DNA Methylation Heterogeneity Patterns in Breast Cancer Cell Lines
Name
Tian-2016-DNA Methylation Heterogeneity Patter.pdf
Size
2.92 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Sun, Shuying
Bertelsmann, Karina
Yu, Linda
Sun, Shuying
Tian, Sunny
Date Issued
September 2016
Journal
Cancer Informatics
Publisher
Libertas Academica, Ltd.
Citation
Sun, Shuying, Sunny Tian, Karina Bertelsmann, Linda Yu, and Shuying Sun. “DNA Methylation Heterogeneity Patterns in Breast Cancer Cell Lines.” Cancer Informatics (September 2016): 1. © 2016 the authors, publisher and licensee Libertas Academica Limited
Version
Final published version
Abstract
Heterogeneous DNA methylation patterns are linked to tumor growth. In order to study DNA methylation heterogeneity patterns for breast cancer cell lines, we comparatively study four metrics: variance, I² statistic, entropy, and methylation state. Using the categorical metric methylation state, we select the two most heterogeneous states to identify genes that directly affect tumor suppressor genes and high- or moderate-risk breast cancer genes. Utilizing the Gene Set Enrichment Analysis software and the ConsensusPath Database visualization tool, we generate integrated gene networks to study biological relations of heterogeneous genes. This analysis has allowed us to contribute 19 potential breast cancer biomarker genes to cancer databases by locating “hub genes” – heterogeneous genes of significant biological interactions, selected from numerous cancer modules. We have discovered a considerable relationship between these hub genes and heterogeneously methylated oncogenes. Our results have many implications for further heterogeneity analyses of methylation patterns and early detection of breast cancer susceptibility.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-NonCommercial 3.0 Unported
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.4137/cin.s40300
