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Determining the Effect of DNA Methylation on Gene Expression in Cancer Cells

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 1101))

Abstract

DNA methylation, a DNA modification by adding methyl group to cytosine, has an important role in the regulation of gene expression. DNA methylation is known to be associated with gene transcription by interfering with DNA-binding proteins, such as transcription factors. DNA methylation is closely related to tumorigenesis, and the methylation state of some genes can be used as a biomarker for tumorigenesis. Aberrant DNA methylation of genomic regions, including CpG islands, CpG shores, and first exons, is related to the altered gene expression pattern characteristics of all human cancers. Subheading 1 surveys recent developments on DNA methylation and gene expressions in cancer. Then we provide analysis of DNA methylation and gene expression in 30 breast cancer cell lines representing different tumor phenotypes. This study conducted an integrated analysis to identify the relationship between DNA methylation in various genomic regions and expression levels of downstream genes, using MethylCapseq data (affinity purification followed by next-generation sequencing of eluted DNA) and Affymetrix gene expression microarray data. The goal of this study was to assess genome-wide methylation profiles associated with different molecular subtypes of human breast cancer (luminal, basal A, and basal B) and to comprehensively investigate the effect of DNA methylation on gene expression in breast cancer phenotypes. This showed that methylation of genomic regions near transcription start sites, CpG island, CpG shore, and first exon was strongly associated with gene repression, and the effects of the regions on gene expression patterns were different for different molecular subtypes of breast cancer. The results further indicated that aberrant methylation of specific genomic regions was significantly associated with different breast cancer subtypes.

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References

  1. Sproul D et al (2011) Transcriptionally repressed genes become aberrantly methylated and distinguish tumors of different lineages in breast cancer. Proc Natl Acad Sci USA 108(11):4364–4369

    Article  PubMed  CAS  Google Scholar 

  2. Chen RZ et al (1998) DNA hypomethylation leads to elevated mutation rates. Nature 395(6697):89–93

    Article  PubMed  CAS  Google Scholar 

  3. Baylin SB et al (1998) Alterations in DNA methylation: a fundamental aspect of neoplasia. Adv Cancer Res 72:141–196

    Article  PubMed  CAS  Google Scholar 

  4. Das PM, Singal R (2004) DNA methylation and cancer. J Clin Oncol 22:4632–4642

    Article  PubMed  CAS  Google Scholar 

  5. Baylln SB et al (1997) Alterations in DNA methylation: a fundamental aspect of neoplasia. Adv Cancer Res 72:141–196

    Article  Google Scholar 

  6. Syeed N et al (2012) 5′-CpG island promoter hypermethylation of the CAV-1 gene in breast cancer patients of Kashmir. Asian Pac J Cancer Prev 13(1):371–375

    Article  PubMed  Google Scholar 

  7. Maeda K et al (2003) Hypermethylation of the CDKN2A gene in colorectal cancer is associated with shorter survival. Oncol Rep 10:935–938

    PubMed  CAS  Google Scholar 

  8. Yi J et al (2001) P16 gene methylation in colorectal cancers associated with Duke’s staging. World J Gastroenterol 7:722–725

    PubMed  CAS  Google Scholar 

  9. Nakayama M et al (2004) GSTP1 CpG island hypermethylation as a molecular biomarker for prostate cancer. J Cell Biochem 91(3):540–552

    Article  PubMed  CAS  Google Scholar 

  10. Jha AK et al (2012) Promoter hypermethylation of p73 and p53 genes in cervical cancer patients among north Indian population. Mol Biol Rep 39(9):9145–9157

    Article  PubMed  CAS  Google Scholar 

  11. Irizarry RA et al (2009) The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores. Nat Genet 41(2):178–186

    Article  PubMed  CAS  Google Scholar 

  12. Brenet F et al (2011) DNA methylation of the first exon is tightly linked to transcriptional silencing. PLoS One 6(1):e14524

    Article  PubMed  CAS  Google Scholar 

  13. Li M et al (2009) Integrated analysis of DNA methylation and gene expression reveals specific signaling pathways associated with platinum resistance in ovarian cancer. BMC Med Genomics 2:34–46

    Article  PubMed  Google Scholar 

  14. Cancer Genome Atlas Research Network (2011) Integrated genomic analyses of ovarian carcinoma. Nature 474(7353):609–615

    Article  Google Scholar 

  15. Balch C et al (2010) Role of epigenomics in ovarian and endometrial cancers. Epigenomics 2(3):419–447

    Article  PubMed  CAS  Google Scholar 

  16. Neve RM et al (2006) A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell 10:515–527

    Article  PubMed  CAS  Google Scholar 

  17. Gautier L et al (2004) affy–-analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 20:307–315

    Article  PubMed  CAS  Google Scholar 

  18. Biomedical Informatics, The Ohio State University Medical Center. http://motif.bmi.ohio-state.edu/jinlab/BMI730/BMI730-10-Lecture10.ppt

  19. Chae H, et al. (2011) mCpG-SNP-EXPRESS (methyl-CpG Single Nucleotide Polymorphism Gene EXPRESSion). http://biohealth.snu.ac.kr/mcpg-snp-express.

  20. Feng J et al (2012) Identifying ChIP-seq enrichment using MACS. Nat Protoc 7(9):1728–1740

    Article  PubMed  CAS  Google Scholar 

  21. Rao X et al (2012) CpG island shore methylation regulates caveolin-1 expression in breast cancer. Oncogene. doi:10.1038/onc.2012.474

    Google Scholar 

  22. Warnes GR, et al. (2010). gplots: Various R programming tools for plotting data. R package version 2.8.0. http://CRAN.R-project.org/package=gplots

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Acknowledgement

This work was supported by the Rural Development Administration(RDA), Next-Generation Information Computing Development Program, the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean Government (MEST) (No. 20120006013) and the Brain Korea 21 Project in 2012.

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Lee, CJ., Evans, J., Kim, K., Chae, H., Kim, S. (2014). Determining the Effect of DNA Methylation on Gene Expression in Cancer Cells. In: Ochs, M. (eds) Gene Function Analysis. Methods in Molecular Biology, vol 1101. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-721-1_9

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  • DOI: https://doi.org/10.1007/978-1-62703-721-1_9

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-720-4

  • Online ISBN: 978-1-62703-721-1

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