) and survival time of patients with UM. Based on the transcriptome and clinical data from The Cancer Genome Atlas, we systematically identified m6A regulators. Then, we constructed an m6A regulators-based signature to predict the prognostic risk using univariate and LASSO Cox analyses. The signature was then validated by performing Kaplan-Meier, and receiver operating characteristic analyses. Through the correlation analysis, m6A regulators-related lncRNAs were identified, and they were divided into different clustering subtypes according to their expression. We further assessed differences in TME scores, the survival time of patients, and immune cell infiltration levels between different clustering subtypes. Finally, we screened out the common immune genes shared by m6A-related lncRNAs and determined their expression in different risk groups and clustering subtypes. For further validation, we used single-cell sequencing data from the GSE139829 dataset to explore the expression distribution of immune genes in the TME of UM. We constructed a prognostic risk signature representing an independent prognostic factor for UM using 3 m6A regulators. Patients in the low-risk group exhibited a more favorable prognosis and lower immune cell infiltration levels than patients in the high-risk group. Two subtypes (cluster 1/2) were identified based on m6A regulators-related lncRNAs. The TME scores, prognosis, and immune cell infiltration have a marked difference between cluster 1 and cluster 2. Additionally, 13 common immune genes shared by 5 lncRNAs were screened out. We found that these immune genes were differentially expressed in different risk groups and clustering subtypes and were widely distributed in 3 cell types of TME. In conclusion, our study demonstrated the important role of m6A regulators and related lncRNAs in TME remodeling. The signature developed using m6A regulators might serve as a promising parameter for the clinical prediction of UM.

Genetic alterations and functional networks of m6A RNA methylation regulators in pancreatic cancer based on data mining

BackgroundPancreatic cancer is a fatal malignancy of the digestive system and the 5-year survival rate remains low. Therefore, new molecular therapeutic targets are required to improve treatments, prognosis, and the survival of patients. N6-methyladenosine (m6A) is the most prevalent reversible methylation in mammalian messenger RNA (mRNA) and has critical roles in the tumorigenesis and metastasis of various malignancies. However, the role of m6A in pancreatic cancer is still unclear. Exploring genetic alterations and functional networks of m6A regulators in pancreatic cancer may provide new strategies for its treatment.MethodsIn this study, we used data from the Cancer Genome Atlas (TCGA) database and other public databases through cBioPortal, LinkedOmics, UALCAN, GEPIA, STRING, and the database for annotation, visualization, and integrated discovery (DAVID) to systematically analyze the molecular alterations and functions of 20 main m6A regulators in pancreatic cancer.ResultsWe found that m6A regulators had widespread genetic alterations, and that their expression levels were significantly correlated with pancreatic cancer malignancy. Moreover, m6A regulators were associated with the prognosis of pancreatic cancer patients.Conclusionsm6A regulators play a crucial part in the occurrence and development of pancreatic cancer. Our study will guide further studies of m6A RNA modification in pancreatic cancer and could potentially provide new strategies for pancreatic cancer treatment.

Gene Characteristics and Prognostic Values of m6A RNA Methylation Regulators in Nonsmall Cell Lung Cancer.

Background N6-methyladenosine (m6A) is the most common internal modification present in mRNAs and long noncoding RNAs (lncRNAs), associated with tumorigenesis and cancer progression. However, little is known about the roles of m6A and its regulatory genes in nonsmall cell lung cancer (NSCLC). Here, we systematically explored the roles and prognostic significance of m6A-associated regulatory genes in NSCLC. Methods The copy number variation (CNV), mutation, mRNA expression data, and corresponding clinical pathology information of 1057 NSCLC patients were downloaded from the cancer genome atlas (TCGA) database. The gain and loss levels of CNVs were determined by utilizing segmentation analysis and GISTIC algorithm. The GSEA was conducted to explore the functions related to different levels of m6A regulatory genes. Logrank test was utilized to assess the prognostic significance of m6A-related gene's CNV. Results The genetic alterations of ten m6A-associated regulators were identified in 102 independent NSCLC samples and significantly related to advanced tumor stage. Deletions or shallow deletions corresponded to lower mRNA expression while copy number gains or amplifications were related to increased mRNA expression of m6A regulatory genes. Survival analysis showed the patients with copy number loss of FTO with worse disease-free survival (DFS) or overall survival (OS). Besides, copy number loss of YTHDC2 was also with poor OS for NSCLC patients. Moreover, high FTO expression was significantly associated with oxidative phosphorylation, translation, and metabolism of mRNA. Conclusion Our findings provide novel insight for better understanding of the roles of m6A regulators and RNA epigenetic modification in the pathogenesis of NSCLC.

N6-Methyladenosine RNA modification in cerebrospinal fluid as a novel potential diagnostic biomarker for progressive multiple sclerosis

BackgroundProgressive multiple sclerosis (PMS) is an uncommon and severe subtype of MS that worsens gradually and leads to irreversible disabilities in young adults. Currently, there are no applicable or reliable biomarkers to distinguish PMS from relapsing–remitting multiple sclerosis (RRMS). Previous studies have demonstrated that dysfunction of N6-methyladenosine (m6A) RNA modification is relevant to many neurological disorders. Thus, the aim of this study was to explore the diagnostic biomarkers for PMS based on m6A regulatory genes in the cerebrospinal fluid (CSF).MethodsGene expression matrices were downloaded from the ArrayExpress database. Then, we identified differentially expressed m6A regulatory genes between MS and non-MS patients. MS clusters were identified by consensus clustering analysis. Next, we analyzed the correlation between clusters and clinical characteristics. The random forest (RF) algorithm was applied to select key m6A-related genes. The support vector machine (SVM) was then used to construct a diagnostic gene signature. Receiver operating characteristic (ROC) curves were plotted to evaluate the accuracy of the diagnostic model. In addition, CSF samples from MS and non-MS patients were collected and used for external validation, as evaluated by an m6A RNA Methylation Quantification Kit and by real-time quantitative polymerase chain reaction.ResultsThe 13 central m6A RNA methylation regulators were all upregulated in MS patients when compared with non-MS patients. Consensus clustering analysis identified two clusters, both of which were significantly associated with MS subtypes. Next, we divided 61 MS patients into a training set (n = 41) and a test set (n = 20). The RF algorithm identified eight feature genes, and the SVM method was successfully applied to construct a diagnostic model. ROC curves revealed good performance. Finally, the analysis of 11 CSF samples demonstrated that RRMS samples exhibited significantly higher levels of m6A RNA methylation and higher gene expression levels of m6A-related genes than PMS samples.ConclusionsThe dynamic modification of m6A RNA methylation is involved in the progression of MS and could potentially represent a novel CSF biomarker for diagnosing MS and distinguishing PMS from RRMS in the early stages of the disease.

The functions and prognostic values of m6A RNA methylation regulators in thyroid carcinoma

BackgroundN6-Methyladenosine (m6A) is the most common RNA modification and regulates RNA splicing, translation, translocation, and stability. Aberrant expression of m6A has been reported in various types of human cancers. m6A RNA modification is dynamically and reversibly mediated by different regulators, including methyltransferase, demethylases, and m6A binding proteins. However, the role of m6A RNA methylation regulators in thyroid cancer remains unknown. The aim of this study is to investigate the effect of the 13 main m6A RNA modification regulators in thyroid carcinoma.MethodsWe obtained clinical data and RNA sequencing data of 13 m6A RNA methylation regulators from The Cancer Genome Atlas (TCGA) THCA database. We performed consensus clustering to identify the clinical relevance of m6A RNA methylation regulators in thyroid carcinoma. Then we used LASSO Cox regression analysis to generate a prognostic signature based on m6A RNA modification regulator expression. Kyoto Encyclopedia of Genes and Genomes, Gene Ontology and Gene Set Enrichment Analyses were performed to explore differential cellular processes and signaling pathways between the two groups based on risk signature.ResultsWe found that most of the m6A RNA modification regulators are down-regulated in 450 patients with thyroid carcinoma. We derived a three m6A RNA modification regulator genes-based risk signature (FTO, RBM15 and KIAA1429), that is an independent prognostic biomarker in patients with thyroid carcinoma. Moreover, we found that this risk signature could better predict outcome in male than female. Functional research in vitro demonstrated that the m6A RNA methylation regulators involved in the model acted significant role in the proliferation and migration of thyroid cancer cells.ConclusionsOur study revealed the influence of m6A RNA methylation regulators on thyroid carcinoma through biological experiments and three-gene prognostic model.

Significance of N6-Methyladenosine RNA Methylation Regulators in Immune Infiltrates of Ovarian Cancer

N6-methyladenosine (m6A) RNA methylation regulators play an important role in the occurrence and development of tumors. Here, we aimed to identify the potential roles of m6A RNA methylation regulators in immune infiltrates of ovarian cancer. We obtained two distinct m6A patterns (m6Acluster.A and m6Acluster.B) based on the expression levels of all 21 m6A RNA methylation regulators from The Cancer Genome Atlas (TCGA) database using a consensus clustering algorithm. Differential analysis of m6Acluster.A and m6Acluster.B identified 196 m6A-related genes. We further validated the m6A regulation mechanism based on the 196 m6A-related genes using another consensus clustering algorithm. Considering individual differences, principal component analysis algorithms were used to calculate an m6A score for each sample in order to quantify the m6A patterns. A low m6A score was associated with immune activation and enhanced response to immune checkpoint inhibitors, whereas a high m6A score was associated with tumor progression. Finally, we successfully verified the correlation between m6A regulators and immune microenvironment in OC using our microarray analysis data. In summary, m6A regulators play non-negligible roles in immune infiltrates of ovarian cancer. Our investigation of m6A patterns may help to guide future immunotherapy strategies for advanced ovarian cancer.