Research Papers:

Promoter DNA methylation analysis reveals a combined diagnosis of CpG-based biomarker for prostate cancer

Yuanyuan Tang, Shusuan Jiang, Yinmin Gu, Weidong Li, Zengnan Mo, Yuanjie Huang, Tianyu Li and Yanling Hu _

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Oncotarget. 2017; 8:58199-58209. https://doi.org/10.18632/oncotarget.16437

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Yuanyuan Tang1,*, Shusuan Jiang2,*, Yinmin Gu3, Weidong Li3, Zengnan Mo2,4, Yuanjie Huang3, Tianyu Li2,4 and Yanling Hu3,4,5

1Guangxi Reproductive Medical Research Center, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China

2Department of Urology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China

3Life Sciences Institute, Guangxi Medical University, Nanning, Guangxi 530021, China

4Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi 530021, China

5Guangxi Colleges and Universities Key Laboratory of Biological Molecular Medicine Research, Guangxi Medical University, Nanning, Guangxi 530021, China

*These authors have contributed equally to this work

Correspondence to:

Yanling Hu, email: ylhuteam@163.com

Tianyu Li, email: litianyu@gxmu.edu.cn

Keywords: prostate cancer, DNA methylation, promoter, diagnostic biomarker, gene

Received: October 20, 2016     Accepted: February 28, 2017     Published: March 22, 2017


Background: Prostate cancer (PCa) is the most common tumor in elderly men. However, the specificity and sensitivity of serum prostate-specific antigen levels in PCa diagnosis are controversial. This study aims to reveal a novel diagnosis biomarker in PCa.

Materials and Methods: The differential methylated CpG sites between 423 primary PCa and 39 adjacent samples from The Cancer Genome Atlas (TCGA) on Illumina HumanMethylation 450 platform were analyzed. The diagnostic methylation markers were mined using the Prediction Analysis of Microarrays package in Bioconductor. Then, the Gene Expression Omnibus data was used for verification. Pyrosequencing was applied to improve methylation levels of five CpGs (cg06363129, cg08843517, cg05385513, cg07220448 and cg11417025).

Results: The area under curve of receiver operating characteristic of eight diagnostic methylation CpGs (cg06363129, cg08843517, cg03576469, cg05385513, cg07220448, cg11417025, cg20883831, and cg23824801) in TCGA data ranged from 0.910 to 0.939. Except for cg20883831 and cg23824801, the correlations between methylation levels of six other sites and their expressions in patients were significant (r > 0.5 and P < 0.001). The methylation level of cg06363129 was significantly different between the groups of Gleason Score (GS) = 7 and GS ≥ 8 (P < 0.05). Pyrosequencing in our samples confirmed that four diagnostic methylation sites (cg06363129, cg08843517, cg05385513, and cg11417025) had high diagnostic efficacy.

Conclusions: The combined diagnosis of four methylation CpGs sites (cg06363129, cg08843517, cg05385513, and cg11417025) in the gene promoter has high tissue specificity and diagnostic efficacy for PCa. Results revealed a novel potential biomarker for prostate cancer diagnosis.

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