scholarly journals The Prognostic Values of m6A RNA Methylation Regulators in Thyroid Carcinoma

2020 ◽  
Author(s):  
Di Zhang ◽  
Yue Ma ◽  
Xu-Chen Cao ◽  
Li Fu ◽  
Yue Yu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Ontology ◽  
Thyroid Carcinoma ◽  
Signaling Pathways ◽  
Rna Modification ◽  
Consensus Clustering ◽  
Gene Set Enrichment ◽  
Rna Methylation ◽  
Gene Set ◽  
M6a Rna Methylation

Abstract Background: N6-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.Methods: The gene expression profile of m6A RNA modification regulations and clinical information of patients with thyroid carcinoma were obtained from The Cancer Genome Atlas database. Consensus clustering was applied to identify two clusters of thyroid carcinomas with different clinical outcome. LASSO Cox regression analysis was used to construct gene-based prognostic signature based on the expression of m6A RNA methylation regulators. 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.Results: We found that most of the m6A RNA modification regulators are down-regulated in 450 patients with thyroid carcinoma. We identified two clusters based on the gene expression profiles of 13 m6A RNA modification regulators using consensus clustering. The cluster 2 subgroup correlates with an unfavorable outcome compared with the cluster 1 subgroup. In addition, 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. There were significantly different signaling pathways between high and low risk group by Kyoto Encyclopedia of Genes and Genomes, Gene Ontology and gene set enrichment analyses. Moreover, we found that this risk signature could better predict outcome in male than female. Conclusion: Our study revealed the prognostic value of m6A RNA methylation regulators in patients with thyroid carcinoma.

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

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Fei Ye ◽  
Tianzhu Wang ◽  
Xiaoxin Wu ◽  
Jie Liang ◽  
Jiaoxing Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Sclerosis ◽  
Clustering Analysis ◽  
Roc Curves ◽  
Progressive Multiple Sclerosis ◽  
Rna Modification ◽  
Diagnostic Model ◽  
Consensus Clustering ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract Background Progressive 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). Methods Gene 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. Results The 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. Conclusions The 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.

scholarly journals The m6A RNA methylation regulates oncogenic signaling pathways driving cell malignant transformation and carcinogenesis

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Mohammad Burhan Uddin ◽  
Zhishan Wang ◽  
Chengfeng Yang
Keyword(s):  
Signaling Pathways ◽  
Malignant Transformation ◽  
Noncoding Rna ◽  
Rna Modification ◽  
Oncogenic Signaling ◽  
Aberrant Expression ◽  
Rna Methylation ◽  
Rna Molecules ◽  
M6a Rna Methylation ◽  
Oncogenic Signaling Pathways

AbstractThe m6A RNA methylation is the most prevalent internal modification in mammalian mRNAs which plays critical biological roles by regulating vital cellular processes. Dysregulations of the m6A modification due to aberrant expression of its regulatory proteins are frequently observed in many pathological conditions, particularly in cancer. Normal cells undergo malignant transformation via activation or modulation of different oncogenic signaling pathways through complex mechanisms. Accumulating evidence showing regulation of oncogenic signaling pathways at the epitranscriptomic level has added an extra layer of the complexity. In particular, recent studies demonstrated that, in many types of cancers various oncogenic signaling pathways are modulated by the m6A modification in the target mRNAs as well as noncoding RNA transcripts. m6A modifications in these RNA molecules control their fate and metabolism by regulating their stability, translation or subcellular localizations. In this review we discussed recent exciting studies on oncogenic signaling pathways that are modulated by the m6A RNA modification and/or their regulators in cancer and provided perspectives for further studies. The regulation of oncogenic signaling pathways by the m6A modification and its regulators also render them as potential druggable targets for the treatment of cancer.

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

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhi-Hao Yu ◽  
Shao-Ting Feng ◽  
Di Zhang ◽  
Xu-Chen Cao ◽  
Yue Yu ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Thyroid Carcinoma ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Rna Modification ◽  
Sequencing Data ◽  
Aberrant Expression ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract Background N6-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. Methods We 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. Results We 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. Conclusions Our study revealed the influence of m6A RNA methylation regulators on thyroid carcinoma through biological experiments and three-gene prognostic model.

scholarly journals Current insights into the implications of m6A RNA methylation and autophagy interaction in human diseases

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xuechai Chen ◽  
Jianan Wang ◽  
Muhammad Tahir ◽  
Fangfang Zhang ◽  
Yuanyuan Ran ◽  
...  
Keyword(s):  
Intervertebral Disc Degeneration ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Degradation Process ◽  
Human Diseases ◽  
Rna Modification ◽  
Rna Methylation ◽  
M6a Rna Methylation ◽  
The Impact

AbstractAutophagy is a conserved degradation process crucial to maintaining the primary function of cellular and organismal metabolism. Impaired autophagy could develop numerous diseases, including cancer, cardiomyopathy, neurodegenerative disorders, and aging. N6-methyladenosine (m6A) is the most common RNA modification in eukaryotic cells, and the fate of m6A modified transcripts is controlled by m6A RNA binding proteins. m6A modification influences mRNA alternative splicing, stability, translation, and subcellular localization. Intriguingly, recent studies show that m6A RNA methylation could alter the expression of essential autophagy-related (ATG) genes and influence the autophagy function. Thus, both m6A modification and autophagy could play a crucial role in the onset and progression of various human diseases. In this review, we summarize the latest studies describing the impact of m6A modification in autophagy regulation and discuss the role of m6A modification-autophagy axis in different human diseases, including obesity, heart disease, azoospermatism or oligospermatism, intervertebral disc degeneration, and cancer. The comprehensive understanding of the m6A modification and autophagy interplay may help in interpreting their impact on human diseases and may aid in devising future therapeutic strategies.

scholarly journals The role of m6A modification in the biological functions and diseases

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Xiulin Jiang ◽  
Baiyang Liu ◽  
Zhi Nie ◽  
Lincan Duan ◽  
Qiuxia Xiong ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Rna Modification ◽  
Biological Functions ◽  
Rna Methylation ◽  
Downstream Target ◽  
Different Types ◽  
M6a Rna Methylation

AbstractN6-methyladenosine (m6A) is the most prevalent, abundant and conserved internal cotranscriptional modification in eukaryotic RNAs, especially within higher eukaryotic cells. m6A modification is modified by the m6A methyltransferases, or writers, such as METTL3/14/16, RBM15/15B, ZC3H3, VIRMA, CBLL1, WTAP, and KIAA1429, and, removed by the demethylases, or erasers, including FTO and ALKBH5. It is recognized by m6A-binding proteins YTHDF1/2/3, YTHDC1/2 IGF2BP1/2/3 and HNRNPA2B1, also known as “readers”. Recent studies have shown that m6A RNA modification plays essential role in both physiological and pathological conditions, especially in the initiation and progression of different types of human cancers. In this review, we discuss how m6A RNA methylation influences both the physiological and pathological progressions of hematopoietic, central nervous and reproductive systems. We will mainly focus on recent progress in identifying the biological functions and the underlying molecular mechanisms of m6A RNA methylation, its regulators and downstream target genes, during cancer progression in above systems. We propose that m6A RNA methylation process offer potential targets for cancer therapy in the future.

scholarly journals The Role of m6A Ribonucleic Acid Modification in the Occurrence of Atherosclerosis

2021 ◽  
Vol 12 ◽  
Author(s):  
Jie Fu ◽  
Xinghui Cui ◽  
Xiaoyun Zhang ◽  
Min Cheng ◽  
Xiaoxia Li ◽  
...  
Keyword(s):  
Messenger Rna ◽  
Biological Activities ◽  
Rna Modification ◽  
Acid Modification ◽  
Rna Methylation ◽  
Mrna Metabolism ◽  
Modification Process ◽  
M6a Rna Methylation ◽  
The Relationship

The N6-methyladenosine (m6A) modification is the most abundant epitranscriptomic modification in eukaryotic messenger RNA (mRNA). The m6A modification process is jointly regulated by various enzymes and proteins, such as methyltransferases, demethylases and related m6A-binding proteins. The process is dynamic and reversible, and it plays an essential role in mRNA metabolism and various biological activities. Recently, an increasing number of researchers have confirmed that the onset and development of many diseases are closely associated with the molecular biological mechanism of m6A RNA methylation. This study focuses on the relationship between m6A RNA modification and atherosclerosis (AS). It thoroughly summarizes the mechanisms and processes of m6A RNA modification in AS-related cells and the relationships between m6A RNA modification and AS risk factors, and it provides a reference for exploring new targets for the early diagnosis and treatment of AS.

The effect of m6A RNA methylation regulators on tumor microenvironment in clear cell renal cell carcinoma

2021 ◽  
Author(s):  
Shuaishuai Huang ◽  
Xiaodong Qing ◽  
Qiuzi Lin ◽  
Qiaoling Wu ◽  
Xue Wang ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Tumor Microenvironment ◽  
Immune Checkpoint ◽  
Renal Cell ◽  
Clear Cell ◽  
Gene Signature ◽  
Consensus Clustering ◽  
Cell Renal Cell Carcinoma ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract Background: m6A RNA methylation and tumor microenvironment (TME) have been reported to play important roles in the progression and prognosis of clear cell renal cell carcinoma (ccRCC). However, whether m6A RNA methylation regulators affect TME in ccRCC remains unknown. Thus, the current study is designed to comprehensively evaluate the effect of m6A RNA methylation regulators on TME in ccRCC.Methods: Transcriptome data of ccRCC was obtained from The Cancer Genome Atlas (TCGA) database. Consensus clustering analysis was conducted based on the expressions of m6A RNA methylation regulators. Survival differences were evaluated by Kaplan-Meier (K-M) analysis between the clusters. DESeq2 package was used to analyze the differentially expressed genes (DEGs) between the clusters. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were analyzed by ClusterProfiler R package. Immune, stromal and ESTIMATE scores were assessed by ESTIMATE algorithm. CIBERSORT algorithm was applied to evaluate immune infiltration. The expressions of human leukocyte antigen (HLA), immune checkpoint molecules, and Th1/IFNγ gene signature associated with TME were also compared between the clusters. TIDE algorithm and subclass mapping were used to analyze the clinical response of different clusters to PD-1 and CTLA-4 blockade. Results: The expressions of fifteen m6A regulators were significantly different between ccRCC and normal kidney tissues. Based on the expressions of those fifteen m6A regulators, two clusters were identified by consensus clustering, in which cluster 1 had better overall survival (OS). A total of 4,429 DEGs were found between the two clusters, and were enriched into immune-related biological processes. Further analysis of the two clusters’ TME showed that cluster 1 had lower immune and ESTIMATE scores, higher expressions of HLA and lower expressions of immune checkpoint molecules. Besides, immune infiltration and the expressions of Th1/IFNγ gene signature also have significant differences between two clusters. Conclusions: Our study revealed that m6A regulators were important participants in the development of ccRCC, with a close relationship with TME.

scholarly journals ExAtlas: An interactive online tool for meta-analysis of gene expression data

2015 ◽  
Vol 13 (06) ◽  
pp. 1550019 ◽  
Author(s):  
Alexei A. Sharov ◽  
David Schlessinger ◽  
Minoru S. H. Ko
Keyword(s):  
Gene Expression ◽  
Gene Ontology ◽  
Gene Expression Data ◽  
Fixed Effects ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Data Sets ◽  
Expression Data ◽  
Gene Set ◽  
Public Data

We have developed ExAtlas, an on-line software tool for meta-analysis and visualization of gene expression data. In contrast to existing software tools, ExAtlas compares multi-component data sets and generates results for all combinations (e.g. all gene expression profiles versus all Gene Ontology annotations). ExAtlas handles both users’ own data and data extracted semi-automatically from the public repository (GEO/NCBI database). ExAtlas provides a variety of tools for meta-analyses: (1) standard meta-analysis (fixed effects, random effects, z-score, and Fisher’s methods); (2) analyses of global correlations between gene expression data sets; (3) gene set enrichment; (4) gene set overlap; (5) gene association by expression profile; (6) gene specificity; and (7) statistical analysis (ANOVA, pairwise comparison, and PCA). ExAtlas produces graphical outputs, including heatmaps, scatter-plots, bar-charts, and three-dimensional images. Some of the most widely used public data sets (e.g. GNF/BioGPS, Gene Ontology, KEGG, GAD phenotypes, BrainScan, ENCODE ChIP-seq, and protein–protein interaction) are pre-loaded and can be used for functional annotations.

scholarly journals Integration of GWAS Summary Statistics and Gene Expression Reveals Target Cell Types Underlying Kidney Function Traits

2020 ◽  
Vol 31 (10) ◽  
pp. 2326-2340 ◽  
Author(s):  
Yong Li ◽  
Stefan Haug ◽  
Pascal Schlosser ◽  
Alexander Teumer ◽  
Adrienne Tin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Kidney Function ◽  
Cell Types ◽  
Gene Set Enrichment Analysis ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Rna Seq ◽  
Cell Type ◽  
Gene Set Enrichment ◽  
Gene Set

BackgroundGenetic variants identified in genome-wide association studies (GWAS) are often not specific enough to reveal complex underlying physiology. By integrating RNA-seq data and GWAS summary statistics, novel computational methods allow unbiased identification of trait-relevant tissues and cell types.MethodsThe CKDGen consortium provided GWAS summary data for eGFR, urinary albumin-creatinine ratio (UACR), BUN, and serum urate. Genotype-Tissue Expression Project (GTEx) RNA-seq data were used to construct the top 10% specifically expressed genes for each of 53 tissues followed by linkage disequilibrium (LD) score–based enrichment testing for each trait. Similar procedures were performed for five kidney single-cell RNA-seq datasets from humans and mice and for a microdissected tubule RNA-seq dataset from rat. Gene set enrichment analyses were also conducted for genes implicated in Mendelian kidney diseases.ResultsAcross 53 tissues, genes in kidney function–associated GWAS loci were enriched in kidney (P=9.1E-8 for eGFR; P=1.2E-5 for urate) and liver (P=6.8·10-5 for eGFR). In the kidney, proximal tubule was enriched in humans (P=8.5E-5 for eGFR; P=7.8E-6 for urate) and mice (P=0.0003 for eGFR; P=0.0002 for urate) and confirmed as the primary cell type in microdissected tubules and organoids. Gene set enrichment analysis supported this and showed enrichment of genes implicated in monogenic glomerular diseases in podocytes. A systematic approach generated a comprehensive list of GWAS genes prioritized by cell type–specific expression.ConclusionsIntegration of GWAS statistics of kidney function traits and gene expression data identified relevant tissues and cell types, as a basis for further mechanistic studies to understand GWAS loci.

scholarly journals Revealing Biological Pathways Implicated in Lung Cancer from TCGA Gene Expression Data Using Gene Set Enrichment Analysis

2014 ◽  
Vol 13s1 ◽  
pp. CIN.S13882 ◽  
Author(s):  
Binghuang Cai ◽  
Xia Jiang
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Gene Expression Data ◽  
Lung Squamous Cell Carcinoma ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Expression Data ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Pathway Gene

Analyzing biological system abnormalities in cancer patients based on measures of biological entities, such as gene expression levels, is an important and challenging problem. This paper applies existing methods, Gene Set Enrichment Analysis and Signaling Pathway Impact Analysis, to pathway abnormality analysis in lung cancer using microarray gene expression data. Gene expression data from studies of Lung Squamous Cell Carcinoma (LUSC) in The Cancer Genome Atlas project, and pathway gene set data from the Kyoto Encyclopedia of Genes and Genomes were used to analyze the relationship between pathways and phenotypes. Results, in the form of pathway rankings, indicate that some pathways may behave abnormally in LUSC. For example, both the cell cycle and viral carcinogenesis pathways ranked very high in LUSC. Furthermore, some pathways that are known to be associated with cancer, such as the p53 and the PI3K-Akt signal transduction pathways, were found to rank high in LUSC. Other pathways, such as bladder cancer and thyroid cancer pathways, were also ranked high in LUSC.

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