Victor V. Levenson

Differential methylation of cell‐free circulating DNA among patients with pancreatic cancer versus chronic pancreatitis

Although patients with chronic pancreatitis (CP) have an increased risk of pancreatic cancer (PanCa), the timely detection of PanCa often is difficult, because the symptoms of CP and PanCa are very similar. Moreover, secondary inflammation may be identified in PanCa, further complicating diagnosis. To improve the survival of patients with PanCa, a reliable test to differentiate CP from PanCa is needed. In this article, the authors describe a methylation profile of cell‐free plasma DNA that distinguished CP from PanCa with >90% accuracy.

DNA methylation as a universal biomarker

Cell-free circulating DNA carries not only tumor-specific changes in its sequence but also distinctive epigenetic marks, namely DNA methylation, in certain GC-rich fragments. These fragments are usually located within the promoters and first exons of many genes, comprising CpG islands. Analysis of DNA methylation using cell-free circulating DNA can facilitate development of very accurate biomarkers for detection, diagnosis, prediction of response to therapy and prognosis of outcomes. Recent data suggest that benign and inflammatory diseases have very specific methylation patterns within cell-free circulating DNA, which are different from the pattern of a malignant tumor of the same organ. In addition, specific methylation patterns have been detected for cancers of different organs, so a differential diagnosis of site-specific cancer appears feasible. Currently, cancer-related applications dominate the field, although methylation-based biomarkers may also be possible for other diseases, including neurodegenerative and psychiatric disorders.

MSRE-PCR for analysis of gene-specific DNA methylation.

Abnormal DNA methylation is observed in certain promoters of neoplastic cells, although the likelihood of methylation for each individual promoter varies. Simultaneous analysis of many promoters in the same sample can allow use of statistical methods for identification of neoplasia. Here we describe an assay for such analysis, based on digestion of genomic DNA with methylation-sensitive restriction enzyme and multiplexed PCR with gene-specific primers (MSRE-PCR). MSRE-PCR includes extensive digestion of genomic DNA (uncut fragments cannot be identified by PCR), can be applied to dilute samples (<1 pg/μl), requires limited amount of starting material (42 pg or genomic equivalent of seven cells) and can identify methylation in a heterogeneous mix containing <2% of cells with methylated fragments. When applied to 53 promoters of breast cancer cell lines MCF-7, MDA-MB-231 and T47D, MSRE-PCR correctly identified the methylation status of genes analyzed by other techniques. For selected genes results of MSRE-PCR were confirmed by methylation-specific PCR and bisulfite sequencing. The assay can be configured for any number of desired targets in any user-defined set of genes.

Methylation patterns of cell-free plasma DNA in relapsing-remitting multiple sclerosis

BACKGROUND There is growing interest for identification of new targets for biomarker development in multiple sclerosis (MS). The goal of this study was to compare the concentration and the methylation patterns of cell-free plasma DNA (cfpDNA) in patients with relapsing-remitting multiple sclerosis (RRMS) and healthy individuals. METHODS Three 30-patient cohorts were examined: patients with RRMS, in either remission or exacerbation, and healthy individuals as controls. Concentration of cfpDNA was determined using a standard fluorometric assay. Patterns of methylation in 56 gene promoters were determined by a microarray-based assay (MethDet-56). The data were analyzed to identify statistically relevant differences among the study groups. RESULTS The concentration of cfpDNA in patients with RRMS was four to eight-fold higher compared to healthy controls. Significant differences in cfpDNA methylation patterns were detected in all three comparisons: RRMS patients in remission versus healthy controls were recognized with 79.2% sensitivity and 92.9% specificity; RRMS patients in exacerbation versus healthy controls were recognized with 75.9% sensitivity and 91.5% specificity; and RRMS patients in exacerbation versus those in remission were recognized with 70.8% sensitivity and 71.2% specificity. CONCLUSION Based on our findings, we conclude that patients with RRMS display unique disease- and state-specific changes of cfpDNA. Our findings are of clinical significance as they could be used in the development of potentially new biomarkers for MS. This is the first report in our knowledge describing such changes of cfpDNA in patients with MS.

Differential Methylation Profile of Ovarian Cancer in Tissues and Plasma

An accurate biomarker for detection of ovarian cancer may reduce cancer-related mortality. Using a previously developed microarray-based technique, we evaluated differences in DNA methylation profiles in a panel of 56 genes using sections of serous papillary adenocarcinomas and uninvolved ovaries (n=30) from women in a high-risk group. Methylation profiles were also generated for circulating DNA from blood of patients (n=33) and healthy controls (n=33). Using the most differentially methylated genes for naïve Bayesian analysis, we identified ten of these profiles as potentially informative in tissues. Various combinations of these genes produced 69% sensitivity and 70% specificity for cancer detection as estimated under a stratified, fivefold cross-validation protocol. In plasma, five genes were identified as informative; their combination had 85% sensitivity and 61% specificity for cancer detection. These results suggest that differential methylation profiling in heterogeneous samples has the potential to identify components of a composite biomarker that may detect ovarian cancer in blood with significant accuracy.

Distinctive DNA methylation patterns of cell-free plasma DNA in women with malignant ovarian tumors

OBJECTIVE Epithelial ovarian carcinoma (OvCa) is rarely detected early, and it is also difficult to determine whether an adnexal mass is benign or malignant. Previously, we noted differences in methylation patterns of cell-free plasma DNA (cfpDNA) in women without disease compared to patients with OvCa. In this work, we investigated whether methylation patterns of cfpDNA can differentiate between benign and malignant tumors. METHODS Methylation patterns in cfpDNA were determined in three cohorts (30 samples each) using a microarray-based assay (MethDet 56). Principal component analysis, supervised clustering, linear discrimination analysis, and 25 rounds of 5-fold cross-validation were used to determine informative genes and assess the sensitivity and specificity of differentiating between OvCa vs. healthy control (HC), benign ovarian disease (mostly serous cystadenoma, BOD) vs. HC, and OvCa vs. BOD samples. RESULTS Differential methylation of three promoters (RASSF1A, CALCA, and EP300) differentiated between OvCa vs. HC with a sensitivity of 90.0% and a specificity of 86.7%. Three different promoters (BRCA1, CALCA, and CDKN1C) were informative for differentiating between BOD vs. HC, with a sensitivity of 90.0% and a specificity of 76.7%. Finally, two promoters (RASSF1A and PGR-PROX) were informative for differentiating between OvCa vs. BOD, with a sensitivity of 80.0% and a specificity of 73.3%. CONCLUSIONS This proof-of-principle data show that differential methylation of promoters in cfpDNA may be a useful biomarker to differentiate between certain benign and malignant ovarian tumors.

Methylation profile of circulating plasma DNA in patients with pancreatic cancer.

Detection of pancreatic cancer by blood‐based test may improve outcomes. We sought to establish the feasibility of a blood‐based detection of pancreatic cancer through multiplexed array‐mediated analysis of DNA methylation.

DNA methylation patterns in blood of patients with colorectal cancer and adenomatous colorectal polyps

Colorectal cancer (CRC) screening rates are currently suboptimal. Blood‐based screening could improve rates of earlier detection for CRC and adenomatous colorectal polyps. In this study, we evaluated the feasibility of plasma‐based detection of early CRC and adenomatous polyps using array‐mediated analysis methylation profiling of 56 genes implicated in carcinogenesis. Methylation of 56 genes in patients with Stages I and II CRC (N = 30) and those with adenomatous polyps (N = 30) were compared with individuals who underwent colonoscopy and were found to have neither adenomatous changes nor CRC. Composite biomarkers were developed for adenomatous polyps and CRC, and their sensitivity and specificity was estimated using five‐fold cross validation. Six promoters (CYCD2, HIC1, PAX 5, RASSF1A, RB1 and SRBC) were selected for the biomarker, which differentiated CRC patients and controls with 84% sensitivity and 68% specificity. Three promoters (HIC1, MDG1 and RASSF1A) were selected for the biomarker, which differentiated patients with adenomatous polyps and controls with sensitivity of 55% and specificity of 65%. Methylation profiling of plasma DNA can detect early CRC with significant accuracy and shows promise as a methodology to develop biomarkers for CRC screening.

CpG Methylation Analysis—Current Status of Clinical Assays and Potential Applications in Molecular Diagnostics: A Report of the Association for Molecular Pathology

Methylation of CpG islands in gene promoter regions is a major molecular mechanism of gene silencing and underlies both cancer development and progression. In molecular oncology, testing for the CpG methylation of tissue DNA has emerged as a clinically useful tool for tumor detection, outcome prediction, and treatment selection, as well as for assessing the efficacy of treatment with the use of demethylating agents and monitoring for tumor recurrence. In addition, because CpG methylation occurs early in pre-neoplastic tissues, methylation tests may be useful as markers of cancer risk in patients with either infectious or inflammatory conditions. The Methylation Working Group of the Clinical Practice Committee of the Association of Molecular Pathology has reviewed the current state of clinical testing in this area. We report here our summary of both the advantages and disadvantages of various methods, as well as the needs for standardization and reporting. We then conclude by summarizing the most promising areas for future clinical testing in cancer molecular diagnostics.

DNA Methylation as Clinically Useful Biomarkers—Light at the End of the Tunnel

A recent expansion of our knowledge about epigenetic changes strongly suggests that epigenetic rather than genetic features better reflect disease development, and consequently, can become more conclusive biomarkers for the detection and diagnosis of different diseases. In this paper we will concentrate on the current advances in DNA methylation studies that demonstrate a direct link between abnormal DNA methylation and a disease. This link can be used to develop diagnostic biomarkers that will precisely identify a particular disease. It also appears that disease-specific DNA methylation patterns undergo unique changes in response to treatment with a particular drug, thus raising the possibility of DNA methylation-based biomarkers for the monitoring of treatment efficacy, for prediction of response to treatment, and for the prognosis of outcome. While biomarkers for oncology are the most obvious applications, other fields of medicine are likely to benefit as well. This potential is demonstrated by DNA methylation-based biomarkers for neurological and psychiatric diseases. A special requirement for a biomarker is the possibility of longitudinal testing. In this regard cell-free circulating DNA from blood is especially interesting because it carries methylation markers specific for a particular disease. Although only a few DNA methylation-based biomarkers have attained clinical relevance, the ongoing efforts to decipher disease-specific methylation patterns are likely to produce additional biomarkers for detection, diagnosis, and monitoring of different diseases in the near future.