Discovering DNA methylation patterns for long non-coding RNAs associated with cancer subtypes

Computational Biology and Chemistry
Xiaoke MaXiaofei Yang

Abstract

Despite growing evidence demonstrates that the long non-coding ribonucleic acids (lncRNAs) are critical modulators for cancers, the knowledge about the DNA methylation patterns of lncRNAs is quite limited. We develop a systematic analysis pipeline to discover DNA methylation patterns for lncRNAs across multiple cancer subtypes from probe, gene and network levels. By using The Cancer Genome Atlas (TCGA) breast cancer methylation data, the pipeline discovers various DNA methylation patterns for lncRNAs across four major subtypes such as luminal A, luminal B, her2-enriched as well as basal-like. On the probe and gene level, we find that both differentially methylated probes and lncRNAs are subtype specific, while the lncRNAs are not as specific as probes. On the network level, the pipeline constructs differential co-methylation lncRNA network for each subtype. Then, it identifies both subtype specific and common lncRNA modules by simultaneously analyzing multiple networks. We show that the lncRNAs in subtype specific and common modules differ greatly in terms of topological structure, sequence conservation as well as expression. Furthermore, the subtype specific lncRNA modules serve as biomarkers to improve significantly the accur...Continue Reading

Citations

Dec 15, 2017·Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry·Xiaoke MaJianbang Zhao
Apr 28, 2018·Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry·Enli Zhang, Xiaoke Ma
May 16, 2019·BioData Mining·Lillian Sun, Shuying Sun
Sep 10, 2019·Cancer Informatics·Shuying SunBrittany Enfield
May 30, 2021·Nucleic Acids Research·Yuwei ZhangYi Zhao

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