Genome-Wide DNA Methylation Profiles of Breast Tumors Reveal Loci Associated with Relapse Risk

• Published in: Cancer research (Chicago, Ill.) Ill.), 2009-12, Vol.69 (24_Supplement), p.4046-4046
• Main Authors: Varadan, V., Kamalakaran, S., Giercksky Russnes, H., Levy, D., Kendall, J., Janevski, A., Riggs, M., Banerjee, N., Synnestvedt, M., Schlichting, E., Kåresen, R., Lucito, R., Wigler, M., Dimitrova, N., Naume, B., Hicks, J., Borresen-Dale, A.
• Format: Article
• Language: English
• ISSN: 0008-5472; 1538-7445
• DOI: 10.1158/0008-5472.SABCS-09-4046

Background:Breast cancer prognosis is used in determining the course of adjuvant therapy for patients. Clinical prognostic indices like the Nottingham Prognostic Index have poor specificity, overestimate the risk of disease recurrence and necessitate more specific and robust prognostic markers. Prognostic gene expression markers are already in clinical use and show improved decision support. Methylation of CpG islands, an important regulator of gene expression, is reported to be disregulated in tumors, thus making methylation markers an important alternative to gene expression markers. We present the results of a genome-wide study that explored loci whose methylation status was significantly associated with recurrence risk.Methods:We used 108 frozen primary breast cancer specimens with ten year follow-up and extensive clinical data including histopathological measurements to identify potential epigenetic markers associated with recurrence risk. Using a previously validated array based method (Kamalakaran et. al., Nucleic Acids Research, 2009) we performed genome-wide measurements of differential CpG island methylation covering over 150,000 loci. We evaluated each locus for its ability to stratify patients into good or poor prognosis groups depending on its methylation status. Statistical significance was established using permutation analysis with appropriate multiple testing corrections. Prognostic markers independent of histopathological factors (ER, PR, HER2, tumor size, grade, node status, age) were identified using multivariate Cox regression analysis.Results:The methylation status of several loci proximal to genes significantly stratified samples independent of other clinical variables. Demethylation of several loci were associated with poor prognosis including ADAMTS4 (Hazard Ratio = 17.5, p-value