Panel Of DNA Methylation Biomarkers Research Articles

Discovery of novel DNA methylation biomarker panels for the diagnosis and differentiation between common adenocarcinomas and their liver metastases

Differentiation between adenocarcinomas is sometimes challenging. The promising avenue for discovering new biomarkers lies in bioinformatics using DNA methylation analysis. Utilizing a 2853-sample identification dataset and a 782-sample independent verification dataset, we have identified diagnostic DNA methylation biomarkers that are hypermethylated in cancer and differentiate between breast invasive carcinoma, cholangiocarcinoma, colorectal cancer, hepatocellular carcinoma, lung adenocarcinoma, pancreatic adenocarcinoma and stomach adenocarcinoma. The best panels for cancer type exhibit sensitivity of 77.8–95.9%, a specificity of 92.7–97.5% for tumors, a specificity of 91.5–97.7% for tumors and normal tissues and a diagnostic accuracy of 85.3–96.4%. We have shown that the results can be extended from the primary cancers to their liver metastases, as the best panels diagnose and differentiate between pancreatic adenocarcinoma liver metastases and breast invasive carcinoma liver metastases with a sensitivity and specificity of 83.3–100% and a diagnostic accuracy of 86.8–91.9%. Moreover, the panels could detect hypermethylation of selected regions in the cell-free DNA of patients with liver metastases. At the same time, these were unmethylated in the cell-free DNA of healthy donors, confirming their applicability for liquid biopsies.

Novel DNA Methylation Biomarker Panel for Detection of Esophageal Adenocarcinoma and High-Grade Dysplasia.

Current endoscopy-based screening and surveillance programs have not been proven effective at decreasing esophageal adenocarcinoma (EAC) mortality, creating an unmet need for effective molecular tests for early detection of this highly lethal cancer. We conducted a genome-wide methylation screen to identify novel methylation markers that distinguish EAC and high-grade dysplasia (HGD) from normal squamous epithelium (SQ) or nondysplastic Barrett's esophagus (NDBE). DNA methylation profiling of samples from SQ, NDBE, HGD, and EAC was performed using HM450 methylation arrays (Illumina) and reduced-representation bisulfate sequencing. Ultrasensitive methylation-specific droplet digital PCR and next-generation sequencing (NGS)-based bisulfite-sequencing assays were developed to detect the methylation level of candidate CpGs in independent esophageal biopsy and endoscopic brushing samples. Five candidate methylation markers were significantly hypermethylated in HGD/EAC samples compared with SQ or NDBE (P < 0.01) in both esophageal biopsy and endoscopic brushing samples. In an independent set of brushing samples used to construct biomarker panels, a four-marker panel (model 1) demonstrated sensitivity of 85.0% and 90.8% for HGD and EACs respectively, with 84.2% and 97.9% specificity for NDBE and SQ respectively. In a validation set of brushing samples, the panel achieved sensitivity of 80% and 82.5% for HGD and EAC respectively, at specificity of 67.6% and 96.3% for NDBE and SQ samples. A novel DNA methylation marker panel differentiates HGD/EAC from SQ/NDBE. DNA-methylation-based molecular assays hold promise for the detection of HGD/EAC using esophageal brushing samples.

DNA Hypermethylation af a Panel Of Genes as an Urinary Biomarker For Bladder Cancer Diagnosis.

Several studies have shown frequent changes in DNA methylation in bladder cancer (BCa), which vary among different geographical areas. The aim of this study is to examine the diagnostic accuracy of a panel of DNA methylation biomarkers in a Greek clinical setting contributing to the development of a universal panel of urine biomarkers. Individuals with primary BCa and control individuals matching the gender, age and smoking status of the cancer patients were recruited. DNA methylation was assessed for the gene promoters of RASSF1, RARB, DAPK, TERT and APC in urine samples collected by spontaneous urination using quantitative Methylation Specific PCR (qMSP). All genes had been previously separately associated with BCa. Fifty patients and 35 healthy controls were recruited, with average age of 70.26 years and average smoking status of 44.78 pack-years. In the BCa group, DNA methylation was detected in 27 (61.4%) samples. RASSF1 was methylated in 52.2% of samples. Only 3 (13.6%) samples from the control group were methylated, all in the RASSF1 gene promoter. The specificity and sensitivity of this panel of genes to diagnose BCa was 86% and 61% respectively. The RASSF1 gene could diagnose BCa with specificity 86.4% and sensitivity 52.3%. Promoter DNA methylation of this panel of five genes could be further investigated as urine biomarker for the diagnosis of BCa. The RASSF1 could be a single candidate biomarker for predicting BCa patients versus controls. Studies are required in order to develop a geographically adjusted diagnostic biomarker for BCa.

A panel of DNA methylation biomarkers for detection and improving diagnostic efficiency of lung cancer

Lung cancer remains the leading cause of cancer deaths worldwide. Although low-dose spiral computed tomography (LDCT) screening is used for the detection of lung cancer in a high-risk population, false-positive results of LDCT remain a clinical problem. Here, we developed a blood test of a novel panel of three established lung cancer methylation biomarkers for lung cancer detection. Short stature homeobox 2 gene (SHOX2), ras association domain family 1A gene (RASSF1A), and prostaglandin E receptor 4 gene (PTGER4) methylation was analyzed in a training cohort of 351 individuals (197 controls, 154 cases) and validated from an independent cohort of 149 subjects (89 controls, 60 cases). The novel panel biomarkers distinguished between malignant and benign lung disease at high sensitivity and specificity: 87.0% sensitivity [95% CI 80.2–91.5%], 98.0% specificity [95% CI 94.9–99.4%]. Sensitivity in adenocarcinoma, squamous cell carcinoma, small cell lung cancer, and other lung cancer was 89.0%, 87.5%, 85.7%, and 77.8%, respectively. Notably, cancer patients in stage I and II showed high diagnostic sensitivity at 82.5% and 90.5%, respectively. Moreover, the diagnostic efficiency did not show bias toward age, gender, smoking, and the presence of other (nonlung) cancers. The performance of the panel in the validation cohort confirmed the diagnostic value. These findings clearly showed that this panel of DNA methylation biomarkers was effective in detecting lung cancer noninvasively and may provide clinical utility in stand-alone or in combination with current imaging techniques to improve the diagnosis of lung cancer.

MethPanel: a parallel pipeline and interactive analysis tool for multiplex bisulphite PCR sequencing to assess DNA methylation biomarker panels for disease detection.

SummaryDNA methylation patterns in a cell are associated with gene expression and the phenotype of a cell, including disease states. Bisulphite PCR sequencing is commonly used to assess the methylation profile of genomic regions between different cells. Here we have developed MethPanel, a computational pipeline with an interactive graphical interface to rapidly analyse multiplex bisulphite PCR sequencing data. MethPanel comprises a complete analysis workflow from genomic alignment to DNA methylation calling and supports an unlimited number of PCR amplicons and input samples. MethPanel offers important and unique features, such as calculation of an epipolymorphism score and bisulphite PCR bias correction capabilities, and is designed so that the methylation data from all samples can be processed in parallel. The outputs are automatically forwarded to a shinyApp for convenient display, visualization and remotely sharing data with collaborators and clinicians.Availabilityand implementationMethPanel is freely available at https://github.com/thinhong/MethPanel.Supplementary informationSupplementary data are available at Bioinformatics online.

A panel of DNA methylation signature from peripheral blood may predict colorectal cancer susceptibility

BackgroundDifferential DNA methylation panel derived from peripheral blood could serve as biomarkers of CRC susceptibility. However, most of the previous studies utilized post-diagnostic blood DNA which may be markers of disease rather than susceptibility. In addition, only a few studies have evaluated the predictive potential of differential DNA methylation in CRC in a prospective cohort and on a genome-wide basis. The aim of this study was to identify a potential panel of DNA methylation biomarkers in peripheral blood that is associated with CRC risk and therefore serve as epigenetic biomarkers of disease susceptibility.MethodsDNA methylation profile of a nested case-control study with 166 CRC and 424 healthy normal subjects were obtained from the Gene Expression Omnibus (GEO) database. The differentially methylated markers were identified by moderated t-statistics. The DNA methylation panel was constructed by stepwise logistic regression and the least absolute shrinkage and selection operator in the training dataset. A methylation risk score (MRS) model was constructed and the association between MRS and CRC risk assessed.ResultsWe identified 48 differentially methylated CpGs sites, of which 33 were hypomethylated. Of these, sixteen-CpG based MRS that was associated with CRC risk (OR = 2.68, 95% CI: 2.13, 3.38, P < 0.0001) was constructed. This association is confirmed in the testing dataset (OR = 2.02, 95% CI: 1.48, 2.74, P < 0.0001) and persisted in both males and females, younger and older subjects, short and long time-to-diagnosis. The MRS also predicted CRC with AUC 0.82 (95% CI: 0.76, 0.88), indicating high accuracy.ConclusionsOur study has identified a novel DNA methylation panel that is associated with CRC and could, if validated be useful for the prediction of CRC risk in the future.

Comprehensive evaluation of targeted multiplex bisulphite PCR sequencing for validation of DNA methylation biomarker panels

BackgroundDNA methylation is a well-studied epigenetic mark that is frequently altered in diseases such as cancer, where specific changes are known to reflect the type and severity of the disease. Therefore, there is a growing interest in assessing the clinical utility of DNA methylation as a biomarker for diagnosing disease and guiding treatment. The development of an accurate loci-specific methylation assay, suitable for use on low-input clinical material, is crucial for advancing DNA methylation biomarkers into a clinical setting. A targeted multiplex bisulphite PCR sequencing approach meets these needs by allowing multiple DNA methylated regions to be interrogated simultaneously in one experiment on limited clinical material.ResultsHere, we provide an updated protocol and recommendations for multiplex bisulphite PCR sequencing (MBPS) assays for target DNA methylation analysis. We describe additional steps to improve performance and reliability: (1) pre-sequencing PCR optimisation which includes assessing the optimal PCR cycling temperature and primer concentration and (2) post-sequencing PCR optimisation to achieve uniform coverage of each amplicon. We use a gradient of methylated controls to demonstrate how PCR bias can be assessed and corrected. Methylated controls also allow assessment of the sensitivity of methylation detection for each amplicon. Here, we show that the MBPS assay can amplify as little as 0.625 ng starting DNA and can detect methylation differences of 1% with a sequencing coverage of 1000 reads. Furthermore, the multiplex bisulphite PCR assay can comprehensively interrogate multiple regions on 1–5 ng of formalin-fixed paraffin-embedded DNA or circulating cell-free DNA.ConclusionsThe MBPS assay is a valuable approach for assessing methylated DNA regions in clinical samples with limited material. The optimisation and additional quality control steps described here improve the performance and reliability of this method, advancing it towards potential clinical applications in biomarker studies.

A Diagnostic Panel of DNA Methylation Biomarkers for Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) is one of the most common cancers and lethal diseases in the world. Recognition of the undetermined lung nodules at an early stage is useful for a favorable prognosis. However, there is no good method to identify the undetermined lung nodules and predict their clinical outcome. DNA methylation alteration is frequently observed in LUAD and may play important roles in carcinogenesis, diagnosis, and prediction. This study took advantage of publicly available methylation profiling resources and a machine learning method to investigate methylation differences between LUAD and adjacent non-malignant tissue. The prediction panel was first constructed using 338 tissue samples from LUAD patients including 149 non-malignant ones. This model was then validated with data from The Cancer Genome Atlas database and clinic samples. As a result, the methylation status of four CpG loci in homeobox A9 (HOXA9), keratin-associated protein 8-1 (KRTAP8-1), cyclin D1 (CCND1), and tubby-like protein 2 (TULP2) were highlighted as informative markers. A random forest classification model with an accuracy of 94.57% and kappa of 88.96% was obtained. To evaluate this panel for LUAD, the methylation levels of four CpG loci in HOXA9, KRTAP8-1, CCND1, and TULP2 of tumor samples and matched adjacent lung samples from 25 patients with LUAD were tested. In these LUAD patients, the methylation of HOXA9 was significantly upregulated, whereas the methylation of KRTAP8-1, CCND1, and TULP2 were downregulated obviously in tumor samples compared with adjacent tissues. Our study demonstrates that the methylation of HOXA9, KRTAP8-1, CCND1, and TULP2 has great potential for the early recognition of LUAD in the undetermined lung nodules. The findings also exhibit that the application of improved mathematic algorithms can yield accurate and particularly robust and widely applicable marker panels. This approach could greatly facilitate the discovery process of biomarkers in various fields.

PO-091 Droplet digital PCR based detection of aberrantly methylated genes in bile identifies cholangiocarcinoma in patients with primary sclerosing cholangitis

IntroductionPatients with primary sclerosing cholangitis (PSC) have up to 20% lifetime risk of developing cholangiocarcinomas (CCAs). Identifying CCA in patients with PSC is, however, complicated and current strategies are suffering from low sensitivity. Consequently, the majority of patients are diagnosed at an advanced, incurable stage of disease, highlighting the need for novel detection methods, which could qualify more patients for curative treatment. In the current study, we aimed at establishing a robust DNA methylation biomarker panel in bile for improved detection of CCA.Material and methodsMore than 300 bile samples (100 µl) from patients with PSC, CCA with and without PSC, and other non-malignant liver diseases were collected during endoscopic retrograde cholangiopancreatography or liver transplantation. All samples were analysed for promoter methylation of selected markers, using highly sensitive droplet digital PCR (ddPCR). In each reaction, an in-house 4-marker control assay was included for normalisation, and an algorithm for automated threshold determination, PoDCall, was applied for increased precision (Pharo et al, Clinical Epigenetics 2018).Results and discussionsPreliminary results indicate that the DNA methylation biomarkers have high accuracy for identifying CCA, particularly among patients with PSC. Interestingly, the markers were able to detect 5/8 PSC patients that later developed CCA, and that were not detected by standard diagnostic tools.ConclusionBy using highly sensitive ddPCR based technology and a robust DNA methylation biomarker panel, CCA can be accurately detected in small volumes of bile from patients with PSC.

Genome-wide DNA methylation profiling reveals novel epigenetic signatures in squamous cell lung cancer

BackgroundEpigenetic alterations are strongly associated with the development of cancer. The aim of this study was to identify epigenetic pattern in squamous cell lung cancer (LUSC) on a genome-wide scale.ResultsHere we performed DNA methylation profiling on 24 LUSC and paired non-tumor lung (NTL) tissues by Illumina Human Methylation 450 K BeadArrays, and identified 5214 differentially methylated probes. By integrating DNA methylation and mRNA expression data, 449 aberrantly methylated genes accompanied with altered expression were identified. Ingenuity Pathway analysis highlighted these genes which were closely related to the carcinogenesis of LUSC, such as ERK family, NFKB signaling pathway, Hedgehog signaling pathway, providing new clues for understanding the molecular mechanisms of LUSC pathogenesis. To verify the results of high-throughput screening, we used 56 paired independent tissues for clinical validation by pyrosequencing. Subsequently, another 343 tumor tissues from the Cancer Genome Atlas (TCGA) database were utilized for further validation. Then, we identified a panel of DNA methylation biomarkers (CLDN1, TP63, TBX5, TCF21, ADHFE1 and HNF1B) in LUSC. Furthermore, we performed receiver operating characteristics (ROC) analysis to assess the performance of biomarkers individually, suggesting that they could be suitable as potential diagnostic biomarkers for LUSC. Moreover, hierarchical clustering analysis of the DNA methylation data identified two tumor subgroups, one of which showed increased DNA methylation.ConclusionsCollectively, these results suggest that DNA methylation plays critical roles in lung tumorigenesis and may potentially be proposed as a diagnostic biomarker.Trial registrationChiCTR-RCC-12002830 Date of registration: 2012–12-17.

Abstract LB-247: Early detection of gastric cancer using global and gene-specific promoter DNA methylation in endoscopic biopsies

Abstract Clinically useful molecular tools to triage gastric cancer patients are not currently available. We aimed to develop a molecular tool to predict gastric cancer risk in endoscopy-driven biopsies obtained from high-risk gastric cancer clinics in low resource settings. We discovered and validated a DNA methylation biomarker panel in endoscopic samples obtained from 362 patients seen between 2004 and 2009 in three high-risk gastric cancer clinics in Lima, Perú, and validated it in 306 samples from the Cancer Genome Atlas project (“TCGA”). Global, genome wide and gene-specific DNA methylation analyses were used in a Phase I Biomarker Development Trial to identify a continuous biomarker panel that combines a Global DNA Methylation Index (GDMI) and promoter DNA methylation levels of IRF4, ELMO1, CLIP4 and MSC. We observed an inverse association between the GDMI and histological progression to gastric cancer, when comparing gastritis patients without metaplasia (mean= 5.74, 95% CI, 4.97-6.50), gastritis patients with metaplasia (mean= 4.81, 95% CI, 3.77-5.84), and gastric cancer cases (mean=3.38, 95% CI, 2.82-3.94), respectively (p&amp;lt;0.0001). Promoter methylation of IRF4 (p &amp;lt;0.0001), ELMO1 (p &amp;lt;0.0001), CLIP4 (p &amp;lt;0.0001), and MSC (p &amp;lt;0.0001), is also associated with increasing severity from gastritis with no metaplasia to gastritis with metaplasia and gastric cancer. Our findings suggest that promoter methylation of IRF4, ELMO1, CLIP4 and MSC and a GDMI &amp;gt; 4, is a useful molecular tool for gastric cancer risk stratification in endoscopic biopsies. Citation Format: Francesca Pirini, Sassan Noazin, Martha Jahuira Arias, Sebastian Rodriguez-Torres, Leah Friess, Christina Michailidi, Jaime Cok, Juan Combe, Goria Vargas, William Prado, Ethan Soudry, Jimena Perez, Tikki Yudin, Andrea Mancinelli, Helen Unger, Carmen Ili, Priscilla Brebi, Douglas Berg, Masamichi Hayashi, David Sidransky, Robert Gilman, Rafael E. Guerrero-Preston. Early detection of gastric cancer using global and gene-specific promoter DNA methylation in endoscopic biopsies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-247. doi:10.1158/1538-7445.AM2017-LB-247

Improved Noninvasive Bladder Cancer Diagnosis using Urine Sediments and Novel DNA Methylation Biomarker Panels.

Aberrant DNA methylation status early in carcinogenesis represents a potential indicator of tumor detection. We would like to establish a DNA methylation biomarker panel for bladder cancer detection in the research. Seven candidate genes with known cancer associations were selected for this study. The DNA methylation status of the candidate genes was analyzed by methylation-specific polymerase chain reaction assays to evaluate the relationship between bladder cancer and target gene methylation status in the urine sediments of participants. 112 bladder cancer patients, 10 healthy volunteers, and 17 glandular cystitis patients were enrolled. There were significant differences in the methylation status of p14ARF, RUNX3, RARβ, DAPK, and HPP1 between the healthy control, glandular cystitis, and bladder cancer groups (p = 0.027, p < 0.001, p < 0.001, p = 0.030 and p = 0.003, respectively). A panel composed of all five genes with significant methylation differences yielded an area under the receiver-operating characteristic curve (AUC) of 0.936 and had 98.21% sensitivity and 88.89% specificity, while a panel using just two of these genes (RUNX3 and RARP) yielded an AUC of 0.918 with 96.64% sensitivity and 88.89% specificity. Another panel of two genes (p14ARF and HPP1) had 100% specificity, but an AUC of 0.688 and 37.50% sensitivity. Using the urine of bladder cancer patients and healthy controls, we assessed several novel DNA methylation biomarker panels that demonstrated good bladder cancer detection capability. Based on the results of this study we recommend the RUNX3 and RARβ panel as the first choice for bladder cancer detection. In suspicious or difficult to diagnose cases, the p14ARF and HPP1 panel could be used as an additional diagnostic tool due to its high specificity.

PD46-07 URINARY DNA METHYLATION BIOMARKERS: A NON-INVASIVE METHOD FOR PROSTATE CANCER MONITORING

INTRODUCTION AND OBJECTIVES: The majority of men with prostate cancer (PCa) are diagnosed with low-risk disease given effective PSA screening. To avoid over-treatment, men with low-risk PCa are encouraged to be followed on an Active Surveillance (AS) protocol in which repeated blood tests, digital rectal examinations (DRE) and prostate biopsies are utilized to monitor disease progression. Aberrant DNA methylation is a common feature in a variety of tumours. Tumour-specific gene methylation would be an ideal biomarker since only minute amounts of DNA are required which could be extracted from post-DRE urine samples, thus being a much less invasive method for PCa screening as compared to frequent biopsies. Our group previously identified and validated a panel of DNA methylation biomarkers that predicted the presence of high risk disease and/or post treatment biochemical recurrence in radical prostatectomy samples. In the current study, we investigated if this same panel of biomarkers can be detected in post-DRE urine samples of PCa patients participating in an AS program, and whether methylation of these biomarkers could have prognostic value in predicting development of high-risk PCa. METHODS: We collected post DRE urine samples from PCa patients with lowand intermediate-risk PCa patients followed in an AS program. DNA extracted from urine cell pellets was analyzed for selected methylation biomarkers by multiplex MethyLight, a highly sensitive, methylation specific qPCR assay. Patients were stratified using Chi-square analysis by the percent of methylated reference (PMR). Correlative studies were performed on methylation data and clinical variables such as Gleason score and clinical stage. RESULTS: DNA extracted from DRE urine cell pellets of 142 patients was analyzed for the presence of 9 DNA methylation biomarkers. DNA methylation in one or more biomarkers was seen in 73% of patients. Methylation of 3 independent biomarkers was able to distinguish between low(GS6) and intermediate-risk (GS7) PCa (p<0.05). Multigene analysis showed that methylation in a combination of any 3 genes was able to stratify between GS6 and GS7 patients (p<0.05). CONCLUSIONS: We have demonstrated that our panel of DNA methylation biomarkers can be detected in DRE urine samples of PCa patients. These markers have prognostic value in distinguishing low-risk vs intermediate risk PCa. The promising results from this study may help establish a less invasive method for PCa monitoring for patients in AS programs, resulting in better management and treatment for PCa patients.

755 A five-gene DNA-methylation biomarker panel sensitively detects bladder cancer and discriminates between high-grade and low-grade disease in voided urine

755 A five-gene DNA-methylation biomarker panel sensitively detects bladder cancer and discriminates between high-grade and low-grade disease in voided urine

Identification and validation of the methylation biomarkers of non-small cell lung cancer (NSCLC).

BackgroundDNA methylation was suggested as the promising biomarker for lung cancer diagnosis. However, it is a great challenge to search for the optimal combination of methylation biomarkers to obtain maximum diagnostic performance.ResultsIn this study, we developed a panel of DNA methylation biomarkers and validated their diagnostic efficiency for non-small cell lung cancer (NSCLC) in a large Chinese Han NSCLC retrospective cohort. Three high-throughput DNA methylation microarray datasets (458 samples) were collected in the discovery stage. After normalization, batch effect elimination and integration, significantly differentially methylated genes and the best combination of the biomarkers were determined by the leave-one-out SVM (support vector machine) feature selection procedure. Then, candidate promoters were examined by the methylation status determined single nucleotide primer extension technique (MSD-SNuPET) in an independent set of 150 pairwise NSCLC/normal tissues. Four statistical models with fivefold cross-validation were used to evaluate the performance of the discriminatory algorithms. The sensitivity, specificity and accuracy were 86.3%, 95.7% and 91%, respectively, in Bayes tree model. The logistic regression model incorporated five gene methylation signatures at AGTR1, GALR1, SLC5A8, ZMYND10 and NTSR1, adjusted for age, sex and smoking, showed robust performances in which the sensitivity, specificity, accuracy, and area under the curve (AUC) were 78%, 97%, 87%, and 0.91, respectively.ConclusionsIn summary, a high-throughput DNA methylation microarray dataset followed by batch effect elimination can be a good strategy to discover optimal DNA methylation diagnostic panels. Methylation profiles of AGTR1, GALR1, SLC5A8, ZMYND10 and NTSR1, could be an effective methylation-based assay for NSCLC diagnosis.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-014-0035-3) contains supplementary material, which is available to authorized users.

DNA methylation profiling reveals novel diagnostic biomarkers in renal cell carcinoma

Renal cell carcinoma (RCC) is the tenth most commonly diagnosed cancer in the United States. While it is usually lethal when metastatic, RCC is successfully treated with surgery when tumors are confined to the kidney and have low tumor volume. Because most early stage renal tumors do not result in symptoms, there is a strong need for biomarkers that can be used to detect the presence of the cancer as well as to monitor patients during and after therapy. We examined genome-wide DNA methylation alterations in renal cell carcinomas of diverse histologies and benign adjacent kidney tissues from 96 patients. We observed widespread methylation differences between tumors and benign adjacent tissues, particularly in immune-, G-protein coupled receptor-, and metabolism-related genes. Additionally, we identified a single panel of DNA methylation biomarkers that reliably distinguishes tumor from benign adjacent tissue in all of the most common kidney cancer histologic subtypes, and a second panel does the same specifically for clear cell renal cell carcinoma tumors. This set of biomarkers were validated independently with excellent performance characteristics in more than 1,000 tissues in The Cancer Genome Atlas clear cell, papillary, and chromophobe renal cell carcinoma datasets. These DNA methylation profiles provide insights into the etiology of renal cell carcinoma and, most importantly, demonstrate clinically applicable biomarkers for use in early detection of kidney cancer.

Identification of Highly Methylated Genes across Various Types of B-Cell Non-Hodgkin Lymphoma

Epigenetic alterations of gene expression are important in the development of cancer. In this study, we identified genes which are epigenetically altered in major lymphoma types. We used DNA microarray technology to assess changes in gene expression after treatment of 11 lymphoma cell lines with epigenetic drugs. We identified 233 genes with upregulated expression in treated cell lines and with downregulated expression in B-cell lymphoma patient samples (n = 480) when compared to normal B cells (n = 5). The top 30 genes were further analyzed by methylation specific PCR (MSP) in 18 lymphoma cell lines. Seven of the genes were methylated in more than 70% of the cell lines and were further subjected to quantitative MSP in 37 B-cell lymphoma patient samples (diffuse large B-cell lymphoma (activated B-cell like and germinal center B-cell like subtypes), follicular lymphoma and Burkitt`s lymphoma) and normal B lymphocytes from 10 healthy donors. The promoters of DSP, FZD8, KCNH2, and PPP1R14A were methylated in 28%, 67%, 22%, and 78% of the 36 tumor samples, respectively, but not in control samples. Validation using a second series of healthy donor controls (n = 42; normal B cells, peripheral blood mononuclear cells, bone marrow, tonsils and follicular hyperplasia) and fresh-frozen lymphoma biopsies (n = 25), confirmed the results. The DNA methylation biomarker panel consisting of DSP, FZD8, KCNH2, and PPP1R14A was positive in 89% (54/61) of all lymphomas. Receiver operating characteristic analysis to determine the discriminative power between lymphoma and healthy control samples showed a c-statistic of 0.96, indicating a possible role for the biomarker panel in monitoring of lymphoma patients.

DNA Methylation Biomarkers Offer Improved Diagnostic Efficiency in Lung Cancer

The exceptional high mortality of lung cancer can be instigated to a high degree by late diagnosis. Despite the plethora of studies on potential molecular biomarkers for lung cancer diagnosis, very few have reached clinical implementation. In this study, we developed a panel of DNA methylation biomarkers and validated their diagnostic efficiency in bronchial washings from a large retrospective cohort. Candidate targets from previous high-throughput approaches were examined by pyrosequencing in an independent set of 48 lung tumor/normal paired. Ten promoters were selected and quantitative methylation-specific PCR (qMSP) assays were developed and used to screen 655 bronchial washings from the Liverpool Lung Project (LLP) subjects divided into training (194 cases and 214 controls) and validation (139 cases and 109 controls) sets. Three statistical models were used to select the optimal panel of markers and to evaluate the performance of the discriminatory algorithms. The final logit regression model incorporated hypermethylation at p16, TERT, WT1, and RASSF1. The performance of this 4-gene methylation signature in the validation set showed 82% sensitivity and 91% specificity. In comparison, cytology alone in this set provided 43% sensitivity at 100% specificity. The diagnostic efficiency of the panel did not show any biases with age, gender, smoking, and the presence of a nonlung neoplasm. However, sensitivity was predictably higher in central (squamous and small cell) than peripheral (adenocarcinomas) tumors, as well as in stage 2 or greater tumors. These findings clearly show the impact of DNA methylation-based assays in the diagnosis of cytologically occult lung neoplasms. A prospective trial is currently imminent in the LLP study to provide data on the enhancement of diagnostic accuracy in a clinical setting, including by additional markers.

Methylation profiling of normal individuals reveals mosaic promoter methylation of cancer-associated genes

Epigenetic silencing by promoter methylation of genes associated with cancer initiation and progression is a hallmark of tumour cells. As a consequence, testing for DNA methylation biomarkers in plasma or other body fluids shows great promise for detection of malignancies at early stages and/or for monitoring response to treatment. However, DNA from normal leukocytes may contribute to the DNA in plasma and will affect biomarker specificity if there is any methylation in the leukocytes. DNA from 48 samples of normal peripheral blood mononuclear cells was evaluated for the presence of methylation of a panel of DNA methylation biomarkers that have been implicated in cancer. SMART-MSP, a methylation specific PCR (MSP) methodology based on real time PCR amplification, high-resolution melting and strategic primer design, enabled quantitative detection of low levels of methylated DNA. Methylation was observed in all tested mononuclear cell DNA samples for the CDH1 and HIC1 promoters and in majority of DNA samples for the TWIST1 and DAPK1 promoters. APC and RARB promoter methylation, at a lower average level, was also detected in a substantial proportion of DNA samples. We found no BRCA1, CDKN2A, GSTP1 and RASSF1A promoter methylation in this sample set. Several individuals had higher levels of methylation at several loci suggestive of a methylator phenotype. In conclusion, methylation of many potential DNA methylation biomarkers can be detected in normal peripheral blood mononuclear cells, and is likely to affect their specificity for detecting low level disease. However, we found no evidence of promoter methylation for other genes indicating that panels of analytically sensitive and specific methylation biomarkers in body fluids can be obtained.