Department of Medicine and Cancer Center; Department of Pathology; Howard University College of Medicine; Washington, D.C. USA.
Epigenetics. 2013 Aug;8(8):807-15. doi: 10.4161/epi.25497. Epub 2013 Jul 10.
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.
CpG 岛甲基化表型(CIMP)是结直肠癌(CRC)的潜在机制之一。本研究旨在通过甲基化微阵列分析和对文献中具有前景的 CIMP 标记物的汇编,定义 CRC 中的甲基组特征。根据甲基化数据的统计学差异(第 1 种方法)或使用较低的 95%CI 进行总体甲基化百分比差异(第 2 种方法),生成并分析了 Illumina HumanMethylation27(IHM27)阵列数据。对 9 个基因进行焦磷酸测序验证。使用荟萃分析来鉴定 CIMP 和非 CIMP 标记物,这些标记物在 CRC 中发生过度甲基化,但尚未列入 CIMP 基因列表。我们的第 1 种阵列数据分析方法表明,选择用于进一步验证的基因存在局限性,突出了需要第 2 种生物信息学方法来充分选择具有差异异常甲基化的基因。建立了一个更全面的列表,其中包括 APC、EVL、CD109、PTEN、TWIST1、DCC、PTPRD、SFRP1、ICAM5、RASSF1A、EYA4、30ST2、LAMA1、KCNQ5、ADHEF1 和 TFPI2 等非 CIMP 基因。阵列数据可用于根据其全局甲基化谱对结肠病变进行分类和聚类;然而,其在识别稳健的甲基化标记物方面的有用性是有限的,并且依赖于数据分析方法。我们已经确定了 16 个非 CIMP 面板基因,为它们被纳入更全面的 CIMP+CRC 特征提供了依据。确定 CRC 中甲基组特异性基因的明确列表将有助于更好地管理 CRC 患者。