DNA methylation epigenotypes in breast cancer molecular subtypes

Abstract

IntroductionIdentification of gene expression-based breast cancer subtypes is considered a critical means of prognostication. Genetic mutations along with epigenetic alterations contribute to gene-expression changes occurring in breast cancer. So far, these epigenetic contributions to sporadic breast cancer subtypes have not been well characterized, and only a limited understanding exists of the epigenetic mechanisms affected in those particular breast cancer subtypes. The present study was undertaken to dissect the breast cancer methylome and to deliver specific epigenotypes associated with particular breast cancer subtypes.MethodsBy using a microarray approach, we analyzed DNA methylation in regulatory regions of 806 cancer-related genes in 28 breast cancer paired samples. We subsequently performed substantial technical and biologic validation by pyrosequencing, investigating the top qualifying 19 CpG regions in independent cohorts encompassing 47 basal-like, 44 ERBB2+ overexpressing, 48 luminal A, and 48 luminal B paired breast cancer/adjacent tissues. With the all-subset selection method, we identified the most subtype-predictive methylation profiles in multivariable logistic regression analysis.ResultsThe approach efficiently recognized 15 individual CpG loci differentially methylated in breast cancer tumor subtypes. We further identified novel subtype-specific epigenotypes that clearly demonstrate the differences in the methylation profiles of basal-like and human epidermal growth factor 2 (HER2)-overexpressing tumors.ConclusionsOur results provide evidence that well-defined DNA methylation profiles enable breast cancer subtype prediction and support the utilization of this biomarker for prognostication and therapeutic stratification of patients with breast cancer.

Distinct patterns of promoter CpG island methylation of breast cancer subtypes are associated with stem cell phenotypes

“…Recent studies using array-based methylation analysis have confirmed that the molecular subtypes of breast cancer have subtype-specific methylation profiles. [18][19][20][21] Holm et al 19 demonstrated differences in the methylation profiles of luminal A, luminal B, and basal-like breast cancers, with luminal B and basal-like breast cancers being most and least frequently methylated, respectively. In our study, the number of CpG island loci methylated was highest in the luminal-HER2 subtype and lowest in the basal-like subtype.…”

“…[14][15][16][17] Array-based comprehensive DNA methylation profiling has shown that breast cancer molecular subtypes have their own methylation profiles. [18][19][20][21] Moreover, these different methylation profiles were evident throughout the CpG islands of the genome, not limited to functional genes. 20 Kamalakaran et al 20 reported that the methylation patterns of differentially methylated genes in luminal A tumors were similar to those identified in CD24 þ luminal epithelial cells, and those in basal-like tumors resembled those of CD44 þ breast progenitor cells, suggesting that the methylation patterns of the breast cancer subtypes reflect the methylation patterns of their cells of origin.…”

Epigenetic silencing of neurofilament genes promotes an aggressive phenotype in breast cancer

“…To characterize the vast amount of DNA methylation data generated, comprehensive functional approaches have been initiated and novel tumor suppressor genes and pathways as well as biomarkers for early detection and prognosis prediction of cancer have been discovered. [2][3][4][5][6][7][8][9][10][11] Neurofilament heavy polypeptide (NEFH) has been identified as a candidate DNA hypermethylated gene within the functional breast cancer hypermethylome, a comprehensive approach to define genome-wide functional methylation changes in breast cancer that is based on whole transcriptome expression arrays on breast cancer cell lines after pharmacological inhibition of DNA methylation. 6 NEFH encodes the neurofilament heavy polypeptide and assembles along with neurofilament medium polypeptide (NEFM) and neurofilament light polypeptide (NEFL) into 10 nm filamentous structures known as neurofilaments.…”

936 Quantitative genome-wide methylation analysis of high-grade non-muscle invasive bladder cancer

“…25,33,34 In common with previous reports and across multiple genes, these analyses confirmed and reinforced the array-derived data. 34,35,36 These analyses also showed that for the majority of regions investigated, methylation extended to include contiguous promoter-associated CpG sites. On the basis of previous reports from our own and other groups, 37,38 we employed stringent criteria (b-value differences 0.4) to identify differentially methylated genes across multiple CpG sites; such criteria are more consistently associated with bona fide changes in methylation, and are more likely to show associations with gene expression.…”