Abstract CN05-04: Predictive and prognostic methylated gene markers for breast cancer
Authors: Sukumar Saraswati , Fackler Mary Jo , Cope Leslie , Wolff Antonio W. , Huang Peng , Visvanathan Kala , Zhang Zhe , Umbricht Christopher 
Published: June 2012

To identify methylated gene markers of disease progression, and to better understand the biology of hormone receptor-positive and negative breast cancer, we performed a genome-wide methylation array analysis on 103 primary invasive breast cancers and 21 normal breast samples using the Illumina Infinium HumanMethylation27 array that queried 27,578 CpG loci. Estrogen/Progesterone receptor (ER)-positive tumors displayed more hypermethylated loci than ER-negative tumors. However, the hypermethylated loci in ER-negative tumors were clustered closer to the transcriptional start site compared to ER-positive tumors, suggesting tighter transcriptional regulation by these loci. An ER-classifier set of 200 CpG loci was identified, which independently partitioned primary tumors into ER-subtypes. Forty (32 novel, 8 previously known) CpG loci showed differential methylation specific to either ER-positive or ER-negative tumors; the loci interconnected several important signaling networks including estrogen metabolism, and cellular growth and proliferation. Each of the 40 ER-subtype-specific loci was validated in silico using an independent, publicly available methylome dataset from The Cancer Genome Atlas (TCGA). In addition, we identified 32 methylated CpG loci from 27 genes (17 novel, 10 known) that were significantly associated with disease progression; the majority of these loci were informative particularly in ER-negative breast cancer. Overall, the set was highly enriched in homeobox containing genes, revealing a heretofore unknown function of this gene class acting as a group to disease progression.

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 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 case-control studies, with more uniform standards of sample collection, such as in the context of large mature national 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 and optimizing Human Methylation 450K arrray analysis with this DNA, in collaboration with Illumina Inc., will be presented.

In summary, this study has demonstrated the feasibility of distinguishing ER-subtype in breast cancers and to possibly predict outcome based on CpG DNA methylation. The study suggested pathways which may explain distinctive behaviors among ER-positive and ER-negative tumors. Of great significance, the data strongly support the validity and feasibility of upcoming studies that will, in a prospective-retrospective fashion, examine the prognostic outcome and predictive therapeutic information of methylation markers using existing clinically-annotated tissues from previously conducted prospective randomized trials.

Citation Information: Cancer Prev Res 2011;4(10 Suppl):CN05-04.