Genome-Wide DNA Methylation Profiling in 40 Breast Cancer Cell Lines

  • Leng Han
  • Siyuan Zheng
  • Shuying Sun
  • Tim HM Huang
  • Zhongming Zhao
Conference paper

DOI: 10.1007/978-3-642-14922-1_35

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6215)
Cite this paper as:
Han L., Zheng S., Sun S., Huang T.H., Zhao Z. (2010) Genome-Wide DNA Methylation Profiling in 40 Breast Cancer Cell Lines. In: Huang DS., Zhao Z., Bevilacqua V., Figueroa J.C. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Lecture Notes in Computer Science, vol 6215. Springer, Berlin, Heidelberg

Abstract

DNA methylation plays important roles in gene regulation and functions. Aberrant methylation, either hypomethylation or hypermethylation, has been reported to cause various diseases, especially cancers. Breast cancer ranked the fifth according to the number of cancer deaths in the world. To systematically characterize the epigenetic modification in breast cancer, we examined the genome-wide methylation profiling in 40 breast cancer cell lines. We identified a gene signature consisting of 345 differentially methylated genes, which could be used to discriminate estrogen receptor (ER)-negative and ER-positive breast cancer cell lines. This gene signature is promising for diagnosis and therapies of breast cancer. In the follow up functional analysis of this gene signature, three enriched networks could be highlighted. Interestingly, one of these networks contained estrogen receptor, implying its functional importance of ER-centric module. Finally, we examined the correlation between methylation and expression of these breast cancer cell lines. Very few genes showed significant correlation, suggesting that gene expression regulated by methylation is a complex biological process.

Keywords

breast cancer estrogen receptor methylation network expression 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Leng Han
    • 1
    • 2
  • Siyuan Zheng
    • 1
    • 2
  • Shuying Sun
    • 3
  • Tim HM Huang
    • 4
  • Zhongming Zhao
    • 1
    • 2
    • 5
  1. 1.Department of Biomedical InformaticsVanderbilt University School of MedicineNashvilleUSA
  2. 2.Bioinformatics Resources CenterVanderbilt UniversityNashvilleUSA
  3. 3.Case Comprehensive Cancer CenterCase Western Reserve UniversityClevelandUSA
  4. 4.Human Cancer Genetics ProgramThe Ohio State UniversityColumbusUSA
  5. 5.Department of Cancer BiologyVanderbilt University School of MedicineNashvilleUSA

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