Identification of a m6A RNA methylation regulators-based signature for predicting the prognosis of clear cell renal carcinoma

Jing Chen; Kun Yu; Guansheng Zhong; Wei Shen

doi:10.1186/s12935-020-01238-3

Identification of a m⁶A RNA methylation regulators-based signature for predicting the prognosis of clear cell renal carcinoma

Cancer Cell Int. 2020 May 7:20:157. doi: 10.1186/s12935-020-01238-3. eCollection 2020.

Authors

Jing Chen¹, Kun Yu², Guansheng Zhong³, Wei Shen⁴

Affiliations

¹ 1Department of Urology, Tongde Hospital of Zhejiang Province, Hangzhou, Zhejiang Province China.
² 2Department of Breast and Thyroid Surgery, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, 310014 Zhejiang People's Republic of China.
³ 3Department of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, 79 Qingchun Road, Hangzhou, 310013 Zhejiang People's Republic of China.
⁴ 4Department of Nephrology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, 310014 Zhejiang People's Republic of China.

Abstract

Background: The mortality rate of clear cell renal cell carcinoma (ccRCC) remains high. 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 ccRCC patients.

Methods: The 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 were evaluated. Consensus clustering analysis was conducted to identify clusters of ccRCC 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 independent prognostic significance of the signature.

Results: Five m⁶A-related genes (ZC3H13, METTL14, YTHDF2, YTHDF3 and HNRNPA2B1) showed significantly downregulated in tumor tissue, while seven regulators (YTHDC2, FTO, WTAP, METTL3, ALKBH5, RBM15 and KIAA1429) was remarkably upregulated in ccRCC. Consensus clustering analysis identified two clusters of ccRCC with significant differences in overall survival (OS) and tumor stage between them. We also constructed a two-gene signature, METTL3 and METTL14, serving as an independent prognostic indicator for distinguishing ccRCC patients with different prognosis both in training, validation and our own clinical datasets. The receiver operator characteristic (ROC) curve indicated the area under the curve (AUC) in these three datasets were 0.721, 0.684 and 0.828, respectively, demonstrated that the prognostic signature had a good prediction efficiency.

Conclusions: m⁶A methylation regulators exert as potential biomarkers for prognostic stratification of ccRCC patients and may assist clinicians achieving individualized treatment for this patient population.

Keywords: Clear cell renal cell carcinoma; Epigenetics; Prognostic signature; Survival analysis; m6A methylation.