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

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

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

10.21203/rs.3.rs-50655/v1 ◽

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.

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

10.21203/rs.3.rs-125323/v1 ◽

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.

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

10.21203/rs.3.rs-113477/v1 ◽

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.

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

10.21203/rs.2.22602/v1 ◽

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.

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Prognostic Value of an m6A RNA Methylation Regulator-Based Signature in Patients with Hepatocellular Carcinoma

BioMed Research International ◽

10.1155/2020/2053902 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Xiaomin Wu ◽

Xiaojing Zhang ◽

Leilei Tao ◽

Xichao Dai ◽

Ping Chen

Keyword(s):

Hepatocellular Carcinoma ◽

Regression Analysis ◽

Cox Regression ◽

Malignant Tumors ◽

The Cancer Genome Atlas ◽

Prognostic Signature ◽

Cox Regression Analysis ◽

Rna Methylation ◽

M6a Rna Methylation ◽

Cluster 2

Purposes. Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. Recent researches have demonstrated that m6A methylation regulators play a key role in various cancers, such as gastric cancer and colon adenocarcinoma. Several m6A methylation regulators are reported to predict the prognosis of HCC. Therefore, there is a need to further identify the predictive value of m6A methylation regulators in HCC. Methods. We utilized The Cancer Genome Atlas (TCGA) database to obtain the gene expression profile of m6A RNA methylation regulators and clinical information for patients with HCC. Besides, we identified two clusters of HCC with various clinical factors by consensus clustering analysis. Then the least absolute shrinkage and selection operator (LASSO) and the Cox regression analysis were applied to construct a prognostic signature. Results. Except for ZC3H13 and METTL14, a majority of the thirteen m6A RNA methylation regulators were significantly overexpressed in HCC specimens. HCC patients were classified into two groups (cluster 1 and cluster 2). The cluster 1 was with a significantly worse prognosis than cluster 2, and most of the 13 known m6A RNA methylation regulators were upregulated in cluster 1. Besides, we developed a prognostic signature consisting of YTHDF2, YTHDF1, METTL3, KIAA1429, and ZC3H13, which could successfully differentiate high-risk patients. More importantly, univariate and multivariate Cox regression analysis indicated that the signature-based risk score was an independent prognostic factor for patients with HCC. Conclusions. Our study showed these five m6A RNA methylation regulators can be used as practical and reliable prognostic tools of HCC, which might have potential value for therapeutic strategies.

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The prognostic values of m6A RNA methylation regulators in Uveal melanoma

10.21203/rs.2.12974/v2 ◽

2020 ◽

Author(s):

Jing Tang ◽

Qi Wan ◽

Jianqun Lu

Keyword(s):

Regression Analysis ◽

Uveal Melanoma ◽

Cox Regression ◽

Strategy Development ◽

Lower Percentage ◽

Consensus Clustering ◽

Cox Regression Analysis ◽

Rna Methylation ◽

Mtorc1 Signaling ◽

M6a Rna Methylation

Abstract Background: The aim of this study was to identify gene signatures and prognostic values of m6A methylation regulators in uveal melanoma (UM).Methods: The RNA sequencing dataset and corresponding clinical information were downloaded from TCGA and GEO database. Based on the expression of m6A RNA methylation regulators, the patients were further clustered into different groups by applying the “ClassDiscovery” algorithm. Best survival analysis was performed to select prognostic m6A regulators and multivariate cox regression analysis was applied to constructed m6A regulators signature. The association between mutations and m6A regulators was assessed by Kruskal−Wallis tests and clinical characteristics were examined by using chi-square test.Results: Totally, we identified two molecular subtypes of UM (C1/2) by applying consensus clustering to m6A RNA methylation regulators. In contrast to the C1 subtype, the C2 subtype associates with a better prognosis, have higher percentage of subtype 1 and lower percentage of Monosomy 3 which have been regarded as the well established prognostic markers for UM. The malignant hallmarks of mTORC1 signaling, oxidative phosphorylation, interferon-a response and apoptosis signaling are also significantly enriched in the C1 subtype. Moreover, a 3-m6A regulators signature was constructed by multivariate cox regression analysis method, which closely correlated with chromosome 3 status, subtype 1 of UM and can robustly predict patients’ overall survival time.Conclusions: m6A RNA methylation regulators take a crucial role in the potential malignant progression and prognostic value of UM and might be regarded as a new promising biomarker for UM prognosis and treatment strategy development.

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The prognostic values of m6A RNA methylation regulators in Uveal melanoma

10.21203/rs.2.12974/v3 ◽

2020 ◽

Author(s):

Jing Tang ◽

Qi Wan ◽

Jianqun Lu

Keyword(s):

Regression Analysis ◽

Uveal Melanoma ◽

Cox Regression ◽

Strategy Development ◽

Lower Percentage ◽

Consensus Clustering ◽

Cox Regression Analysis ◽

Rna Methylation ◽

Mtorc1 Signaling ◽

M6a Rna Methylation

Abstract Purpose: The aim of this study was to identify gene signatures and prognostic values of m6A methylation regulators in uveal melanoma (UM). Methods: The RNA sequencing dataset and corresponding clinical information were downloaded from TCGA and GEO database. Based on the expression of m6A RNA methylation regulators , the patients were further clustered into different groups by applying the “ClassDiscovery” algorithm. Best survival analysis was performed to select prognostic m6A regulators and multivariate cox regression analysis was applied to constructed m6A regulators signature. The association between mutations and m6A regulators was assessed by Kruskal−Wallis tests and clinical characteristics were examined by using chi-square test. Result: Totally, we identified two molecular subtypes of UM (C1/2) by applying consensus clustering to m6A RNA methylation regulators. In contrast to the C1 subtype, the C2 subtype associates with a better prognosis, have higher percentage of subtype 1 and lower percentage of Monosomy 3 which have been regarded as the well established prognostic markers for UM. The malignant hallmarks of mTORC1 signaling, oxidative phosphorylation, interferon-a response and apoptosis signaling are also significantly enriched in the C1 subtype. Moreover, a 3 - m6A regulators signature was constructed by multivariate cox regression analysis method, which closely correlated with chromosome 3 status, subtype 1 of UM and can robustly predict patients’ overall survival time. Conclusions: m6A RNA methylation regulators take a crucial role in the potential malignant progression and prognostic value of UM and might be regarded as a new promising biomarker for UM prognosis and treatment strategy development.

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

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.724860 ◽

2021 ◽

Vol 9 ◽

Author(s):

Ran Wei ◽

Jichuan Quan ◽

Shuofeng Li ◽

Hengchang Liu ◽

Xu Guan ◽

...

Keyword(s):

Colorectal Cancer ◽

Cox Regression ◽

Stage Iv ◽

The Cancer Genome Atlas ◽

Poor Overall Survival ◽

Tissue Samples ◽

Cox Regression Analysis ◽

Rna Methylation ◽

M6a Rna Methylation ◽

Highly Correlated

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.

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

Cancer Cell International ◽

10.1186/s12935-021-02090-9 ◽

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.

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

Frontiers in Genetics ◽

10.3389/fgene.2021.671179 ◽

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.

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