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Identification and validation of candidate epigenetic biomarkers in lung adenocarcinoma.

ABSTRACT: Lung cancer is the number one cause of cancer-related deaths worldwide. DNA methylation is an epigenetic mechanism that regulates gene expression, and disease-specific methylation changes can be targeted as biomarkers. We have compared the genome-wide methylation pattern in tumor and tumor-adjacent normal lung tissue from four lung adenocarcinoma (LAC) patients using DNA methylation microarrays and identified 74 differentially methylated regions (DMRs). Eighteen DMRs were selected for validation in a cohort comprising primary tumors from 52 LAC patients and tumor-adjacent normal lung tissue from 32 patients by methylation-sensitive high resolution melting (MS-HRM) analysis. Significant increases in methylation were confirmed for 15 DMRs associated with the genes and genomic regions: OSR1, SIM1, GHSR, OTX2, LOC648987, HIST1H3E, HIST1H3G/HIST1H2BI, HIST1H2AJ/HIST1H2BM, HOXD10, HOXD3, HOXB3/HOXB4, HOXA3, HOXA5, Chr1(q21.1).A, and Chr6(p22.1). In particular the OSR1, SIM1 and HOXB3/HOXB4 regions demonstrated high potential as biomarkers in LAC. For OSR1, hypermethylation was detected in 47/48 LAC cases compared to 1/31 tumor-adjacent normal lung samples. Similarly, 45/49 and 36/48 LAC cases compared to 3/31 and 0/31 tumor-adjacent normal lung samples showed hypermethylation of the SIM1 and HOXB3/HOXB4 regions, respectively. In conclusion, this study has identified and validated 15 DMRs that can be targeted as biomarkers in LAC.

SUBMITTER: Daugaard I

PROVIDER: S-EPMC5080630 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Identification and validation of candidate epigenetic biomarkers in lung adenocarcinoma.

Daugaard Iben I Dominguez Diana D Kjeldsen Tina E TE Kristensen Lasse S LS Hager Henrik H Wojdacz Tomasz K TK Hansen Lise Lotte LL

Scientific reports 20161026

Lung cancer is the number one cause of cancer-related deaths worldwide. DNA methylation is an epigenetic mechanism that regulates gene expression, and disease-specific methylation changes can be targeted as biomarkers. We have compared the genome-wide methylation pattern in tumor and tumor-adjacent normal lung tissue from four lung adenocarcinoma (LAC) patients using DNA methylation microarrays and identified 74 differentially methylated regions (DMRs). Eighteen DMRs were selected for validation ...[more]

PMID: 27782156

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Project description:BACKGROUND We aimed to screen and identify central genetic and molecular targets involved in advancement of lung adenocarcinoma (LUAD) and to perform an integrated analysis and clinical validation. MATERIAL AND METHODS The GEO2R technique was utilized to assess differentially expressed genes (DEGs) among the gene sets GSE75037, GSE85716, and GSE118370. Subsequently, gene Ontology (GO) analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) analytical methods were executed to determine related biofunctions and signaling pathways, which were annotated with tools from the Database for Annotation, Visualization and Integrated Discovery (DAVID) resource. Then, a protein-protein interaction (PPI) network complex consisting of all detected DEGs was built with the STRING web interface. Cytohubba and MCODE plug-ins for Cytoscape software and Gene Expression Profiling Interactive Analysis (GEPIA) were employed to identify the hub genes. Finally, the mRNA expression of the identified hub genes was quantitatively validated by The Cancer Genome Atlas (TCGA) database analysis and real-time quantitative polymerase chain reaction (RT-qPCR). RESULTS We screened 146 upregulated DEGs and 431 downregulated DEGs with the criteria of |logFC| >1 and P<0.05, and the GO analysis indicated that DEGs were implicated in mitotic nuclear division (biological process, BP), the nucleus (cellular component, CC), and protein binding (molecular function, MF) and were associated with multiple KEGG pathways, such as the p53 signaling pathway in cancer. Then, the top 8 genes that predicted significantly different outcomes in LUAD patients were filtered from the DEGs and selected as hub genes. The TCGA database analysis and RT-qPCR results demonstrated that these genes were differentially expressed with the same trends in LUAD tissues compared with normal tissues. CONCLUSIONS Overall, we propose that 8 genes (PECAM1, CDK1, MKI67, SPP1, TOP2A, CHEK1, CCNB1, and RRM2) might be novel hub genes strongly associated with the progression and prognosis of LUAD.

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Identification and validation of candidate epigenetic biomarkers in lung adenocarcinoma.

Publications

Identification and validation of candidate epigenetic biomarkers in lung adenocarcinoma.

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