In this study, we report the results of a genome wide array analysis of primary invasive breast cancers of 27,578 CpG loci. This screen identified hypermethylated genes that specifically segregate with ER-positive or ER-negative tumor subtypes, which were then validated in silico using the newly populated TCGA breast cancer database. The array analysis also identified 100 gene loci that were enriched for homeobox-containing genes and predicted recurrence in breast cancers. Many novel hypermethylated loci were identified. In summary, we demonstrate that the methylome is a rich source of genes whose hypermethylation has the potential to significantly contribute to the understanding of ER-subgroups of breast cancer and predict recurrence in ER-positive and in ER-negative breast cancers.
We observed a significantly higher frequency of hypermethyation in ER-positive compared to ER-negative tumors (p<0.0001). The reason for the hypermethylated phenotype of ER-positive tumors is not yet clear. The simplest explanation could be that the ER-positive markers are drivers that enhance the expression of the DNA methyltransferases, or inhibit the repair processes that remove methyl groups from DNA. On the other hand, reduced methylation in ER-negative tumors might offer an explanation for their relative aggressiveness since the uncontrolled expression of growth factors and their receptors may be facilitated by removing the protective imposition of methylation-mediated silencing. The observation of a higher frequency of hypermethylated genes in ER-positive tumors is substantiated by five recent studies describing the breast cancer methylome (22
). In a study examining 44 primary tumors, Hill et al (22
) confirmed a highly significant difference (ANOVA, p value=0.001) in hypermethylation depending on hormone receptor status; in their study. Similarly, in the Fang study (26
), ER/PR-positive tumors displayed high level of methylation across the top 5% variant loci in the 27K Illumina array. Our study of 103 primary breast cancers identified many novel loci that have the ability to impressively segregate ER-positive and ER-negative tumors (, ), shedding light on many novel pathways and constituent genes that may be involved in the genesis of these subgroups. We tested the strength of these observations using an independent dataset from TCGA for both methylation and expression. All 40 CpG loci showed reproducible associations with ER-subtype and these markers classified essentially all tumors into the correct ER subtype (AUC 0.961). Interestingly, expression of the same genes was also found to be a very strong predictor of ER status. Thus, independent TCGA data strongly validated our findings. With the caveat that both the discovery and validation cohorts represent small sample sets, the reproducibility of the findings supports the strength of this platform to reveal differences that can now be studied in detail.
A major goal of our work is to find markers that can prognosticate recurrence and predict benefit from therapy. Expression array-based analyses have proven to be useful for ER-positive breast cancers (30
). Their utility, however, has been limited in ER-negative breast cancer. Also, DNA mutation and copy number studies have been found less useful in breast cancer compared to other cancers (eg. lung and colon), probably reflecting the greater diversity of breast cancer subtypes (32
). Epigenetically mediated gene silencing through DNA methylation occurs extremely frequently and has now been accepted as a major driver in neoplastic transformation, especially in the breast (12
). Genome-wide methylation analysis allowed us to identify a tumor recurrence marker set of 100 gene loci; a few specific to ER-positive, many loci specific to ER-negative tumors and many common to both (, Supplemental Table 4C
). The emergence of a homeobox gene-methylation signature predictive of recurrence among the 100 recurrence loci and also among all homeobox loci on the array is notable. Substantial inverse correlation was seen between methylation and expression of the genes, both of the ER-stratifying set and the recurrence set of CpG loci, suggesting functional relevance to the effects of methylated genes observed in our study. These genes play critical roles in differentiation and development, growth factor receptor signaling, angiogenesis and more recently an unequivocal role in stem cell function [reviewed in (35
)] At the same time, particularly within the recurrence panel, expression alone could not duplicate the level of performance achieved with methylation probes.
The tissues used for the current analysis were from an institutional cohort of frozen specimens and are therefore, samples of convenience with their inherent drawbacks. Additional studies will need to address the question of the precise role of methylation signatures in prognosticating outcome and predicting response to therapy. More discovery and validation will need to be performed with annotated samples from controlled studies, with more uniform standards of sample collection, such as in the context of large mature randomized clinical trials. To allow investigation on archival specimens, the rapid development of methods to retrieve high quality DNA from paraffin embedded tissues is imperative. Our recent success in standardizing restoration of DNA retrieved from FFPE tissues, in collaboration with Illumina (our unpublished data, AACR Abstract LB 178, 2011), bodes well for the future of these investigations.
In summary, this study has demonstrated the feasibility of distinguishing ER-subtype in breast cancers and possibly predicting outcome based on CpG DNA methylation. The study suggests pathways that may explain distinctive behaviors among ER-positive and ER-negative tumors. In conclusion, the data strongly support upcoming planned studies that will use existing clinically-annotated tissues from previously conducted prospective randomized trials to examine the prognostic outcome and predictive therapeutic information offered by methylation markers in a prospective-retrospective fashion.