Identification of a Two-m6A RNA Methylation Regulator Risk Signature as an Independent Prognostic Biomarker in Papillary Renal Cell Carcinoma by Bioinformatic Analysis
Open Access
- 6 February 2021
- journal article
- research article
- Published by Hindawi Limited in BioMed Research International
- Vol. 2021, 1-10
- https://doi.org/10.1155/2021/4582082
Abstract
N6-Methyladenosine (m6A), the most common form of mRNA modification, is dynamically regulated by the m6A RNA methylation regulators, which play an important role in regulating the gene expression and phenotype in both health and disease. However, the role of m6A in papillary renal cell carcinoma (pRCC) is unknown. The purpose of this work is to investigate the prognostic value of m6A RNA methylation regulators in pRCC; thus, we can build a risk score model based on m6A RNA methylation regulators as a risk signature for predicting the prognosis of pRCC. Here, we investigated the expression and corresponding clinical data by bioinformatic analysis based on 289 pRCC tissues and 32 normal kidney tissues obtained from TCGA database. As a result, we identified the landscape of m6A RNA methylation regulators in pRCC. We grouped all pRCC patients into two clusters by consensus clustering to m6A RNA methylation regulators, but we found that the clusters were not correlated to the prognosis and clinicopathological features of pRCC. Therefore, we additionally built a two-m6A RNA methylation regulator risk score model as a risk signature by the univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression. The risk signature was constructed as follows: 0.031 HNRNPC + 0.199 KIAA 1429 . It revealed that the risk score was associated with the clinicopathological features such as pT status and pN status of pRCC. More importantly, the risk score was an independent prognostic marker for pRCC patients. Thus, m6A RNA methylation regulators contributed to the malignant progression of pRCC influencing its prognosis.Funding Information
- National Natural Science Foundation of China (81972381, 2018YFC1004200, 2017YFC1002001, 7182177, BYSYZD2019032)
This publication has 45 references indexed in Scilit:
- Web-TCGA: an online platform for integrated analysis of molecular cancer data setsBMC Bioinformatics, 2016
- N6-methyladenosine–encoded epitranscriptomicsNature Structural & Molecular Biology, 2016
- Papillary renal cell carcinoma: A review of the current therapeutic landscapeCritical Reviews in Oncology/Hematology, 2015
- N6-methyladenosine marks primary microRNAs for processingNature, 2015
- limma powers differential expression analyses for RNA-sequencing and microarray studiesNucleic Acids Research, 2015
- Gene expression regulation mediated through reversible m6A RNA methylationNature Reviews Genetics, 2014
- Tumour heterogeneity in the clinicNature, 2013
- Topology of the human and mouse m6A RNA methylomes revealed by m6A-seqNature, 2012
- Selection of important variables and determination of functional form for continuous predictors in multivariable model buildingStatistics in Medicine, 2007
- Predicting survival from microarray data—a comparative studyBioinformatics, 2007