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PMID: 20920229 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

DNA methylation epigenotypes in breast cancer molecular subtypes.

Breast cancer research : BCR ·Vol. 12 ·No. 5 ·2010-00-00 ·Pages R77

Bediaga NG, Acha-Sagredo A, Guerra I, Viguri A, Albaina C, Ruiz Diaz I, Rezola R, Alberdi MJ, Dopazo J, Montaner D, Renobales M, Fernández AF, Field JK, Fraga MF, Liloglou T, de Pancorbo MM

Abstract

Identification of gene expression based breast cancer subtypes is considered as 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 there is only a limited understanding of the epigenetic mechanisms affected in those particular breast cancer subtypes. The present study was undertaken to dissect the breast cancer methylome and deliver specific epigenotypes associated with particular breast cancer subtypes. 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 biological 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. Using 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 identify novel subtype specific epigenotypes which 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 enables breast cancer subtype prediction and support the utilization of this biomarker for prognostication and therapeutic stratification of patients with breast cancer.

MeSH Terms
Aged Breast Neoplasms/classification,genetics,metabolism CpG Islands DNA Methylation Epigenesis, Genetic Female Gene Expression Profiling Genes, p53 Genotype Humans Ki-67 Antigen/metabolism Middle Aged Mutation Neoplasm Grading Oligonucleotide Array Sequence Analysis Receptor, ErbB-2/metabolism Tumor Suppressor Protein p53/genetics
Chemicals
Ki-67 Antigen Tumor Suppressor Protein p53 ERBB2 protein, human Receptor, ErbB-2
Authors & Affiliations
16 authors, click to expand affiliations / ORCID
Bediaga Naiara G
BIOMICs Research Group, Centro de Investigacion y Estudios Avanzados ‘Lucio Lascaray’, University of the Basque Country UPV/EHU, Vitoria-Gazteiz, Spain.
Acha-Sagredo Amelia
Guerra Isabel
Viguri Amparo
Albaina Carmen
Ruiz Diaz Irune
Rezola Ricardo
Alberdi María Jesus
Dopazo Joaquín
Montaner David
Renobales Mertxe
Fernández Agustín F
Field John K
Fraga Mario F
Liloglou Triantafillos
de Pancorbo Marian M
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Article Info
Journal
Breast cancer research : BCR
Abbr.
Breast Cancer Res
ISSN
1465-542X
DOI
10.1186/bcr2721
Published
2010-00-00
Epub
2010-00-29
Pages
R77
Language
English
Region
England
NLM ID
100927353
PMCID
PMC3096970
Subset
IM
External Links
PubMed source DOI: 10.1186/bcr2721 PMC Full Text View journal details
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