Genome-wide DNA methylation analysis identifies candidate epigenetic markers and drivers of hepatocellular carcinoma

被引:61
作者
Zheng, Yongchang [2 ,3 ]
Huang, Qianqian [1 ,4 ]
Ding, Zijian [1 ,4 ]
Liu, Tingting [5 ]
Xue, Chenghai [5 ,6 ]
Sang, Xinting [2 ,3 ]
Gu, Jin [1 ,4 ]
机构
[1] Tsinghua Univ, Ctr Synthet & Syst Biol, Dept Automat, Beijing 100084, Peoples R China
[2] Chinese Acad Med Sci, Peking Union Med Coll Hosp, Dept Liver Surg, Beijing, Peoples R China
[3] Peking Union Med Coll, Beijing, Peoples R China
[4] Tsinghua Univ, MOE Key Lab Bioinformat, TNLIST Bioinformat Div, Bioinformat, Beijing, Peoples R China
[5] My Hlth Gene Technol Co Ltd, Tianjin, Peoples R China
[6] Chinese Acad Sci, Inst Automat, Joint Lab Large Scale Med Data Pattern Min & Appl, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
DNA methylation; molecular marker; epigenetic driver; hepatocellular carcinoma; LUNG ADENOCARCINOMA; CANCER; BIOMARKER; HYPOMETHYLATION; REGULARIZATION; OSTEOPONTIN; DIAGNOSIS;
D O I
10.1093/bib/bbw094
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The alteration of DNA methylation landscape is a key epigenetic event in cancer. As the accumulation of large-scale genome-wide DNA methylation data from clinical samples, we are able to characterize the patterns of DNA methylation alterations for identifying candidate epigenetic markers and drivers. In this survey, we take hepatocellular carcinoma (HCC) as an example to show the basic steps of analyzing the DNA methylation patterns in cancer across multiple data sets. We collected three genome-wide DNA methylation data sets with similar to 800 clinical samples and the corresponding gene expression data sets. First, by quantitatively analyzing two global methylation alterations, it is found that about 90% tumors acquire either genome-wide DNA hypo-methylation or CpG island methylator phenotype. Second, probe-level analysis identified 267, 228 and 197 hyper-methylated sites in promoter regions for the three data sets, respectively. These local hyper-methylated patterns are highly consistent: 84 sites (from 61 promoters) are hyper-methylated in all the three studied data sets, including many previously reported genes, such as CDKL2, TBX15 and NKX6-2. Then, these hyper-methylated sites were used as candidate markers to classify tumor and non-tumor samples. The classifiers based on only 10 selected probes can achieve high discriminative ability across different data sets. Finally, by integrative analyzing DNA methylation and gene expression data, we identified 222 candidate epigenetic drivers, which are enriched in inflammatory response and multiple metabolic pathways. A set of high-confidence candidates, including SFN, SPP1 and TKT, are significantly associated with patients' overall survivals. In summary, this study systematically characterized the DNA methylation alterations and their impacts on gene expressions in HCCs based on multiple data sets.
引用
收藏
页码:101 / 108
页数:8
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