Genome-wide methylome analysis using MethylCap-seq uncovers 4 hypermethylated markers with high sensitivity for both adeno- and squamous-cell cervical carcinoma

Background: Cytology-based screening methods for cervical adenocarcinoma (ADC) and to a lesser extent squamous-cell carcinoma (SCC) suffer from low sensitivity. DNA hypermethylation analysis in cervical scrapings may improve detection of SCC, but few methylation markers have been described for ADC. We aimed to identify novel methylation markers for the early detection of both ADC and SCC. Results: Genome-wide methylation profiling for 20 normal cervices, 6 ADC and 6 SCC using MethylCap-seq yielded 53 candidate regions hypermethylated in both ADC and SCC. Verification and independent validation of the 15 most significant regions revealed 5 markers with differential methylation between 17 normals and 13 cancers. Quantitative methylation-specific PCR on cervical cancer scrapings resulted in detection rates ranging between 80% and 92% while between 94% and 99% of control scrapings tested negative. Four markers (SLC6A5, SOX1, SOX14 and TBX20) detected ADC and SCC with similar sensitivity. In scrapings from women referred with an abnormal smear (n = 229), CIN3+ sensitivity was between 36% and 71%, while between 71% and 93% of adenocarcinoma in situ (AdCIS) were detected; and CIN0/1 specificity was between 88% and 98%. Compared to hrHPV, the combination SOX1/SOX14 showed a similar CIN3+ sensitivity (80% vs. 75%, respectively, P>0.2), while specificity improved (42% vs. 84%, respectively, P < 10(-5)). Conclusion: SOX1 and SOX14 are methylation biomarkers applicable for screening of all cervical cancer types

Risk score predicts high-grade prostate cancer in DNA-methylation positive, histopathologically negative biopsies.

BACKGROUND: Prostate cancer (PCa) diagnosis is challenging because efforts for effective, timely treatment of men with significant cancer typically result in over-diagnosis and repeat biopsies. The presence or absence of epigenetic aberrations, more specifically DNA-methylation of GSTP1, RASSF1, and APC in histopathologically negative prostate core biopsies has resulted in an increased negative predictive value (NPV) of ∼90% and thus could lead to a reduction of unnecessary repeat biopsies. Here, it is investigated whether, in methylation-positive men, DNA-methylation intensities could help to identify those men harboring high-grade (Gleason score ≥7) PCa, resulting in an improved positive predictive value. METHODS: Two cohorts, consisting of men with histopathologically negative index biopsies, followed by a positive or negative repeat biopsy, were combined. EpiScore, a methylation intensity algorithm was developed in methylation-positive men, using area under the curve of the receiver operating characteristic as metric for performance. Next, a risk score was developed combining EpiScore with traditional clinical risk factors to further improve the identification of high-grade (Gleason Score ≥7) cancer. RESULTS: Compared to other risk factors, detection of DNA-methylation in histopathologically negative biopsies was the most significant and important predictor of high-grade cancer, resulting in a NPV of 96%. In methylation-positive men, EpiScore was significantly higher for those with high-grade cancer detected upon repeat biopsy, compared to those with either no or low-grade cancer. The risk score resulted in further improvement of patient risk stratification and was a significantly better predictor compared to currently used metrics as PSA and the prostate cancer prevention trial (PCPT) risk calculator (RC). A decision curve analysis indicated strong clinical utility for the risk score as decision-making tool for repeat biopsy. CONCLUSIONS: Low DNA-methylation levels in PCa-negative biopsies led to a NPV of 96% for high-grade cancer. The risk score, comprising DNA-methylation intensity and traditional clinical risk factors, improved the identification of men with high-grade cancer, with a maximum avoidance of unnecessary repeat biopsies. This risk score resulted in better patient risk stratification and significantly outperformed current risk prediction models such as PCPTRC and PSA. The risk score could help to identify patients with histopathologically negative biopsies harboring high-grade PCa. Prostate 76:1078-1087, 2016. © 2016 The Authors. The Prostate Published by Wiley Periodicals, Inc.MDxHealthThis is the author accepted manuscript. It is currently under an indefinite embargo pending publication by Wiley

PubMeth: a cancer methylation database combining text-mining and expert annotation

Epigenetics, and more specifically DNA methylation is a fast evolving research area. In almost every cancer type, each month new publications confirm the differentiated regulation of specific genes due to methylation and mention the discovery of novel methylation markers. Therefore, it would be extremely useful to have an annotated, reviewed, sorted and summarized overview of all available data. PubMeth is a cancer methylation database that includes genes that are reported to be methylated in various cancer types. A query can be based either on genes (to check in which cancer types the genes are reported as being methylated) or on cancer types (which genes are reported to be methylated in the cancer (sub) types of interest). The database is freely accessible at http://www.pubmeth.org

Hyperpolarized 13C-pyruvate MRI detects real-time metabolic flux in prostate cancer metastases to bone and liver: a clinical feasibility study.

BackgroundHyperpolarized (HP) 13C-pyruvate MRI is a stable-isotope molecular imaging modality that provides real-time assessment of the rate of metabolism through glycolytic pathways in human prostate cancer. Heretofore this imaging modality has been successfully utilized in prostate cancer only in localized disease. This pilot clinical study investigated the feasibility and imaging performance of HP 13C-pyruvate MR metabolic imaging in prostate cancer patients with metastases to the bone and/or viscera.MethodsSix patients who had metastatic castration-resistant prostate cancer were recruited. Carbon-13 MR examination were conducted on a clinical 3T MRI following injection of 250 mM hyperpolarized 13C-pyruvate, where pyruvate-to-lactate conversion rate (kPL) was calculated. Paired metastatic tumor biopsy was performed with histopathological and RNA-seq analyses.ResultsWe observed a high rate of glycolytic metabolism in prostate cancer metastases, with a mean kPL value of 0.020 ± 0.006 (s-1) and 0.026 ± 0.000 (s-1) in bone (N = 4) and liver (N = 2) metastases, respectively. Overall, high kPL showed concordance with biopsy-confirmed high-grade prostate cancer including neuroendocrine differentiation in one case. Interval decrease of kPL from 0.026 at baseline to 0.015 (s-1) was observed in a liver metastasis 2 months after the initiation of taxane plus platinum chemotherapy. RNA-seq found higher levels of the lactate dehydrogenase isoform A (Ldha,15.7 ± 0.7) expression relative to the dominant isoform of pyruvate dehydrogenase (Pdha1, 12.8 ± 0.9).ConclusionsHP 13C-pyruvate MRI can detect real-time glycolytic metabolism within prostate cancer metastases, and can measure changes in quantitative kPL values following treatment response at early time points. This first feasibility study supports future clinical studies of HP 13C-pyruvate MRI in the setting of advanced prostate cancer

Food-derived opioid peptides inhibit cysteine uptake with redox and epigenetic consequences

Dietary interventions like gluten-free and casein-free diets have been reported to improve intestinal, autoimmune and neurological symptoms in patients with a variety of conditions; however, the underlying mechanism of benefit for such diets remains unclear. Epigenetic programming, including CpG methylation and histone modifications, occurring during early postnatal development can influence the risk of disease in later life, and such programming may be modulated by nutritional factors such as milk and wheat, especially during the transition from a solely milk-based diet to one that includes other forms of nutrition. The hydrolytic digestion of casein (a major milk protein) and gliadin (a wheat-derived protein) releases peptides with opioid activity, and in the present study, we demonstrate that these food-derived proline-rich opioid peptides modulate cysteine uptake in cultured human neuronal and gastrointestinal (GI) epithelial cells via activation of opioid receptors. Decreases in cysteine uptake were associated with changes in the intracellular antioxidant glutathione and the methyl donor S-adenosylmethionine. Bovine and human casein-derived opioid peptides increased genome-wide DNA methylation in the transcription start site region with a potency order similar to their inhibition of cysteine uptake. Altered expression of genes involved in redox and methylation homeostasis was also observed. These results illustrate the potential of milk- and wheat-derived peptides to exert antioxidant and epigenetic changes that may be particularly important during the postnatal transition from placental to GI nutrition. Differences between peptides derived from human and bovine milk may contribute to developmental differences between breastfed and formula-fed infants. Restricted antioxidant capacity, caused by wheat- and milk-derived opioid peptides, may predispose susceptible individuals to inflammation and systemic oxidation, partly explaining the benefits of gluten-free or casein-free diets

Genome-wide DNA methylation detection by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison.

Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). Objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples, i.e. 65 glioblastoma and 5 non-tumoral tissues. As MethylCap-seq coverages were limited, we focused on the inherent capacity of the methodology to detect methylated loci rather than a quantitative analysis. MethylCap-seq and HM450 data were dichotomized and performances were compared using a gold standard free Bayesian modelling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. In addition, genome-wide characteristics were compared, revealing that HM450 probes identified substantially fewer regions compared to MethylCap-seq. Although results indicated that the latter method can detect more potentially relevant DNA-methylation, this did not translate into the discovery of more differentially methylated loci between tumours and controls compared to HM450. Our results therefore indicate that both methodologies are complementary, with a higher sensitivity for HM450 and a far larger genome-wide coverage for MethylCap-seq, but also that a more comprehensive character does not automatically imply more significant results in biomarker studies

MGMT Promoter Methylation Cutoff with Safety Margin for Selecting Glioblastoma Patients into Trials Omitting Temozolomide: A Pooled Analysis of Four Clinical Trials.

The methylation status of the O &lt;sup&gt;6&lt;/sup&gt; -methylguanine DNA methyltransferase (MGMT) gene promoter is predictive for benefit from temozolomide in glioblastoma (GBM). A clinically optimized cutoff was sought allowing patient selection for therapy without temozolomide, while avoiding to withhold it from patients who may potentially benefit.Experimental Design: Quantitative MGMT methylation-specific PCR data were obtained for newly diagnosed patients with GBM screened or treated with standard radiotherapy and temozolomide in four randomized trials. The pooled dataset was randomly split into a training and test dataset. The unsupervised cutoff was obtained at a 50% probability to be (un)methylated. ROC analysis identified an optimal cutoff supervised by overall survival (OS). For 4,041 patients valid MGMT results were obtained, whereof 1,725 were randomized. The unsupervised cutoff in the training dataset was 1.27 (log &lt;sub&gt;2&lt;/sub&gt; [1,000 × (MGMT+1)/ACTB]), separating unmethylated and methylated patients. The optimal supervised cutoff for unmethylated patients was -0.28 (AUC = 0.61), classifying "truly unmethylated" (≤-0.28) and "gray zone" patients (&gt;-0.28, ≤1.27), the latter comprising approximately 10% of cases. In contrast, for patients with MGMT methylation (&gt;1.27) more methylation was not related to better outcome. Both methylated and gray zone patients performed significantly better for OS than truly unmethylated patients [HR = 0.35, 95% confidence interval (CI), 0.27-0.45, P &lt; 0.0001; HR = 0.58, 95% CI, 0.43-0.78, P &lt; 0.001], validated in the test dataset. The MGMT assay was highly reproducible upon retesting of 218 paired samples (R &lt;sup&gt;2&lt;/sup&gt; = 0.94). Low MGMT methylation (gray zone) may confer some sensitivity to temozolomide treatment, hence the lower safety margin should be considered for selecting patients with unmethylated GBM into trials omitting temozolomide

Strategies for validation and testing of DNA methylation biomarkers

DNA methylation is a stable covalent epigenetic modification of primarily CpG dinucleotides that has recently gained considerable attention for its use as a biomarker in different clinical settings, including disease diagnosis, prognosis and therapeutic response prediction. Although the advent of genome-wide DNA methylation profiling in primary disease tissue has provided a manifold resource for biomarker development, only a tiny fraction of DNA methylation-based assays have reached clinical testing. Here, we provide a critical overview of different analytical methods that are suitable for biomarker validation, including general study design considerations, which might help to streamline epigenetic marker development. Furthermore, we highlight some of the recent marker validation studies and established markers that are currently commercially available for assisting in clinical management of different cancers