Genome‐wide DNA methylation analysis of colorectal adenomas with and without recurrence reveals an association between cytosine‐phosphate‐guanine methylation and histological subtypes

Abstract

Aberrant methylation of DNA is supposed to be a major and early driver of colonic adenoma development, which may result in colorectal cancer (CRC). Although gene methylation assays are used already for CRC screening, differential epigenetic alterations of recurring and nonrecurring colorectal adenomas have yet not been systematically investigated. Here, we collected a sample set of formalin‐fixed paraffin‐embedded colorectal low‐grade adenomas (n = 72) consisting of primary adenomas without and with recurrence (n = 59), recurrent adenomas (n = 10), and normal mucosa specimens (n = 3). We aimed to unveil differentially methylated CpG positions (DMPs) across the methylome comparing not only primary adenomas without recurrence vs primary adenomas with recurrence but also primary adenomas vs recurrent adenomas using the Illumina Human Methylation 450K BeadChip array. Unsupervised hierarchical clustering exhibited a significant association of methylation patterns with histological adenoma subtypes. No significant DMPs were identified comparing primary adenomas with and without recurrence. Despite that, a total of 5094 DMPs (false discovery rate <0.05; fold change >10%) were identified in the comparisons of recurrent adenomas vs primary adenomas with recurrence (674; 98% hypermethylated), recurrent adenomas vs primary adenomas with and without recurrence (241; 99% hypermethylated) and colorectal adenomas vs normal mucosa (4179; 46% hypermethylated). DMPs in cytosine‐phosphate‐guanine (CpG) islands were frequently hypermethylated, whereas open sea‐ and shelf‐regions exhibited hypomethylation. Gene ontology analysis revealed enrichment of genes associated with the immune system, inflammatory processes, and cancer pathways. In conclusion, our methylation data could assist in establishing a more robust and reproducible histological adenoma classification, which is a prerequisite for improving surveillance guidelines.

Epigenome-Wide DNA Methylation Profiling in Colorectal Cancer and Normal Adjacent Colon Using Infinium Human Methylation 450K

“…Conversely, hypomethylation often occurs in the open sea area of the genome. A similar pattern has been observed in another study where hypomethylation of CpG sites was enriched at the open sea area and intergenic region [ 48 , 49 , 50 ].…”

Evaluation of global and intragenic hypomethylation in colorectal adenomas improves patient stratification and colorectal cancer risk prediction

“…In this regard, present surveillance programs, based on size, morphology, and absence of synchronous polyps, frequently result in unnecessary repeated colonoscopy. This implies the need of identifying novel noninvasive, selective, and reliable markers for improving the stratification and the follow-up of those specific patients at higher CRC risk [ 26 ].…”

“…Although epidemiologic studies have shown the efficacy of endoscopic screening [ 23 ], colonoscopy monitoring has some strong limitations that can considerably affect its effectiveness: (i) the intervals are defined according to CRC-risk guidelines considering as main criteria the number and size of the removed polyps but lacking information on important molecular features, (ii) colonoscopy is an invasive procedure [ 25 ], (iii) patients show a low adherence to the surveillance program, and (iv) this type of screening is associated with high costs for the National Health Systems (NHS). Therefore, alternative or supportive biomarkers able to reduce unnecessary invasive procedure and predict recurrence are highly required [ 26 ].…”

SCTR hypermethylation is a diagnostic biomarker in colorectal cancer

“…Furthermore, TCGA CRC gene expression profile was also downloaded from the UCSC Xena Browser. By a systematic search in the GEO database, 8 methylation datasets of the Illumina 450k array were obtained as test set (N = 930): http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42752, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48684, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE68060, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE77718, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE77954, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE101764, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107352, and http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE129364 23‐29 . An additional methylation dataset for the Illumina EPIC array with 4 cell‐free DNA (cfDNA) samples from CRC and 4 samples from healthy controls were obtained from http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE122126 30 …”

“…By a systematic search in the GEO database, 8 methylation datasets of the Illumina 450k array were obtained as test set (N = 930): GSE42752, GSE48684, GSE68060, GSE77718, GSE77954, GSE10 1764, GSE10 7352, and GSE12 9364. [23][24][25][26][27][28][29] An additional methylation dataset for the Illumina EPIC array with 4 cell-free DNA (cfDNA) samples from CRC and 4 samples from healthy controls were obtained from GSE12 2126. 30…”