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PLoS One. 2016 Apr 4;11(4):e0152918. doi: 10.1371/journal.pone.0152918. eCollection 2016.

Identification of Epigenetic Biomarkers of Lung Adenocarcinoma through Multi-Omics Data Analysis.

Author information

1
Division of Biostatistics, Kurume University School of Medicine, Fukuoka, Japan.
2
Biostatistics Center, Kurume University, Kurume, Fukuoka, Japan.
3
Institute of Life Science, College of Medicine, Swansea University, Swansea, United Kingdom.

Abstract

Epigenetic mechanisms such as DNA methylation or histone modifications are essential for the regulation of gene expression and development of tissues. Alteration of epigenetic modifications can be used as an epigenetic biomarker for diagnosis and as promising targets for epigenetic therapy. A recent study explored cancer-cell specific epigenetic biomarkers by examining different types of epigenetic modifications simultaneously. However, it was based on microarrays and reported biomarkers that were also present in normal cells at a low frequency. Here, we first analyzed multi-omics data (including ChIP-Seq data of six types of histone modifications: H3K27ac, H3K4me1, H3K9me3, H3K36me3, H3K27me3, and H3K4me3) obtained from 26 lung adenocarcinoma cell lines and a normal cell line. We identified six genes with both H3K27ac and H3K4me3 histone modifications in their promoter regions, which were not present in the normal cell line, but present in ≥85% (22 out of 26) and ≤96% (25 out of 26) of the lung adenocarcinoma cell lines. Of these genes, NUP210 (encoding a main component of the nuclear pore complex) was the only gene in which the two modifications were not detected in another normal cell line. RNA-Seq analysis revealed that NUP210 was aberrantly overexpressed among the 26 lung adenocarcinoma cell lines, although the frequency of NUP210 overexpression was lower (19.3%) in 57 lung adenocarcinoma tissue samples studied and stored in another database. This study provides a basis to discover epigenetic biomarkers highly specific to a certain cancer, based on multi-omics data at the cell population level.

PMID:
27042856
PMCID:
PMC4820141
DOI:
10.1371/journal.pone.0152918
[Indexed for MEDLINE]
Free PMC Article

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