Pancancer analysis of DNA methylation-driven genes using MethylMix

被引：99

作者：

Gevaert, Olivier ^{[1
]}

Tibshirani, Robert ^{[2
,3
]}

Plevritis, Sylvia K. ^{[4
]}

机构：

[1] Stanford Univ, Dept Med, Biomed Informat Res, Stanford, CA 94305 USA

[2] Stanford Univ, Dept Hlth Res & Policy, Stanford, CA 94305 USA

[3] Stanford Univ, Dept Stat, Stanford, CA 94305 USA

[4] Stanford Univ, Dept Radiol, Stanford, CA 94305 USA

来源：

GENOME BIOLOGY | 2015年 / 16卷

关键词：

EMBRYONIC STEM; CANCER TYPES; REVEALS; PACKAGE; TMEM25; CELLS;

D O I：

10.1186/s13059-014-0579-8

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 [微生物学]; 090105 [作物生产系统与生态工程];

摘要：

Aberrant DNA methylation is an important mechanism that contributes to oncogenesis. Yet, few algorithms exist that exploit this vast dataset to identify hypo- and hypermethylated genes in cancer. We developed a novel computational algorithm called MethylMix to identify differentially methylated genes that are also predictive of transcription. We apply MethylMix to 12 individual cancer sites, and additionally combine all cancer sites in a pancancer analysis. We discover pancancer hypo- and hypermethylated genes and identify novel methylation-driven subgroups with clinical implications. MethylMix analysis on combined cancer sites reveals 10 pancancer clusters reflecting new similarities across malignantly transformed tissues.

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