RNA N6-Methyladenosine-Related Gene Contribute to Clinical Prognostic Impact on Patients With Liver Cancer

Wang, Wei; Sun, Bo; Yang, Xia; Sun, Shenghong; He, Chuanchao

doi:10.3389/fgene.2020.00306

Cited by 10 publications

(10 citation statements)

References 44 publications

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“…We collected 23 widely reported m6A RNA methylation regulators (2,(25)(26)(27)(28)(29), studied their expression differences in normal and cancerous tissues, and evaluated the relationship between m6A regulation of tumor-related genes and clinically relevant factors in the hematological malignancies.…”

Section: Selection Of M6a Rna Methylation Regulatorsmentioning

confidence: 99%

Clinical and Prognostic Pan-Cancer Analysis of N6-Methyladenosine Regulators in Two Types of Hematological Malignancies: A Retrospective Study Based on TCGA and GTEx Databases

et al. 2021

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N6-methyladenosine (m6A) is one of the most active modification factors of mRNA, which is closely related to cell proliferation, differentiation, and tumor development. Here, we explored the relationship between the pathogenesis of hematological malignancies and the clinicopathologic parameters. The datasets of hematological malignancies and controls were obtained from the TCGA [AML (n = 200), DLBCL (n = 48)] and GTEx [whole blood (n = 337), blood vascular artery (n = 606)]. We analyzed the m6A factor expression differences in normal tissue and tumor tissue and their correlations, clustered the express obvious clinical tumor subtypes, determined the tumor risk score, established Cox regression model, performed univariate and multivariate analysis on all datasets. We found that the AML patients with high expression of IGF2BP3, ALKBH5, and IGF2BP2 had poor survival, while the DLBCL patients with high expression of METTL14 had poor survival. In addition, “Total” datasets analysis revealed that IGF2BP1, ALKBH5, IGF2BP2, RBM15, METTL3, and ZNF217 were potential oncogenes for hematologic system tumors. Collectively, the expressions of some m6A regulators are closely related to the occurrence and development of hematologic system tumors, and the intervention of specific regulatory factors may lead to a breakthrough in the treatment in the future.

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Section: Selection Of M6a Rna Methylation Regulatorsmentioning

confidence: 99%

Clinical and Prognostic Pan-Cancer Analysis of N6-Methyladenosine Regulators in Two Types of Hematological Malignancies: A Retrospective Study Based on TCGA and GTEx Databases

et al. 2021

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“…In fact, their precise roles and mechanisms are widely studied. The prognostic value of these regulators have also been analyzed in multiple malignant tumors, including liver cancer ( 45 ), gastric cancer ( 46 ), clear cell renal cell carcinoma (ccRCC) ( 47 , 48 ), colorectal cancer ( 32 ). The prognostic signature obtained using two m 6 A RNA methylation regulators (METTL14 and METTL3) had significant value in ccRCC, the AUC value for their risk prediction is 0.706 ( 47 , 48 ).…”

Section: Discussionmentioning

confidence: 99%

A Ten-N6-Methyladenosine (m6A)-Modified Gene Signature Based on a Risk Score System Predicts Patient Prognosis in Rectum Adenocarcinoma

Huang

Wang

et al. 2021

Front. Oncol.

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ObjectivesThe study aims to analyze the expression of N6-methyladenosine (m6A)-modified genes in rectum adenocarcinoma (READ) and identify reliable prognostic biomarkers to predict the prognosis of READ.Materials and MethodsRNA sequence data of READ and corresponding clinical survival data were obtained from The Cancer Genome Atlas (TCGA) database. N6-methyladenosine (m6A)-modified genes in READ were downloaded from the “m6Avar” database. Differentially expressed m6A-modified genes in READ stratified by different clinicopathological characteristics were identified using the “limma” package in R. Protein-protein interaction (PPI) network and co-expression analysis of differentially expressed genes (DEGs) were performed using “STRING” and Cytoscape, respectively. Principal component analysis (PCA) was done using R. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were used to functionally annotate the differentially expressed genes in different subgroups. Univariate Cox regression analyses were conducted to identify the powerful independent prognostic factors in READ associated with overall survival (OS). A robust likelihood-based survival model was built using the “rbsurv” package to screen for survival-associated signature genes. The Support Vector Machine (SVM) was used to predict the prognosis of READ through the risk score of survival-associated signature genes. Correlation analysis were carried out using GraphPad prism 8.ResultsWe screened 974 differentially expressed m6A-modified genes among four types of READ samples. Two READ subgroups (group 1 and group 2) were identified by K means clustering according to the expression of DEGs. The two subgroups were significantly different in overall survival and pathological stages. Next, 118 differentially expressed genes between the two subgroups were screened and the expression of 112 genes was found to be related to the prognosis of READ. Next, a panel of 10 survival-associated signature genes including adamtsl1, csmd2, fam13c, fam184a, klhl4, olfml2b, pdzd4, sec14l5, setbp1, tmem132b was constructed. The signature performed very well for prognosis prediction, time-dependent receiver-operating characteristic (ROC) analysis displaying an area under the curve (AUC) of 0.863, 0.8721, and 0.8752 for 3-year survival rate, prognostic status, and pathological stage prediction, respectively. Correlation analysis showed that the expression levels of the 10 m6A-modified genes were positively correlated with that of m6A demethylase FTO and ALKBH5.ConclusionThis study identified potential m6A-modified genes that may be involved in the pathophysiology of READ and constructed a novel gene expression panel for READ risk stratification and prognosis prediction.

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“…THCA patients were clustered into different subgroups based on the pyroptosis-related DEGs using the “ConsensusClusterPlus” package in R [ 20 ].…”

Section: Methodsmentioning

confidence: 99%

Identification and validation of a pyroptosis-related prognostic signature for thyroid cancer

Shi

Sun

et al. 2021

Cancer Cell Int

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Background Pyroptosis is a form of programmed cell death triggered by inflammasomes. However, the roles of pyroptosis-related genes in thyroid cancer (THCA) remain still unclear. Objective This study aimed to construct a pyroptosis-related signature that could effectively predict THCA prognosis and survival. Methods A LASSO Cox regression analysis was performed to build a prognostic model based on the expression profile of each pyroptosis-related gene. The predictive value of the prognostic model was validated in the internal cohort. Results A pyroptosis-related signature consisting of four genes was constructed to predict THCA prognosis and all patients were classified into high- and low-risk groups. Patients with a high-risk score had a poorer overall survival (OS) than those in the low-risk group. The area under the curve (AUC) of the receiver operator characteristic (ROC) curves assessed and verified the predictive performance of this signature. Multivariate analysis showed the risk score was an independent prognostic factor. Tumor immune cell infiltration and immune status were significantly higher in low-risk groups, which indicated a better response to immune checkpoint inhibitors (ICIs). Of the four pyroptosis-related genes in the prognostic signature, qRT-PCR detected three of them with significantly differential expression in THCA tissues. Conclusion In summary, our pyroptosis-related risk signature may have an effective predictive and prognostic capability in THCA. Our results provide a potential foundation for future studies of the relationship between pyroptosis and the immunotherapy response.

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RNA N6-Methyladenosine-Related Gene Contribute to Clinical Prognostic Impact on Patients With Liver Cancer

Cited by 10 publications

References 44 publications

Clinical and Prognostic Pan-Cancer Analysis of N6-Methyladenosine Regulators in Two Types of Hematological Malignancies: A Retrospective Study Based on TCGA and GTEx Databases

Clinical and Prognostic Pan-Cancer Analysis of N6-Methyladenosine Regulators in Two Types of Hematological Malignancies: A Retrospective Study Based on TCGA and GTEx Databases

A Ten-N6-Methyladenosine (m6A)-Modified Gene Signature Based on a Risk Score System Predicts Patient Prognosis in Rectum Adenocarcinoma

Identification and validation of a pyroptosis-related prognostic signature for thyroid cancer

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