[HTML][HTML] Effect of m6A RNA Methylation Regulators on Malignant Progression and Prognosis in Renal Clear Cell Carcinoma

J Wang, C Zhang, W He, X Gou - Frontiers in oncology, 2020 - frontiersin.org
J Wang, C Zhang, W He, X Gou
Frontiers in oncology, 2020frontiersin.org
Objectives: This study aims to explore the roles of 13 m6A RNA methylation regulators in
clear cell renal cell carcinoma (ccRCC), and identify a risk signature and prognostic values
of m6A RNA methylation regulators in ccRCC. Materials and Methods: RNA sequence data
of ccRCC was obtained from The Cancer Genome Atlas (TCGA) database. Differentially
expressed of 13 m6A RNA methylation regulators in ccRCC stratified by different
clinicopathological characteristics were unveiled using “limma” package in R version 3.6. 0 …
Objectives: This study aims to explore the roles of 13 m6A RNA methylation regulators in clear cell renal cell carcinoma (ccRCC), and identify a risk signature and prognostic values of m6A RNA methylation regulators in ccRCC.
Materials and Methods: RNA sequence data of ccRCC was obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed of 13 m6A RNA methylation regulators in ccRCC stratified by different clinicopathological characteristics were unveiled using “limma” package in R version 3.6.0. Cox regression and LASSO analyses were conducted to identify the powerful independent prognostic factors in ccRCC associated with overall survival (OS). Protein-protein interaction (PPI) network and correlation analyses of the 13 m6A RNA methylation regulators were performed using “STRING” and R package, respectively. Principal component analysis (PCA) was also done using R. In addition, gene ontology (GO), GSEA and Kyoto Encyclopedia of Genes and Genomes pathways were used to functionally annotate the differentially expressed genes in different subgroups.
Results: Most of the 13 m6A RNA methylation regulators are differentially expressed in ccRCC tissue samples stratified by different clinicopathological characteristics in 537 patients. Next, a risk signature for predicting prognosis of ccRCC patients, was established based on two powerful independent prognostic m6A RNA methylation regulators (METTL14 and METTL3). Then, two subgroups (cluster1 and 2) were identified by consensus clustering to the two powerful independent factors and the cluster1 had a poorer prognosis than cluster2. Furthermore, the genes in cluster1 were significantly enriched in cancer-related pathways, biological process, and hallmarks, including “cell adhesion molecules (CAMs),” “leukocyte migration,” “Wnt/β-catenin signaling,” and so on.
Conclusion: M6A RNA methylation regulators play important roles in the initiation and progression of ccRCC and provide a novel sight to understand m6A RNA modification in ccRCC.
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