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01.10.2010 | Research article | Ausgabe 5/2010 Open Access

Breast Cancer Research 5/2010

DNA methylation epigenotypes in breast cancer molecular subtypes

Breast Cancer Research > Ausgabe 5/2010
Naiara G Bediaga, Amelia Acha-Sagredo, Isabel Guerra, Amparo Viguri, Carmen Albaina, Irune Ruiz Diaz, Ricardo Rezola, María Jesus Alberdi, Joaquín Dopazo, David Montaner, Mertxe de Renobales, Agustín F Fernández, John K Field, Mario F Fraga, Triantafillos Liloglou, Marian M de Pancorbo
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​bcr2721) contains supplementary material, which is available to authorized users.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

NGB, TL, AFF, and AAS carried out the methylation assays and helped prepare the manuscript. IG, AV, RR, and IR provided tissues and clinical data. MCA and MJA carried out HER2, CH5/6, CK14, and EGFR1 assays and provided pathologic supports for tissue microdissection. DM and JD performed the statistical analysis. MMP, TL, MFF, MR, and JKF conceived the study and prepared the manuscript. All authors read and approved the final manuscript.



Identification of gene expression-based breast cancer subtypes is considered a critical means of prognostication. Genetic mutations along with epigenetic alterations contribute to gene-expression changes occurring in breast cancer. So far, these epigenetic contributions to sporadic breast cancer subtypes have not been well characterized, and only a limited understanding exists of the epigenetic mechanisms affected in those particular breast cancer subtypes. The present study was undertaken to dissect the breast cancer methylome and to deliver specific epigenotypes associated with particular breast cancer subtypes.


By using a microarray approach, we analyzed DNA methylation in regulatory regions of 806 cancer-related genes in 28 breast cancer paired samples. We subsequently performed substantial technical and biologic validation by pyrosequencing, investigating the top qualifying 19 CpG regions in independent cohorts encompassing 47 basal-like, 44 ERBB2+ overexpressing, 48 luminal A, and 48 luminal B paired breast cancer/adjacent tissues. With the all-subset selection method, we identified the most subtype-predictive methylation profiles in multivariable logistic regression analysis.


The approach efficiently recognized 15 individual CpG loci differentially methylated in breast cancer tumor subtypes. We further identified novel subtype-specific epigenotypes that clearly demonstrate the differences in the methylation profiles of basal-like and human epidermal growth factor 2 (HER2)-overexpressing tumors.


Our results provide evidence that well-defined DNA methylation profiles enable breast cancer subtype prediction and support the utilization of this biomarker for prognostication and therapeutic stratification of patients with breast cancer.
Additional file 1: Table S1. PCR primer and sequencing primer sequences and PCR conditions. (XLS 57 KB)
Additional file 2: Table S2. Genes differently methylated that provided optimal distinction between tumor and normal samples (P < 0.001 and Δ b >|0.20|). (XLSX 18 KB)
Additional file 3: Table S3. Comparison of quantitative methylation measurements at five CpG loci by both GoldenGate array and pyrosequencing. (XLS 31 KB)
Additional file 4: Table S4. Methylation levels in tumors and adjacent tissues. (DOCX 14 KB)
Authors’ original file for figure 1
Authors’ original file for figure 2
Authors’ original file for figure 3
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