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全基因组甲基化分析确定了CIMP-H型结直肠癌中一组核心的高甲基化基因。

Genome-wide methylation analysis identifies a core set of hypermethylated genes in CIMP-H colorectal cancer.

作者信息

McInnes Tyler, Zou Donghui, Rao Dasari S, Munro Francesca M, Phillips Vicky L, McCall John L, Black Michael A, Reeve Anthony E, Guilford Parry J

机构信息

Cancer Genetics Laboratory, Centre for Translational Cancer Research (Te Aho Matatū), Department of Biochemistry, University of Otago, Dunedin, 9054, New Zealand.

Department of Surgical Sciences, Dunedin School of Medicine, University of Otago, Dunedin, 9054, New Zealand.

出版信息

BMC Cancer. 2017 Mar 28;17(1):228. doi: 10.1186/s12885-017-3226-4.

DOI:10.1186/s12885-017-3226-4
PMID:28351398
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5371203/
Abstract

BACKGROUND

Aberrant DNA methylation profiles are a characteristic of all known cancer types, epitomized by the CpG island methylator phenotype (CIMP) in colorectal cancer (CRC). Hypermethylation has been observed at CpG islands throughout the genome, but it is unclear which factors determine whether an individual island becomes methylated in cancer.

METHODS

DNA methylation in CRC was analysed using the Illumina HumanMethylation450K array. Differentially methylated loci were identified using Significance Analysis of Microarrays (SAM) and the Wilcoxon Signed Rank (WSR) test. Unsupervised hierarchical clustering was used to identify methylation subtypes in CRC.

RESULTS

In this study we characterized the DNA methylation profiles of 94 CRC tissues and their matched normal counterparts. Consistent with previous studies, unsupervized hierarchical clustering of genome-wide methylation data identified three subtypes within the tumour samples, designated CIMP-H, CIMP-L and CIMP-N, that showed high, low and very low methylation levels, respectively. Differential methylation between normal and tumour samples was analysed at the individual CpG level, and at the gene level. The distribution of hypermethylation in CIMP-N tumours showed high inter-tumour variability and appeared to be highly stochastic in nature, whereas CIMP-H tumours exhibited consistent hypermethylation at a subset of genes, in addition to a highly variable background of hypermethylated genes. EYA4, TFPI2 and TLX1 were hypermethylated in more than 90% of all tumours examined. One-hundred thirty-two genes were hypermethylated in 100% of CIMP-H tumours studied and these were highly enriched for functions relating to skeletal system development (Bonferroni adjusted p value =2.88E-15), segment specification (adjusted p value =9.62E-11), embryonic development (adjusted p value =1.52E-04), mesoderm development (adjusted p value =1.14E-20), and ectoderm development (adjusted p value =7.94E-16).

CONCLUSIONS

Our genome-wide characterization of DNA methylation in colorectal cancer has identified 132 genes hypermethylated in 100% of CIMP-H samples. Three genes, EYA4, TLX1 and TFPI2 are hypermethylated in >90% of all tumour samples, regardless of CIMP subtype.

摘要

背景

异常的DNA甲基化谱是所有已知癌症类型的一个特征,在结直肠癌(CRC)中以CpG岛甲基化表型(CIMP)为代表。在整个基因组的CpG岛均观察到高甲基化,但尚不清楚哪些因素决定了个体的CpG岛在癌症中是否会发生甲基化。

方法

使用Illumina HumanMethylation450K芯片分析结直肠癌中的DNA甲基化。使用微阵列显著性分析(SAM)和Wilcoxon符号秩和检验(WSR)来鉴定差异甲基化位点。采用无监督层次聚类来识别结直肠癌中的甲基化亚型。

结果

在本研究中,我们对94例结直肠癌组织及其配对的正常组织的DNA甲基化谱进行了特征分析。与先前的研究一致,全基因组甲基化数据的无监督层次聚类在肿瘤样本中识别出三种亚型,分别命名为CIMP-H、CIMP-L和CIMP-N,它们分别显示出高、低和极低的甲基化水平。在个体CpG水平和基因水平上分析了正常样本与肿瘤样本之间的差异甲基化。CIMP-N肿瘤中高甲基化的分布显示出肿瘤间的高度变异性,并且在本质上似乎是高度随机的,而CIMP-H肿瘤除了高度可变的高甲基化基因背景外,在一部分基因上表现出一致的高甲基化。EYA4、TFPI2和TLX1在所有检测的肿瘤中超过90%发生高甲基化。在100%研究的CIMP-H肿瘤中,有132个基因发生高甲基化,这些基因在与骨骼系统发育(Bonferroni校正P值=2.88E-15)、节段特化(校正P值=9.62E-11)、胚胎发育(校正P值=1.52E-04)、中胚层发育(校正P值=1.14E-20)和外胚层发育(校正P值=7.94E-16)相关的功能上高度富集。

结论

我们对结直肠癌DNA甲基化的全基因组特征分析确定了132个在100%的CIMP-H样本中发生高甲基化的基因。无论CIMP亚型如何,EYA4、TLX1和TFPI2这三个基因在所有肿瘤样本中超过90%发生高甲基化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11f9/5371203/450832a9b94c/12885_2017_3226_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11f9/5371203/bcf8e0af87ac/12885_2017_3226_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11f9/5371203/365c3837e207/12885_2017_3226_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11f9/5371203/8f372d098e8d/12885_2017_3226_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11f9/5371203/0aee32286124/12885_2017_3226_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11f9/5371203/450832a9b94c/12885_2017_3226_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11f9/5371203/bcf8e0af87ac/12885_2017_3226_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11f9/5371203/365c3837e207/12885_2017_3226_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11f9/5371203/8f372d098e8d/12885_2017_3226_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11f9/5371203/0aee32286124/12885_2017_3226_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11f9/5371203/450832a9b94c/12885_2017_3226_Fig5_HTML.jpg

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