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The Integrative Network of Gene Expression, MicroRNA, Methylation and Copy Number Variation in Colon and Rectal Cancer

Huang, Tao

Current Bioinformatics. Volume 11:Issue 1 (2016); pp 59-65 -- Bentham Science Publishers

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  • Title:
    The Integrative Network of Gene Expression, MicroRNA, Methylation and Copy Number Variation in Colon and Rectal Cancer
  • Author: Huang, Tao
  • Found In: Current Bioinformatics. Volume 11:Issue 1 (2016); pp 59-65
  • Journal Title: Current Bioinformatics
  • Subjects: Bioinformatics--Periodicals; Dewey: 570.285
  • Rights: Licensed
  • Publication Details: Bentham Science Publishers
  • Abstract:

    Gene expression level changes in cancer patients have been studied for a long time and have proven to be useful in classifying patients, predicting drug response, etc. But factors that control the gene expression in pathological conditions are still unclear. Identifying the putative causal factors could greatly help in understanding the mechanisms of cancer development and progression. It is believed that the microRNA, methylation and copy number variation (CNV) are possible regulators in gene expression. We analyzed the profiles of gene expression, microRNA, methylation and CNV in colon and rectal cancer patients. A multiple regression based method was developed to construct an integrative network including different levels of components. The regulatory effects of microRNA, methylation and copy number variation on gene expression were evaluated and compared. The cis-regulation effects from methylation to gene expression are very strong. 43.2% of cis methylation-expression appears as the most important methylation-expression regulator. 80.0% of cis methylation-expression is within the top five most important methylation-expression regulators. The functions of microRNA dominated genes, methylation dominated genes and CNV dominated genes were analyzed. The CNV dominated genes were involved in gene expression, protein modification and protein kinase activity. The methylation dominated genes showed notable immune response and calcium ion binding. The microRNA dominated genes were notable with regard to biological regulation and signal transduction. By decomposing the networks of gene, microRNA, methylation and CNV, the network modules were identified. Some modules provided useful clues about the mechanisms of gene expression regulation. Our methods provide a general framework for studying the integrative network derived from multiple large-scale biological data. The R script for our integrative network construction method is available from supporting information.


  • Identifier: System Number: ETOCvdc_100077668126.0x000001; Journal ISSN: 1574-8936
  • Publication Date: 2016
  • Physical Description: Electronic
  • Shelfmark(s): 3494.651200
  • UIN: ETOCvdc_100077668126.0x000001

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