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

2021 ◽  
Vol 12 ◽  
Author(s):  
Jing Gu ◽  
Fangfang Bi
Keyword(s):  
Ovarian Cancer ◽  
Clustering Algorithm ◽  
Checkpoint Inhibitors ◽  
Advanced Ovarian Cancer ◽  
The Cancer Genome Atlas ◽  
Regulation Mechanism ◽  
Consensus Clustering ◽  
Differential Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation

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.

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

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Fei Li ◽  
Ping Zhang
Keyword(s):  
Pancreatic Adenocarcinoma ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Pancreatic Tumors ◽  
Molecular Characteristics ◽  
Main Role ◽  
Consensus Clustering ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation

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.

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

Mutagenesis ◽  
2021 ◽  
Vol 36 (5) ◽  
pp. 369-379
Author(s):  
Min Deng ◽  
Lin Fang ◽  
Shao-Hua Li ◽  
Rong-Ce Zhao ◽  
Jie Mei ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
High Risk ◽  
Risk Score ◽  
Critical Role ◽  
Risk Groups ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract 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.

scholarly journals Identification of a m6A RNA methylation regulators-based signature for predicting the prognosis of esophageal adenocarcinoma

2020 ◽  
Author(s):  
Yue Zhou ◽  
Shuyan Li ◽  
Liqing Zou ◽  
Tiantian Guo ◽  
Xi Yang ◽  
...  
Keyword(s):  
Esophageal Adenocarcinoma ◽  
Clustering Analysis ◽  
Cox Regression ◽  
Area Under The Curve ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract BackgroundN6-methyladenosine (m6A) is an abundant modification in RNAs that affects RNA metabolism, and it is reported to be closely related to cancer occurrence and metastasis. The aim of this study was to identify novel prognostic biomarkers by using m6A RNA methylation regulators capable of improving the risk-stratification criteria of survival for esophageal adenocarcinoma patients.MethodsThe gene expression data of 16 m6A methylation regulators and its relevant clinical information were extracted from The Cancer Genome Atlas (TCGA) database. The expression pattern of these m6A methylation regulators was evaluated. Consensus clustering analysis was conducted to identify clusters of esophageal adenocarcinoma patients with different prognosis. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were performed to construct multiple-gene risk signature. A survival analysis was carried out to determine the prognosis significance.ResultsTen m6A methylation regulators (HNRNPA2B1, HNRNPC, YTHDF1, METTL3, YTHDF2, RBM15, YTHDC1, WTAP, KIAA1429 and YTHDF3) showed significant up-regulation in tumor tissue. Consensus clustering analysis identified three clusters of esophageal adenocarcinoma patients with different overall survival. A five-gene signature, HNRNPA2B1, KIAA1429, WTAP, METTL16 and ALKBH5, was constructed to serve as a prognostic indicator for distinguish esophageal adenocarcinoma patients with different prognosis. The receiver operator characteristic (ROC) curve which indicated the area under the curve (AUC) were 0.803, demonstrated that the prognostic signature had preferable prediction efficiency.Conclusionsm6A methylation regulators exert as potential biomarkers for prognostic stratification of esophageal adenocarcinoma patients and might help clinicians make individualized therapy for this patient population.

M 6A-related genes characterization in hepatocellular cancer identifies prognostic relevant gene signatures

2020 ◽  
Author(s):  
peng zhu ◽  
Qianqian Ren ◽  
Nan He ◽  
Cheng Zhou ◽  
Zhao Gong ◽  
...  
Keyword(s):  
Clinical Outcomes ◽  
Cox Regression ◽  
Hepatocellular Cancer ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Prognostic Signature ◽  
High Group ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract Background Hepatocellular carcinoma (HCC) is among the most common types of cancers that threat the public health worldwide. N6-methyladenosine (m6A) RNA methylation, associated with cancer initiation and progression, is dynamically regulated by m6A RNA methylation associated genes. However, little is known about the expression status and the prognostic value of m6A associated genes in HCC. This study aimed to identify the expression profiling pattern and clinical significance of m6A-related genes in HCC. Methods The Cancer Genome Atlas (TCGA-LIHC), the Gene Expression Omnibus (GSE14520) and the Human Protein Atlas (HPA) databases were gathered for this study. Consensus clustering analysis was performed to identify the clusters of HCC with different clinical outcome. A prognostic signature built by the least absolute shrinkage and selection operator (LASSO) Cox regression model was utilized to discover subtypes correlated with different clinical outcomes of HCC patients and the differences between subgroups were characterized in terms of epigenetic dysregulation and somatic mutation frequencies. Results Most of the m6A-related genes were upregulated and involved with the prognosis and malignancy of HCC. A four-gene prognostic signature revealed two HCC subtypes (namely, risk-high group and risk-low group) that correlated with different clinical outcomes. Patients in risk-high group were accompanied with much more epigenetic silencing and significant mutation at TP53 and FLG, while ALB were mutated frequently for risk-low group. Conclusion Our characterization tightly links the expression of m6A genes with clinical outcomes of HCC, providing valuable molecular-level information that points to decoding heterogeneity, guiding personalized management and treatment of HCC patients.

scholarly journals Expectations and Challenges of First-Line Maintenance Therapy for Advanced Ovarian Cancer

Medicina ◽  
2021 ◽  
Vol 57 (5) ◽  
pp. 501
Author(s):  
Tadahiro Shoji ◽  
Chie Sato ◽  
Hidetoshi Tomabechi ◽  
Eriko Takatori ◽  
Yoshitaka Kaido ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Immune Checkpoint ◽  
Clinical Studies ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Advanced Ovarian Cancer ◽  
Targeted Drugs ◽  
First Line ◽  
Double Blind ◽  
Platinum Based Chemotherapy

The incidence of ovarian cancer, which has had a poor prognosis, is increasing annually. Currently, the prognosis is expected to improve with the use of molecular-targeted drugs and immune checkpoint inhibitors as maintenance therapies after the first-line chemotherapy. The GOG218 and ICON7 studies reported the usefulness of bevacizumab and the SOLO-1 and PRIMA (A Phase 3, Randomized, Double-Blind, Placebo-Controlled, Multicenter Study of Niraparib Maintenance Treatment in Patients With Advanced Ovarian Cancer Following Response on Front-Line Platinum-Based Chemotherapy) studies have reported the usefulness of olaparib and niraparib, respectively. The ATHENA study investigating the usefulness of rucaparib is currently ongoing. Although clinical studies of immune checkpoint inhibitors are lagging in the field of gynecology, many clinical studies using programmed death cell-1 (PD-1) and PD-1 ligand 1 (PD-L1) antibodies are currently ongoing. Some biomarkers have been identified for molecular-targeted drugs, but none have been identified for immune checkpoint inhibitors, which is a challenge that should be addressed in the future.

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 Development and Validation of a Unique Gignature of Cancer Stemness-related Genes for Predicting the Overall survival of Colorectal Cancer Patients

2020 ◽  
Author(s):  
Ran Wei ◽  
Jichuan Quan ◽  
Shuofeng Li ◽  
Zhao Lu ◽  
Xu Guan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Cancer Stemness ◽  
Poor Overall Survival ◽  
Tissue Samples ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract 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 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 2 key modules and 34 key genes as prognosis-related candidate biomarkers. Finally, a 3-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. Conclusions: 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.

scholarly journals Prognostic Value of A Risk Score Model Constructed By m6A Methylation Regulators In Breast Cancer

2021 ◽  
Author(s):  
Xiaowei Qiu ◽  
Qiaoli Zhang ◽  
Jingnan Xu ◽  
Xin Jiang ◽  
Xuewei Qi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Score ◽  
Prognostic Value ◽  
Validation Cohort ◽  
Risk Group ◽  
The Cancer Genome Atlas ◽  
Rna Methylation ◽  
Model Based ◽  
Prognosis Model ◽  
M6a Rna Methylation

Abstract Background: N6-methyladenosine (m6A) methylation modification can affect the tumorigenesis, progression, and metastasis of breast cancer (BC). Up to now, a prognostic model based on m6A methylation regulators for BC is still lacking. This study aimed to construct an accurate prediction prognosis model by m6A methylation regulators for BC patients.Methods: After processing of The Cancer Genome Atlas (TCGA) datasets, the differential expression and correlation analysis of m6A RNA methylation regulators were applied. Next, tumor samples were clustered into different groups and clinicopathologic features in different clusters were explored. By univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) analysis, m6A regulators with prognostic value were identified to develop a prediction model. Furthermore, we constructed and validated a predictive nomogram to predict the prognosis of BC patients.Results: 19 m6A related genes were extracted and 908 BC patients enrolled from TCGA dataset. After univariate Cox and LASSO analysis, 3 m6A RNA methylation regulators (YTHDF3, ZC3H13 and HNRNPC) were selected to establish the prognosis model based on median risk score (RS) in training and validation cohort. With the increasing of RS, the expression levels of YTHDF3 and ZC3H13 were individually elevated, while the HNRNPC expressed decreasingly. By survival analysis and Receiver Operating Characteristic (ROC) curve, we found that the overall survival (OS) of high-risk group was significantly shorter than that of the low-risk group based on Kaplan-Meier (KM) analysis in each cohort. Univariate and multivariate analysis identified the RS, age, and pathological stage are independent prognostic factors. A nomogram was constructed to predict 1- and 3-year OS and the calibration plots validate the performance. The C-index of nomogram reached 0.757 (95% CI:0.7-0.814) in training cohort and 0.749 (95% CI:0.648-0.85) in validation cohort, respectively.Conclusions: We successfully constructed a predictive prognosis model by m6A RNA methylation regulators. These results indicated that the m6A RNA methylation regulators are potential therapeutic targets of BC patients.

scholarly journals Comprehensive Analysis of The Significance of Hypoxia-Related Genes in Ovarian Cancer

2021 ◽  
Author(s):  
Wancheng Zhao ◽  
Lili Yin
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Mesenchymal Transition ◽  
Principal Component ◽  
Vital Role ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Mesenchymal Transition ◽  
Cancer Genome Atlas ◽  
Pca Algorithm

Abstract Background: Hypoxia-related genes have been reported to play important roles in a variety of cancers. However, their roles in ovarian cancer (OC) have remained unknown. The aim of our research was to explore the significance of hypoxia-related genes in OC patients.Methods: In this study, 15 hypoxia-related genes were screened from The Cancer Genome Atlas (TCGA) database to group the ovarian cancer patients using the consensus clustering method. Principal component analysis (PCA) was performed to calculate the hypoxia score for each patient to quantify the hypoxic status. Results: The OC patients from TCGA-OV dataset were divided into two distinct hypoxia statuses (cluster.A and cluster.B) based on the expression level of the 15 hypoxia-related genes. Most hypoxia-related genes were expressed more highly in the cluster.A group than in the cluster.B group. We also found that patients in the cluster.A group exhibited higher expression of immune checkpoint-related genes, epithelial-mesenchymal transition-related genes, and immune activation-related genes, as well as elevated immune infiltrates. PCA algorithm indicated that patients in the cluster.A group had higher hypoxia scores than that in in the cluster.B group.Conclusions: In summary, our research elucidated the vital role of hypoxia-related genes in immune infiltrates of OC. Our investigation of hypoxic status may be able to improve the efficacy of immunotherapy for OC.

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.

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