Research Paper|Volume 13, Issue 16|pp 20164—20178

Identification of 4-methylation driven genes based prognostic signature in thyroid cancer: an integrative analysis based on the methylmix algorithm

Zhiwei Chen⁵, Xiaoli Liu⁵, Fangfang Liu⁵, Guolie Zhang², Haijian Tu³, Wei Lin⁴, Haifeng Lin¹

¹Department of Gastroenterology, The Affiliated Hospital of Putian University, Putian 351100, Fujian Province, China
²Department of Thyroid Surgery, The Affiliated Hospital of Putian University, Putian 351100, Fujian Province, China
³Clinical Laboratory, The Affiliated Hospital of Putian University, Putian 351100, Fujian Province, China
⁴Department of Gastrointestinal Surgery, The Affiliated Hospital of Putian University, Putian 351100, Fujian Province, China
⁵Department of Pathology, The Affiliated Hospital of Putian University, Putian 351100, Fujian Province, China

Received: May 24, 2021Accepted: July 1, 2021Published: August 29, 2021

https://doi.org/10.18632/aging.203338

Copyright: © 2021 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Thyroid cancer (TC) is known with a high rate of persistence and recurrence. We aimed to develop a prognostic signature to monitor and assess the survival of TC patients. mRNA expression and methylation data were downloaded from the TCGA database. Then, R package methylmix was applied to construct a mixed model was used to identify methylation-driven genes (MDGs) according to the methylation levels. Furthermore, an MDGs based prognostic signature and predictive nomogram were constructed according to the analysis of univariate and multivariate Cox regression. Totally 62 methylation-driven genes that were mainly enriched in substrate-dependent cell migration, cellular response to mechanical stimulus, et al. were found in TC tissues. aldolase C (AldoC), C14orf62, dishevelled 1 (DVL1), and protein tyrosine phosphatase receptor type C (PTPRC) were identified to be significantly related to patients' survival, and may serve as independent prognostic biomarkers for TC. Additionally, the prognostic methylation signature and a novel prognostic, predictive nomogram was established based on the methylation level of 4 MDGs. In this study, we developed a 4-MDGs based prognostic model, which might be the potential predictors for the survival rate of TC patients, and this findings might provide a novel sight for accurate monitoring and prognosis assessment.