Data from Intermediate- and Low-Methylation Epigenotypes Do Not Correspond to CpG Island Methylator Phenotype (Low and -Zero) in Colorectal Cancer

Autor: Maria M. Sasiadek, Lukasz Laczmanski, Nikolaus Blin, Zygmunt Grzebieniak, Marek Bebenek, Joanna Kozlowska, Blazej Misiak, David Ramsey, Elzbieta Szmida, Michael Walter, Pawel Karpinski
Rok vydání: 2023
DOI: 10.1158/1055-9965.c.6515566.v1
Popis: Background: Most recent genome-wide studies on the CpG island methylation in colorectal cancer (CRC) have led to the discovery of at least 3 distinct methylation clusters. However, there remains an uncertainty whether the CRC clusters identified in these studies represent compatible phenotypes.Methods: We carried out comprehensive genome-scale DNA methylation profiling by Illumina Infinium HumanMethylation27 of 21 DNA pools that represent 84 CRC samples divided according to their high-, intermediate-, and low-methylation epigenotypes (HME, IME, and LME, respectively) and 70 normal-adjacent colonic tissues. We have also examined the relationship among 3 epigenotypes and chromosomal gains and deletions (assessed by Comparative Genomic Hybridization) in a group of 100 CRC samples.Results: The HME subgroup showed features associated with CpG island methylator phenotype – high (CIMP-high) including methylation of specific CpG sites (CpGs) as well as significantly lower mean number of chromosomal imbalances when compared with other epigenotypes. The IME subgroup displayed the lowest number of methylated CpGs (717 vs. 2,399 and 2,679 in HME and LME, respectively) and highest mean number of chromosomal imbalances when compared with HME (P, 0.001) and LME (P, 0.004). A comparison between the methylation profiles of 3 epigenotypes revealed more similarities between the HME and LME (1,669 methylated CpGs overlapped) than HME and IME (673 methylated CpGs overlapped).Conclusion: Our results provide evidence that IME and LME CRCs show opposite features to those that have been previously attributed to CIMP-low and CIMP-0 CRCs.Impact: These discrepancies should be considered when interpreting the data from a particular epigenotyping method. Cancer Epidemiol Biomarkers Prev; 22(2); 201–8. ©2012 AACR.
Databáze: OpenAIRE