J Cancer 2021; 12(21):6507-6518. doi:10.7150/jca.53208

Research Paper

Analysis of Methylation‐driven Genes in Pancreatic Ductal Adenocarcinoma for Predicting Prognosis

Zihan Zhang1,2, Rui Zhu3, Wentian Sun1,2, Jun Wang2✉, Jin Liu1✉

1. Lab for Aging Research, National Clinical Research Center for Geriatrics, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
2. State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Orthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China.
3. State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Prosthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, China.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
Citation:
Zhang Z, Zhu R, Sun W, Wang J, Liu J. Analysis of Methylation‐driven Genes in Pancreatic Ductal Adenocarcinoma for Predicting Prognosis. J Cancer 2021; 12(21):6507-6518. doi:10.7150/jca.53208. Available from https://www.jcancer.org/v12p6507.htm

File import instruction

Abstract

Purpose: Considerable variations in methylation profile have been found in various cancers to modulate tumorigenesis and affect prognosis. To provide a theoretical basis for early detection, prognosis evaluation and targeted treatment for patients with pancreatic ductal adenocarcinoma: PDAC, this study identified methylation-driven genes in PDAC and explored their prognostic performance.

Methods: The methylation, expression and clinical data of PDAC patients were extracted from TCGA database. Based on the β-mixture model of the MethylMix R package, the differential methylation status and connection between methylation and expression degree were examined to screen out methylation-driven genes in PDAC. COX analyses and lasso regressions were applied to construct a linear risk model based on methylation-driven genes. Univariate and multivariate analyses were performed to ensure the risk model was an independent prognostic factor. Joint survival analyses of methylation and gene expression were conducted to explore the prognostic value of component genes. The methylation sites in the key genes were also investigated.

Results: A total of 118 methylation-driven genes in PDAC were identified, and two genes (FOXI2, MYEOV) constituted the risk model whose AUC was 0.722 at one year of overall survival rate, displaying a better performance on survival prediction than other clinical features. Further survival analyses demonstrated that the expression of MYEOV and combined methylation and expression levels of the genes MYEOV and FOXI2 can be potential biomarkers for survival prediction and targets of drug manipulation of PDAC patients. Close relationships were discovered between two sites in MYEOV and one site in FOXI2 and the prognosis of PDAC patients.

Conclusion: Concentrating on DNA methylation, our study identified potential biomarkers and developed a reliable short-term predictive model for prognosis of PDAC patients.

Keywords: Pancreatic ductal adenocarcinoma, DNA methylation, Proportional hazards models, Survival analysis, Prognosis