CpG island methylator phenotype in adenocarcinomas from the digestive tract:Methods,conclusions,and controversies
CpG island methylator phenotype in adenocarcinomas from the digestive tract:Methods,conclusions,and controversies作者机构:Genomic Functional Analysis SectionNational Human Genome Research InstituteNational Institutes of HealthRockvilleMD 20852United States
出 版 物:《World Journal of Gastrointestinal Oncology》 (世界胃肠肿瘤学杂志(英文版)(电子版))
年 卷 期:2017年第9卷第3期
页 面:105-120页
核心收录:
学科分类:1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
基 金:funded by the Intramural program of the National Human Genome Research Institute the National Institutes of Health
主 题:CpG island methylator phenotype CpG island Promoter DNA methylation Hypermethylation Gastrointestinal cancer
摘 要:Over the last two decades, cancer-related alterations in DNA methylation that regulate transcription have been reported for a variety of tumors of the gastrointestinal tract. Due to its relevance for translational research, great emphasis has been placed on the analysis and molecular characterization of the CpG island methylator phenotype(CIMP), defined as widespread hypermethylation of CpG islands in clinically distinct subsets of cancer patients. Here, we present an overview of previous work in this field and also explore some open questions using crossplatform data for esophageal, gastric, and colorectal adenocarcinomas from The Cancer Genome Atlas. We provide a data-driven, pan-gastrointestinal stratification of individual samples based on CIMP status and we investigate correlations with oncogenic alterations, including somatic mutations and epigenetic silencing of tumor suppressor genes. Besides known events in CIMP such as BRAF V600 E mutation, CDKN2 A silencing or MLH1 inactivation, we discuss the potential role of emerging actors such as Wnt pathway deregulation through truncating mutations in RNF43 and epigenetic silencing of WIF1. Our results highlight the existence of molecular similarities that are superimposed over a larger backbone of tissue-specific features and can be exploited to reduce heterogeneity of response in clinical trials.