Subtype Dependent Alterations of the DNA Methylation Landscape in Breast Cancer.
Authors: S. Kamalakaran, H. Giercksky Russnes, A. Janevski, D. Levy, J. Kendall, V. Varadan, M. Riggs, N. Banerjee, M. Synnestvedt, E. Schlichting, R. Kåresen, R. Lucito, M. Wigler, N. Dimitrova, B. Naume, A. Borresen-Dale, A. Borresen-Dale, J. Hicks
Journal: Cancer Research (2009)

Abstract Background: The diversity of breast cancers at the clinical, histopathological and molecular level reflects variation in underlying biology and affects the clinical implications for patients. Gene expression studies have identified five breast cancer subtypes with distinct expression profiles – Luminal A, Luminal B, basal, ErbB2 enriched and Normal-Like. DNA methylation is an important regulator of gene expression that is also known to be deregulated in tumors. We set out to determine the relationship between DNA methylation and breast cancer subtypes in 108 breast cancer samples with previously determined expression subtypes.Methods: We performed high-throughput genome-wide scans of CpG methylation in 108 tumors and 11 normal tissues using our previously validated Methylation Oligonucleotide Microarray Analysis (MOMA) method [Kamalakaran, S et al. Nucleic Acids Research, 2009)]. We identified loci that were most varied across all tumors or had the most significant alterations and performed unsupervised hierarchical clustering on those loci. We then used a genetic algorithm based feature selection method to identify a subset of those loci that could cluster the sample set by expression subtype. We then characterized the loci contributing to subsetting and where possible, the relationship between methylation and gene expression.Results: Unsupervised hierarchical clustering using the 500 most differentially methylated loci across all tumors and 100 most significant altered loci between tumors and Normal tissues clustered the tumors into 3 major clusters – 82% of Cluster I belonged to Luminal Subtypes (22 Luminal A and 4 Luminal B), and 86% of Cluster II samples were of Basal or ErbB2+ subtypes. Cluster III did not show any expression subtype specific enrichment, but contained samples whose expression subtype was inconclusive with weak correlations to multiple expression subtypes. Interestingly, methylation loci that contributed to this clustering were not localized to CpG islands immediately upstream of genes, with 354 loci far from gene transcription start sites. These non-geneic loci did not show any significant regulatory potential based on cross-species conservation measures and no clear function could be assigned to these regions. The remaining 146 loci could be mapped to known genes. Gene expression microarray measurements were available for 79 of these geneic loci and 36 showed significant correlation of methylation to expression levels (p&amp;lt;0.05), implying possible functional effects of the methylation on gene expression. Additionally, distinct subtype specific patterns of methylation could also be detected in known cancer associated genes. CpG islands in the HOXA gene cluster and many other homeobox genes were significantly more methylated in Luminal A tumors.Conclusions: Our results suggest that there are subtype dependant genome-wide alterations in the methylation landscape in breast cancers, especially near homeobox genes. Many more CpG islands with no apparent functional significance get methylated according to subtype in addition to those CpG islands associated with genes with known cancer related functions. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 1144.