Abstract—Among the thousands of gene promoters hyper- or hypomethylated in cancer genomes, only a small portion of them play “driver” roles in tumorigenesis, whereas the others are only “passengers”. Here, we develop an approach to identify driver methylation genes of cancer with integrated promoter methylation and gene expression data generated from paired cancer and normal samples for each of a cohort of breast cancer patients, taking the advantage that data of paired samples could provide the relative gene methylation change information from normal to tumor for each individual patient. We applied this approach to analyze a dataset of breast cancer and discovered some novel cancer driver genes. The identified driver genes with methylation alteration may help us to reveal new molecular targets for potential epigenetic therapy.

Index Terms—Methylation, expression, driver gene, breast cancer.

Xiaopei Shen and Shan Li are with the Bioinformatics Centre, School of Life Science, University of Electronic Science and Technology of China, Chengdu, 610054, China (e-mail: bioshenxp@gmail.com, shineyong27@yahoo.cn).
Zheng Guo is with the Department of Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350004, China (e-mail: guoz@ems.hrbmu.edu.cn).

 

Cite:Xiaopei Shen, Shan Li, and Zheng Guo, "Identifying Driver Genes of Breast Cancer by Integrated Analysis of Methylation and Expression Data in Paired Disease-Normal Samples of Patients," International Journal of Bioscience, Biochemistry and Bioinformatics vol. 3, no. 3, pp. 267-270, 2013.