Genome-scale analysis of DNA methylation in lung adenocarcinoma and integration with mRNA expression

Abstract

Lung cancer is the leading cause of cancer death worldwide, and adenocarcinoma is its most common histological subtype. Clinical and molecular evidence indicates that lung adenocarcinoma is a heterogeneous disease, which has important implications for treatment. Here we performed genome-scale DNA methylation profiling using the Illumina Infinium HumanMethylation27 platform on 59 matched lung adenocarcinoma/non-tumor lung pairs, with genome-scale verification on an independent set of tissues. We identified 766 genes showing altered DNA methylation between tumors and non-tumor lung. By integrating DNA methylation and mRNA expression data, we identified 164 hypermethylated genes showing concurrent down-regulation, and 57 hypomethylated genes showing increased expression. Integrated pathways analysis indicates that these genes are involved in cell differentiation, epithelial to mesenchymal transition, RAS and WNT signaling pathways, and cell cycle regulation, among others. Comparison of DNA methylation profiles between lung adenocarcinomas of current and never-smokers showed modest differences, identifying only LGALS4 as significantly hypermethylated and down-regulated in smokers.LGALS4, encoding a galactoside-binding protein involved in cell-cell and cell-matrix interactions, was recently shown to be a tumor suppressor in colorectal cancer. Unsupervised analysis of the DNA methylation data identified two tumor subgroups, one of which showed increased DNA methylation and was significantly associated with KRAS mutation and to a lesser extent, with smoking. Our analysis lays the groundwork for further molecular studies of lung adenocarcinoma by identifying novel epigenetically deregulated genes potentially involved in lung adenocarcinoma development/progression, and by describing an epigenetic subgroup of lung adenocarcinoma associated with characteristic molecular alterations.

A functional methylome map of ulcerative colitis

“…Keeping these limitations in mind, the presented identification of 61 cis-links between epigenetic modifications and disease-associated transcripts supports the hypothesis that pathophysiological events are a reflection of-and potentially controlled by-epigenetic modifications with consequences on transcriptional changes. The identified cis-links show both negative and positive correlations between DNAm and RNA expression, which is in concordance with two recent studies applying similar approaches (Gervin et al 2012;Selamat et al 2012), yet the nature of positive correlations remains unexplained by the current understanding of epigenetic regulation. The majority of identified loci are associated with biological processes which are either directly or indirectly linked to immune processes, which is consistent with previous findings on functional genomics of UC (Dieckgraefe et al 2000;Lawrance et al 2001;Costello et al 2005), as well as with findings on UC genetics (Anderson et al 2011).…”

“…A group of 20 monozygotic twins, discordant for UC, was selected as an entry level to perform a three-layer genome-wide scan to target mechanisms that show significant differences between healthy and diseased individuals. The validity of such an approach has been recently demonstrated in psoriasis and lung adenocarcinoma (Gervin et al 2012;Selamat et al 2012). Obviously, such approaches cannot demonstrate the causality of epigenetic modifications for altered mRNA levels.…”

Identification of hub genes and pathways associated with bladder cancer based on co-expression network analysis

“…LGALS4 has been identified as one of the genes involved in numerous types of human tumor, including sinonasal adenocarcinoma tumors (34), colorectal cancer (35) and breast cancer (36). There has also been a previous report that compared expression changes at mRNA and protein levels in the rat model and identified the gene exhibiting concordant changes with LGALS4 levels in bladder tumors (37).…”

Overexpression and proliferation dependence of acyl-CoA thioesterase 11 and 13 in lung adenocarcinoma

“…Microarray data from cell lines or small sample sizes (<10 samples) were excluded. Six microarray datasets including GSE2514 (11), GSE7670 (12), GSE10072 (13), GSE31210 (14), GSE32863 (15), and GSE43458 (16) were collected and the relative expression levels of fatty acyl-CoA metabolic enzymes between adjacent non-tumor lung tissue and lung adenocarcinoma were analyzed in these microarray datasets. The expression value was analyzed using the GEO2R interface (http://www.ncbi.nlm.nih.gov/geo/geo2r/).…”