Comprehensive methylome analysis of ovarian tumors reveals hedgehog signaling pathway regulators as prognostic DNA methylation biomarkers

The Diversity of Methylation Patterns in Serous Borderline Ovarian Tumors and Serous Ovarian Carcinomas

Background: Changes in DNA methylation patterns are a pivotal mechanism of carcinogenesis. In some tumors, aberrant methylation precedes genetic changes, while gene expression may be more frequently modified due to methylation alterations than by mutations. Methods: Herein, 128 serous ovarian tumors were analyzed, including borderline ovarian tumors (BOTS) with (BOT.V600E) and without (BOT) the BRAF V600E mutation, low-grade (lg), and high-grade (hg) ovarian cancers (OvCa). The methylome of the samples was profiled with Infinium MethylationEPIC microarrays. Results: The biggest number of differentially methylated (DM) CpGs and regions (DMRs) was found between lgOvCa and hgOvCa. By contrast, the BOT.V600E tumors had the lowest number of DM CpGs and DMRs compared to all other groups and, in relation to BOT, their genome was strongly downmethylated. Remarkably, the ten most significant DMRs, discriminating BOT from lgOvCa, encompassed the MHC region on chromosome 6. We also identified hundreds of DMRs, being of potential use as predictive biomarkers in BOTS and hgOvCa. DMRs with the best discriminative capabilities overlapped the following genes: BAIAP3, IL34, WNT10A, NEU1, SLC44A4, and HMOX1, TCN2, PES1, RP1-56J10.8, ABR, NCAM1, RP11-629G13.1, AC006372.4, NPTXR in BOTS and hgOvCa, respectively. Conclusions: The global genome-wide hypomethylation positively correlates with the increasing aggressiveness of ovarian tumors. We also assume that the immune system may play a pivotal role in the transition from BOTS to lgOvCa. Given that the BOT.V600E tumors had the lowest number of DM CpGs and DMRs compared to all other groups, when methylome is considered, such tumors might be placed in-between BOT and OvCa.

Epigenetic silencing of ZIC4 unveils a potential tumor suppressor role in pediatric choroid plexus carcinoma

Zic family member ZIC4 is a transcription factor that has been shown to be silenced in several cancers. However, understanding the regulation and function of ZIC4 in pediatric choroid plexus tumors (CPTs) remained limited. This study employed data mining and bioinformatics analysis to investigate the DNA methylation status of ZIC4 in CPTs and its correlation with patient survival. Our results unveiled ZIC4 methylation as a segregating factor, dividing CPT cohorts into two clusters, with hyper-methylation linked to adverse prognosis. Hyper-methylation of ZIC4 was confirmed in a choroid plexus carcinoma-derived cell line (CCHE-45) by bisulfite sequencing. Furthermore, our study demonstrated that demethylating agent and a histone methyltransferase inhibitor could reverse ZIC4 silencing. RNA sequencing and proteomic analysis showed that ZIC4 over-expression influenced genes and proteins involved in immune response, antigen processing and presentation, endoplasmic reticulum stress, and metabolism. Functionally, re-expressing ZIC4 negatively impacted cell proliferation and migration. Ultimately, these findings underscore ZIC4 hyper-methylation as a prognostic marker in CPTs and shed light on potential mechanisms underlying its tumor suppressor role in CPC. This insight paves the way for novel therapeutic targets in treating aggressive CPTs.

Epigenetic regulation in ovarian cancer

Ovarian cancer is one of the diseases that have the highest mortality rate for women, especially women over 50 years old. In the future, incidence and mortality rates are predicted to extend in countries with low HDI. Instability in the structure and function of genetic factors has long been known as a cause of cancer, including ovarian cancer. Besides understanding gene mutations, epigenetic alterations have emerged as another aspect leading to the pathogenesis of ovarian neoplasm. The development and progression of this fatal disease have been found to be associated with abnormalities of epigenetic regulation. DNA methylation, histone modification, and non-coding RNAs-based gene silencing are processes of interest in developing ovarian carcinoma and are also new targets for cancer detection or treatment.

Age-Related DNA Methylation in Normal Kidney Tissue Identifies Epigenetic Cancer Risk Susceptibility Loci in the ANKRD34B and ZIC1 Genes

Both age-dependent and age-independent alteration of DNA methylation in human tissues are functionally associated with the development of many malignant and non-malignant human diseases. TCGA-KIRC data were biometrically analyzed to identify new loci with age-dependent DNA methylation that may contribute to tumor risk in normal kidney tissue. ANKRD34B and ZIC1 were evaluated as candidate genes by pyrosequencing of 539 tissues, including 239 normal autopsy, 157 histopathologically tumor-adjacent normal, and 143 paired tumor kidney samples. All candidate CpG loci demonstrated a strong correlation between relative methylation levels and age (R = 0.70−0.88, p < 2 × 10−16) and seven out of 10 loci were capable of predicting chronological age in normal kidney tissues, explaining 84% of the variance (R = 0.92). Moreover, significantly increased age-independent methylation was found for 9 out of 10 CpG loci in tumor-adjacent tissues, compared to normal autopsy tissues (p = 0.001−0.028). Comparing tumor and paired tumor-adjacent tissues revealed two patient clusters showing hypermethylation, one cluster without significant changes in methylation, and a smaller cluster demonstrating hypomethylation in the tumors (p < 1 × 10−10). Taken together, our results show the presence of additional methylation risk factors besides age for renal cancer in normal kidney tissue. Concurrent tumor-specific hypermethylation suggests a subset of these loci are candidates for epigenetic renal cancer susceptibility.

DNA methylation marker to estimate ovarian cancer cell fraction

Evaluation of a cancer cell fraction is important for accurate molecular analysis, and pathological analysis is the gold standard for evaluation. Despite the potential convenience, no established molecular markers for evaluation are available. In this study, we aimed to identify ovarian cancer cell fraction markers using DNA methylation highly specific to ovarian cancer cells. Using genome-wide DNA methylation data, we screened candidate marker genes methylated in 30 ovarian cancer FFPE samples and 12 high-grade serous ovarian cancer cell lines, and unmethylated in two female leucocytes and two normal fallopian epithelial cell samples. Methylation levels of two genes, SIM1, and ZNF154, showed high correlation with pathological cancer cell fractions among the 30 ovarian cancer FFPE samples (R = 0.61 for SIM1, 0.71 for ZNF154). For cost-effective analysis of FFPE samples, pyrosequencing primers were designed, and successfully established for SIM1 and ZNF154. Correlation between a pathological cancer cell fraction and methylation levels obtained by pyrosequencing was confirmed to be high (R = 0.53 for SIM1, 0.64 for ZNF154). Finally, an independent validation cohort of 29 ovarian cancer FFPE samples was analyzed. ZNF154 methylation showed a high correlation with the pathological cancer cell fraction (R = 0.77, P < 0.0001). Therefore, the ZNF154 methylation level was considered to be useful for the estimation of ovarian cancer cell fraction, and is expected to help accurate molecular analysis.

Identification of a four-gene methylation biomarker panel in high-grade serous ovarian carcinoma

Background The lack of effective biomarkers for the screening and early detection of ovarian cancer (OC) is one of the most pressing problems in oncogynecology. Because epigenetic alterations occur early in the cancer development, they provide great potential to serve as such biomarkers. In our study, we investigated a potential of a four-gene methylation panel (including CDH13, HNF1B, PCDH17 and GATA4 genes) for the early detection of high-grade serous ovarian carcinoma (HGSOC). Methods For methylation detection we used methylation sensitive high-resolution melting analysis and real-time methylation specific analysis. We also investigated the relation between gene hypermethylation and gene relative expression using the 2-ΔΔCt method. Results The sensitivity of the examined panel reached 88.5%. We were able to detect methylation in 85.7% (12/14) of early stage tumors and in 89.4% (42/47) of late stage tumors. The total efficiency of the panel was 94.4% and negative predictive value reached 90.0%. The specificity and positive predictive value achieved 100% rates. Our results showed lower gene expression in the tumor samples in comparison to control samples. The more pronounced downregulation was measured in the group of samples with detected methylation. Conclusions In our study we designed the four-gene panel for HGSOC detection in ovarian tissue with 100% specificity and sensitivity of 88.5%. The next challenge is translation of the findings to the less invasive source for biomarker examination, such as plasma. Our results indicate that combination of examined genes deserve consideration for further testing in clinical molecular diagnosis of HGSOC.

Accurate Prediction of Prognosis by Integrating Clinical and Molecular Characteristics in Colon Cancer

Various factors affect the prognosis of patients with colon cancer. Complicated factors are found to be conducive to accurate assessment of prognosis. In this study, we developed a series of prognostic prediction models for survival time of colon cancer patients after surgery. Analysis of nine clinical characteristics showed that the most important factor was the positive lymph node ratio (LNR). High LNR was the most important clinical factor affecting 1- and 3-year survival; M0&age < 70 was the most important feature for 5 years. The performance of the model was improved through the integration of clinical characteristics and four types of molecule features (mRNA, lncRNA, miRNA, DNA methylation). The model provides guidance for clinical practice. According to the high-risk molecular features combined with age ≥ 70&T3, poorly differentiated or undifferentiated, M0&well differentiated, M0&T2, LNR high, T4&poorly differentiated, or undifferentiated, the survival time may be less than 1 year; for patients with high risk of molecular features combined with M0&T2, M0&T4, LNR 0& M0, LNR median &T3, and LNR high, the survival is predicted less than 3 years; and the survival of patients with M1&T3, M0 and high risk molecular features is less than 5 years. Using multidimensional and complex patient information, this study establishes potential criteria for clinicians to evaluate the survival of patients for colon cancer.

The Hedgehog signaling pathway promotes chemotherapy resistance via multidrug resistance protein 1 in ovarian cancer

Various studies have revealed that the Hedgehog (Hh) signaling pathway promotes ovarian cancer invasion, migration and drug resistance. Previous studies by our group have identified a set of genes, including multidrug resistance gene 1 (MDR1), that are regulated by Hh signaling in ovarian cancer. However, the association between Hh signaling activation and MDR1 expression requires further validation. In the present study, reverse transcription-quantitative PCR or western blot assays were used to evaluate the mRNA and protein expression levels of MDR1, Sonic Hh (Shh), glioma-associated oncogene 2 (Gli2), Gli1 and γ-phosphorylated H2A.X variant histone (γ-H2AX). MTT and colony-formation assays were performed to determine the effect of cisplatin (DDP) after inhibiting the Hh pathway in ovarian cancer cells. The results indicated that MDR1, Gli2 and Shh levels were much higher in SK-OV-3 cells with acquired DDP resistance than in native SK-OV-3 cells. ES-2 cells with overexpression of Gli2 were capable of efficiently forming colonies in the presence of low DDP concentrations. By contrast, Gli2 knockdown in SK-OV-3 cells decreased the colony-forming ability under the same concentration of DDP. As determined by MTT assays, knockdown of Gli2 or targeting of the Hh signaling pathway with either Gli-antagonist 61 (GANT61) or cyclopamine, in combination with DDP treatment, diminished the viability of ES-2 and SK-OV-3 cells, whereas Gli2 overexpression increased the viability of ES-2 cells in the presence of DDP. Knockdown of Gli2 or targeting the Hh signaling pathway with GANT61 also increased γ-H2AX levels but decreased the expression of MDR1 in the presence of DDP. MDR1 expression is regulated by the Hh signaling pathway and is likely a downstream transcription factor of Gli2. In conclusion, targeting the Hh signaling pathway increases the sensitivity of ovarian cancer to DDP. MDR1 is a target gene of the Hh signaling pathway and this pathway may affect chemoresistance of ovarian cancer to DDP via MDR1.

Expression and clinical significance of methyl-CpG binding domain protein 2 in high-grade serous ovarian cancer

Platinum resistance is an important cause of clinical recurrence and mortality of patients with high-grade serous ovarian cancer (HGSOC). Methyl-CpG binding domain protein 2 (MBD2) serves an important role in tumor progression; however, its role in HGSOC remains unclear. The aim of the present study was to investigate the expression of MBD2 in HGSOC and its role in drug resistance and prognosis of HGSOC. MBD2 expression was analyzed by immunohistochemical staining and western blotting. The associations between MBD2 expression and clinical pathological features, platinum resistance and patient prognosis were analyzed using a χ² test, Kaplan-Meier analysis and Cox regression analysis. Positive MBD2 expression was detected in 73 (63.5%) of the HGSOC tissue samples, whereas it was undetectable in all 16 normal tissue samples (100%) analyzed, indicating a significantly higher expression level in tumor tissues compared with normal tissues (P<0.001). Additionally, MBD2 expression was significantly higher in platinum-resistant cases compared with that in platinum-sensitive cases (P<0.05). In addition, high expression of MBD2 was negatively associated with relapse-free survival (P<0.05). In conclusion, MBD2 was demonstrated to be a potential drug target and a biomarker for poor prognosis in HGSOC.

Ovarian cancer detection by DNA methylation in cervical scrapings

Background

Ovarian cancer (OC) is the most lethal gynecological cancer, worldwide, largely due to its vague and nonspecific early stage symptoms, resulting in most tumors being found at advanced stages. Moreover, due to its relative rarity, there are currently no satisfactory methods for OC screening, which remains a controversial and cost-prohibitive issue. Here, we demonstrate that Papanicolaou test (Pap test) cervical scrapings, instead of blood, can reveal genetic/epigenetic information for OC detection, using specific and sensitive DNA methylation biomarkers.

Results

We analyzed the methylomes of tissues (50 OC tissues versus 6 normal ovarian epithelia) and cervical scrapings (5 OC patients versus 10 normal controls), and integrated public methylomic datasets, including 79 OC tissues and 6 normal tubal epithelia. Differentially methylated genes were further classified by unsupervised hierarchical clustering, and each candidate biomarker gene was verified in both OC tissues and cervical scrapings by either quantitative methylation-specific polymerase chain reaction (qMSP) or bisulfite pyrosequencing. A risk-score by logistic regression was generated for clinical application.

One hundred fifty-one genes were classified into four clusters, and nine candidate hypermethylated genes from these four clusters were selected. Among these, four genes fulfilled our selection criteria and were validated in training and testing set, respectively. The OC detection accuracy was demonstrated by area under the receiver operating characteristic curves (AUCs) in 0.80–0.83 of AMPD3, 0.79–0.85 of AOX1, 0.78–0.88 of NRN1, and 0.82–0.85 of TBX15. From this, we found OC-risk score, equation generated by logistic regression in training set and validated an OC-associated panel comprising AMPD3, NRN1, and TBX15, reaching a sensitivity of 81%, specificity of 84%, and OC detection accuracy of 0.91 (95% CI, 0.82–1) in testing set.

Conclusions

Ovarian cancer detection from cervical scrapings is feasible, using particularly promising epigenetic biomarkers such as AMPD3/NRN1/TBX15. Further validation is warranted.

Epigenetic Biomarkers in the Management of Ovarian Cancer: Current Prospectives

Ovarian cancer (OC) causes significant morbidity and mortality as neither detection nor screening of OC is currently feasible at an early stage. Difficulty to promptly diagnose OC in its early stage remains challenging due to non-specific symptoms in the early-stage of the disease, their presentation at an advanced stage and poor survival. Therefore, improved detection methods are urgently needed. In this article, we summarize the potential clinical utility of epigenetic signatures like DNA methylation, histone modifications, and microRNA dysregulation, which play important role in ovarian carcinogenesis and discuss its application in development of diagnostic, prognostic, and predictive biomarkers. Molecular characterization of epigenetic modification (methylation) in circulating cell free tumor DNA in body fluids offers novel, non-invasive approach for identification of potential promising cancer biomarkers, which can be performed at multiple time points and probably better reflects the prevailing molecular profile of cancer. Current status of epigenetic research in diagnosis of early OC and its management are discussed here with main focus on potential diagnostic biomarkers in tissue and body fluids. Rapid and point of care diagnostic applications of DNA methylation in liquid biopsy has been precluded as a result of cumbersome sample preparation with complicated conventional methods of isolation. New technologies which allow rapid identification of methylation signatures directly from blood will facilitate sample-to answer solutions thereby enabling next-generation point of care molecular diagnostics. To date, not a single epigenetic biomarker which could accurately detect ovarian cancer at an early stage in either tissue or body fluid has been reported. Taken together, the methodological drawbacks, heterogeneity associated with ovarian cancer and non-validation of the clinical utility of reported potential biomarkers in larger ovarian cancer populations has impeded the transition of epigenetic biomarkers from lab to clinical settings. Until addressed, clinical implementation as a diagnostic measure is a far way to go.

Epigenetic activation of POTE genes in ovarian cancer

The POTE gene family consists of 14 homologous genes localized to autosomal pericentromeres, and a sub-set of POTEs are cancer-testis antigen (CTA) genes. POTEs are over-expressed in epithelial ovarian cancer (EOC), including the high-grade serous subtype (HGSC), and expression of individual POTEs correlates with chemoresistance and reduced survival in HGSC. The mechanisms driving POTE overexpression in EOC and other cancers is unknown. Here, we investigated the role of epigenetics in regulating POTE expression, with a focus on DNA hypomethylation. Consistent with their pericentromeric localization, Pan-POTE expression in EOC correlated with expression of the pericentromeric repeat NBL2, which was not the case for non-pericentromeric CTAs. POTE genomic regions contain LINE-1 (L1) sequences, and Pan-POTE expression correlated with both global and POTE-specific L1 hypomethylation in EOC. Analysis of individual POTEs using RNA-seq and DNA methylome data from fallopian tube epithelia (FTE) and HGSC revealed that POTEs C, E, and F have increased expression in HGSC in conjunction with DNA hypomethylation at 5' promoter or enhancer regions. Moreover, POTEs C/E/F showed additional increased expression in recurrent HGSC in conjunction with 5' hypomethylation, using patient-matched samples. Experiments using decitabine treatment and DNMT knockout cell lines verified a functional contribution of DNA methylation to POTE repression, and epigenetic drug combinations targeting histone deacetylases (HDACs) and histone methyltransferases (HMTs) in combination with decitabine further increased POTE expression. In summary, several alterations of the cancer epigenome, including pericentromeric activation, global and locus-specific L1 hypomethylation, and locus-specific 5' CpG hypomethylation, converge to promote POTE expression in ovarian cancer.

MGT-SM: A Method for Constructing Cellular Signal Transduction Networks

A cellular signal transduction network is an important means to describe biological responses to environmental stimuli and exchange of biological signals. Constructing the cellular signal transduction network provides an important basis for the study of the biological activities, the mechanism of the diseases, drug targets and so on. The statistical approaches to network inference are popular in literature. Granger test has been used as an effective method for causality inference. Compared with bivariate granger tests, multivariate granger tests reduce the indirect causality and were used widely for the construction of cellular signal transduction networks. A multivariate Granger test requires that the number of time points in the time-series data is more than the number of nodes involved in the network. However, there are many real datasets with a few time points which are much less than the number of nodes in the network. In this study, we propose a new multivariate Granger test-based framework to construct cellular signal transduction network, called MGT-SM. Our MGT-SM uses SVD to compute the coefficient matrix from gene expression data and adopts Monte Carlo simulation to estimate the significance of directed edges in the constructed networks. We apply the proposed MGT-SM to Yeast Synthetic Network and MDA-MB-468, and evaluate its performance in terms of the recall and the AUC. The results show that MGT-SM achieves better results, compared with other popular methods (CGC2SPR, PGC, and DBN).

Aberrant methylation of PCDH17 gene in high-grade serous ovarian carcinoma

BACKGROUND

Aberrant DNA methylation of protocadherins (PCDHs) has been associated with development and progression of various types of cancer. It could represent possible direction in the search for critically needed tumor biomarkers for ovarian cancer.

OBJECTIVE

To investigate methylation of δ2 group of non-clustered PCDHs in high-grade serous ovarian carcinoma (HGSOC) tissue in comparison with control tissue.

METHODS

We used next-generation sequencing for detecting regions with the most altered methylation. For further confirmation of discovered alterations we used methylation-sensitive high-resolution melting analysis.

RESULTS

PCDH17 methylation was detected in almost 70% of HGSOC patients without any methylation in the group of control samples and was found both in the late stage tumors as well as in the early stage ones. Other selected PCDHs did not show any relevant changes in methylation. Subsequent gene expression analysis of PCDH17 revealed decreased expression in all of the tumor samples in comparison to the control ones. Statistically significant negative correlation was found between methylation and levels of expression suggesting potentially methylation-based silencing.

CONCLUSIONS

Methylation of PCDH17 could play an important role in development and progression of HGSOC and has potential to become a target in the search for new clinical biomarkers.

Epigenetic loss of heparan sulfate 3-O-sulfation sensitizes ovarian carcinoma to oncogenic signals and predicts prognosis

Precision medicine requires markers for therapeutic guidance. The purpose of this study was to determine whether epithelial ovarian cancer (EOC) epigenetics can lead to the identification of biomarkers for precision medicine. Through integrative methylomics, we discovered and validated the epigenetic signature of NEFH and HS3ST2 as an independent prognostic factor for type II EOC in our dataset (n = 84), and two independent methylomics datasets (total n = 467). Integrated transcriptomics dataset (n = 1147) and tissue microarrays (n = 54) of HS3ST2 also related to high-methylation statuses and the EOC prognosis. Mechanistic explorations of HS3ST2 have assessed responses to oncogenic stimulations such as IL-6, EGF, and FGF2 in cancer cells. The combination of HS3ST2 and various oncogenic ligands also confers the worse outcome. 3-O-sulfation of heparan sulfate by HS3ST2 makes ovarian cancer cells intrinsically sensitive to oncogenic signals, which sheds new light on the application of HS3ST2 as a companion diagnostic for targeted therapy using kinase inhibitors or therapeutic antibodies.

Epigenetics in ovarian cancer

Ovarian cancer is a disease with a poor prognosis and little progress has been made to improve treatment. It is now recognized that there are several histotypes of ovarian cancer, each with distinct epidemiologic and genomic characteristics. Cancer therapy is moving beyond classical chemotherapy to include epigenetic approaches. Epigenetics is the dynamic regulation of gene expression by DNA methylation and histone post translational modification in response to environmental cues. Improvement in technology to study DNA methylation has enabled a more agnostic approach and, with larger samples sets, has begun to unravel how epigenetics contributes to the etiology, response to chemotherapy and prognosis in of ovarian cancer. Investigations into histone modifications in ovarian cancer are more nascent. Much more is needed to be done to fully realize the potential that epigenetics holds for ovarian cancer clinical care.

Integrated transcriptomic and epigenomic analysis of ovarian cancer reveals epigenetically silenced GULP1

Many epigenetically inactivated genes involved in ovarian cancer (OC) development and progression remain to be identified. In this study we undertook an integrated approach that consisted of identification of genome-wide expression patterns of primary OC samples and normal ovarian surface epithelium along with a pharmacologic unmasking strategy using 3 OC and 3 immortalized normal ovarian epithelial cell lines. Our filtering scheme identified 43 OC specific methylated genes and among the 5 top candidates (GULP1, CLIP4, BAMBI, NT5E, TGFβ2), we performed extended studies of GULP1. In a training set, we identified GULP1 methylation in 21/61 (34%) of cases with 100% specificity. In an independent cohort, the observed methylation was 40% (146/365) in OC, 12.5% (2/16) in borderline tumors, 11% (2/18) in cystadenoma and 0% (0/13) in normal ovarian epithelium samples. GULP1 methylation was associated with clinicopathological parameters such as stage III/IV (p = 0.001), poorly differentiated grade (p = 0.033), residual disease (p < 0.0003), worse overall (p = 0.02) and disease specific survival (p = 0.01). Depletion of GULP1 in OC cells led to increased pro-survival signaling, inducing survival and colony formation, whereas reconstitution of GULP1 negated these effects, suggesting that GULP1 is required for maintaining cellular growth control.

Clinicopathologic and Prognostic Significance of the Zinc Finger of the Cerebellum Family in Invasive Breast Cancer

Purpose

Five members of the zinc finger of the cerebellum (ZIC) family-ZIC1, ZIC2, ZIC3, ZIC4, and ZIC5-have been shown to be involved in various carcinomas. Here, we aimed to explore the clinicopathologic and prognostic roles of ZIC family members in invasive breast cancer patients using immunohistochemical analysis, western blotting analysis, and real-time quantitative polymerase chain reaction (RT-qPCR).

Methods

A total of 241 female invasive breast cancer patients who underwent radical mastectomy between 2009 and 2011 were enrolled. ZIC proteins in 241 pairs of breast tumors and corresponding normal tissues were investigated using immunohistochemistry and the clinicopathologic roles of proteins were analyzed using Pearson's chi-square test. Kaplan-Meier curves and Cox regression analysis were also used to analyze the prognostic value of the ZIC proteins. In addition, 12 pairs of fresh-frozen breast tumors and matched normal tissues were used in the western blotting analysis and RT-qPCR.

Results

Only ZIC1 expression in normal tissues was obviously higher than that in tumors (p<0.001). On multivariate analysis, ZIC1 expression (in overall survival analysis: hazard ratio [HR], 0.405, 95% confidence interval [CI], 0.233-0.702, p=0.001; in disease-free survival analysis: HR, 0.395, 95% CI, 0.234-0.669, p=0.001) was identified as a prognostic indicator of invasive breast cancer.

Conclusion

ZIC1, but not the other proteins, was obviously decreased in breast tumors and associated with clinicopathologic factors. Thus, ZIC1 might be a novel indicator to predict the overall and disease-free survival of invasive breast cancer patients.

Distinct methylation profile of mucinous ovarian carcinoma reveals susceptibility to proteasome inhibitors

Mucinous type of epithelial ovarian cancer (MuOC) is a unique subtype with a poor survival outcome in recurrent and advanced stages. The role of type-specific epigenomics and its clinical significance remains uncertain. We analyzed the methylomic profiles of 6 benign mucinous adenomas, 24 MuOCs, 103 serous type of epithelial ovarian cancers (SeOCs) and 337 nonepithelial ovarian cancers. MuOC and SeOC exhibited distinct DNA methylation profiles comprising 101 genes, 81 of which exhibited low methylation in MuOC and were associated with the response to glucocorticoid, ATP hydrolysis-coupled proton transport, proteolysis involved in the cellular protein catabolic process and ion transmembrane transport. Hierarchical clustering analysis showed that the profiles of MuOC were similar to colorectal adenocarcinoma and stomach adenocarcinoma. Genetic interaction network analysis of differentially methylated genes in MuOC showed a dominant network module is the proteasome subunit beta (PSMB) family. Combined functional module and methylation analysis identified PSMB8 as a candidate marker for MuOC. Immunohistochemical staining of PSMB8 used to validate in 94 samples of ovarian tumors (mucinous adenoma, MuOC or SeOC) and 62 samples of gastrointestinal cancer. PSMB8 was commonly expressed in MuOC and gastrointestinal cancer samples, predominantly as strong cytoplasmic and occasionally weak nuclei staining, but was not expressed in SeOC samples. Carfilzomib, a second-generation proteasome inhibitor, suppressed MuOC cell growth in vitro. This study unveiled a mucinous-type-specific methylation profile and suggests the potential use of a proteasome inhibitor to treat MuOC.

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.

Methylome analysis of extreme chemoresponsive patients identifies novel markers of platinum sensitivity in high-grade serous ovarian cancer

BACKGROUND

Despite an early response to platinum-based chemotherapy in advanced stage high-grade serous ovarian cancer (HGSOC), the majority of patients will relapse with drug-resistant disease. Aberrant epigenetic alterations like DNA methylation are common in HGSOC. Differences in DNA methylation are associated with chemoresponse in these patients. The objective of this study was to identify and validate novel epigenetic markers of chemoresponse using genome-wide analysis of DNA methylation in extreme chemoresponsive HGSOC patients.

METHODS

Genome-wide next-generation sequencing was performed on methylation-enriched tumor DNA of two HGSOC patient groups with residual disease, extreme responders (≥18 months progression-free survival (PFS), n = 8) and non-responders (≤6 months PFS, n = 10) to platinum-based chemotherapy. DNA methylation and expression data of the same patients were integrated to create a gene list. Genes were validated on an independent cohort of extreme responders (n = 21) and non-responders (n = 31) using pyrosequencing and qRT-PCR. In silico validation was performed using publicly available DNA methylation (n = 91) and expression (n = 208) datasets of unselected advanced stage HGSOC patients. Functional validation of FZD10 on chemosensitivity was carried out in ovarian cancer cell lines using siRNA-mediated silencing.

RESULTS

Integrated genome-wide methylome and expression analysis identified 45 significantly differentially methylated and expressed genes between two chemoresponse groups. Four genes FZD10, FAM83A, MYO18B, and MKX were successfully validated in an external set of extreme chemoresponsive HGSOC patients. High FZD10 and MKX methylation were related with extreme responders and high FAM83A and MYO18B methylation with non-responders. In publicly available advanced stage HGSOC datasets, FZD10 and MKX methylation levels were associated with PFS. High FZD10 methylation was strongly associated with improved PFS in univariate analysis (hazard ratio (HR) = 0.43; 95% CI, 0.27-0.71; P = 0.001) and multivariate analysis (HR = 0.39; 95% CI, 0.23-0.65; P = 0.003). Consistently, low FZD10 expression was associated with improved PFS (HR = 1.36; 95% CI, 0.99-1.88; P = 0.058). FZD10 silencing caused significant sensitization towards cisplatin treatment in survival assays and apoptosis assays.

CONCLUSIONS

By applying genome-wide integrated methylome analysis on extreme chemoresponsive HGSOC patients, we identified novel clinically relevant, epigenetically-regulated markers of platinum-sensitivity in HGSOC patients. The clinical potential of these markers in predictive and therapeutic approaches has to be further validated in prospective studies.

An epigenetic signature of adhesion molecules predicts poor prognosis of ovarian cancer patients

DNA methylation is a promising biomarker for cancer. The epigenetic effects of cell adhesion molecules may affect the therapeutic outcome and the present study examined their effects on survival in ovarian cancer. We integrated methylomics and genomics datasets in The Cancer Genome Atlas (n = 391) and identified 106 highly methylated adhesion-related genes in ovarian cancer tissues. Univariate analysis revealed the methylation status of eight genes related to progression-free survival. In multivariate Cox regression analysis, four highly methylated genes (CD97, CTNNA1, DLC1, HAPLN2) and three genes (LAMA4, LPP, MFAP4) with low methylation were significantly associated with poor progression-free survival. Low methylation of VTN was an independent poor prognostic factor for overall survival after adjustment for age and stage. Patients who carried any two of CTNNA1, DLC1 or MFAP4 were significantly associated with poor progression-free survival (hazard ratio: 1.59; 95% confidence interval: 1.23, 2.05). This prognostic methylation signature was validated in a methylomics dataset generated in our lab (n = 37, hazard ratio: 16.64; 95% confidence interval: 2.68, 103.14) and in another from the Australian Ovarian Cancer Study (n = 91, hazard ratio: 2.43; 95% confidence interval: 1.11, 5.36). Epigenetics of cell adhesion molecules is related to ovarian cancer prognosis. A more comprehensive methylomics of cell adhesion molecules is needed and may advance personalized treatment with adhesion molecule-related drugs.

Methylomics of nitroxidative stress on precancerous cells reveals DNA methylation alteration at the transition from in situ to invasive cervical cancer

Epigenetic dysregulation is important in cervical cancer development, but the underlying mechanism is largely unknown. Increasing evidence indicates that DNA methylation is sensitive to changes in microenvironmental factors, such as nitric oxide (NO) in the chronic inflammatory cervix. However, the epigenomic effects of NO in cancer have not been investigated. In this study, we explored the methylomic effects of nitroxidative stress in HPV-immortalized precancerous cells. Chronic NO exposure promoted the acquisition of malignant phenotypes such as cell growth, migration, invasion, and anchorage-independent growth. Epigenetic analysis confirmed hypermethylation of PTPRR. Whole-genome methylation analysis showed BOLA2B, FGF8, HSPA6, LYPD2, and SHE were hypermethylated in cells. The hypermethylation BOLA2B, FGF8, HSPA6, and SHE was confirmed in cervical scrapings from invasive cancer, but not in CIN3/CIS, CIN2 and CIN1 (p=0.019, 0.023, 0.023 and 0.027 respectively), suggesting the role in the transition from in situ to invasive process. Our results reveal that nitroxidative stress causes epigenetic changes in HPV-infected cells. Investigation of these methylation changes in persistent HPV infection may help identify new biomarkers of DNA methylation for cervical cancer screening, especially for precancerous lesions.

Mutual regulation of microRNAs and DNA methylation in human cancers

microRNAs (miRNAs) and DNA methylation are the 2 epigenetic modifications that have emerged in recent years as the most critical players in the regulation of gene expression. Compelling evidence has indicated the roles of miRNAs and DNA methylation in modulating cellular transformation and tumorigenesis. miRNAs act as negative regulators of gene expression and are involved in the regulation of both physiologic conditions and during diseases, such as cancer, inflammatory diseases, and psychiatric disorders, among others. Meanwhile, aberrant DNA methylation manifests in both global genome changes and in localized gene promoter changes, which influences the transcription of cancer genes. In this review, we described the mutual regulation of miRNAs and DNA methylation in human cancers. miRNAs regulate DNA methylation by targeting DNA methyltransferases or methylation-related proteins. On the other hand, both hyper- and hypo-methylation of miRNAs occur frequently in human cancers and represent a new level of complexity in gene regulation. Therefore, understanding the mechanisms underlying the mutual regulation of miRNAs and DNA methylation may provide helpful insights in the development of efficient therapeutic approaches.

Genome-wide methylation profiling of ovarian cancer patient-derived xenografts treated with the demethylating agent decitabine identifies novel epigenetically regulated genes and pathways

Background

In high-grade serous ovarian cancer (HGSOC), intrinsic and/or acquired resistance against platinum-containing chemotherapy is a major obstacle for successful treatment. A low frequency of somatic mutations but frequent epigenetic alterations, including DNA methylation in HGSOC tumors, presents the cancer epigenome as a relevant target for innovative therapy. Patient-derived xenografts (PDXs) supposedly are good preclinical models for identifying novel drug targets. However, the representativeness of global methylation status of HGSOC PDXs compared to their original tumors has not been evaluated so far. Aims of this study were to explore how representative HGSOC PDXs are of their corresponding patient tumor methylome and to evaluate the effect of epigenetic therapy and cisplatin on putative epigenetically regulated genes and their related pathways in PDXs.

Methods

Genome-wide analysis of the DNA methylome of HGSOC patients with their corresponding PDXs, from different generations, was performed using Infinium 450 K methylation arrays. Furthermore, we analyzed global methylome changes after treatment of HGSOC PDXs with the FDA approved demethylating agent decitabine and cisplatin. Findings were validated by bisulfite pyrosequencing with subsequent pathway analysis. Publicly available datasets comprising HGSOC patients were used to analyze the prognostic value of the identified genes.

Results

Only 0.6–1.0 % of all analyzed CpGs (388,696 CpGs) changed significantly (p < 0.01) during propagation, showing that HGSOC PDXs were epigenetically stable. Treatment of F3 PDXs with decitabine caused a significant reduction in methylation in 10.6 % of CpG sites in comparison to untreated PDXs (p < 0.01, false discovery rate <10 %). Cisplatin treatment had a marginal effect on the PDX methylome. Pathway analysis of decitabine-treated PDX tumors revealed several putative epigenetically regulated pathways (e.g., the Src family kinase pathway). In particular, the C-terminal Src kinase (CSK) gene was successfully validated for epigenetic regulation in different PDX models and ovarian cancer cell lines. Low CSK methylation and high CSK expression were both significantly associated (p < 0.05) with improved progression-free survival and overall survival in HGSOC patients.

Conclusions

HGSOC PDXs resemble the global epigenome of patients over many generations and can be modulated by epigenetic drugs. Novel epigenetically regulated genes such as CSK and related pathways were identified in HGSOC. Our observations encourage future application of PDXs for cancer epigenome studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0361-5) contains supplementary material, which is available to authorized users.

Tripartite Motif 16 Inhibits the Migration and Invasion in Ovarian Cancer Cells

Tripartite motif 16 (TRIM16), a member of the RING B-box coiled-coil (RBCC)/tripartite motif (TRIM) protein family, has been shown to play a role in tumor development and progression. However, the role of TRIM16 in ovarian cancer has never been revealed. Thus, in this study, we investigated the roles and mechanisms of TRIM16 in ovarian cancer. Our results demonstrated that TRIM16 expression was low in ovarian cancer cell lines. In addition, overexpression of TRIM16 significantly inhibited the migration and invasion in vitro, as well as suppressed the epithelial-mesenchymal transition (EMT) phenotype in ovarian cancer cells. Furthermore, overexpression of TRIM16 greatly inhibited the protein expression levels of Shh, Smo, Ptc, Gli-1, MMP2, and MMP9 in ovarian cancer cells. Taken together, these results strongly suggest that TRIM16 inhibits the migration and invasion via suppressing the Sonic hedgehog signaling pathway in ovarian cancer cells. Thus, TRIM16 may be a novel potential therapeutic target for ovarian cancer.

Cracking the Code of Human Diseases Using Next-Generation Sequencing: Applications, Challenges, and Perspectives

Next-generation sequencing (NGS) technologies have greatly impacted on every field of molecular research mainly because they reduce costs and increase throughput of DNA sequencing. These features, together with the technology's flexibility, have opened the way to a variety of applications including the study of the molecular basis of human diseases. Several analytical approaches have been developed to selectively enrich regions of interest from the whole genome in order to identify germinal and/or somatic sequence variants and to study DNA methylation. These approaches are now widely used in research, and they are already being used in routine molecular diagnostics. However, some issues are still controversial, namely, standardization of methods, data analysis and storage, and ethical aspects. Besides providing an overview of the NGS-based approaches most frequently used to study the molecular basis of human diseases at DNA level, we discuss the principal challenges and applications of NGS in the field of human genomics.

Statistical methods for detecting differentially methylated regions based on MethylCap-seq data

DNA methylation is a well-established epigenetic mark, whose pattern throughout the genome, especially in the promoter or CpG islands, may be modified in a cell at a disease stage. Recently developed probabilistic approaches allow distributing methylation signals at nucleotide resolution from MethylCap-seq data. Standard statistical methods for detecting differential methylation suffer from 'curse of dimensionality' and sparsity in signals, resulting in high false-positive rates. Strong correlation of signals between CG sites also yields spurious results. In this article, we review applicability of high-dimensional mean vector tests for detection of differentially methylated regions (DMRs) and compare and contrast such tests with other methods for detecting DMRs. Comprehensive simulation studies are conducted to highlight the performance of these tests under different settings. Based on our observation, we make recommendations on the optimal test to use. We illustrate the superiority of mean vector tests in detecting cancer-related canonical gene pathways, which are significantly enriched for acute myeloid leukemia and ovarian cancer.

Emerging technologies for studying DNA methylation for the molecular diagnosis of cancer

DNA methylation is an epigenetic mechanism that plays a key role in regulating gene expression and other functions. Although this modification is seen in different sequence contexts, the most frequently detected DNA methylation in mammals involves cytosine-guanine dinucleotides. Pathological alterations in DNA methylation patterns are described in a variety of human diseases, including cancer. Unlike genetic changes, DNA methylation is heavily influenced by subtle modifications in the cellular microenvironment. In all cancers, aberrant DNA methylation is involved in the alteration of a large number of oncological pathways with relevant theranostic utility. Several technologies for DNA methylation mapping have been developed recently and successfully applied in cancer studies. The scope of these technologies varies from assessing a single cytosine-guanine locus to genome-wide distribution of DNA methylation. Here, we review the strengths and weaknesses of these approaches in the context of clinical utility for the molecular diagnosis of human cancers.

Genome-wide DNA methylation analysis reveals estrogen-mediated epigenetic repression of metallothionein-1 gene cluster in breast cancer

Background

Recent genome-wide analysis has shown that DNA methylation spans long stretches of chromosome regions consisting of clusters of contiguous CpG islands or gene families. Hypermethylation of various gene clusters has been reported in many types of cancer. In this study, we conducted methyl-binding domain capture (MBDCap) sequencing (MBD-seq) analysis on a breast cancer cohort consisting of 77 patients and 10 normal controls, as well as a panel of 38 breast cancer cell lines.

Results

Bioinformatics analysis determined seven gene clusters with a significant difference in overall survival (OS) and further revealed a distinct feature that the conservation of a large gene cluster (approximately 70 kb) metallothionein-1 (MT1) among 45 species is much lower than the average of all RefSeq genes. Furthermore, we found that DNA methylation is an important epigenetic regulator contributing to gene repression of MT1 gene cluster in both ERα positive (ERα+) and ERα negative (ERα−) breast tumors. In silico analysis revealed much lower gene expression of this cluster in The Cancer Genome Atlas (TCGA) cohort for ERα + tumors. To further investigate the role of estrogen, we conducted 17β-estradiol (E2) and demethylating agent 5-aza-2′-deoxycytidine (DAC) treatment in various breast cancer cell types. Cell proliferation and invasion assays suggested MT1F and MT1M may play an anti-oncogenic role in breast cancer.

Conclusions

Our data suggests that DNA methylation in large contiguous gene clusters can be potential prognostic markers of breast cancer. Further investigation of these clusters revealed that estrogen mediates epigenetic repression of MT1 cluster in ERα + breast cancer cell lines. In all, our studies identify thousands of breast tumor hypermethylated regions for the first time, in particular, discovering seven large contiguous hypermethylated gene clusters.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-015-0045-9) contains supplementary material, which is available to authorized users.

Global DNA methylation profiling technologies and the ovarian cancer methylome

Cytosine methylation in DNA constitutes an important epigenetic layer of transcriptional and regulatory control in many eukaryotes. Profiling DNA methylation across the genome is critical to understanding the influence of epigenetics in normal biology and disease, such as cancer. Genome-wide analyses such as arrays and next-generation sequencing (NGS) technologies have been used to assess large fractions of the methylome at a single-base-pair resolution. However, the range of DNA methylation profiling techniques can make selecting the appropriate protocol a challenge. This chapter discusses the advantages and disadvantages of various methylome detection approaches to assess which is appropriate for the question at hand. Here, we focus on four prominent genome-wide approaches: whole-genome bisulfite sequencing (WGBS); methyl-binding domain capture sequencing (MBDCap-Seq); reduced-representation-bisulfite-sequencing (RRBS); and Infinium Methylation450 BeadChips (450 K, Illumina). We discuss some of the requirements, merits, and challenges that should be considered when choosing a methylome technology to ensure that it will be informative. In addition, we show how genome-wide methylation detection arrays and high-throughput sequencing have provided immense insight into ovarian cancer-specific methylation signatures that may serve as diagnostic biomarkers or predict patient response to epigenetic therapy.

DNA methylation profiling reveals novel diagnostic biomarkers in renal cell carcinoma

BACKGROUND

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.

METHODS

We examined genome-wide DNA methylation alterations in renal cell carcinomas of diverse histologies and benign adjacent kidney tissues from 96 patients.

RESULTS

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.

CONCLUSIONS

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.

The novel, small-molecule DNA methylation inhibitor SGI-110 as an ovarian cancer chemosensitizer

PURPOSE

To investigate SGI-110 as a "chemosensitizer" in ovarian cancer and to assess its effects on tumor suppressor genes (TSG) and chemoresponsiveness-associated genes silenced by DNA methylation in ovarian cancer.

EXPERIMENTAL DESIGN

Several ovarian cancer cell lines were used for in vitro and in vivo platinum resensitization studies. Changes in DNA methylation and expression levels of TSG and other cancer-related genes in response to SGI-110 were measured by pyrosequencing and RT-PCR.

RESULTS

We demonstrate in vitro that SGI-110 resensitized a range of platinum-resistant ovarian cancer cells to cisplatin (CDDP) and induced significant demethylation and reexpression of TSG, differentiation-associated genes, and putative drivers of ovarian cancer cisplatin resistance. In vivo, SGI-110 alone or in combination with CDDP was well tolerated and induced antitumor effects in ovarian cancer xenografts. Pyrosequencing analyses confirmed that SGI-110 caused both global (LINE1) and gene-specific hypomethylation in vivo, including TSGs (RASSF1A), proposed drivers of ovarian cancer cisplatin resistance (MLH1 and ZIC1), differentiation-associated genes (HOXA10 and HOXA11), and transcription factors (STAT5B). Furthermore, DNA damage induced by CDDP in ovarian cancer cells was increased by SGI-110, as measured by inductively coupled plasma-mass spectrometry analysis of DNA adduct formation and repair of cisplatin-induced DNA damage.

CONCLUSIONS

These results strongly support further investigation of hypomethylating strategies in platinum-resistant ovarian cancer. Specifically, SGI-110 in combination with conventional and/or targeted therapeutics warrants further development in this setting.

Decitabine reactivated pathways in platinum resistant ovarian cancer

Combination therapy with decitabine, a DNMTi and carboplatin resensitized chemoresistant ovarian cancer (OC) to platinum inducing promising clinical activity. We investigated gene-expression profiles in tumor biopsies to identify decitabine-reactivated pathways associated with clinical response. Gene-expression profiling was performed using RNA from paired tumor biopsies before and 8 days after decitabine from 17 patients with platinum resistant OC. Bioinformatic analysis included unsupervised hierarchical-clustering, pathway and GSEA distinguishing profiles of "responders" (progression-free survival, PFS>6 months) and "non-responders" (PFS< 6 months). Functional validation of selected results was performed in OC cells/tumors. Pre-treatment tumors from responders expressed genes associated with enhanced glycosphingolipid biosynthesis, translational misregulation, decreased ABC transporter expression, TGF-β signaling, and numerous metabolic pathways. Analysis of post-treatment biopsies from responders revealed overexpression of genes associated with reduced Hedgehog pathway signaling, reduced DNA repair/replication, and cancer-associated metabolism. GO and GSEA analyses revealed upregulation of genes associated with glycosaminoglycan binding, cell-matrix adhesion, and cell-substrate adhesion. Computational findings were substantiated by experimental validation of expression of key genes involved in two critical pathways affected by decitabine (TGF-β and Hh). Gene-expression profiling identified specific pathways altered by decitabine and associated with platinum-resensitization and clinical benefit in OC. Our data could influence patient stratification for future studies using epigenetic therapies.

Molecular epigenetics in the management of ovarian cancer: are we investigating a rational clinical promise?

Epigenetics is essentially a phenotypical change in gene expression without any alteration of the DNA sequence; the emergence of epigenetics in cancer research and mainstream oncology is fueling new hope. However, it is not yet known whether this knowledge will translate to improved clinical management of ovarian cancer. In this malignancy, women are still undergoing chemotherapy similar to what was approved in 1978, which to this day represents one of the biggest breakthroughs for treating ovarian cancer. Although liquid tumors are benefiting from epigenetically related therapies, solid tumors like ovarian cancer are not (yet?). Herein, we will review the science of molecular epigenetics, especially DNA methylation, histone modifications and microRNA, but also include transcription factors since they, too, are important in ovarian cancer. Pre-clinical and clinical research on the role of epigenetic modifications is also summarized. Unfortunately, ovarian cancer remains an idiopathic disease, for the most part, and there are many areas of patient management, which could benefit from improved technology. This review will also highlight the evidence suggesting that epigenetics may have pre-clinical utility in pharmacology and clinical applications for prognosis and diagnosis. Finally, drugs currently in clinical trials (i.e., histone deacetylase inhibitors) are discussed along with the promise for epigenetics in the exploitation of chemoresistance. Whether epigenetics will ultimately be the answer to better management in ovarian cancer is currently unknown; but we hope so in the future.

Next-generation technologies and data analytical approaches for epigenomics

Epigenetics refers to the collection of heritable features that modulate the genome-environment interaction without being encoded in the actual DNA sequence. While being mitotically and sometimes even meiotically transmitted, epigenetic traits often demonstrate extensive flexibility. This allows cells to acquire diverse gene expression patterns during differentiation, but also to adapt to a changing environment. However, epigenetic alterations are not always beneficial to the organism, as they are, for example, frequently identified in human diseases such as cancer. Accurate and cost-efficient genome-scale profiling of epigenetic features is thus of major importance to pinpoint these "epimutations," for example, to monitor the epigenetic impact of environmental exposure. Over the last decade, the field of epigenetics has been revolutionized by several innovative "epigenomics" technologies exactly addressing this need. In this review, we discuss and compare widely used next-generation methods to assess DNA methylation and hydroxymethylation, noncoding RNA expression, histone modifications, and nucleosome positioning. Although recent methods are typically based on "second-generation" sequencing, we also pay attention to still commonly used array- and PCR-based methods, and look forward to the additional advantages of single-molecule sequencing. As the current bottleneck in epigenomics research is the analysis rather than generation of data, the basic difficulties and problem-solving strategies regarding data preprocessing and statistical analysis are introduced for the different technologies. Finally, we also consider the complications associated with epigenomic studies of species with yet unsequenced genomes and possible solutions.

Ras-induced epigenetic inactivation of the RRAD (Ras-related associated with diabetes) gene promotes glucose uptake in a human ovarian cancer model

RRAD (Ras-related associated with diabetes) is a small Ras-related GTPase that is frequently inactivated by DNA methylation of the CpG island in its promoter region in cancer tissues. However, the role of the methylation-induced RRAD inactivation in tumorigenesis remains unclear. In this study, the Ras-regulated transcriptome and epigenome were profiled by comparing T29H (a Ras(V12)-transformed human ovarian epithelial cell line) with T29 (an immortalized but non-transformed cell line) through reduced representation bisulfite sequencing and digital gene expression. We found that Ras(V12)-mediated oncogenic transformation was accompanied by RRAD promoter hypermethylation and a concomitant loss of RRAD expression. In addition, we found that the RRAD promoter was hypermethylated, and its transcription was reduced in ovarian cancer versus normal ovarian tissues. Treatment with the DNA methyltransferase inhibitor 5-aza-2'-deoxycytidine resulted in demethylation in the RRAD promoter and restored RRAD expression in T29H cells. Additionally, treatment with farnesyltransferase inhibitor FTI277 resulted in restored RRAD expression and inhibited DNA methytransferase expression and activity in T29H cells. By employing knockdown and overexpression techniques in T29 and T29H, respectively, we found that RRAD inhibited glucose uptake and lactate production by repressing the expression of glucose transporters. Finally, RRAD overexpression in T29H cells inhibited tumor formation in nude mice, suggesting that RRAD is a tumor suppressor gene. Our results indicate that Ras(V12)-mediated oncogenic transformation induces RRAD epigenetic inactivation, which in turn promotes glucose uptake and may contribute to ovarian cancer tumorigenesis.

Pathway modulations and epigenetic alterations in ovarian tumorbiogenesis

Cellular pathways are numerous and are highly integrated in function in the control of cellular systems. They collectively regulate cell division, proliferation, survival and apoptosis of cells and mutagenesis of key genes that control these pathways can initiate neoplastic transformations. Understanding these pathways is crucial to future therapeutic and preventive strategies of the disease. Ovarian cancers are of three major types; epithelial, germ-cell, and stromal. However, ovarian cancers of epithelial origin, arising from the mesothelium, are the predominant form. Of the subtypes of ovarian cancer, the high-grade serous tumors are fatal, with low survival rate due to late detection and poor response to treatments. Close examination of preserved ovarian tissues and in vitro studies have provided insights into the mechanistic changes occurring in cells mediated by a few key genes. This review will focus on pathways and key genes of the pathways that are mutated or have aberrant functions in the pathology of ovarian cancer. Non-genetic mechanisms that are gaining prominence in the pathology of ovarian cancer, miRNAs and epigenetics, will also be discussed in the review.

DNA methylation profiling can classify HIV-associated lymphomas

BACKGROUND

HIV-positive patients have a 60-fold to 200-fold increased incidence of non-Hodgkin lymphomas, including Burkitt lymphoma, diffuse large B-cell lymphoma, and primary central nervous system lymphoma. HIV-associated lymphomas frequently have features such as extranodal involvement, decreased responses to standard chemotherapy, and high relapse rates, which indicate a poor prognosis. General pathological features do not clearly differentiate HIV-associated lymphomas from non-HIV lymphomas.

METHODS

To investigate the features of HIV-associated lymphomas, we performed genome-wide DNA methylation profiling of HIV and non-HIV lymphomas using Illumina GoldenGate Methylation Cancer Panel I and Illumina Infinium HumanMethylation450 BeadChip microarrays. DNA methylation profiles in HIV-associated and non-HIV lymphomas were characterized using unsupervised hierarchical clustering analyses.

RESULTS

The analyses of promoter regions revealed unique DNA methylation profiles in HIV-associated lymphomas, suggesting profile differences compared with non-HIV lymphomas, which implies specific gene regulation in HIV-associated lymphoma involving DNA methylation. Based on HumanMethylation450 BeadChip data, 2541 target sites were selected as differing significantly in comparisons between HIV-associated and non-HIV-associated lymphomas using Wilcoxon's rank-sum test (P <0.05) and Δβ values more than 0.30. Recurrent cases of HIV-associated lymphoma had different profiles compared with nonrecurrent HIV lymphomas.

CONCLUSION

DNA methylation profiling indicated that 2541 target sites differed significantly in HIV-associated lymphoma, which may partly explain the poor prognosis. Our data indicate that the methylation profiles of target genes have potential in elucidating HIV-associated lymphomagenesis and can serve as new prognostic markers.

Ovarian cancer stem cells: are they real and why are they important?

The cancer stem cell hypothesis has been put forward as a paradigm to describe varying levels of aggressiveness in heterogeneous tumors. Specifically, many subpopulations have been clearly demonstrated to possess increased tumorigenicity in mice, broad differentiating capacity, and resistance to therapy. However, the extent to which these experimental findings are potentially clinically significant is still not clear. This review will describe the principles of this emerging hypothesis, ways in which it may be appropriate in ovarian cancer based on the clinical course of the disease, and how we might exploit it to improve outcomes in ovarian cancer patients.