Toward a comprehensive and systematic methylome signature in colorectal cancers
Toward a comprehensive and systematic methylome signature in colorectal cancers
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DOI：
10.4161/epi.25497
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发表时间：
2013-08-01
期刊：
影响因子：
3.7
通讯作者：
Brim, Hassan
中科院分区：
文献类型：
--
作者：
Ashktorab, Hassan;Rahi, Hamed;Brim, Hassan
CpG岛甲基化表型(CIMP)是结直肠癌的潜在发病机制之一。这项研究旨在通过甲基化微阵列分析和文献中有希望的CIMP标记的汇编来定义结直肠癌中的甲基组特征。根据甲基化数据中的统计差异(第一种方法)或基于使用较低95%可信区间(第二种方法)的甲基化百分比的总体差异来生成和分析Illumina Human Methylation27(IHM27)阵列数据。对9个基因进行焦磷酸测序验证。Meta分析用于确定结直肠癌中甲基化的CIMP和非CIMP标记，但尚未列入CIMP基因列表。我们的第一种阵列数据分析方法展示了选择基因进行进一步验证的局限性，强调了第二种生物信息学方法的必要性，以充分选择具有差异异常甲基化的基因。建立了包括APC、EVL、CD109、PTEN、Twist1、DCC、PTPRD、SFRP1、ICAM5、RASSF1A、EYA4、30ST2、LAMA1、KCNQ5、ADHEF1和TFPI2等非CIMP基因的较为完整的清单。阵列数据有助于根据其全球甲基化特征对结肠病变进行分类和分类；然而，其在识别稳健的甲基化标记方面的有用性是有限的，并依赖于数据分析方法。我们已经确定了16个非CIMP面板基因，我们为将其纳入更全面的CIMP+CRC特征提供了理论基础。确定结直肠癌中甲基组特异基因的确定列表将有助于更好地对结直肠癌患者进行临床治疗。
CpG Island Methylator Phenotype (CIMP) is one of the underlying mechanisms in colorectal cancer (CRC). This study aimed to define a methylome signature in CRC through a methylation microarray analysis and a compilation of promising CIMP markers from the literature. Illumina HumanMethylation27 (IHM27) array data was generated and analyzed based on statistical differences in methylation data (1st approach) or based on overall differences in methylation percentages using lower 95% CI (2nd approach). Pyrosequencing was performed for the validation of nine genes. A meta-analysis was used to identify CIMP and non-CIMP markers that were hypermethylated in CRC but did not yet make it to the CIMP genes' list. Our 1st approach for array data analysis demonstrated the limitations in selecting genes for further validation, highlighting the need for the 2nd bioinformatics approach to adequately select genes with differential aberrant methylation. A more comprehensive list, which included non-CIMP genes, such as APC, EVL, CD109, PTEN, TWIST1, DCC, PTPRD, SFRP1, ICAM5, RASSF1A, EYA4, 30ST2, LAMA1, KCNQ5, ADHEF1, and TFPI2, was established. Array data are useful to categorize and cluster colonic lesions based on their global methylation profiles; however, its usefulness in identifying robust methylation markers is limited and rely on the data analysis method. We have identified 16 non-CIMP-panel genes for which we provide rationale for inclusion in a more comprehensive characterization of CIMP+ CRCs. The identification of a definitive list for methylome specific genes in CRC will contribute to better clinical management of CRC patients.