Biomedical subjects

Kurt Berlin

Publications and source records attributed to Kurt Berlin.

9 recordsLinked to original sources

PubMed2006

DNA methylation profiling of human chromosomes 6, 20 and 22.

DNA methylation is the most stable type of epigenetic modification modulating the transcriptional plasticity of mammalian genomes. Using bisulfite DNA sequencing, we report high-resolution methylation profiles of human chromosomes 6, 20 and 22, providing a resource of about 1.9 million CpG methylation values derived from 12 different tissues. Analysis of six annotation categories showed that evolutionarily conserved regions are the predominant sites for differential DNA methylation and that a core region surrounding the transcriptional start site is an informative surrogate for promoter methylation. We find that 17% of the 873 analyzed genes are differentially methylated in their 5' UTRs and that about one-third of the differentially methylated 5' UTRs are inversely correlated with transcription. Despite the fact that our study controlled for factors reported to affect DNA methylation such as sex and age, we did not find any significant attributable effects. Our data suggest DNA methylation to be ontogenetically more stable than previously thought.

5' Untranslated Regions↗

PubMed2006

Novel method for high throughput DNA methylation marker evaluation using PNA-probe library hybridization and MALDI-TOF detection.

The methylation of CpG dinucleotides has become a topic of great interest in cancer research, and the methylation of promoter regions of several tumor suppressor genes has been identified as a marker of tumorigenesis. Evaluation of DNA methylation markers in tumor tissue requires hundreds of samples, which must be analyzed quantitatively due to the heterogeneous composition of biological material. Therefore novel, fast and inexpensive methods for high throughput analysis are needed. Here we introduce a new assay based on peptide nucleic acid (PNA)-library hybridization and subsequent MALDI-TOF analysis. This method is multiplexable, allows the use of standard 384 well automated pipetting, and is more specific and flexible than established methods, such as microarrays and MS-SNuPE. The approach was used to evaluate three candidate colon cancer methylation markers previously identified in a microarray study. The methylation of the genes Ade-nomatous polyposis coli (APC), glycogen synthase kinase-beta-3 (GSK3beta) and eyes absent 4 (EYA4) was analyzed in 12 colon cancer and 12 normal tissues. APC and EYA4 were confirmed as being differentially methylated in colon cancer patients whereas GSK3beta did not show differential methylation.

Colorectal Neoplasms↗

PubMed2005

Differential DNA methylation of gene promoters in small B-cell lymphomas.

Improved care of patients with small B-cell lymphomas (SBCLs) is likely to result from the ongoing discovery of molecular markers that better define these malignant neoplasms. We identified multiple gene loci whose DNA methylation patterns differed between 3 types of SBCL: B-cell chronic lymphocytic leukemia/small lymphocytic lymphoma, mantle cell lymphoma, and grades I and II follicular lymphoma. This analysis was performed using an oligonucleotide microarray that allowed determination of the DNA methylation status of 156 loci in 38 genes. Combined bisulfite restriction analysis and methylation-specific polymerase chain reaction were used to validate the differential methylation of 6 of these genes. By using non-Hodgkin lymphoma cell lines as models, these genes were examined further for methylation and gene expression relationships. This study illustrates nonrandom epigenetic alterations in SBCLs that seem to preferentially involve lymphomas of germinal center derivation.

DNA Methylation↗

PubMed2004

DNA methylation profiling of the human major histocompatibility complex: a pilot study for the human epigenome project.

The Human Epigenome Project aims to identify, catalogue, and interpret genome-wide DNA methylation phenomena. Occurring naturally on cytosine bases at cytosine-guanine dinucleotides, DNA methylation is intimately involved in diverse biological processes and the aetiology of many diseases. Differentially methylated cytosines give rise to distinct profiles, thought to be specific for gene activity, tissue type, and disease state. The identification of such methylation variable positions will significantly improve our understanding of genome biology and our ability to diagnose disease. Here, we report the results of the pilot study for the Human Epigenome Project entailing the methylation analysis of the human major histocompatibility complex. This study involved the development of an integrated pipeline for high-throughput methylation analysis using bisulphite DNA sequencing, discovery of methylation variable positions, epigenotyping by matrix-assisted laser desorption/ionisation mass spectrometry, and development of an integrated public database available at http://www.epigenome.org. Our analysis of DNA methylation levels within the major histocompatibility complex, including regulatory exonic and intronic regions associated with 90 genes in multiple tissues and individuals, reveals a bimodal distribution of methylation profiles (i.e., the vast majority of the analysed regions were either hypo- or hypermethylated), tissue specificity, inter-individual variation, and correlation with independent gene expression data.

CpG Islands↗

PubMed2004

A real-time PCR assay for DNA-methylation using methylation-specific blockers.

DNA methylation-based biomarkers have been discovered that could potentially be used for the diagnosis of cancer by detection of circulating, tumor-derived DNA in bodily fluids. Any methylation detection assay that would be applied to these samples must be capable of detecting small amounts of tumor DNA in the presence of background normal DNA. We have developed a real-time PCR assay, called HeavyMethyl, that is well suited for this application. HeavyMethyl uses methylation-specific oligonucleotide blockers and a methylation-specific probe to achieve methylation-specific amplification and detection. We tested the assays on unmethylated and artificially methylated DNA in order to determine the limit of detection. After careful optimization, our glutathione-S-transferase pi1 and Calcitonin assays can amplify as little as 30 and 60 pg of methylated DNA, respectively, and neither assay amplifies unmethylated DNA. The Calcitonin assay showed a highly significant methylation difference between normal colon and colon adenocarcinomas, and methylation was also detected in serum DNA from colon cancer patients. These assays show that HeavyMethyl technology can be successfully employed for the analysis of very low concentrations of methylated DNA, e.g. in serum of patients with tumors.

Adenocarcinoma↗

PubMed2004

Future potential of the Human Epigenome Project.

Deciphering the information encoded in the human genome is key for the further understanding of human biology, physiology and evolution. With the draft sequence of the human genome completed, elucidation of the epigenetic information layer of the human genome becomes accessible. Epigenetic mechanisms are mediated by either chemical modifications of the DNA itself or by modifications of proteins that are closely associated with DNA. Defects of the epigenetic regulation involved in processes such as imprinting, X chromosome inactivation, transcriptional control of genes, as well as mutations affecting DNA methylation enzymes, contribute fundamentally to the etiology of many human diseases. Headed by the Human Epigenome Consortium, the Human Epigenome Project is a joint effort by an international collaboration that aims to identify, catalog and interpret genome-wide DNA methylation patterns of all human genes in all major tissues. Methylation variable positions are thought to reflect gene activity, tissue type and disease state, and are useful epigenetic markers revealing the dynamic state of the genome. Like single nucleotide polymorphisms, methylation variable positions will greatly advance our ability to elucidate and diagnose the molecular basis of human diseases.

CpG Islands↗

PubMed2003

The androgen receptor gene is preferentially hypermethylated in follicular non-Hodgkin's lymphomas.

This investigation examined promoter DNA methylation of the androgen receptor (AR) gene in non-Hodgkin's lymphoma (NHL) representing different stages of B-cell differentiation. Steroid hormones are important endocrine messengers with a broad range of physiological functions, including regulation of B-cell lymphopoiesis. Some of these effects are mediated via specific receptors such as AR that can act as a ligand-dependent transcription factor for other genes. DNA was isolated from 76 NHL specimens representing pregerminal center, germinal center, and postgerminal center states of differentiation. Initial methylation data were obtained from oligonucleotide microarrays and was confirmed and extended using methylation-specific PCR. Methylation of the AR gene promoter was present in a nonrandom pattern. Those tumors derived from pregerminal center or postgerminal center stages showed virtually no methylation and expressed AR mRNA. Cases of germinal center origin, mainly follicular lymphomas and some diffuse large B-cell lymphomas, showed hypermethylation. Studies with NHL cell lines revealed that demethylation or reversal of histone deacetylation partially restored AR expression but reversal of both simultaneously provided a synergistic release from suppression. Promoter methylation of AR occurs in a differentiation stage-selective manner; those cases arising in the germinal center are preferentially methylated. Full re-expression of AR requires both demethylation and reacetylation, a finding that may affect treatment decisions.

Cell Line, Tumor↗

PubMed2003

Analysis and accurate quantification of CpG methylation by MALDI mass spectrometry.

As the DNA sequence of the human genome is now nearly finished, the main task of genome research is to elucidate gene function and regulation. DNA methylation is of particular importance for gene regulation and is strongly implicated in the development of cancer. Even minor changes in the degree of methylation can have severe consequences. An accurate quantification of the methylation status at any given position of the genome is a powerful diagnostic indicator. Here we present the first assay for the analysis and precise quantification of methylation on CpG positions in simplex and multiplex reactions based on matrix-assisted laser desorption/ ionisation mass spectrometry detection. Calibration curves for CpGs in two genes were established and an algorithm was developed to account for systematic fluctuations. Regression analysis gave R(2) >or= 0.99 and standard deviation around 2% for the different positions. The limit of detection was approximately 5% for the minor isomer. Calibrations showed no significant differences when carried out as simplex or multiplex analyses. All variable parameters were thoroughly investigated, several paraffin-embedded tissue biopsies were analysed and results were verified by established methods like analysis of cloned material. Mass spectrometric results were also compared to chip hybridisation.

Base Sequence↗

PubMed2002

Tumour class prediction and discovery by microarray-based DNA methylation analysis.

Aberrant DNA methylation of CpG sites is among the earliest and most frequent alterations in cancer. Several studies suggest that aberrant methylation occurs in a tumour type-specific manner. However, large-scale analysis of candidate genes has so far been hampered by the lack of high throughput assays for methylation detection. We have developed the first microarray-based technique which allows genome-wide assessment of selected CpG dinucleotides as well as quantification of methylation at each site. Several hundred CpG sites were screened in 76 samples from four different human tumour types and corresponding healthy controls. Discriminative CpG dinucleotides were identified for different tissue type distinctions and used to predict the tumour class of as yet unknown samples with high accuracy using machine learning techniques. Some CpG dinucleotides correlate with progression to malignancy, whereas others are methylated in a tissue-specific manner independent of malignancy. Our results demonstrate that genome-wide analysis of methylation patterns combined with supervised and unsupervised machine learning techniques constitute a powerful novel tool to classify human cancers.

Algorithms↗