@article {20028698, title = {Changes in the pattern of DNA methylation associate with twin discordance in systemic lupus erythematosus.}, journal = {Genome research}, volume = {20}, year = {2010}, month = {2010 Feb}, pages = {170-9}, abstract = {

Monozygotic (MZ) twins are partially concordant for most complex diseases, including autoimmune disorders. Whereas phenotypic concordance can be used to study heritability, discordance suggests the role of non-genetic factors. In autoimmune diseases, environmentally driven epigenetic changes are thought to contribute to their etiology. Here we report the first high-throughput and candidate sequence analyses of DNA methylation to investigate discordance for autoimmune disease in twins. We used a cohort of MZ twins discordant for three diseases whose clinical signs often overlap: systemic lupus erythematosus (SLE), rheumatoid arthritis, and dermatomyositis. Only MZ twins discordant for SLE featured widespread changes in the DNA methylation status of a significant number of genes. Gene ontology analysis revealed enrichment in categories associated with immune function. Individual analysis confirmed the existence of DNA methylation and expression changes in genes relevant to SLE pathogenesis. These changes occurred in parallel with a global decrease in the 5-methylcytosine content that was concomitantly accompanied with changes in DNA methylation and expression levels of ribosomal RNA genes, although no changes in repetitive sequences were found. Our findings not only identify potentially relevant DNA methylation markers for the clinical characterization of SLE patients but also support the notion that epigenetic changes may be critical in the clinical manifestations of autoimmune disease.

}, author = {Javierre, Biola M and Fernandez, Agustin F and Richter, Julia and Fatima Al-Shahrour and Martin-Subero, J Ignacio and Rodriguez-Ubreva, Javier and Berdasco, Maria and Fraga, Mario F and O{\textquoteright}Hanlon, Terrance P and Rider, Lisa G and Jacinto, Filipe V and Lopez-Longo, F Javier and Dopazo, Joaquin and Forn, Marta and Peinado, Miguel A and Carre{\~n}o, Luis and Sawalha, Amr H and Harley, John B and Siebert, Reiner and Esteller, Manel and Miller, Frederick W and Ballestar, Esteban} } @article {547, title = {DNA methylation epigenotypes in breast cancer molecular subtypes.}, journal = {Breast Cancer Res}, volume = {12}, year = {2010}, month = {2010}, pages = {R77}, abstract = {

INTRODUCTION: 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.

METHODS: 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.

RESULTS: 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.

CONCLUSIONS: 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.

}, keywords = {Aged, Breast Neoplasms, CpG Islands, DNA Methylation, Epigenesis, Genetic, Female, Gene Expression Profiling, Genes, p53, Genotype, Humans, Ki-67 Antigen, Middle Aged, mutation, Neoplasm Grading, Oligonucleotide Array Sequence Analysis, Receptor, ErbB-2, Tumor Suppressor Protein p53}, issn = {1465-542X}, doi = {10.1186/bcr2721}, author = {Bediaga, Naiara G and Acha-Sagredo, Amelia and Guerra, Isabel and Viguri, Amparo and Albaina, Carmen and Ruiz Diaz, Irune and Rezola, Ricardo and Alberdi, Maria Jesus and Dopazo, Joaquin and Montaner, David and Renobales, Mertxe and Fernandez, Agustin F and Field, John K and Fraga, Mario F and Liloglou, Triantafillos and de Pancorbo, Marian M} }