Literature DB >> 20144234

Genome-wide methylation and expression profiling identifies promoter characteristics affecting demethylation-induced gene up-regulation in melanoma.

Jill C Rubinstein1, Nam Tran, Shuangge Ma, Ruth Halaban, Michael Krauthammer.   

Abstract

BACKGROUND: Abberant DNA methylation at CpG dinucleotides represents a common mechanism of transcriptional silencing in cancer. Since CpG methylation is a reversible event, tumor supressor genes that have undergone silencing through this mechanism represent promising targets for epigenetically active anti-cancer therapy. The cytosine analog 5-aza-2'-deoxycytidine (decitabine) induces genomic hypomethylation by inhibiting DNA methyltransferase, and is an example of an epigenetic agent that is thought to act by up-regulating silenced genes.
METHODS: It is unclear why decitabine causes some silenced loci to re-express, while others remain inactive. By applying data-mining techniques to large-scale datasets, we attempted to elucidate the qualities of promoter regions that define susceptibility to the drug's action. Our experimental data, derived from melanoma cell strains, consist of genome-wide gene expression data before and after treatment with decitabine, as well as genome-wide data on un-treated promoter methylation status, and validation of specific genes by bisulfite sequencing.
RESULTS: We show that the combination of promoter CpG content and methylation level informs the ability of decitabine treatment to up-regulate gene expression. Promoters with high methylation levels and intermediate CpG content appear most susceptible to up-regulation by decitabine, whereas few of those highly methylated promoters with high CpG content are up-regulated. For promoters with low methylation levels, those with high CpG content are more likely to be up-regulated, whereas those with low CpG content are underrepresented among up-regulated genes.
CONCLUSIONS: Clinically, elucidating the patterns of action of decitabine could aid in predicting the likelihood of up-regulating epigenetically silenced tumor suppressor genes and others from pathways involved with tumor biology. As a first step toward an eventual translational application, we build a classifier to predict gene up-regulation based on promoter methylation and CpG content, which achieves a performance of 0.77 AUC.

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Year:  2010        PMID: 20144234      PMCID: PMC2843643          DOI: 10.1186/1755-8794-3-4

Source DB:  PubMed          Journal:  BMC Med Genomics        ISSN: 1755-8794            Impact factor:   3.063


  25 in total

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Journal:  Cell       Date:  1999-11-24       Impact factor: 41.582

2.  The activation of human gene MAGE-1 in tumor cells is correlated with genome-wide demethylation.

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3.  ROCR: visualizing classifier performance in R.

Authors:  Tobias Sing; Oliver Sander; Niko Beerenwinkel; Thomas Lengauer
Journal:  Bioinformatics       Date:  2005-08-11       Impact factor: 6.937

4.  Gene silencing. Methylation meets acetylation.

Authors:  T H Bestor
Journal:  Nature       Date:  1998-05-28       Impact factor: 49.962

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Journal:  Genes Dev       Date:  1989-05       Impact factor: 11.361

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Journal:  Genes Dev       Date:  1988-09       Impact factor: 11.361

7.  Decitabine activates specific caspases downstream of p73 in myeloid leukemia.

Authors:  Ingo Tamm; Mandy Wagner; Karin Schmelz
Journal:  Ann Hematol       Date:  2005-12       Impact factor: 3.673

8.  Methylation of the 5' CpG island of the p16/CDKN2 tumor suppressor gene in normal and transformed human tissues correlates with gene silencing.

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Journal:  Cancer Res       Date:  1995-10-15       Impact factor: 12.701

9.  Genome-wide screen of promoter methylation identifies novel markers in melanoma.

Authors:  Yasuo Koga; Mattia Pelizzola; Elaine Cheng; Michael Krauthammer; Mario Sznol; Stephan Ariyan; Deepak Narayan; Annette M Molinaro; Ruth Halaban; Sherman M Weissman
Journal:  Genome Res       Date:  2009-06-02       Impact factor: 9.043

10.  DNA motifs associated with aberrant CpG island methylation.

Authors:  F Alex Feltus; Eva K Lee; Joseph F Costello; Christoph Plass; Paula M Vertino
Journal:  Genomics       Date:  2006-02-17       Impact factor: 5.736

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  5 in total

1.  A semantic web framework to integrate cancer omics data with biological knowledge.

Authors:  Matthew E Holford; James P McCusker; Kei-Hoi Cheung; Michael Krauthammer
Journal:  BMC Bioinformatics       Date:  2012-01-25       Impact factor: 3.169

2.  Expression of proteins involved in epigenetic regulation in human cutaneous melanoma and peritumoral skin.

Authors:  Anatoly Uzdensky; Svetlana Demyanenko; Mikhail Bibov; Svetlana Sharifulina; Oleg Kit; Yury Przhedetski; Viktoria Pozdnyakova
Journal:  Tumour Biol       Date:  2014-05-22

Review 3.  Advances in genetic and epigenetic analyses of gliomas: a neuropathological perspective.

Authors:  Nadejda M Tsankova; Peter Canoll
Journal:  J Neurooncol       Date:  2014-06-25       Impact factor: 4.130

4.  Genome-scale DNA methylation pattern profiling of human bone marrow mesenchymal stem cells in long-term culture.

Authors:  Mi Ran Choi; Yong-Ho In; Jungsun Park; Taesung Park; Kyoung Hwa Jung; Jin Choul Chai; Mi Kyung Chung; Young Seek Lee; Young Gyu Chai
Journal:  Exp Mol Med       Date:  2012-08-31       Impact factor: 8.718

5.  Integrating Early Transcriptomic Responses to Rhizotoxins in Rice (Oryza sativa. L.) Reveals Key Regulators and a Potential Early Biomarker of Cadmium Toxicity.

Authors:  Li-Yao Huang; Chung-Wen Lin; Ruey-Hua Lee; Chih-Yun Chiang; Yung-Chuan Wang; Ching-Han Chang; Hao-Jen Huang
Journal:  Front Plant Sci       Date:  2017-08-18       Impact factor: 5.753

  5 in total

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