Towards understanding the breast cancer epigenome: a comparison of genome-wide DNA methylation and gene expression data

被引:16
作者
Singhal, Sandeep K. [1 ]
Usmani, Nawaid [1 ]
Michiels, Stefan [2 ,3 ]
Metzger-Filho, Otto [4 ]
Saini, Kamal S. [5 ]
Kovalchuk, Olga [6 ,7 ]
Parliament, Matthew [1 ]
机构
[1] Univ Alberta, Cross Canc Inst, Dept Oncol, Edmonton, AB, Canada
[2] Inst Gustave Roussy, Serv Biostat & Epidemiol, Villejuif, France
[3] Univ Paris 11, INSERM, CESP, U1018, Villejuif, France
[4] Harvard Univ, Sch Med, Dana Farber Canc Inst, Dept Med Oncol, 44 Binney St, Boston, MA 02115 USA
[5] Quantum Hlth Analyt SPRL, Liege, Belgium
[6] Univ Lethbridge, Dept Biol Sci, Lethbridge, AB T1K 3M4, Canada
[7] Canada Canc & Aging Res Labs Ltd, Lethbridge, AB, Canada
关键词
DNA methylation; breast cancer; epigenetics; expression; microarray; 5-HYDROXYMETHYLCYTOSINE; 5-METHYLCYTOSINE; CPG; CLASSIFICATION; NORMALIZATION; EPIGENETICS; METHYLOME; MECHANISM; PROFILES; SUBTYPES;
D O I
10.18632/oncotarget.6503
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Until recently, an elevated disease risk has been ascribed to a genetic predisposition, however, exciting progress over the past years has discovered alternate elements of inheritance that involve epigenetic regulation. Epigenetic changes are heritably stable alterations that include DNA methylation, histone modifications and RNA-mediated silencing. Aberrant DNA methylation is a common molecular basis for a number of important human diseases, including breast cancer. Changes in DNA methylation profoundly affect global gene expression patterns. What is emerging is a more dynamic and complex association between DNA methylation and gene expression than previously believed. Although many tools have already been developed for analyzing genome-wide gene expression data, tools for analyzing genome-wide DNA methylation have not yet reached the same level of refinement. Here we provide an in-depth analysis of DNA methylation in parallel with gene expression data characteristics and describe the particularities of low-level and high-level analyses of DNA methylation data. Low-level analysis refers to pre-processing of methylation data (i.e. normalization, transformation and filtering), whereas high-level analysis is focused on illustrating the application of the widely used class comparison, class prediction and class discovery methods to DNA methylation data. Furthermore, we investigate the influence of DNA methylation on gene expression by measuring the correlation between the degree of CpG methylation and the level of expression and to explore the pattern of methylation as a function of the promoter region.
引用
收藏
页码:3002 / 3017
页数:16
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