Dataset Information

Identification of candidate tumour suppressor genes frequently methylated in renal cell carcinoma.

ABSTRACT: Promoter region hyermethylation and transcriptional silencing is a frequent cause of tumour suppressor gene (TSG) inactivation in many types of human cancers. Functional epigenetic studies, in which gene expression is induced by treatment with demethylating agents, may identify novel genes with tumour-specific methylation. We used high-density gene expression microarrays in a functional epigenetic study of 11 renal cell carcinoma (RCC) cell lines. Twenty-eight genes were then selected for analysis of promoter methylation status in cell lines and primary RCC. Eight genes (BNC1, PDLIM4, RPRM, CST6, SFRP1, GREM1, COL14A1 and COL15A1) showed frequent (>30% of RCC tested) tumour-specific promoter region methylation. Hypermethylation was associated with transcriptional silencing. Re-expression of BNC1, CST6, RPRM and SFRP1 suppressed the growth of RCC cell lines and RNA interference knock-down of BNC1, SFRP1 and COL14A1 increased the growth of RCC cell lines. Methylation of BNC1 or COL14A1 was associated with a poorer prognosis independent of tumour size, stage or grade. The identification of these epigenetically inactivated candidate RCC TSGs can provide insights into renal tumourigenesis and a basis for developing novel therapies and biomarkers for prognosis and detection.

SUBMITTER: Morris MR

PROVIDER: S-EPMC3021900 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of candidate tumour suppressor genes frequently methylated in renal cell carcinoma.

Morris M R MR Ricketts C C Gentle D D Abdulrahman M M Clarke N N Brown M M Kishida T T Yao M M Latif F F Maher E R ER

Oncogene 20100215 14

Promoter region hyermethylation and transcriptional silencing is a frequent cause of tumour suppressor gene (TSG) inactivation in many types of human cancers. Functional epigenetic studies, in which gene expression is induced by treatment with demethylating agents, may identify novel genes with tumour-specific methylation. We used high-density gene expression microarrays in a functional epigenetic study of 11 renal cell carcinoma (RCC) cell lines. Twenty-eight genes were then selected for analys ...[more]

PMID: 20154727

Similar Datasets

Project description:Aberrant methylated genes (DMGs) play an important role in the etiology and pathogenesis of esophageal squamous cell carcinoma (ESCC). In this study, we aimed to integrate three cohorts profile datasets to ascertain aberrant methylated-differentially expressed genes and pathways associated with ESCC by comprehensive bioinformatics analysis. We downloaded data of gene expression microarrays (GSE20347, GSE38129) and gene methylation microarrays (GSE52826) from the Gene Expression Omnibus (GEO) database. Aberrantly differentially expressed genes (DEGs) were obtained by GEO2R tool. The David database was then used to perform Gene ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome pathway enrichment analyses on selected genes. STRING and Cytoscape software were used to construct a protein-protein interaction (PPI) network, then the modules in the PPI networks were analyzed with MCODE and the hub genes chose from the PPI networks were verified by Oncomine and TCGA database. In total, 291 hypomethylation-high expression genes and 168 hypermethylation-low expression genes were identified at the screening step, and finally found six mostly changed hub genes including KIF14, CDK1, AURKA, LCN2, TGM1, and DSG1. Pathway analysis indicated that aberrantly methylated DEGs mainly associated with the P13K-AKT signaling, cAMP signaling and cell cycle process. After validation in multiple databases, most hub genes remained significant. Patients with high expression of AURKA were associated with shorter overall survival. To summarize, we have identified six feasible aberrant methylated-differentially expressed genes and pathways in ESCC by bioinformatics analysis, potentially providing valuable information for the molecular mechanisms of ESCC. Our data combined the analysis of gene expression profiling microarrays and gene methylation profiling microarrays, simultaneously, and in this way, it can shed a light for screening and diagnosis of ESCC in future.

Dataset Information

Identification of candidate tumour suppressor genes frequently methylated in renal cell carcinoma.

Publications

Identification of candidate tumour suppressor genes frequently methylated in renal cell carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets