The cellular ratio of immune tolerance (immunoCRIT) is a definite marker for aggressiveness of solid tumors and may explain tumor dissemination patterns.

The adaptive immune system is involved in tumor establishment and aggressiveness. Tumors of the ovaries, an immune-privileged organ, spread via transceolomic routes and rarely to distant organs. This is contrary to tumors of non-immune privileged organs, which often disseminate hematogenously to distant organs. Epigenetics-based immune cell quantification allows direct comparison of the immune status in benign and malignant tissues and in blood. Here, we introduce the "cellular ratio of immune tolerance" (immunoCRIT) as defined by the ratio of regulatory T cells to total T lymphocytes. The immunoCRIT was analyzed on 273 benign tissue samples of colorectal, bronchial, renal and ovarian origin as well as in 808 samples from primary colorectal, bronchial, mammary and ovarian cancers. ImmunoCRIT is strongly increased in all cancerous tissues and gradually augmented strictly dependent on tumor aggressiveness. In peripheral blood of ovarian cancer patients, immunoCRIT incrementally increases from primary diagnosis to disease recurrence, at which distant metastases frequently occur. We postulate that non-pathological immunoCRIT values observed in peripheral blood of immune privileged ovarian tumor patients are sufficient to prevent hematogenous spread at primary diagnosis. Contrarily, non-immune privileged tumors establish high immunoCRIT in an immunological environment equivalent to the bloodstream and thus spread hematogenously to distant organs. In summary, our data suggest that the immunoCRIT is a powerful marker for tumor aggressiveness and disease dissemination.

Association of DNA methylation of phosphoserine aminotransferase with response to endocrine therapy in patients with recurrent breast cancer.

To understand the biological basis of resistance to endocrine therapy is of utmost importance in patients with steroid hormone receptor-positive breast cancer. Not only will this allow us prediction of therapy success, it may also lead to novel therapies for patients resistant to current endocrine therapy. DNA methylation in the promoter regions of genes is a prominent epigenetic gene silencing mechanism that contributes to breast cancer biology. In the current study, we investigated whether promoter DNA methylation could be associated with resistance to endocrine therapy in patients with recurrent breast cancer. Using a microarray-based technology, the promoter DNA methylation status of 117 candidate genes was studied in a cohort of 200 steroid hormone receptor-positive tumors of patients who received the antiestrogen tamoxifen as first-line treatment for recurrent breast cancer. Of the genes analyzed, the promoter DNA methylation status of 10 genes was significantly associated with clinical outcome of tamoxifen therapy. The association of the promoter hypermethylation of the strongest marker, phosphoserine aminotransferase (PSAT1) with favorable clinical outcome was confirmed by an independent quantitative DNA methylation detection method. Furthermore, the extent of DNA methylation of PSAT1 was inversely associated with its expression at the mRNA level. Finally, also at the mRNA level, PSAT1 was a predictor of tamoxifen therapy response. Concluding, our work indicates that promoter hypermethylation and mRNA expression of PSAT1 are indicators of response to tamoxifen-based endocrine therapy in steroid hormone receptor-positive patients with recurrent breast cancer.

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.

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.

Oligonucleotide-based microarray for DNA methylation analysis: principles and applications.

Gene silencing via promoter CpG island hypermethylation offers tumor cells growth advantages. This epigenetic event is pharmacologically reversible, and uncovering a unique set of methylation-silenced genes in tumor cells can bring a new avenue to cancer treatment. However, high-throughput tools capable of surveying the methylation status of multiple gene promoters are needed for this discovery process. Herein we describe an oligonucleotide-based microarray technique that is both versatile and sensitive in revealing hypermethylation in defined regions of the genome. DNA samples are bisulfite-treated and PCR-amplified to distinguish CpG dinucleotides that are methylated from those that are not. Fluorescently labeled PCR products are hybridized to arrayed oligonucleotides that can discriminate between methylated and unmethylated alleles in regions of interest. Using this technique, two clinical subtypes of non-Hodgkin's lymphomas, mantle cell lymphoma, and grades I/II follicular lymphoma, were further separated based on the differential methylation profiles of several gene promoters. Work is underway in our laboratory to extend the interrogation power of this microarray system in multiple candidate genes. This novel tool, therefore, holds promise to monitor the outcome of various epigenetic therapies on cancer patients.

Diabetes: a candidate disease for efficient DNA methylation profiling.

Methylation has been implied in a number of biological processes and has been shown to vary under environmental influences as well as in age. Most results on the correlation of methylation patterns with phenotypic characteristics of cells have been obtained by analysis of very few or even single genomic fragments for methylation. However, variation of methylation may more often than not be a phenomenon that affects multiple genomic loci. The role of methylation has been most conclusively demonstrated in complex disease, with cancer being the most prominent example. The influence of aging and environmental influences such as diet seems to be on global methylation patterns, in turn exerting local effects on groups of genes. Hence, methylation seems literally to be orchestrating complex genetic systems. It could, therefore, be considered an archetypal "genomics" parameter. In consequence, technologies used to analyze methylation patterns should be as industrialized as possible to capture the local events across the entire genome. Epigenomics' research team is the first to have achieved the industrialized production of genome sequence-specific wide methylation data. Our microarray and mass-spectrometry-based detection platform currently allow the analysis of up to 50,000 methylation positions per day, for the first time making methylation data amenable to sophisticated information mining. The information content of methylation position has never been analyzed using the high-dimensional statistical methods that are recognized to be required for the analysis of, for example, mRNA expression profiles or proteomic data. As methylation patterns are nothing but a quasi-digital form of expression data, their information content must be evaluated using similar but adapted algorithms. This article presents a broad set of studies that demonstrate that methylation yields information that is comparable or even superior to the current state of the art, namely, mRNA profiling. We argue that the resulting robust, digital and-because of the highly stable nature of DNA as the analyte-more reproducible information could become the "gold standard" for clinical diagnostics and disease gene identification in age-related, environmentally influenced and epigenetic disease in general, substituting for mRNA expression.

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.