Identification and validation of m6A RNA methylation regulators with clinical prognostic value in Papillary thyroid cancer

Xinyi Wang; Xiaorui Fu; Junjia Zhang; Chengfeng Xiong; Shuyong Zhang; Yunxia Lv

doi:10.1186/s12935-020-01283-y

Identification and validation of m⁶A RNA methylation regulators with clinical prognostic value in Papillary thyroid cancer

Cancer Cell Int. 2020 May 29:20:203. doi: 10.1186/s12935-020-01283-y. eCollection 2020.

Authors

Xinyi Wang^#¹, Xiaorui Fu^#¹, Junjia Zhang², Chengfeng Xiong³, Shuyong Zhang³, Yunxia Lv³

Affiliations

¹ Queen Mary College, Medical Department, Nanchang University, Nanchang, Jiangxi People's Republic of China.
² Department of Breast and Endocrine Surgical Oncology, Graduate School of Medicine, Tohoku University, Sendai, Miyagi 980-8574 Japan.
³ Department of Thyroid Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi People's Republic of China.

^# Contributed equally.

Abstract

Background: Papillary thyroid cancer (PTC) is a type of malignant tumor with excellent prognosis, accounting for more than 80% of thyroid cancer. Recently, numerous studies illustrated the importance of N ⁶-methyladenosine (m⁶A) RNA modification to tumorigenesis, but it has never been reported in PTC.

Methods: We downloaded data from The Cancer Genome Atlas (TCGA) and analyzed RNA expression, single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) of 19 m⁶A RNA methylation regulators in PTC. Then we used nonnegative matrix factorization (NMF) to cluster patients into two m⁶A subtypes and compared them in overall survival (OS) and disease-free survival (DFS). The Weighted correlation network analysis (WGCNA) and univariate Cox proportional hazard model (CoxPH) were used to select genes for the construction of a m⁶A-related signature. The accuracy and prognostic value of this signature were validated by using receiver operating characteristic (ROC) curves, K-M (Kaplan-Meier) survival analysis, univariant and multivariant analyses.

Results: CNVs and differential expression of m⁶A regulators were observed in PTC patients. Especially IGF2BP2 (Insulin-like growth factor 2 mRNA binding protein 2), which was most significantly overexpressed in tumor tissue. We chose 4 genes in the m⁶A-related module from WGCNA: IGF2BP2, STT3A, MTHFD1 and GSTM4, and used them to construct a m⁶A-related signature. The prognostic value of this signature was validated, and risk scores provided by the signature was the independent prognostic factor for PTC. A nomogram was also provided for clinical usage.

Conclusions: We performed a comprehensive evaluation of the m⁶A RNA modification landscape of PTC and explored its underlying mechanisms. Our m⁶A-related signature was of great significance in predicting the DFS of patients with PTC. And IGF2BP2 was a gene worthy for further analysis as its strong correlation with DFS and clinical phenotypes of PTC.

Keywords: IGF2BP2; Papillary thyroid cancer; RNA methylation; TCGA; m6A.