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. 2019 Mar 4;11(1):38.
doi: 10.1186/s13148-019-0619-z.

Discovery and validation of DNA methylation markers for overall survival prognosis in patients with thymic epithelial tumors

Affiliations

Discovery and validation of DNA methylation markers for overall survival prognosis in patients with thymic epithelial tumors

Songlin Li et al. Clin Epigenetics. .

Abstract

Background: The current prognosis of thymic epithelial tumors (TETs) is according to the World Health Organization (WHO) histologic classification and the Masaoka staging system. These methods of prognosis have certain limitations in clinical application and there is a need to seek new method for determining the prognosis of patients with TETs. To date, there have been no studies done on the use of DNA methylation biomarkers for prognosis of TETs. The present study was therefore carried out to identify DNA methylation biomarkers that can determine the overall survival in patients with TETs.

Methods: Bioinformatic analysis of TCGA 450 K methylation array data, transcriptome sequencing data, WHO histologic classification and Masaoka staging system was performed to identify differentially expressed methylation sites between thymoma and thymic carcinoma as well as the different DNA methylation sites associated with the overall survival in patients with TETs. Using pyrosequencing, 4 different methylation sites (cg05784862, cg07154254, cg02543462, and cg06288355) were sequenced from tumor tissues of 100 Chinese patients with TETs. A prognostic model for TETs was constructed using these four methylation sites.

Results: The TCGA dataset showed 5155 and 6967 hyper- and hypomethylated CpG sites in type A-B3 group and type C group, respectively, of which 3600 were located within the gene promoter regions. One hundred thirty-four genes were silenced by promoter hypermethylation and 174 mRNAs were upregulated. Analysis of univariate and multivariate Cox regression showed significant association between the methylation levels of 187 sites and the overall survival in patients with TETs. cg05784862(KSR1), cg07154254(ELF3), cg02543462(ILRN), and cg06288355(RAG1) were identified as independent prognostic factors for overall survival in patients with TETs after adjusting for Masaoka staging in 100 Chinese patients. The prognostic model which consists of the four abovementioned genes had higher accuracy for predicting the 5-year overall survival in patients with TETs as compared to the Masaoka clinical staging. (Time-dependent ROC analysis AUC 1.000 vs 0.742, P = 2.7 × 10-6).

Conclusions: The methylation levels of cg05784862(KSR1), cg07154254(ELF3), cg02543462(ILRN), and cg06288355(RAG1) sites are associated with the progression of TETs and may serve as new biomarkers for predicting the overall survival in patients with TETs.

Keywords: DNA methylation; Prognostic model; Thymic epithelial tumors.

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Conflict of interest statement

Ethics approval and consent to participate

This study was approved by the Medical Ethics Committee at Institute of Surgery Research, Third Affiliated Hospital, Army Medical University (Third Military Medical University). Written informed consent was obtained from all patients prior to their enrolment for permission to use their clinical information and tissue samples for prognostic analysis.

Consent for publication

Not available.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
A volcano plots showing significantly expressed methylation sites in 392,653 probes in HumanMethylation450K array between thymoma with WHO histological type C and type A to B3. The red dots represent significantly differential methylation probes among all 392,653 probes included into analysis according to criteria mentioned in the “Methods” section
Fig. 2
Fig. 2
A heatmap showing methylation profiles of 542 significantly expressed methylation sites which localize within promotor regions in corresponding genes and could be involved in regulation of mRNA expression for genes across all 124 cases. The top is the list of patients’ identifiers provided by TCGA, and the terminal characters in each patient’s IDs indicate classification of WHO histological types
Fig. 3
Fig. 3
Kaplan-Meier curves showing methylation profile stratifies thymoma patients in whole population into survival subgroups in TCGA dataset. ac High methylation in cg05784862(KSR1), cg07154254(ELF3), and cg02543462(ILRN) is associated with significantly longer overall survival. d Low methylation in cg06288355(RAG1) is associated with significantly longer overall survival
Fig. 4
Fig. 4
Representative images of pyrosequencing for cg07154254 in ELF3 in four patients. Increased methylation shown in patients no. 141 and no. 135 and low methylation in patients no. 29 and No.33
Fig. 5
Fig. 5
Box plots showing the distribution of beta values in cg05784862 in KSR1, cg07154254(ELF3), cg02543462(ILRN), and cg06288355(RAG1) between thymoma with WHO histological type C and type A to B3 in validation set. The boxes with shadow represent patients with WHO histological type C
Fig. 6
Fig. 6
Kaplan-Meier curves showing methylation profile stratifies thymoma patients in whole population into survival subgroups in validation set. ac High methylation in cg05784862(KSR1), cg07154254(ELF3), and cg02543462(ILRN) is associated with significantly longer overall survival. d Low methylation in cg06288355(RAG1) is associated with significantly longer overall survival
Fig. 7
Fig. 7
Time-dependent curves showing different capacities for predicting 5-year overall survival in validation set. Risk score is constructed from linear combination of each coefficient in univariate Cox regression for the four methylation sites in TCGA dataset and beta value in validation set as proposed in the “Methods” section

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