DETECTION OF EPIGENOMIC NETWORK COMMUNITY ONCOMARKERS

• 成果类型: Article
• 署名作者: Bartlett, Thomas E.; Zaikin, Alexey
• 署名单位: University of London; University College London; University of London; University College London
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/16-AOAS939
• 发表日期: 2016
• 页码: 1373-1396
• 关键词: cpg island methylation; breast; genome; progression; regression; transcription; lesions; models

摘要

In this paper we propose network methodology to infer prognostic cancer biomarkers based on the epigenetic pattern DNA methylation. Epigenetic processes such as DNA methylation reflect environmental risk factors, and are increasingly recognised for their fundamental role in diseases such as cancer. DNA methylation is a gene-regulatory pattern, and hence provides a means by which to assess genomic regulatory interactions. Network models are a natural way to represent and analyse groups of such interactions. The utility of network models also increases as the quantity of data and number of variables increase, making them increasingly relevant to large-scale genomic studies. We propose methodology to infer prognostic genomic networks from a DNA methylation-based measure of genomic interaction and association. We then show how to identify prognostic biomarkers from such networks, which we term network community oncomarkers. We illustrate the power of our proposed methodology in the context of a large publicly available breast cancer dataset.