Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

CirDNA methylome analysis in prostate cancer

ABSTRACT: DNA modification profiling of circulating DNA (cirDNA) from plasma samples from prostate cancer patients (T2-3N0Mx), benign prostatic hyperplasia and control individuals Epigenetic differences are a common feature of many diseases, including cancer, and disease-associated changes have even been detected in bodily fluids. DNA modification studies in circulating DNA (cirDNA) may lead to the development of specific non-invasive biomarkers. Three-conditions experiment: Prostate cancer (n=19), bening prostatic hyperplasia (n=20), controls without any know prostatic disease (n=20). cirDNA was isolated and the modified fraction of the genome was enriched using DNA-modification-sensitive digestion and adaptor-mediated PCR. Enriched fraction was labelled with Cy3. DNA samples extracted from white blood cells (WBC) of 20 individuals unrelated to this project were pooled and used as reference (Cy5-labelled).

ORGANISM(S): Homo sapiens

SUBMITTER: Rene Cortese

PROVIDER: E-GEOD-36195 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Epigenetic markers of prostate cancer in plasma circulating DNA.

Cortese Rene R Kwan Andrew A Lalonde Emilie E Bryzgunova Olga O Bondar Anna A Wu Ying Y Gordevicius Juozas J Park Mina M Oh Gabriel G Kaminsky Zachary Z Tverkuviene Justina J Laurinavicius Arvydas A Jankevicius Feliksas F Sendorek Dorota H S DH Haider Syed S Wang Sun-Chong SC Jarmalaite Sonata S Laktionov Pavel P Boutros Paul C PC Petronis Arturas A

Human molecular genetics 20120522 16

Epigenetic differences are a common feature of many diseases, including cancer, and disease-associated changes have even been detected in bodily fluids. DNA modification studies in circulating DNA (cirDNA) may lead to the development of specific non-invasive biomarkers. To test this hypothesis, we investigated cirDNA modifications in prostate cancer patients with locally confined disease (n = 19), in patients with benign prostate hyperplasias (n = 20) and in men without any known prostate diseas ...[more]

PMID: 22619380

Similar Datasets

Project description:We describe a simple method, Digital Restriction Enzyme Analysis of Methylation (DREAM), based on sequential DNA digestion with a pair of methylation-blocked and methylation-tolerant neoschizomeric restriction enzymes SmaI/XmaI followed by end repair and ultra-deep sequencing. DREAM provides information on 160,000 unique CpG sites of which 39,000 are in CpG islands, and 33,000 are at transcription start sites (-1 kb to +1 kb) of 13,139 RefSeq genes. We compared DNA methylation values in white blood cells from 4 healthy individuals and found them to be remarkably uniform. Interindividual differences >30% were observed only at 227 of 28,331 (0.8%) of autosomal CCCGGG sites covered by 100+ sequencing reads. Similarly, differences at only 59 sites were observed between the cord and adult blood. Conserved methylation patterns in healthy blood cells contrasted with extensive changes affecting 18-40% of CpG sites in leukemia. The method is cost effective, quantitative (r2=0.93 when compared to bisulfite pyrosequencing), reproducible (r2=0.997), and can detect differences >25% with false positive rate <0.001. Accurate analysis of changes in DNA methylation will be useful in quantifying epigenetic effects of environment and nutrition, correlating developmental epigenetic variation with phenotypes, understanding epigenetics of cancer and chronic diseases, measuring the effects of drugs on DNA methylation or deriving new biological insights into mammalian genomes. Digital restriction enzyme analysis of methylation (DREAM) was performed to determine the DNA methylation profiles of healthy white blood cells from cord blood and adult blood, acute myeloid leukemia bone marrow, and two leukemia cell lines (HEL and K562). In this approach, genomic DNA is sequentially cut at CCCGGG sites with the methylation-sensitive enzyme SmaI (blunt ends) and its methylation-tolerant neoschizomer XmaI (5'CCGG overhangs), creating different end sequences that represent methylation status of the CCCGGG sites. These end sequences are analyzed by next-generation sequencing, and thereafter the methylation status at individual CCCGGG sites across the genome can be determined.

Dataset Information

CirDNA methylome analysis in prostate cancer

Publications

Epigenetic markers of prostate cancer in plasma circulating DNA.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure