Establishment of a Risk Signature Based on m6A RNA Methylation Regulators That Predicts Poor Prognosis in Renal Cell Carcinoma

• Published in: OncoTargets and therapy Vol. 14; pp. 413 - 426
• Main Authors: Wei, Jingsun, Qian, Yucheng, Tang, Yang, Ge, Xiaoxu, Jiang, Kai, Fang, Yimin, Fu, Dongliang, Kong, Xiangxing, Xiao, Qian, Ding, Kefeng
• Format: Journal Article
• Language: English
• Published: New Zealand Dove Medical Press Limited 01.01.2021; Taylor & Francis Ltd; Dove
• Subjects: Bioinformatics; Carcinoma, Renal cell; Datasets; DNA methylation; Gene expression; Genomes; Genomics; Kidney cancer; Medical prognosis; Metastasis; Methylation; Methyltransferases; N6-methyladenosine; Original Research; Prognosis; Proteins; Reading; Regression analysis; Renal cell carcinoma; Risk assessment; RNA; RNA modification; Tumors; Variance analysis; United States > US; m6A methylation; renal cell carcinoma; TCGA; prognostic signature
• ISSN: 1178-6930; 1178-6930
• DOI: 10.2147/OTT.S288663

N6-methyladenosine (m6A) modifications represent one of the most common methylation modifications, and they are mediated by m6A RNA methylation regulators. However, their functions in renal cell carcinoma (RCC) are not completely understood. The aim of this study was to investigate the effects of the regulators in RCC. The expression levels of the 13 main m6A RNA methylation regulators in RCC were detected and consensus clustering was performed to explore their relationships with RCC. Thereafter, a risk signature based on the regulators was established. This risk model was fully verified by conducting prognostic analyses using two datasets (The Cancer Genome Atlas [TCGA] and Gene Expression Omnibus [GEO] datasets) and a ROC curve analysis. Of the 13 main m6A regulators, six were significantly upregulated and four were significantly downregulated in 893 RCC cases compared to 128 normal controls in the TCGA database. Consensus clustering based on the regulators identified two clusters of RCC cases, which were significantly associated with a pathological characteristic (T status). Thus, these results indicated that m6A RNA methylation regulators were associated with RCC. Thereafter, a risk model involving two of the regulators (METTL14 and WTAP) was established. The alterations in the mRNA and protein expression levels of these two regulators were further confirmed based on Human Protein Atlas data and real-time PCR in RCC and normal cell lines. The results indicated that the risk model may serve as an independent prognostic marker of overall survival, and it was also associated with clinicopathological characteristics (T status, M status, pathological stage, and gender) in RCC. Collectively, the results of this study indicated that the risk model (based on two m6A RNA methylation regulators) may serve as an independent prognostic indicator of RCC, which may aid further investigation into m6A RNA modification in RCC.