title: Array-based DNA methylation profiling for breast cancer subtype discrimination.
abstract: BACKGROUND
  Abnormal DNA methylation is well established for breast cancer and contributes to its progression by silencing tumor suppressor genes. DNA methylation profiling platforms might provide an alternative approach to expression microarrays for accurate breast tumor subtyping. We sought to determine whether the distinction of the inflammatory breast cancer (IBC) phenotype from the non-IBC phenotype by transcriptomics could be sustained by methylomics.
  
  
  RESULTS
  We performed methylation profiling on a cohort of IBC (N = 19) and non-IBC (N = 43) samples using the Illumina Infinium Methylation Assay. These results were correlated with gene expression profiles. Methylation values allowed separation of breast tumor samples into high and low methylation groups. This separation was significantly related to DNMT3B mRNA levels. The high methylation group was enriched for breast tumor samples from patients with distant metastasis and poor prognosis, as predicted by the 70-gene prognostic signature. Furthermore, this tumor group tended to be enriched for IBC samples (54% vs. 24%) and samples with a high genomic grade index (67% vs. 38%). A set of 16 CpG loci (14 genes) correctly classified 97% of samples into the low or high methylation group. Differentially methylated genes appeared to be mainly related to focal adhesion, cytokine-cytokine receptor interactions, Wnt signaling pathway, chemokine signaling pathways and metabolic processes. Comparison of IBC with non-IBC led to the identification of only four differentially methylated genes (TJP3, MOGAT2, NTSR2 and AGT). A significant correlation between methylation values and gene expression was shown for 4,981 of 6,605 (75%) genes.
  
  
  CONCLUSIONS
  A subset of clinical samples of breast cancer was characterized by high methylation levels, which coincided with increased DNMT3B expression. Furthermore, an association was observed with molecular signatures indicative of poor patient prognosis. The results of the current study also suggest that aberrant DNA methylation is not the main force driving the molecular biology of IBC.
authors.affiliation: Translational Cancer Research Group, Laboratory of Pathology, University of Antwerp/University Hospital Antwerp, Oncology Center, Sint-Augustinus, Antwerp, Belgium.
authors.forename: Ilse
authors.initials: I
authors.lastname: Van der Auwera
authors.forename: Wayne
authors.initials: W
authors.lastname: Yu
authors.forename: Liping
authors.initials: L
authors.lastname: Suo
authors.forename: Leander
authors.initials: L
authors.lastname: Van Neste
authors.forename: Peter
authors.initials: P
authors.lastname: van Dam
authors.forename: Eric A
authors.initials: EA
authors.lastname: Van Marck
authors.forename: Patrick
authors.initials: P
authors.lastname: Pauwels
authors.forename: Peter B
authors.initials: PB
authors.lastname: Vermeulen
authors.forename: Luc Y
authors.initials: LY
authors.lastname: Dirix
authors.forename: Steven J
authors.initials: SJ
authors.lastname: Van Laere
mesh_terms: D000328:Adult; D001943:Breast Neoplasms / Q000175:diagnosis / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D015331:Cohort Studies; D019175:DNA Methylation; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis