DNA methylation profiles of ovarian epithelial carcinoma tumors and cell lines

Current Applications and Challenges of Next-Generation Sequencing in Plasma Circulating Tumour DNA of Ovarian Cancer

Circulating tumour DNA (ctDNA) facilitates longitudinal study of the tumour genome, which, unlike tumour tissue biopsies, globally reflects intratumor and intermetastatis heterogeneity. Despite its costs, next-generation sequencing (NGS) has revolutionised the study of ctDNA, ensuring a more comprehensive and multimodal approach, increasing data collection, and introducing new variables that can be correlated with clinical outcomes. Current NGS strategies can comprise a tumour-informed set of genes or the entire genome and detect a tumour fraction as low as 10-5. Despite some conflicting studies, there is evidence that ctDNA levels can predict the worse outcomes of ovarian cancer (OC) in both early and advanced disease. Changes in those levels can also be informative regarding treatment efficacy and tumour recurrence, capable of outperforming CA-125, currently the only universally utilised plasma biomarker in high-grade serous OC (HGSOC). Qualitative evaluation of sequencing shows that increasing copy number alterations and gene variants during treatment may correlate with a worse prognosis in HGSOC. However, following tumour clonality and emerging variants during treatment poses a more unique opportunity to define treatment response, select patients based on their emerging resistance mechanisms, like BRCA secondary mutations, and discover potential targetable variants. Sequencing of tumour biopsies and ctDNA is not always concordant, likely as a result of clonal heterogeneity, which is better captured in the plasma samples than it is in a large number of biopsies. These incoherences may reflect tumour clonality and reveal the acquired alterations that cause treatment resistance. Cell-free DNA methylation profiles can be used to distinguish OC from healthy individuals, and NGS methylation panels have been shown to have excellent diagnostic capabilities. Also, methylation signatures showed promise in explaining treatment responses, including BRCA dysfunction. ctDNA is evolving as a promising new biomarker to track tumour evolution and clonality through the treatment of early and advanced ovarian cancer, with potential applicability in prognostic prediction and treatment selection. While its role in HGSOC paves the way to clinical applicability, its potential interest in other histological subtypes of OC remains unknown.

The role of DNA methylation in ovarian cancer chemoresistance: A narrative review

Background and Aims

Ovarian cancer (OC) is the most lethal gynecological cancer. In 2018, it was responsible for over 180,000 deaths worldwide. The high mortality rate is the culmination of a lack of early diagnosis and high rates of chemotherapy resistance, which is synonymous with disease recurrence. Over the last two decades, an increasingly significant role of epigenetic mechanisms, in particular DNA methylation, has emerged. This review will discuss several of the most significant genes whose hypo/hypermethylation profiles are associated with chemoresistance. Aside from functionally elucidating and evaluating these epimutations, this review will discuss recent trials of DNA methyltransferase inhibitors (DNMTi). Finally, we will propose future directions that could enhance the feasibility of utilizing these candidate epimutations as clinical biomarkers.

Methods

To perform this review, a comprehensive literature search based on our keywords was conducted across the online databases PubMed and Google Scholar for identifying relevant studies published up until August 2022.

Results

Epimutations affecting MLH1, MSH2, and Ras-association domain family 1 isoform A (DNA damage repair and apoptosis); ATP-binding cassette subfamily B member 1 and methylation-controlled J (drug export); secreted frizzled-related proteins (Wnt/β-catenin signaling), neurocalcin delta (calcium and G protein-coupled receptor signaling), and zinc finger protein 671 all have potential as biomarkers for chemoresistance. However, specific uncertainties relating to these epimutations include histotype-specific differences, intrinsic versus acquired chemoresistance, and the interplay with complete surgical debulking. DNMTi for chemoresistant OC patients has shown some promise; however, issues surrounding their efficacy and dose-limiting toxicities remain; a personalized approach is required to maximize their effectiveness.

Conclusion

Establishing a panel of aberrantly methylated chemoresistance-related genes to predict chemoresponsiveness and patients' suitability to DNMTi could significantly reduce OC recurrence, while improving DNMTi therapy viability. To achieve this, a large-scale prospective genome-wide DNA methylation profile study that spans different histotypes, includes paired samples (before and after chemotherapy), and integrates transcriptomic and methylomic analysis, is warranted.

Role of DNA methylation in the relationship between glioma risk factors and glioma incidence: a two-step Mendelian randomization study

Genetic evidence suggests glioma risk is altered by leukocyte telomere length, allergic disease (asthma, hay fever or eczema), alcohol consumption, childhood obesity, low-density lipoprotein cholesterol (LDLc) and triglyceride levels. DNA methylation (DNAm) variation influences many of these glioma-related traits and is an established feature of glioma. Yet the causal relationship between DNAm variation with both glioma incidence and glioma risk factors is unknown. We applied a two-step Mendelian randomization (MR) approach and several sensitivity analyses (including colocalization and Steiger filtering) to assess the association of DNAm with glioma risk factors and glioma incidence. We used data from a recently published catalogue of germline genetic variants robustly associated with DNAm variation in blood (32,851 participants) and data from a genome-wide association study of glioma risk (12,488 cases and 18,169 controls, sub-divided into 6191 glioblastoma cases and 6305 non-glioblastoma cases). MR evidence indicated that DNAm at 3 CpG sites (cg01561092, cg05926943, cg01584448) in one genomic region (HEATR3) had a putative association with glioma and glioblastoma risk (False discovery rate [FDR] < 0.05). Steiger filtering provided evidence against reverse causation. Colocalization presented evidence against genetic confounding and suggested that differential DNAm at the 3 CpG sites and glioma were driven by the same genetic variant. MR provided little evidence to suggest that DNAm acts as a mediator on the causal pathway between risk factors previously examined and glioma onset. To our knowledge, this is the first study to use MR to appraise the causal link of DNAm with glioma risk factors and glioma onset. Subsequent analyses are required to improve the robustness of our results and rule out horizontal pleiotropy.

Review the progression of ovarian clear cell carcinoma from the perspective of genomics and epigenomics

Ovarian clear cell carcinoma (OCCC) is a rare subtype of epithelial ovarian cancer with unique molecular characteristics, specific biological and clinical behavior, poor prognosis and high resistance to chemotherapy. Pushed by the development of genome-wide technologies, our knowledge about the molecular features of OCCC has been considerably advanced. Numerous studies are emerging as groundbreaking, and many of them are promising treatment strategies. In this article, we reviewed studies about the genomics and epigenetics of OCCC, including gene mutation, copy number variations, DNA methylation and histone modifications.

DNA methylation-based profiling reveals distinct clusters with survival heterogeneity in high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) is the most common type of epigenetically heterogeneous ovarian cancer. Methylation typing has previously been used in many tumour types but not in HGSOC. Methylation typing in HGSOC may promote the development of personalized care. The present study used DNA methylation data from The Cancer Genome Atlas database and identified four unique methylation subtypes of HGSOC. With the poorest prognosis and high frequency of residual tumours, cluster 4 featured hypermethylation of a panel of genes, which indicates that demethylation agents may be tested in this group and that neoadjuvant chemotherapy may be used to reduce the possibility of residual lesions. Cluster 1 and cluster 2 were significantly associated with metastasis genes and metabolic disorders, respectively. Two feature CpG sites, cg24673765 and cg25574024, were obtained through Cox proportional hazards model analysis of the CpG sites. Based on the methylation level of the two CpG sites, the samples were classified into high- and low-risk groups to identify the prognostic information. Similar results were obtained in the validation set. Taken together, these results explain the epigenetic heterogeneity of HGSOC and provide guidance to clinicians for the prognosis of HGSOC based on DNA methylation sites.

A pan-cancer survey of cell line tumor similarity by feature-weighted molecular profiles

Patient-derived cell lines are often used in pre-clinical cancer research, but some cell lines are too different from tumors to be good models. Comparison of genomic and expression profiles can guide the choice of pre-clinical models, but typically not all features are equally relevant. We present TumorComparer, a computational method for comparing cellular profiles with higher weights on functional features of interest. In this pan-cancer application, we compare ∼600 cell lines and ∼8,000 tumor samples of 24 cancer types, using weights to emphasize known oncogenic alterations. We characterize the similarity of cell lines and tumors within and across cancers by using multiple datum types and rank cell lines by their inferred quality as representative models. Beyond the assessment of cell lines, the weighted similarity approach is adaptable to patient stratification in clinical trials and personalized medicine.

The Role of H3K4 Trimethylation in CpG Islands Hypermethylation in Cancer

CpG methylation in transposons, exons, introns and intergenic regions is important for long-term silencing, silencing of parasitic sequences and alternative promoters, regulating imprinted gene expression and determining X chromosome inactivation. Promoter CpG islands, although rich in CpG dinucleotides, are unmethylated and remain so during all phases of mammalian embryogenesis and development, except in specific cases. The biological mechanisms that contribute to the maintenance of the unmethylated state of CpG islands remain elusive, but the modification of established DNA methylation patterns is a common feature in all types of tumors and is considered as an event that intrinsically, or in association with genetic lesions, feeds carcinogenesis. In this review, we focus on the latest results describing the role that the levels of H3K4 trimethylation may have in determining the aberrant hypermethylation of CpG islands in tumors.

A Biobank of Colorectal Cancer Patient-Derived Xenografts

Colorectal cancer (CRC) is a challenging disease, with a high mortality rate and limited effective treatment options, particularly for late-stage disease. Patient-derived xenografts (PDXs) have emerged as an informative, renewable experimental resource to model CRC architecture and biology. Here, we describe the generation of a biobank of CRC PDXs from stage I to stage IV patients. We demonstrate that PDXs within our biobank recapitulate the histopathological and mutation features of the original patient tumor. In addition, we demonstrate the utility of this resource in pre-clinical chemotherapy and targeted treatment studies, highlighting the translational potential of PDX models in the identification of new therapies that will improve the overall survival of CRC patients.

Epigenomics-Guided Drug Development: Recent Advances in Solving the Cancer Treatment "jigsaw puzzle"

The human epigenome plays a key role in determining cellular identity and eventually function. Drug discovery undertakings have focused mainly on the role of genomics in carcinogenesis, with the focus turning to the epigenome recently. Drugs targeting DNA and histone modifications are under development with some such as 5-azacytidine, decitabine, vorinostat, and panobinostat already approved by the Food and Drug Administration (FDA) and the European Medicines Agency (EMA). This expert review offers a critical analysis of the epigenomics-guided drug discovery and development and the opportunities and challenges for the next decade. Importantly, the coupling of epigenetic editing techniques, such as clustered regularly interspersed short palindromic repeat (CRISPR)-CRISPR-associated protein-9 (Cas9) and APOBEC-coupled epigenetic sequencing (ACE-seq) with epigenetic drug screens, will allow the identification of small-molecule inhibitors or drugs able to reverse epigenetic changes responsible for many diseases. In addition, concrete and sustainable innovation in cancer treatment ought to integrate epigenome targeting drugs with classic therapies such as chemotherapy and immunotherapy.

Anti-Cancer Effects of Synergistic Drug-Bacterium Combinations on Induced Breast Cancer in BALB/c Mice

Cancer development and progression are extremely complex due to the alteration of various genes and pathways. In most cases, multiple agents are required to control cancer progression. The purpose of this study is to investigate, using a mouse model, the synergistic interactions of anti-cancer agents, 1'-S-1'-acetoxychavicol acetate (ACA), Mycobacterium indicus pranii (MIP), and cisplatin (CDDP) in double and triple combinations to treat chemo-sensitize and immune-sensitize breast cancer. Changes in tumor volume and body weight were monitored. Organs were harvested and stained using hematoxylin-eosin for histopathological assessment. Milliplex enzyme-linked immunosorbent assay (ELISA) was performed to determine cytokine levels, while immunohistochemistry (IHC) was conducted on tumor biopsies to verify systemic drug effects. In vivo mouse models showed tumor regression with maintenance of regular body weight for all the different treatment regimens. IHC results provided conclusive evidence indicating that combination regimens were able to down-regulate nuclear factor kappa-B activation and reduce the expression of its regulated pro-inflammatory proteins. Reduction of pro-inflammatory cytokines (e.g., IL-6, TNF-α, and IFN-ɣ) levels were observed when using the triple combination, which indicated that the synergistic drug combination was able to significantly control cancer progression. In conclusion, ACA, MIP, and CDDP together serve as promising candidates for further development and for subsequent clinical trials against estrogen-sensitive breast cancer.

Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models

Patient-derived tumor xenograft (PDX) mouse models are widely used for drug screening. The underlying assumption is that PDX tissue is very similar with the original patient tissue, and it has the same response to the drug treatment. To investigate whether the primary tumor site information is well preserved in PDX, we analyzed the gene expression profiles of PDX mouse models originated from different tissues, including breast, kidney, large intestine, lung, ovary, pancreas, skin, and soft tissues. The popular Monte Carlo feature selection method was employed to analyze the expression profile, yielding a feature list. From this list, incremental feature selection and support vector machine (SVM) were adopted to extract distinctively expressed genes in PDXs from different primary tumor sites and build an optimal SVM classifier. In addition, we also set up a group of quantitative rules to identify primary tumor sites. A total of 755 genes were extracted by the feature selection procedures, on which the SVM classifier can provide a high performance with MCC 0.986 on classifying primary tumor sites originated from different tissues. Furthermore, we obtained 16 classification rules, which gave a lower accuracy but clear classification procedures. Such results validated that the primary tumor site specificity was well preserved in PDX as the PDXs from different primary tumor sites were still very different and these PDX differences were similar with the differences observed in patients with tumor. For example, VIM and ABHD17C were highly expressed in the PDX from breast tissue and also highly expressed in breast cancer patients.

Involvement of epigenetic modification of TERT promoter in response to all-trans retinoic acid in ovarian cancer cell lines

BACKGROUND

All-trans retinoic acid (ATRA) is currently being used to treat hematological malignancies, given the ability to inhibit cell proliferation. This effect seems to be related to epigenetic changes of the TERT (Telomerase Reverse Transcriptase) promoter. When hypomethylated, ATRA-inducible TERT repressors can bind the promoter, repressing transcription of TERT, the rate-limiting component of telomerase. Ovarian carcinomas are heterogeneous tumors characterized by several aberrantly methylated genes among which is TERT. We recently found a hypomethylation of TERT promoter in about one third of serous carcinoma, the most lethal histotype. Our aim was to investigate the potential role of ATRA as an anticancer drug in a sub-group of ovarian carcinoma where the TERT promoter was hypomethylated.

METHODS

The potential antiproliferative and cytotoxic effect of ATRA was investigated in seven serous ovarian carcinoma and one teratocarcinoma cell lines and the results were compared to the methylation status of their TERT promoter.

RESULTS

The serous ovarian carcinoma cell line OVCAR3, harboring a hypomethylated TERT promoter, was the best and fastest responder. PA1 and SKOV3, two cell lines with an intermediate methylated promoter, revealed a weaker and delayed response. On the contrary, the other 5 cell lines with a highly methylated promoter did not respond to ATRA, indicative of ATRA-resistant cells.

CONCLUSIONS

Our results demonstrate an inverse correlation between the methylation level of TERT promoter and ATRA efficacy in ovarian carcinoma cell lines. Although these results are preliminary, ATRA treatment could become a new powerful, personalized therapy in serous ovarian carcinoma patients, but only in those with tumors harboring a hypomethylated TERT promoter.

DNA Methylation of Tumor Suppressor Genes in Pituitary Neuroendocrine Tumors

CONTEXT

Epigenetic alterations may play a role in the development and behavior of pituitary neuroendocrine tumors (PitNETs).

OBJECTIVE

To evaluate the effect of methylation of tumor suppressor genes (TSGs) on their gene expression and on the behavior of PitNETs.

MATERIAL AND METHODS

We used methylation-specific multiplex ligation-dependent probe amplification and quantitative real-time PCR techniques to analyze the DNA-promoter hypermethylation and gene expression of 35 TSGs in 105 PitNETs. We defined functionality, size, and invasiveness of tumors according to their clinical manifestations, Hardy's classification, and MRI invasiveness of the cavernous sinus, respectively.

RESULTS

We observed different methylation patterns among PitNET subtypes. The methylation status of TP73 correlated negatively with its gene expression in the overall series (P = 0.013) and in some subtypes. MSH6 and CADM1 showed higher methylation frequency in macroadenomas than in microadenomas in the overall series and in corticotroph PitNETs (all P ≤ 0.053). ESR1 and RASSF1 were more highly methylated in noninvasive than in invasive tumors in the overall series (P = 0.054 and P = 0.031, respectively) and in the gonadotroph subtype (P = 0.055 and P = 0.050, respectively). ESR1 and CASP8 appeared more hypermethylated in functioning than in silent corticotroph tumors (P = 0.034 and P = 0.034, respectively).

CONCLUSIONS

DNA methylation of TSGs has a selective effect on their gene expression and on the growth and invasiveness of PitNETs. Its involvement in their functionality is biased because all silent operated tumors are macroadenomas, whereas all operated microadenomas are functioning ones. Therefore, the subtypes of PitNETs should be considered different entities.

A Bioinformatic Profile of Gene Expression of Colorectal Carcinoma Derived Organoids

Colorectal carcinoma is one of the common cancers in human. It has been intensely debated whether the in vitro cancer cell lines are closely enough for recapitulating the original tumor in understanding the molecular characteristic of CRC. Organoid as a new in vitro 3D culture system has sprang out in CRC study for the capability in reviving the original tissue. The aim of this study is to profile the gene expression of CRC organoid. The gene expression GSE64392 was from GEO database contained 20-patients-derived 37 organoid samples, including 22 colorectal tumor organoid samples and 15 paired healthy samples. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were applied for classifying differentially expressed genes (DEGs). Protein interaction among DEGs was analyzed by Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape software. In total, 853 gene sequences were identified. GO analysis revealed that DEGs were extensively involved in various biological process (BP), like proliferation, cell cycle, and biosynthesis. KEEG pathway analysis showed that WNT, MAPK, TGF-β, SHH, ECM-receptor interaction, and FGF pathways were altered. DEGs which were identified with protein interactions were major response for extracellular matrix organization and the GPCR pathway. In conclusion, our study profiled the DEGs in CRC organoids and promotes our understanding of the CRC organoids as a new model for colorectal cancer research.

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.

Distinct DNA Methylation Profiles in Ovarian Tumors: Opportunities for Novel Biomarkers

Aberrant methylation of multiple promoter CpG islands could be related to the biology of ovarian tumors and its determination could help to improve treatment strategies. DNA methylation profiling was performed using the Methylation Ligation-dependent Macroarray (MLM), an array-based analysis. Promoter regions of 41 genes were analyzed in 102 ovarian tumors and 17 normal ovarian samples. An average of 29% of hypermethylated promoter genes was observed in normal ovarian tissues. This percentage increased slightly in serous, endometrioid, and mucinous carcinomas (32%, 34%, and 45%, respectively), but decreased in germ cell tumors (20%). Ovarian tumors had methylation profiles that were more heterogeneous than other epithelial cancers. Unsupervised hierarchical clustering identified four groups that are very close to the histological subtypes of ovarian tumors. Aberrant methylation of three genes (BRCA1, MGMT, and MLH1), playing important roles in the different DNA repair mechanisms, were dependent on the tumor subtype and represent powerful biomarkers for precision therapy. Furthermore, a promising relationship between hypermethylation of MGMT, OSMR, ESR1, and FOXL2 and overall survival was observed. Our study of DNA methylation profiling indicates that the different histotypes of ovarian cancer should be treated as separate diseases both clinically and in research for the development of targeted therapies.

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.

Bridging the divide: preclinical research discrepancies between triple-negative breast cancer cell lines and patient tumors

Triple-negative breast cancer (TNBC) is the most refractory subtype of breast cancer and disproportionately accounts for the majority of breast cancer related deaths. Effective treatment of this disease remains an unmet medical need. Over the past several decades, TNBC cell lines have been used as the foundation for drug development and disease modeling. However, ever-mounting research demonstrates striking differences between cell lines and clinical TNBC tumors, disconnecting bench research and actual clinical responses. In this review, we discuss the limitations of cell lines and the importance of using patients' tumors for translational research, and highlight the usage of patient-derived xenograft (PDXs) models that have emerged as a clinically relevant platform for preclinical studies. PDX tumors possess tumor heterogeneity with similar cellular, molecular, genetic and epigenetic properties akin to those found within patients' tumors. Moreover, PDX and clinical tumors possess abnormal vasculature with higher blood vessel permeability, a feature that is not always demonstrated in in vivo cell line xenografts. Development of clinically relevant, novel drug-nanoparticles capable of accumulating in PDX tumors through the enhanced permeability and retention effect in tumor vasculature may lead to new and effective TNBC treatments.

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.

Effects of folylpolyglutamate synthase modulation on global and gene-specific DNA methylation and gene expression in human colon and breast cancer cells

Folylpolyglutamate synthase (FPGS) plays a critical role in intracellular folate homeostasis. FPGS-induced polyglutamylated folates are better substrates for several enzymes involved in the generation of S-adenosylmethionine, the primary methyl group donor, and hence FPGS modulation may affect DNA methylation. DNA methylation is an important epigenetic determinant in gene expression and aberrant DNA methylation is mechanistically linked cancer development. We investigated whether FPGS modulation would affect global and gene-specific promoter DNA methylation with consequent functional effects on gene expression profiles in HCT116 colon and MDA-MB-435 breast cancer cells. Although FPGS modulation altered global DNA methylation and DNA methyltransferases (DNMT) activity, the effects of FPGS modulation on global DNA methylation and DNMT activity could not be solely explained by intracellular folate concentrations and content of long-chain folylpolyglutamates, and it may be cell-specific. FPGS modulation influenced differential gene expression and promoter cytosine-guanine dinucleotide sequences (CpG) DNA methylation involved in cellular development, cell cycle, cell death and molecular transport. Some of the altered gene expression was associated with promoter CpG DNA methylation changes. In both the FPGS-overexpressed HCT116 and MDA-MB-435 cell lines, we identified several differentially expressed genes involved in folate biosynthesis and one-carbon metabolism, which might in part have contributed to the observed increased efficacy of 5-fluorouracil in response to FPGS overexpression. Our data suggest that FPGS modulation affects global and promoter CpG DNA methylation and expression of several genes involved in important biological pathways. The potential role of FPGS modulation in DNA methylation and its associated downstream functional effects warrants further studies.

Epigenetic analysis of sporadic and Lynch-associated ovarian cancers reveals histology-specific patterns of DNA methylation

Diagnosis and treatment of epithelial ovarian cancer is challenging due to the poor understanding of the pathogenesis of the disease. Our aim was to investigate epigenetic mechanisms in ovarian tumorigenesis and, especially, whether tumors with different histological subtypes or hereditary background (Lynch syndrome) exhibit differential susceptibility to epigenetic inactivation of growth regulatory genes. Gene candidates for epigenetic regulation were identified from the literature and by expression profiling of ovarian and endometrial cancer cell lines treated with demethylating agents. Thirteen genes were chosen for methylation-specific multiplex ligation-dependent probe amplification assays on 104 (85 sporadic and 19 Lynch syndrome-associated) ovarian carcinomas. Increased methylation (i.e., hypermethylation) of variable degree was characteristic of ovarian carcinomas relative to the corresponding normal tissues, and hypermethylation was consistently more prominent in non-serous than serous tumors for individual genes and gene sets investigated. Lynch syndrome-associated clear cell carcinomas showed the highest frequencies of hypermethylation. Among endometrioid ovarian carcinomas, lower levels of promoter methylation of RSK4, SPARC, and HOXA9 were significantly associated with higher tumor grade; thus, the methylation patterns showed a shift to the direction of high-grade serous tumors. In conclusion, we provide evidence of a frequent epigenetic inactivation of RSK4, SPARC, PROM1, HOXA10, HOXA9, WT1-AS, SFRP2, SFRP5, OPCML, and MIR34B in the development of non-serous ovarian carcinomas of Lynch and sporadic origin, as compared to serous tumors. Our findings shed light on the role of epigenetic mechanisms in ovarian tumorigenesis and identify potential targets for translational applications.

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.

γ-Glutamyl hydrolase modulation significantly influences global and gene-specific DNA methylation and gene expression in human colon and breast cancer cells

γ-Glutamyl hydrolase (GGH) plays an important role in folate homeostasis by catalyzing hydrolysis of polyglutamylated folate into monoglutamates. Polyglutamylated folates are better substrates for several enzymes involved in the generation of S-adenosylmethionine, the primary methyl group donor, and hence, GGH modulation may affect DNA methylation. DNA methylation is an important epigenetic determinant in gene expression, in the maintenance of DNA integrity and stability, and in chromatin modifications, and aberrant or dysregulation of DNA methylation has been mechanistically linked to the development of human diseases including cancer. Using a recently developed in vitro model of GGH modulation in HCT116 colon and MDA-MB-435 breast cancer cells, we investigated whether GGH modulation would affect global and gene-specific DNA methylation and whether these alterations were associated with significant gene expression changes. In both cell lines, GGH overexpression decreased global DNA methylation and DNA methyltransferase (DNMT) activity, while GGH inhibition increased global DNA methylation and DNMT activity. Epigenomic and gene expression analyses revealed that GGH modulation influenced CpG promoter DNA methylation and gene expression involved in important biological pathways including cell cycle, cellular development, and cellular growth and proliferation. Some of the observed altered gene expression appeared to be regulated by changes in CpG promoter DNA methylation. Our data suggest that the GGH modulation-induced changes in total intracellular folate concentrations and content of long-chain folylpolyglutamates are associated with functionally significant DNA methylation alterations in several important biological pathways.

Epigenetic determinants of ovarian clear cell carcinoma biology

Targeted approaches have revealed frequent epigenetic alterations in ovarian cancer, but the scope and relation of these changes to histologic subtype of disease is unclear. Genome-wide methylation and expression data for 14 clear cell carcinoma (CCC), 32 non-CCC and four corresponding normal cell lines were generated to determine how methylation profiles differ between cells of different histological derivations of ovarian cancer. Consensus clustering showed that CCC is epigenetically distinct. Inverse relationships between expression and methylation in CCC were identified, suggesting functional regulation by methylation, and included 22 hypomethylated (UM) genes and 276 hypermethylated (HM) genes. Categorical and pathway analyses indicated that the CCC-specific UM genes were involved in response to stress and many contain hepatocyte nuclear factor (HNF) 1-binding sites, while the CCC-specific HM genes included members of the estrogen receptor alpha (ERalpha) network and genes involved in tumor development. We independently validated the methylation status of 17 of these pathway-specific genes, and confirmed increased expression of HNF1 network genes and repression of ERalpha pathway genes in CCC cell lines and primary cancer tissues relative to non-CCC specimens. Treatment of three CCC cell lines with the demethylating agent Decitabine significantly induced expression for all five genes analyzed. Coordinate changes in pathway expression were confirmed using two primary ovarian cancer datasets (p < 0.0001 for both). Our results suggest that methylation regulates specific pathways and biological functions in CCC, with hypomethylation influencing the characteristic biology of the disease while hypermethylation contributes to the carcinogenic process.

Clinical importance and therapeutic implication of E-cadherin gene methylation in human ovarian cancer

E-cadherin (E-cad) is widely expressed in epithelial cells and acts as a pivotal tumor suppressor. The promoter methylation of E-cad has been reported to closely relate to its downregulation in many kinds of cancers. E-cad expression and methylation status were detected by immunohistochemistry (IHC) and methylation-specific polymerase chain reaction (MS-PCR) in 50 ovarian cancer tissues. 5-Aza-2'-deoxycytidine (5-Aza-dC) was used to demethylate E-cad in SKOV3 and ES2 ovarian cancer cell lines, of which the effect was verified by Western blot and MS-PCR. Then MTT and transwell experiments were conducted to detect the capacity of cell proliferation and migration for these cells. Downregulation of E-cad expression was observed in 60 % of ovarian cancer tissues (30/50) by IHC, whereas MS-PCR result indicated that E-cad was methylated in 64 % of (32/50) ovarian cancer specimens. And E-cad expression was significantly correlated with E-cad methylation (P = 0.004). 5-Aza-dC was used to process SKOV3 and ES2 ovarian cancer cell lines. By MTT experiment, we found that the proliferation of 5-Aza-dC-treated SKOV3 and ES2 was significantly suppressed by 28.0 % (P < 0.05) and 32.3 % (P < 0.05). By transwell experiment, the motility of SKOV3 and ES2 was found to be significantly suppressed by 38.2 and 27.4 % (P < 0.05), respectively, after treated with 5-Aza-dC. E-cad methylation is one of the main reasons for the expression reduction in ovarian cancer. 5-Aza-dC treatment could significantly restore the expression of E-cad and suppress growth and invasion of SKOV3 and ES2 cells. These results suggest E-cad methylation may be a promising target for ovarian cancer therapy.

Human endometrial DNA methylome is cycle-dependent and is associated with gene expression regulation

Human endometrium undergoes major gene expression changes, resulting in altered cellular functions in response to cyclic variations in circulating estradiol and progesterone, largely mediated by transcription factors and nuclear receptors. In addition to classic modulators, epigenetic mechanisms regulate gene expression during development in response to environmental factors and in some diseases and have roles in steroid hormone action. Herein, we tested the hypothesis that DNA methylation plays a role in gene expression regulation in human endometrium in different hormonal milieux. High throughput, genome-wide DNA methylation profiling of endometrial samples in proliferative, early secretory, and midsecretory phases revealed dynamic DNA methylation patterns with segregation of proliferative from secretory phase samples by unsupervised cluster analysis of differentially methylated genes. Changes involved different frequencies of gain and loss of methylation within or outside CpG islands. Comparison of changes in transcriptomes and corresponding DNA methylomes from the same samples revealed association of DNA methylation and gene expression in a number of loci, some important in endometrial biology. Human endometrial stromal fibroblasts treated in vitro with estradiol and progesterone exhibited DNA methylation changes in several genes observed in proliferative and secretory phase tissues, respectively. Taken together, the data support the observation that epigenetic mechanisms are involved in gene expression regulation in human endometrium in different hormonal milieux, adding endometrium to a small number of normal adult tissues exhibiting dynamic DNA methylation. The data also raise the possibility that the interplay between steroid hormone and methylome dynamics regulates normal endometrial functions and, if abnormal, may result in endometrial dysfunction and associated disorders.

A novel method for identification and quantification of consistently differentially methylated regions

Advances in biotechnology have resulted in large-scale studies of DNA methylation. A differentially methylated region (DMR) is a genomic region with multiple adjacent CpG sites that exhibit different methylation statuses among multiple samples. Many so-called “supervised” methods have been established to identify DMRs between two or more comparison groups. Methods for the identification of DMRs without reference to phenotypic information are, however, less well studied. An alternative “unsupervised” approach was proposed, in which DMRs in studied samples were identified with consideration of nature dependence structure of methylation measurements between neighboring probes from tiling arrays. Through simulation study, we investigated effects of dependencies between neighboring probes on determining DMRs where a lot of spurious signals would be produced if the methylation data were analyzed independently of the probe. In contrast, our newly proposed method could successfully correct for this effect with a well-controlled false positive rate and a comparable sensitivity. By applying to two real datasets, we demonstrated that our method could provide a global picture of methylation variation in studied samples. R source codes to implement the proposed method were freely available at http://www.csjfann.ibms.sinica.edu.tw/eag/programlist/ICDMR/ICDMR.html.

Tumor hypomethylation at 6p21.3 associates with longer time to recurrence of high-grade serous epithelial ovarian cancer

To reveal biologic mechanisms underlying clinical outcome of high-grade serous (HGS) epithelial ovarian carcinomas (EOC), we evaluated the association between tumor epigenetic changes and time to recurrence (TTR). We assessed methylation at approximately 450,000 genome-wide CpGs in tumors of 337 Mayo Clinic (Rochester, MN) patients. Semi-supervised clustering of discovery (n=168) and validation (n=169) sets was used to determine clinically relevant methylation classes. Clustering identified two methylation classes based on 60 informative CpGs, which differed in TTR in the validation set [R vs. L class, P=2.9×10(-3), HR=0.52; 95% confidence interval (CI), 0.34-0.80]. Follow-up analyses considered genome-wide tumor mRNA expression (n=104) and CD8 T-cell infiltration (n=89) in patient subsets. Hypomethylation of CpGs located in 6p21.3 in the R class associated with cis upregulation of genes enriched in immune response processes (TAP1, PSMB8, PSMB9, HLA-DQB1, HLA-DQB2, HLA-DMA, and HLA-DOA), increased CD8 T-cell tumor infiltration (P=7.6×10(-5)), and trans-regulation of genes in immune-related pathways (P=1.6×10(-32)). This is the most comprehensive assessment of clinical outcomes with regard to epithelial ovarian carcinoma tumor methylation to date. Collectively, these results suggest that an epigenetically mediated immune response is a predictor of recurrence and, possibly, treatment response for HGS EOC.

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.

Single CpG island methylation is not sufficient to maintain the silenced expression of CASPASE-8 apoptosis-related gene among women with epithelial ovarian cancer

Despite impressive research efforts, the biology of epithelial ovarian cancer (EOC) remains poorly understood and alterations in the expression of CASPASE-8 contribute to a worse tumor prognosis. This study assesses the methylation of the CpG island within the CASPASE-8 promoter and CASPASE-8 gene expression both in cystadenoma tumors and in primary and metastatic EOC. DNA and RNA were obtained from women with normal ovarian tissues (n=18), ovarian serous cystadenoma tumors (n=11) and EOC (n=16) using Trizol(®). The methylation frequency of the CpG island in the CASPASE-8 promoter was assessed using the methylation-specific PCR assay after DNA bisulfite conversion. Quantitative PCR was performed to quantify the relative levels of CASPASE-8 in each sample. The differences between samples with each group were evaluated using the Mann-Whitney U and Kruskal-Wallis tests as indicated. Hemimethylation of the CASPASE-8 promoter was found in 11.8% of the normal ovary samples, 20% of the cystadenoma tumors and 20% of the metastatic EOC, while methylation of the CASPASE-8 promoter was absent in the EOC primary tissues (P=0.047). An increased CASPASE-8 expression level was observed in all tumor groups. Significant differences were observed in the CASPASE-8 expression levels when compared with all ovarian tumor groups (P=0.0278). Promoter DNA methylation did not associate with expression levels of CASPASE-8, suggesting the presence of other mechanisms in relation to gene expression control in EOC; thus providing a better understanding of this complex disease.

Integrative DNA methylation and gene expression analysis in high-grade soft tissue sarcomas

Background

High-grade soft tissue sarcomas are a heterogeneous, complex group of aggressive malignant tumors showing mesenchymal differentiation. Recently, soft tissue sarcomas have increasingly been classified on the basis of underlying genetic alterations; however, the role of aberrant DNA methylation in these tumors is not well understood and, consequently, the usefulness of methylation-based classification is unclear.

Results

We used the Infinium HumanMethylation27 platform to profile DNA methylation in 80 primary, untreated high-grade soft tissue sarcomas, representing eight relevant subtypes, two non-neoplastic fat samples and 14 representative sarcoma cell lines. The primary samples were partitioned into seven stable clusters. A classification algorithm identified 216 CpG sites, mapping to 246 genes, showing different degrees of DNA methylation between these seven groups. The differences between the clusters were best represented by a set of eight CpG sites located in the genes SPEG, NNAT, FBLN2, PYROXD2, ZNF217, COL14A1, DMRT2 and CDKN2A. By integrating DNA methylation and mRNA expression data, we identified 27 genes showing negative and three genes showing positive correlation. Compared with non-neoplastic fat, NNAT showed DNA hypomethylation and inverse gene expression in myxoid liposarcomas, and DNA hypermethylation and inverse gene expression in dedifferentiated and pleomorphic liposarcomas. Recovery of NNAT in a hypermethylated myxoid liposarcoma cell line decreased cell migration and viability.

Conclusions

Our analysis represents the first comprehensive integration of DNA methylation and transcriptional data in primary high-grade soft tissue sarcomas. We propose novel biomarkers and genes relevant for pathogenesis, including NNAT as a potential tumor suppressor in myxoid liposarcomas.

Hypomethylation signature of tumor-initiating cells predicts poor prognosis of ovarian cancer patients

DNA methylation contributes to tumor formation, development and metastasis. Epigenetic dysregulation of stem cells is thought to predispose to malignant development. The clinical significance of DNA methylation in ovarian tumor-initiating cells (OTICs) remains unexplored. We analyzed the methylomic profiles of OTICs (CP70sps) and their derived progeny using a human methylation array. qRT-PCR, quantitative methylation-specific PCR (qMSP) and pyrosequencing were used to verify gene expression and DNA methylation in cancer cell lines. The methylation status of genes was validated quantitatively in cancer tissues and correlated with clinicopathological factors. ATG4A and HIST1H2BN were hypomethylated in OTICs. Methylation analysis of ATG4A and HIST1H2BN by qMSP in 168 tissue samples from patients with ovarian cancer showed that HIST1H2BN methylation was a significant and independent predictor of progression-free survival (PFS) and overall survival (OS). Multivariate Cox regression analysis showed that patients with a low level of HIST1H2BN methylation had poor PFS (hazard ratio (HR), 4.5; 95% confidence interval (CI), 1.4-14.8) and OS (HR, 4.3; 95% CI, 1.3-14.0). Hypomethylation of both ATG4A and HIST1H2BN predicted a poor PFS (HR, 1.8; 95% CI, 1.0-3.6; median, 21 months) and OS (HR, 1.7; 95% CI, 1.0-3.0; median, 40 months). In an independent cohort of ovarian tumors, hypomethylation predicted early disease recurrence (HR, 1.7; 95% CI, 1.1-2.5) and death (HR, 1.4; 95% CI, 1.0-1.9). The demonstration that expression of ATG4A in cells increased their stem properties provided an indication of its biological function. Hypomethylation of ATG4A and HIST1H2BN in OTICs predicts a poor prognosis for ovarian cancer patients.

Reduced H3K27me3 and DNA hypomethylation are major drivers of gene expression in K27M mutant pediatric high-grade gliomas

Two recurrent mutations, K27M and G34R/V, within histone variant H3.3 were recently identified in ∼50% of pHGGs. Both mutations define clinically and biologically distinct subgroups of pHGGs. Here, we provide further insight about the dominant-negative effect of K27M mutant H3.3, leading to a global reduction of the repressive histone mark H3K27me3. We demonstrate that this is caused by aberrant recruitment of the PRC2 complex to K27M mutant H3.3 and enzymatic inhibition of the H3K27me3-establishing methyltransferase EZH2. By performing chromatin immunoprecipitation followed by next-generation sequencing and whole-genome bisulfite sequencing in primary pHGGs, we show that reduced H3K27me3 levels and DNA hypomethylation act in concert to activate gene expression in K27M mutant pHGGs.

Differentially methylated loci distinguish ovarian carcinoma histological types: evaluation of a DNA methylation assay in FFPE tissue

Epigenomic markers can identify tumor subtypes, but few platforms can accommodate formalin-fixed paraffin-embedded (FFPE) tumor tissue. We tested different amounts of bisulfite-converted (bs) DNA from six FFPE ovarian carcinomas (OC) of serous, endometrioid, and clear cell histologies and two HapMap constitutional genomes to evaluate the performance of the GoldenGate methylation assay. Methylation status at each 1,505 CpG site was expressed as β-values. Comparing 400 ng versus 250 ng bsDNA, reproducibility of the assay ranged from Spearman r² = 0.41 to 0.90, indicating that β-values obtained with a lower DNA amount did not always correlate well with the higher amount. Average methylation for the six samples was higher using 250 ng (β-value = 0.45, SD = 0.29) than with 400 ng (β-value = 0.36, SD = 0.32). Reproducibility between duplicate HapMap samples (r² = 0.76 to 0.92) was also variable. Using 400 ng input bsDNA, THBS2 and ERG were differentially methylated across all histologic types and between endometrioid and clear cell types at <0.1% false discovery rate. Methylation did not always correlate with gene expression (r² = −0.70 to 0.15). We found that lower bsDNA overestimates methylation, and, using higher bsDNA amounts, we confirmed a previous report of higher methylation of THBS2 in clear cell OC, which could provide new insight into biological pathways that distinguish OC histological types.

Effects of 5-Aza-2'-deoxycytidine on the methylation state and function of the WWOX gene in the HO-8910 ovarian cancer cell line

The aim of this study was to explore the effects of 5-Aza-2′-deoxycytidine (5-Aza-CdR), a DNA methylation inhibitor, on the methylation state and function of the WWOX gene in the HO-8910 ovarian cancer cell line. The HO-8910 cells were divided into two groups, a control group and a 5-Aza-CdR-treated group. The methylation state of the WWOX gene was evaluated using a methylation-specific PCR assay. The effect of 5-Aza-CdR on the HO-8910 cells was analyzed using MTT and cell invasion assays, as well as flow cytometry. The animal models were established by intraperitoneal transplantation of the cells into nude mice. Following treatment with 5-Aza-CdR, a demethylation state was detected in the HO-8910 cells. WWOX protein expression was significantly higher in the 5-Aza-CdR-treated group compared with that in the control group. The cell growth rate at each tested time point and the number of invasive cells were lower in the 5-Aza-CdR-treated group compared with that in the control group. Flow cytometry revealed that 67.13% of the cells were arrested at the G₀/G₁ stage in the 5-Aza-CdR-treated group. The tumorigenic ability of the 5-Aza-CdR-treated group was lower compared with that of the control group. In conclusion, the methylation state of the WWOX gene in HO-8910 cells may be reversed using 5-Aza-CdR, which may also inhibit the growth of these cells.

Extracting coordinated patterns of DNA methylation and gene expression in ovarian cancer

OBJECTIVE

DNA methylation, a regulator of gene expression, plays an important role in diverse biological processes including developmental process, carcinogenesis and aging. In particular, aberrant DNA methylation has been largely observed in several types of cancers. Currently, it is important to extract disease-specific gene sets associated with the regulation of DNA methylation.

MATERIALS AND METHODS

Here we propose a novel approach to find the minimum regulatory units of genes, co-methylated and co-expressed gene pairs (MEGP) that are highly correlated gene pairs between DNA methylation and gene expression showing the co-regulatory relationship. To evaluate whether our method is applicable to extract disease-associated genes, we applied our method to a large-scale dataset from the Cancer Genome Atlas extracting significantly associated MEGP and analyzed their functional correlation.

RESULTS

We observed that many MEGP physically interacted with each other and showed high semantic similarity with gene ontology terms. Furthermore, we performed gene set enrichment tests to identify how they are correlated in a complex biological process. Our MEGP were highly enriched in the biological pathway associated with ovarian cancers.

CONCLUSIONS

Our approach is useful for discovering coordinated epigenetic markers associated with specific diseases.

Epigenome-wide ovarian cancer analysis identifies a methylation profile differentiating clear-cell histology with epigenetic silencing of the HERG K+ channel

Ovarian cancer remains the leading cause of death in women with gynecologic malignancies, despite surgical advances and the development of more effective chemotherapeutics. As increasing evidence indicates that clear-cell ovarian cancer may have unique pathogenesis, further understanding of molecular features may enable us to begin to understand the underlying biology and histology-specific information for improved outcomes. To study epigenetics in clear-cell ovarian cancer, fresh frozen tumor DNA (n = 485) was assayed on Illumina Infinium HumanMethylation450 BeadChips. We identified a clear-cell ovarian cancer tumor methylation profile (n = 163) which we validated in two independent replication sets (set 1, n = 163; set 2, n = 159), highlighting 22 CpG loci associated with nine genes (VWA1, FOXP1, FGFRL1, LINC00340, KCNH2, ANK1, ATXN2, NDRG21 and SLC16A11). Nearly all of the differentially methylated CpGs showed a propensity toward hypermethylation among clear-cell cases. Several loci methylation inversely correlated with tumor gene expression, most notably KCNH2 (HERG, a potassium channel) (P = 9.5 × 10(-7)), indicating epigenetic silencing. In addition, a predicted methylation class mainly represented by the clear-cell cases (20 clear cell out of 23 cases) had improved survival time. Although these analyses included only 30 clear-cell carcinomas, results suggest that loss of expression of KCNH2 (HERG) by methylation could be a good prognostic marker, given that overexpression of the potassium (K(+)) channel Eag family members promotes increased proliferation and results in poor prognosis. Validation in a bigger cohort of clear-cell tumors of the ovary is warranted.

Epigenetic silencing of BLU through interfering apoptosis results in chemoresistance and poor prognosis of ovarian serous carcinoma patients

Epithelial ovarian carcinoma is usually present at the advanced stage, during which the patients generally have poor prognosis. Our study aimed to evaluate the correlation of gene methylation and the clinical outcome of patients with advanced-stage, high-grade ovarian serous carcinoma. The methylation status of eight candidate genes was first evaluated by methylation-specific PCR and capillary electrophoresis to select three potential genes including DAPK, CDH1, and BLU (ZMYND10) from the exercise group of 40 patients. The methylation status of these three genes was further investigated in the validation group consisting of 136 patients. Patients with methylated BLU had significantly shorter progression-free survival (PFS; hazard ratio (HR) 1.48, 95% CI 1.01-2.56, P=0.013) and overall survival (OS; HR 1.83, 95% CI 1.07-3.11, P=0.027) in the multivariate analysis. Methylation of BLU was also an independent risk factor for 58 patients undergoing optimal debulking surgery for PFS (HR 2.37, 95% CI 1.03-5.42, P=0.043) and OS (HR 3.96, 95% CI 1.45-10.81, P=0.007) in the multivariate analysis. A possible mechanism of BLU in chemoresistance was investigated in ovarian cancer cell lines by in vitro apoptotic assays. In vitro studies have shown that BLU could upregulate the expression of BAX and enhance the effect of paclitaxel-induced apoptosis in ovarian cancer cells. Our study suggested that methylation of BLU could be a potential prognostic biomarker for advanced ovarian serous carcinoma.

Recursively partitioned mixture model clustering of DNA methylation data using biologically informed correlation structures

DNA methylation is a well-recognized epigenetic mechanism that has been the subject of a growing body of literature typically focused on the identification and study of profiles of DNA methylation and their association with human diseases and exposures. In recent years, a number of unsupervised clustering algorithms, both parametric and non-parametric, have been proposed for clustering large-scale DNA methylation data. However, most of these approaches do not incorporate known biological relationships of measured features, and in some cases, rely on unrealistic assumptions regarding the nature of DNA methylation. Here, we propose a modified version of a recursively partitioned mixture model (RPMM) that integrates information related to the proximity of CpG loci within the genome to inform correlation structures from which subsequent clustering analysis is based. Using simulations and four methylation data sets, we demonstrate that integrating biologically informative correlation structures within RPMM resulted in improved goodness-of-fit, clustering consistency, and the ability to detect biologically meaningful clusters compared to methods which ignore such correlation. Integrating biologically-informed correlation structures to enhance modeling techniques is motivated by the rapid increase in resolution of DNA methylation microarrays and the increasing understanding of the biology of this epigenetic mechanism.

Genomic insights into cancer-associated aberrant CpG island hypermethylation

Carcinogenesis is thought to occur through a combination of mutational and epimutational events that disrupt key pathways regulating cellular growth and division. The DNA methylomes of cancer cells can exhibit two striking differences from normal cells; a global reduction of DNA methylation levels and the aberrant hypermethylation of some sequences, particularly CpG islands (CGIs). This aberrant hypermethylation is often invoked as a mechanism causing the transcriptional inactivation of tumour suppressor genes that directly drives the carcinogenic process. Here, we review our current understanding of this phenomenon, focusing on how global analysis of cancer methylomes indicates that most affected CGI genes are already silenced prior to aberrant hypermethylation during cancer development. We also discuss how genome-scale analyses of both normal and cancer cells have refined our understanding of the elusive mechanism(s) that may underpin aberrant CGI hypermethylation.

Integrative prediction of gene function and platinum-free survival from genomic and epigenetic features in ovarian cancer

The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to discover genes critical to the development, progression, and therapeutic resistance of cancer. We seek to identify those genetic and epigenetic aberrations that have the most impact on gene function within the tumor. First, we perform a bioinformatics analysis of copy number variation (CNV) and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We were specifically interested in copy number variation as our base genomic property in the prediction of tumor suppressors and oncogenes in the altered ovarian tumor. We identify changes in DNA methylation and expression specifically for all amplified and deleted genes. We statistically define tumor suppressor and oncogenic gene function from integrative analysis of three modalities: copy number variation, DNA methylation, and gene expression. Our method (1) calculates the extent of genomic and epigenetic alterations of defined tumor suppressor and oncogenic features for the functional prediction of significant ovarian cancer gene candidates and (2) identifies the functional activity or inactivity of known tumor suppressors and oncogenes in ovarian cancer. We applied our protocol on 42 primary serous ovarian cancer samples using MOMA-ROMA representational array assays. Additionally, we provide the basis for incorporating epigenetic profiles of ovarian tumors for the purposes of platinum-free survival prediction in the context of TCGA data.

Reducing confounding and suppression effects in TCGA data: an integrated analysis of chemotherapy response in ovarian cancer

Background

Despite initial response in adjuvant chemotherapy, ovarian cancer patients treated with the combination of paclitaxel and carboplatin frequently suffer from recurrence after few cycles of treatment, and the underlying mechanisms causing the chemoresistance remain unclear. Recently, The Cancer Genome Atlas (TCGA) research network concluded an ovarian cancer study and released the dataset to the public. The TCGA dataset possesses large sample size, comprehensive molecular profiles, and clinical outcome information; however, because of the unknown molecular subtypes in ovarian cancer and the great diversity of adjuvant treatments TCGA patients went through, studying chemotherapeutic response using the TCGA data is difficult. Additionally, factors such as sample batches, patient ages, and tumor stages further confound or suppress the identification of relevant genes, and thus the biological functions and disease mechanisms.

Results

To address these issues, herein we propose an analysis procedure designed to reduce suppression effect by focusing on a specific chemotherapeutic treatment, and to remove confounding effects such as batch effect, patient's age, and tumor stages. The proposed procedure starts with a batch effect adjustment, followed by a rigorous sample selection process. Then, the gene expression, copy number, and methylation profiles from the TCGA ovarian cancer dataset are analyzed using a semi-supervised clustering method combined with a novel scoring function. As a result, two molecular classifications, one with poor copy number profiles and one with poor methylation profiles, enriched with unfavorable scores are identified. Compared with the samples enriched with favorable scores, these two classifications exhibit poor progression-free survival (PFS) and might be associated with poor chemotherapy response specifically to the combination of paclitaxel and carboplatin. Significant genes and biological processes are detected subsequently using classical statistical approaches and enrichment analysis.

Conclusions

The proposed procedure for the reduction of confounding and suppression effects and the semi-supervised clustering method are essential steps to identify genes associated with the chemotherapeutic response.

Promoter methylation status of HIN-1 associated with outcomes of ovarian clear cell adenocarcinoma

Background

This study is to analyze promoter methylation of various tumor suppressor genes in different types of ovarian carcinoma and to identify potential therapeutic targets of ovarian clear cell adenocarcinoma (OCCA).

Materials and methods

The promoter methylation statuses of 40 genes in primary ovarian carcinomas including 47 clear- and 63 non-clear-cell type tissues, 6 OCCA cell lines, 29 benign ovarian endometriotic cysts, and 31 normal controls were analyzed by methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA). The MS-MLPA results were correlated with clinicopathological features and outcomes of 47 OCCA patients. Functions of the target genes were further explored by Western Blot Analysis, apoptosis assay, and caspase-3/7 activity analysis.

Results

Frequencies of methylated RASSF1A, CDH13, CACNA1A, HIN-1, and sFRP5 genes in OCCA tissues were significantly higher than those in non-OCCA cancerous tissues and benign endometriotic cysts. The expected OS for patients with methylated promoters of HIN-1 was significantly worse than those for patients without methylated HIN-1 (30% vs. 62%, p = 0.002). The HIN-1 gene was over-expressed in ES2 cells, a significant reduction in cell growth and induction of apoptosis, and increasing paclitaxel sensitivity by reducing phosphorylation of Akt were observed.

Conclusions

Methylation of HIN-1 promoter is a novel epigenetic biomarker associated with poor outcomes in OCCA patients. Ectopic expression of the HIN-1 gene increased paclitaxel sensitivity which is partly through Akt pathway.

Epigenetic biomarkers in the diagnosis of ovarian cancer

INTRODUCTION

Current diagnostic methods for ovarian cancer have limited performance. Recent advances within the field of epigenetics have shifted the clinical implementation of epigenetic biomarkers as a diagnostic approach from a dream for the future to a present-day consideration. Patients could potentially benefit greatly from this novel diagnostic approach.

AREAS COVERED

Epigenetic mechanisms in cancer are discussed, with a focus on potential diagnostic epigenetic biomarkers in ovarian cancer in tissue and body fluids. A literature search was undertaken (on 22-09-2011) for these subjects using the search syntax ((((((((((((((("ovarian") OR "ovary") OR "ovarian cancer") OR "ovarian cancers") OR "cancer of the ovary") OR "tumour of the ovary") OR "ovarian tumor") OR "ovarian tumors") OR "ovarian tumour") OR "ovarian tumours") OR "ovarian neoplasm") OR "ovarian neoplasms" OR "ovarian carcinoma") OR "ovarian carcinomas") OR "carcinoma of the ovary")) AND ((((((((("epigenetics") OR "epigenetic") OR "epigenome") OR "methylation") OR "hypermethylation") OR "chromatin modification") OR "histone") OR "histones") OR "acetylation")

EXPERT OPINION

To date no single epigenetic biomarker is able to accurately detect early ovarian cancer in either tissue or body fluids. A panel of epigenetic biomarkers based on aberrant DNA methylation in body fluids, especially blood, has the best chance of being implemented in clinical practice, as it is semi-invasive. However, progression toward clinical use is hampered by the lack of detection techniques combining high throughput and accuracy with low cost, by difficulties in establishing reliable reference values and by the heterogeneous nature of ovarian cancer. Until addressed, implementation as a diagnostic measure complimenting current techniques in select cases seems a far way to go, and implementation as a primary screening tool is yet even farther away.

Translational genomics: the challenge of developing cancer biomarkers

Early detection and definitive treatment of cancer have been shown to decrease death and suffering in epidemiologic and intervention studies. Application of genomic approaches to many malignancies has produced thousands of candidate biomarkers for detection and prognostication, yet very few have become established in clinical practice. Fundamental issues related to tumor heterogeneity, cancer progression, natural history, and biomarker performance have provided challenges to biomarker development. Technical issues in biomarker assay detection limits, specificity, clinical deployment, and regulation have also slowed progress. The recent emergence of biomarkers and molecular imaging strategies for treatment selection and monitoring demonstrates the promise of cancer biomarkers. Organized efforts by interdisciplinary teams will spur progress in cancer diagnostics.