scholarly journals Development and Validation of an m6A RNA Methylation Regulators-Based Signature for Predicting the Prognosis of Adrenocortical Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Chengquan Shen ◽  
Jing Liu ◽  
Xiaokun Yang ◽  
Wei Jiao ◽  
Yonghua Wang
Keyword(s):  
Survival Analysis ◽  
Prognostic Factor ◽  
Adrenocortical Carcinoma ◽  
Cox Regression ◽  
Independent Prognostic Factor ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Predictive Values ◽  
Rna Methylation ◽  
M6a Rna Methylation

BackgroundAdrenocortical carcinoma (ACC) is an aggressive and rare neoplasm that originates from the cortex of the adrenal gland. N6-methyladenosine (m6A) RNA methylation, the most common form of mRNA modification, has been reported to be correlated with the occurrence and development of the malignant tumor. This study aims to identify the significance of m6A RNA methylation regulators in ACC and construct a m6A based signature to predict the prognosis of ACC patients.Materials and methodsRNA-seq data from The Cancer Genome Atlas (TCGA) database was used to identify the expression level of m6A RNA methylation regulators in ACC. An m6A based signature was further constructed and its prognostic and predictive values were assessed by survival analysis and nomogram.Results11 m6A RNA regulators were differentially expressed in ACC and three m6A RNA regulators were finally selected in a signature to predict the prognosis of ACC patients. Survival analysis indicated that high risk scores were closely related to poor survival outcomes in ACC patients. Univariate and multivariate Cox regression analyses demonstrated that the m6A based signature was an independent prognostic factor for ACC patients. A nomogram with clinical factors and the m6A based signature was also constructed to superiorly predict the prognosis of ACC patients. The expression levels of m6A RNA methylation regulators, which were contained in the signature, were also verified in human ACC tissues and normal tissues by using vitro experiments.ConclusionWe identified and validated an m6A based signature, which can be used as an independent prognostic factor in evaluating the prognosis of ACC patients. Further clinical trials and experimental explorations are needed to confirm our observations and mechanisms underlying prognostic values of these m6A RNA methylation regulators in ACC.

scholarly journals A model of twenty-three metabolic-related genes predicting overall survival for lung adenocarcinoma

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10008
Author(s):  
Zhenyu Zhao ◽  
Boxue He ◽  
Qidong Cai ◽  
Pengfei Zhang ◽  
Xiong Peng ◽  
...  
Keyword(s):  
Prognostic Factor ◽  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Independent Prognostic Factor ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Mechanism Analysis ◽  
Cox Regression Analysis

Background The highest rate of cancer-related deaths worldwide is from lung adenocarcinoma (LUAD) annually. Metabolism was associated with tumorigenesis and cancer development. Metabolic-related genes may be important biomarkers and metabolic therapeutic targets for LUAD. Materials and Methods In this study, the gleaned cohort included LUAD RNA-SEQ data from the Cancer Genome Atlas (TCGA) and corresponding clinical data (n = 445). The training cohort was utilized to model construction, and data from the Gene Expression Omnibus (GEO, GSE30219 cohort, n = 83; GEO, GSE72094, n = 393) were regarded as a testing cohort and utilized for validation. First, we used a lasso-penalized Cox regression analysis to build a new metabolic-related signature for predicting the prognosis of LUAD patients. Next, we verified the metabolic gene model by survival analysis, C-index, receiver operating characteristic (ROC) analysis. Univariate and multivariate Cox regression analyses were utilized to verify the gene signature as an independent prognostic factor. Finally, we constructed a nomogram and performed gene set enrichment analysis to facilitate subsequent clinical applications and molecular mechanism analysis. Result Patients with higher risk scores showed significantly associated with poorer survival. We also verified the signature can work as an independent prognostic factor for LUAD survival. The nomogram showed better clinical application performance for LUAD patient prognostic prediction. Finally, KEGG and GO pathways enrichment analyses suggested several especially enriched pathways, which may be helpful for us investigative the underlying mechanisms.

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 Molecular Characterization and Clinical Relevance of m6A RNA Methylation Regulators in Cervical Cancer

2020 ◽  
Author(s):  
Jin Chen ◽  
Ji He ◽  
Xiaolei Ma ◽  
Xia Guo
Keyword(s):  
Cervical Cancer ◽  
Clinical Relevance ◽  
Cox Regression ◽  
Critical Role ◽  
The Cancer Genome Atlas ◽  
Rna Modification ◽  
Lasso Regression ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract Background: RNA modification, such as methylation of N6 adenosine (m6A), plays a critical role in many biological processes. However, the role of m6A RNA modification in cervical cancer (CC) remains largely unknown. Methods: The present study systematically investigated the molecular signatures and clinical relevance of 20 m6A RNA methylation regulators (writers, erasers, readers) in CC. The mRNA expression and clinical significance of m6A-related genes were investigated using data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) cervical cancer cohort. Mutations, copy number variation (CNV), differential expression, gene ontology analysis and the construction of a mRNA-microRNA regulatory network were performed to investigate the underlying mechanisms involved in the abnormal expression of m6A-related genes. Results: We found inclusive genetic information alterations among the m6A regulators and that their transcript expression levels were significantly associated with cancer hallmark-related pathways activity, such as the PI3K-AKT signaling pathway, microRNAs in cancer and the focal adhesion pathway, which were significantly enriched. Moreover, m6A regulators were found to be potentially useful for prognostic stratification and we identified FMR1 and ZC3H13 as potential prognostic risk oncogenes by LASSO regression. The ROC curves of 3, 5 and 10 years were 0.685, 0.726 and 0.741, respectively. The specificity for 3, 5 and 10 years were 0.598, 0.631 and 0.833, the sensitivity were 0.707, 0.752 and 0.811, respectively. Conclusions: Multivariable Cox regression analysis revealed that the risk score is an independent prognostic marker and can be used to predict the clinical and pathological features of CC.

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 Status and Prognostic Value of m6A RNA Methylation Regulators in Lung Adenocarcinoma

Life ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 619
Author(s):  
Xiuhong Li ◽  
Zian Feng ◽  
Rui Wang ◽  
Jie Hu ◽  
Xiaodong He ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Survival Analysis ◽  
Lung Adenocarcinoma ◽  
Roc Curve ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
Kaplan Meier ◽  
M6a Rna Methylation ◽  
Prediction Efficiency

N6-methyladenosine (m6A) RNA modification is the most abundant modification method in mRNA, and it plays an important role in the occurrence and development of many cancers. This paper mainly discusses the role of m6A RNA methylation regulators in lung adenocarcinoma (LUAD) to identify novel prognostic biomarkers. The gene expression data of 19 m6A methylation regulators in LUAD patients and its relevant clinical parameters were extracted from The Cancer Genome Atlas (TCGA) database. We selected three significantly differentially expressed m6A regulators in LUAD to construct the risk signature, and evaluated its prognostic prediction efficiency using the receiver operating characteristic (ROC) curve. Kaplan–Meier survival analysis and Cox regression analysis were used to identify the independent prognostic significance of the risk signature. The ROC curve indicated that the area under the curve (AUC) was 0.659, which means that the risk signature had a good prediction efficiency. The results of the Kaplan–Meier survival analysis and Cox regression analysis showed that the risk score can be used as an independent prognostic factor for LUAD. In addition, we explored the differential signaling pathways and cellular processes related to m6A methylation regulators in LUAD.

scholarly journals m6A RNA Methylation Regulators Elicit Malignant Progression and Predict Clinical Outcome in Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Wenli Li ◽  
Jun Liu ◽  
Zhanzhong Ma ◽  
Xiaofeng Zhai ◽  
Binbin Cheng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cell ◽  
Clinical Outcome ◽  
Cox Regression ◽  
Expression Profiles ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Rna Methylation ◽  
M6a Rna Methylation

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, and N6-methyladenosine (m6A) is a predominant internal modification of RNA in various cancers. We obtained the expression profiles of m6A-related genes for HCC patients from the International Cancer Genome Consortium and The Cancer Genome Atlas datasets. Most of the m6A RNA methylation regulators were confirmed to be differentially expressed among groups stratified by clinical characteristics and tissues. The clinical factors (including stage, grade, and gender) were correlated with the two subgroups (cluster 1/2). We identified an m6A RNA methylation regulator-based signature (including METTL3, YTHDC2, and YTHDF2) that could effectively stratify a high-risk subset of these patients by univariate and LASSO Cox regression, and receiver operating characteristic (ROC) analysis indicated that the signature had a powerful predictive ability. Immune cell analysis revealed that the genes in the signature were correlated with B cell, CD4 T cell, CD8 T cell, dendritic cell, macrophage, and neutrophil. Functional enrichment analysis suggested that these three genes may be involved in genetic and epigenetic events with known links to HCC. Moreover, the nomogram was established based on the signature integrated with clinicopathological features. The calibration curve and the area under ROC also demonstrated the good performance of the nomogram in predicting 3- and 5-year OS in the ICGC and TCGA cohorts. In summary, we demonstrated the vital role of m6A RNA methylation regulators in the initial presentation and progression of HCC and constructed a nomogram which would predict the clinical outcome and provide a basis for individualized therapy.

scholarly journals The Cancer Genome Atlas Predicts the Prognosis of Lung Carcinoma Based on Genes Associated with m6A Methylation

2021 ◽  
Author(s):  
Huanqing Liu ◽  
Tingting Li ◽  
Chunsheng Dong ◽  
Jun Lyu
Keyword(s):  
Lung Cancer ◽  
Survival Rate ◽  
Lung Carcinoma ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Predictive Values ◽  
Rna Methylation ◽  
Cancer Genome Atlas ◽  
M6a Rna Methylation ◽  
Genome Atlas

Abstract Lung cancer has become a predominant cause of death in relation with carcinoma worldwide. N6-methylladenosine (m6A) is a common mRNA that is internally modified, which has a pivotal role in mRNA splicing, outputting, localizing, and translating and in identifying stable features. This study evaluated the expression pattern and prognostic value of m6A-related genes in lung cancer. Expression data of lung cancer samples with related clinical information were obtained from The Cancer Genome Atlas (TCGA). Then, R software was used in combination with several corresponding software packages to identify the regulatory factors of m6A RNA methylation with differential expression. Three genes (METTL3, YTHDF1, and FTO) were overexpressed in lung cancer. METTL3 had a low survival rate (P < 0.05). Significant differences in survival rate were observed among the subgroups, which possessed differently expressed m6A levels. Two latent predicting factors (METTL3 and KIAA1429) that met the independent predictive values were selected. M6A RNA methylation modulators may be involved with the malignant progression of lung cancer, and the two selected risk characteristics of m6A RNA methylation regulators may be a potential prognostic biological marker for guiding customized therapies in patients with lung carcinoma.

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 Identification of miRNA-Based Signature as a Novel Potential Prognostic Biomarker in Patients with Breast Cancer

2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Jia Tang ◽  
Wei Ma ◽  
Qinlong Zeng ◽  
Jieliang Tan ◽  
Keshen Cao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Clinical Features ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Receiver Operating Curve ◽  
Risk Scores ◽  
Prognostic Indicators ◽  
The Novel ◽  
Predictive Values ◽  
Cox Regression Analysis

To identify the novel, noninvasive biomarkers to assess the outcome and prognosis of breast cancer (BC), patients with high sensitivity and specificity are greatly desired. Herein, the miRNA expression profile and matched clinical features of BC patients were extracted from The Cancer Genome Atlas (TCGA) database. The preliminary candidates were screened out by the univariate Cox regression test. Then, with the help of LASSO Cox regression analysis, the hsa-let-7b, hsa-mir-101-2, hsa-mir-135a-2, hsa-mir-22, hsa-mir-30a, hsa-mir-31, hsa-mir-3130-1, hsa-mir-320b-1, hsa-mir-3678, hsa-mir-4662a, hsa-mir-4772, hsa-mir-493, hsa-mir-556, hsa-mir-652, hsa-mir-6733, hsa-mir-874, and hsa-mir-9-3 were selected to construct the overall survival (OS) predicting signature, while the hsa-mir-130a, hsa-mir-204, hsa-mir-217, hsa-mir-223, hsa-mir-24-2, hsa-mir-29b-1, hsa-mir-363, hsa-mir-5001, hsa-mir-514a-1, hsa-mir-624, hsa-mir-639, hsa-mir-659, and hsa-mir-6892 were adopted to establish the recurrence-free survival (RFS) predicting signature. Referring to the median risk scores generated by the OS and RFS formulas, respectively, subgroup patients with high risk were strongly related to a poor OS and RFS revealed by Kaplan-Meier (K-M) plots. Meanwhile, receiver operating curve (ROC) analysis validated the accuracy and stability of these two signatures. When stratified by clinical features, such as tumor stage, age, and molecular subtypes, we found that the miRNA-based OS and RFS classifiers were still significant in predicting OS/RFS and showed the best predictive values than any other features. Besides, functional prediction analyses showed that these targeted genes of the enrolled miRNAs were enriched in cancer-associated pathways, such as MAPK/RTK, Ras, and PI3K-Akt signaling pathways. In summary, our observations demonstrate that the novel miRNA-based OS and RFS signatures are independent prognostic indicators for BC patients and worthy to be validated by further prospective studies.

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