Genome-scale meta-analysis of DNA methylation during progression of lung adenocarcinoma

Abstract

ABSTRACT. Identification of epigenetic alterations in tumors has become a common method for identifying genes critical to cancer development and progression. Thus, we identified DNA methylation alterations on the genome scale during lung adenocarcinoma (LADC) progression to understand the carcinogenic process and identify clinically relevant biomarkers. We found that epigenetic alterations in LADC mainly occur during the early stage of LADC progression, and there are no significant methylation differences between early-stage and late-stage LADCs. This suggests that DNA methylation alterations characterize a turning point of early events in LADC progression. By comparing DNA methylation between early-stage LADCs and normal lung tissues, we further identified 940 genes with significant alterations in DNA methylation. Sixty-seven genes were found to exhibit strong correlation between methylation alterations and expression changes, based on associated gene expression data. According to gene ontology analysis, these genes are involved in lung development, respiratory 9200-9214 (2015) system development, cell cycle, histidine metabolism, the Wnt signaling pathway, and the p53 signaling pathway. We also found that genes on chromosome 18 most frequently showed promoter hypermethylation. Moreover, we found that LADC-associated DNA hypomethylation occurred preferentially at neither histone H3 lysine 4 nor histone H3 lysine 27 mark domains in human embryonic stem cells (NMDs) and that hypomethylation of NMDs was associated with a poor prognostic signature in LADC. Our findings have important implications for LADC progression because of the identification of novel epigenetic biomarkers potentially involved in early-stage LADC and for establishing the importance of NMD DNA hypomethylation for predicting prognosis in LADC.

DNA methylation-based epigenetic signatures predict somatic genomic alterations in gliomas

“…Besides DNA methylation levels, many array-based bioinformatics tools have been developed, such as MGMT-STP27 13 , InfiniumPurify 25 (which estimates tumor purity), and ChAMP-CNV 26 , that allow for further unification of glioma biomarkers into a single assay. Lastly, the successful development of this DNA methylation-based, infiltrating glioma-specific classifier highlights that methylation-based tumor classification systems can be easily developed for other tumor types, not only for genomic alteration-based classification, but further grading and prognosis, such as for breast 3 or lung cancer 27 .…”

Identification of prognostic signature of non–small cell lung cancer based on TCGA methylation data

“…A previous study proved DNA methylation would be a better biomarker for diagnosis and prognosis because of its predictive stability when compared with gene and miRNA expression profiles 40 . A 4-gene methylation signature was recently proposed to predict the outcome of early-stage lung adenocarcinoma 41 . Nonetheless, studies on a methylation-based prediction model for NSCLC are scarce.…”

DNA methylation in lung tissues of mouse offspring exposed in utero to polycyclic aromatic hydrocarbons

“…The cancer genomics community has made recent progress in studies profiling methylation patterns in lung cancer tissues in an effort to identify CpG sites that may serve as biomarkers of disease or molecular targets for therapy (Belinsky, 2015; Freeman et al, 2016; Sato et al, 2013; Vizoso et al, 2015; Wang et al, 2017; Yan et al, 2017; Zhang et al, 2015). This study is the first to profile genome-wide DNA promoter methylation in lung tissues of mice exposed to environmental PAH carcinogens.…”