Prediction of the Prognosis Based on Chromosomal Instability-Related DNA Methylation Patterns of ELOVL2 and UBAC2 in PTCs

• Main Authors: Jun Han, Meijun Chen, Qingxiao Fang, Yanqing Zhang, Yihan Wang, Jamaspishvili Esma, Hong Qiao
• Format: Article
• Language: English
• Published: Elsevier 2019-12-01
• Series: Molecular Therapy: Nucleic Acids
• Online Access: http://www.sciencedirect.com/science/article/pii/S2162253119302756

Papillary thyroid carcinoma (PTC) is the most common malignant tumor of endocrine systems. Chromosomal instability (CIN) is crucial to the clinical prognoses of tumor patients. DNA methylation plays an important role in the regulation of gene expression and CIN. Based on PTC samples from The Cancer Genome Atlas database, we used multiple regression analyses to identify methylation patterns of CpG sites with the strongest correlation with gene expression. A total of 4,997 genes were obtained through combining the CpG sites, which were represented as featured DNA methylation patterns. In order to identify CIN-related epigenetic markers of PTC survival, we developed a method to characterize CIN based on DNA methylation patterns of genes using the Student’s t statistics. We found that 1,239 genes were highly associated with CIN. With the use of the log-rank test, univariate Cox regression analyses, and the Kaplan-Meier method, DNA methylation patterns of UBAC2 and ELOVL2, highly correlated with CIN, provided potential prognostic values for PTC. The higher these two genes, risk scores were correlated with worse PTC patient prognoses. Moreover, the ELOVL2 risk score was significantly different in the four stages of PTC, suggesting that it was related to the progress of PTC. The DNA methylation pattern associated with CIN may therefore be a good predictor of PTC survival. Keywords: papillary thyroid carcinoma, chromosomal instability, DNA methylation, gene expression, prognosis