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1.  PP2A-B55β Antagonizes Cyclin E1 Proteolysis and Promotes its Dysregulation in Cancer 
Cancer research  2014;74(7):2006-2014.
Cyclin E1 regulates the initiation of S phase in cellular division. However, in many cancers cyclin E1 is aberrantly overexpressed and this molecular phenotype correlates with increased tumor aggressiveness and poor patient survival. The molecular cause(s) of cyclin E1 abnormalities in cancers is poorly understood. Here, we show cyclin E1 overexpression in cancer is promoted by dysregulation of the protein phosphatase PP2A-B55β. PP2A-B55β targets the N- and C-terminal phosphodegrons of cyclin E1 for dephosphorylation, thus protecting it from degradation mediated by the SCFFbxw7 ubiquitin ligase. Augmented B55β expression stabilizes cyclin E1 and promotes its overexpression in cancer-derived cell lines and breast tumors. Conversely, B55β ablation enforces the degradation of cyclin E1 and inhibits cancer cell proliferation in vitro and tumor formation in vivo. Therefore, PP2A-B55β promotes cyclin E1 overexpression by antagonizing its degradation and its inhibition could represent a therapeutic mechanism for abrogating cyclin E1 function in cancers.
doi:10.1158/0008-5472.CAN-13-1263
PMCID: PMC4064712  PMID: 24509904
B55β; PPP2R2B; Cyclin E; SCFFbxw7; Fbw7
2.  The Dynamics of DNA Methylation Covariation Patterns in Carcinogenesis 
PLoS Computational Biology  2014;10(7):e1003709.
Recently it has been observed that cancer tissue is characterised by an increased variability in DNA methylation patterns. However, how the correlative patterns in genome-wide DNA methylation change during the carcinogenic progress has not yet been explored. Here we study genome-wide inter-CpG correlations in DNA methylation, in addition to single site variability, during cervical carcinogenesis. We demonstrate how the study of changes in DNA methylation covariation patterns across normal, intra-epithelial neoplasia and invasive cancer allows the identification of CpG sites that indicate the risk of neoplastic transformation in stages prior to neoplasia. Importantly, we show that the covariation in DNA methylation at these risk CpG loci is maximal immediately prior to the onset of cancer, supporting the view that high epigenetic diversity in normal cells increases the risk of cancer. Consistent with this, we observe that invasive cancers exhibit increased covariation in DNA methylation at the risk CpG sites relative to normal tissue, but lower levels relative to pre-cancerous lesions. We further show that the identified risk CpG sites undergo preferential DNA methylation changes in relation to human papilloma virus infection and age. Results are validated in independent data including prospectively collected samples prior to neoplastic transformation. Our data are consistent with a phase transition model of carcinogenesis, in which epigenetic diversity is maximal prior to the onset of cancer. The model and algorithm proposed here may allow, in future, network biomarkers predicting the risk of neoplastic transformation to be identified.
Author Summary
DNA methylation is a covalent modification of DNA which can regulate how active genes are. DNA methylation is altered at many genomic loci in cancer cells, leading to widespread functional disruption. Importantly, DNA methylation alterations across the genome are seen even in early carcinogenesis. Although the pattern of DNA methylation change during carcinogenesis has been studied at individual genomic loci, no study has yet analysed how these patterns change at a systems-level, specifically how do DNA methylation patterns at pairs of genomic sites change during disease progression. Doing so can shed light on how the epigenetic diversity of cell populations changes during the carcinogenic process. This study performs a systems-level analysis of the dynamic changes in DNA methylation correlation pattern during cervical carcinogenesis, demonstrating that epigenetic diversity is maximal just prior to the onset of cancer. Importantly, this supports the view that the risk of cancer development is closely related to an increase in epigenetic diversity in apparently healthy cells. In addition, the study provides a computational algorithm which successfully identifies the altered genomic sites confering the risk of cervical cancer.
doi:10.1371/journal.pcbi.1003709
PMCID: PMC4091688  PMID: 25010556
3.  A BRCA1-mutation associated DNA methylation signature in blood cells predicts sporadic breast cancer incidence and survival 
Genome Medicine  2014;6(6):47.
Background
BRCA1 mutation carriers have an 85% risk of developing breast cancer but the risk of developing non-hereditary breast cancer is difficult to assess. Our objective is to test whether a DNA methylation (DNAme) signature derived from BRCA1 mutation carriers is able to predict non-hereditary breast cancer.
Methods
In a case/control setting (72 BRCA1 mutation carriers and 72 BRCA1/2 wild type controls) blood cell DNA samples were profiled on the Illumina 27 k methylation array. Using the Elastic Net classification algorithm, a BRCA1-mutation DNAme signature was derived and tested in two cohorts: (1) The NSHD (19 breast cancers developed within 12 years after sample donation and 77 controls) and (2) the UKCTOCS trial (119 oestrogen receptor positive breast cancers developed within 5 years after sample donation and 122 controls).
Results
We found that our blood-based BRCA1-mutation DNAme signature applied to blood cell DNA from women in the NSHD resulted in a receiver operating characteristics (ROC) area under the curve (AUC) of 0.65 (95% CI 0.51 to 0.78, P = 0.02) which did not validate in buccal cells from the same individuals. Applying the signature in blood DNA from UKCTOCS volunteers resulted in AUC of 0.57 (95% CI 0.50 to 0.64; P = 0.03) and is independent of family history or any other known risk factors. Importantly the BRCA1-mutation DNAme signature was able to predict breast cancer mortality (AUC = 0.67; 95% CI 0.51 to 0.83; P = 0.02). We also found that the 1,074 CpGs which are hypermethylated in BRCA1 mutation carriers are significantly enriched for stem cell polycomb group target genes (P <10-20).
Conclusions
A DNAme signature derived from BRCA1 carriers is able to predict breast cancer risk and death years in advance of diagnosis. Future studies may need to focus on DNAme profiles in epithelial cells in order to reach the AUC thresholds required of preventative measures or early detection strategies.
doi:10.1186/gm567
PMCID: PMC4110671  PMID: 25067956
4.  Relationship between genome and epigenome - challenges and requirements for future research 
BMC Genomics  2014;15(1):487.
Understanding the links between genetic, epigenetic and non-genetic factors throughout the lifespan and across generations and their role in disease susceptibility and disease progression offer entirely new avenues and solutions to major problems in our society. To overcome the numerous challenges, we have come up with nine major conclusions to set the vision for future policies and research agendas at the European level.
doi:10.1186/1471-2164-15-487
PMCID: PMC4073504  PMID: 24942464
Genome; Epigenome; Microbiome; Environment
5.  Hypomethylation of the CTCFL/BORIS promoter and aberrant expression during endometrial cancer progression suggests a role as an Epi-driver gene 
Oncotarget  2014;5(4):1052-1061.
Cancers arise through accumulating genetic and epigenetic alterations, considered relevant for phenotype and approaches to targeting new therapies. We investigated a unique collection of endometrial cancer precursor samples and clinically annotated primary and metastatic lesions for two evolutionary and functionally related transcription factors, CCCTC-binding factor (zinc finger protein) (CTCF) and its paralogue CTCF-like factor, also denoted Brother of the Regulator of Imprinted Sites (CTCFL/BORIS). CTCF, a chromatin modeling- and transcription factor, is normally expressed in a ubiquitous fashion, while CTCFL/BORIS is restricted to the testis. In cancer, CTCF is thought to be a tumor suppressor, while CTCFL/BORIS has been suggested as an oncogene. CTCF mutations were identified in 13 %, with CTCF hotspot frameshift mutations at p.T204, all observed solely in the endometrioid subtype, but with no association with outcome. Interestingly, CTCFL/BORIS was amongst the top ranked genes differentially expressed between endometrioid and non-endometrioid tumors, and increasing mRNA level of CTCFL/BORIS was highly significantly associated with poor survival. As aberrant CTCFL/BORIS expression might relate to loss of methylation, we explored methylation status in clinical samples from complex atypical hyperplasia, through primary tumors to metastatic lesions, demonstrating a pattern of DNA methylation loss during disease development and progression in line with the increase in CTCFL/BORIS mRNA expression observed. Thus, CTCF and CTCFL/BORIS are found to diverge in the different subtypes of endometrial cancer, with CTCFL/BORIS activation through demethylation from precursors to metastatic lesions. We thus propose, CTCFL/BORIS as an Epi-driver gene in endometrial cancer, suggesting a potential for future vaccine development.
PMCID: PMC4011582  PMID: 24658009
CTCFL/BORIS; CTCF; metastasis; recurrence; epi-driver gene
6.  Role of DNA Methylation and Epigenetic Silencing of HAND2 in Endometrial Cancer Development 
PLoS Medicine  2013;10(11):e1001551.
TB filled in by Laureen
Please see later in the article for the Editors' Summary
Background
Endometrial cancer incidence is continuing to rise in the wake of the current ageing and obesity epidemics. Much of the risk for endometrial cancer development is influenced by the environment and lifestyle. Accumulating evidence suggests that the epigenome serves as the interface between the genome and the environment and that hypermethylation of stem cell polycomb group target genes is an epigenetic hallmark of cancer. The objective of this study was to determine the functional role of epigenetic factors in endometrial cancer development.
Methods and Findings
Epigenome-wide methylation analysis of >27,000 CpG sites in endometrial cancer tissue samples (n = 64) and control samples (n = 23) revealed that HAND2 (a gene encoding a transcription factor expressed in the endometrial stroma) is one of the most commonly hypermethylated and silenced genes in endometrial cancer. A novel integrative epigenome-transcriptome-interactome analysis further revealed that HAND2 is the hub of the most highly ranked differential methylation hotspot in endometrial cancer. These findings were validated using candidate gene methylation analysis in multiple clinical sample sets of tissue samples from a total of 272 additional women. Increased HAND2 methylation was a feature of premalignant endometrial lesions and was seen to parallel a decrease in RNA and protein levels. Furthermore, women with high endometrial HAND2 methylation in their premalignant lesions were less likely to respond to progesterone treatment. HAND2 methylation analysis of endometrial secretions collected using high vaginal swabs taken from women with postmenopausal bleeding specifically identified those patients with early stage endometrial cancer with both high sensitivity and high specificity (receiver operating characteristics area under the curve = 0.91 for stage 1A and 0.97 for higher than stage 1A). Finally, mice harbouring a Hand2 knock-out specifically in their endometrium were shown to develop precancerous endometrial lesions with increasing age, and these lesions also demonstrated a lack of PTEN expression.
Conclusions
HAND2 methylation is a common and crucial molecular alteration in endometrial cancer that could potentially be employed as a biomarker for early detection of endometrial cancer and as a predictor of treatment response. The true clinical utility of HAND2 DNA methylation, however, requires further validation in prospective studies.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Cancer, which is responsible for 13% of global deaths, can develop anywhere in the body, but all cancers are characterized by uncontrolled cell growth and reduced cellular differentiation (the process by which unspecialized cells such as “stem” cells become specialized during development, tissue repair, and normal cell turnover). Genetic alterations—changes in the sequence of nucleotides (DNA's building blocks) in specific genes—are required for this cellular transformation and subsequent cancer development (carcinogenesis). However, recent evidence suggests that epigenetic modifications—reversible, heritable changes in gene function that occur in the absence of nucleotide sequence changes—may also be involved in carcinogenesis. For example, the addition of methyl groups to a set of genes called stem cell polycomb group target genes (PCGTs; polycomb genes control the expression of their target genes by modifying their DNA or associated proteins) is one of the earliest molecular changes in human cancer development, and increasing evidence suggests that hypermethylation of PCGTs is an epigenetic hallmark of cancer.
Why Was This Study Done?
The methylation of PCGTs, which is triggered by age and by environmental factors that are associated with cancer development, reduces cellular differentiation and leads to the accumulation of undifferentiated cells that are susceptible to cancer development. It is unclear, however, whether epigenetic modifications have a causal role in carcinogenesis. Here, the researchers investigate the involvement of epigenetic factors in the development of endometrial (womb) cancer. The risk of endometrial cancer (which affects nearly 50,000 women annually in the United States) is largely determined by environmental and lifestyle factors. Specifically, the risk of this cancer is increased in women in whom estrogen (a hormone that drives cell proliferation in the endometrium) is functionally dominant over progesterone (a hormone that inhibits endometrial proliferation and causes cell differentiation); obese women and women who have taken estrogen-only hormone replacement therapies fall into this category. Thus, endometrial cancer is an ideal model in which to study whether epigenetic mechanisms underlie carcinogenesis.
What Did the Researchers Do and Find?
The researchers collected data on genome-wide DNA methylation at cytosine- and guanine-rich sites in endometrial cancers and normal endometrium and integrated this information with the human interactome and transcriptome (all the physical interactions between proteins and all the genes expressed, respectively, in a cell) using an algorithm called Functional Epigenetic Modules (FEM). This analysis identified HAND2 as the hub of the most highly ranked differential methylation hotspot in endometrial cancer. HAND2 is a progesterone-regulated stem cell PCGT. It encodes a transcription factor that is expressed in the endometrial stroma (the connective tissue that lies below the epithelial cells in which most endometrial cancers develop) and that suppresses the production of the growth factors that mediate the growth-inducing effects of estrogen on the endometrial epithelium. The researchers hypothesized, therefore, that epigenetic deregulation of HAND2 could be a key step in endometrial cancer development. In support of this hypothesis, the researchers report that HAND2 methylation was increased in premalignant endometrial lesions (cancer-prone, abnormal-looking tissue) compared to normal endometrium, and was associated with suppression of HAND2 expression. Moreover, a high level of endometrial HAND2 methylation in premalignant lesions predicted a poor response to progesterone treatment (which stops the growth of some endometrial cancers), and analysis of HAND2 methylation in endometrial secretions collected from women with postmenopausal bleeding (a symptom of endometrial cancer) accurately identified individuals with early stage endometrial cancer. Finally, mice in which the Hand2 gene was specifically deleted in the endometrium developed precancerous endometrial lesions with age.
What Do These Findings Mean?
These and other findings identify HAND2 methylation as a common, key molecular alteration in endometrial cancer. These findings need to be confirmed in more women, and studies are needed to determine the immediate molecular and cellular consequences of HAND2 silencing in endometrial stromal cells. Nevertheless, these results suggest that HAND2 methylation could potentially be used as a biomarker for the early detection of endometrial cancer and for predicting treatment response. More generally, these findings support the idea that methylation of HAND2 (and, by extension, the methylation of other PCGTs) is not a passive epigenetic feature of cancer but is functionally involved in cancer development, and provide a framework for identifying other genes that are epigenetically regulated and functionally important in carcinogenesis.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001551
The US National Cancer Institute provides information on all aspects of cancer and has detailed information about endometrial cancer for patients and professionals (in English and Spanish)
The not-for-profit organization American Cancer Society provides information on cancer and how it develops and specific information on endometrial cancer (in several languages)
The UK National Health Service Choices website includes an introduction to cancer, a page on endometrial cancer, and a personal story about endometrial cancer
The not-for-profit organization Cancer Research UK provides general information about cancer and specific information about endometrial cancer
Wikipedia has a page on cancer epigenetics (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
The Eve Appeal charity that supported this research provides useful information on gynecological cancers
doi:10.1371/journal.pmed.1001551
PMCID: PMC3825654  PMID: 24265601
7.  Cellular network entropy as the energy potential in Waddington's differentiation landscape 
Scientific Reports  2013;3:3039.
Differentiation is a key cellular process in normal tissue development that is significantly altered in cancer. Although molecular signatures characterising pluripotency and multipotency exist, there is, as yet, no single quantitative mark of a cellular sample's position in the global differentiation hierarchy. Here we adopt a systems view and consider the sample's network entropy, a measure of signaling pathway promiscuity, computable from a sample's genome-wide expression profile. We demonstrate that network entropy provides a quantitative, in-silico, readout of the average undifferentiated state of the profiled cells, recapitulating the known hierarchy of pluripotent, multipotent and differentiated cell types. Network entropy further exhibits dynamic changes in time course differentiation data, and in line with a sample's differentiation stage. In disease, network entropy predicts a higher level of cellular plasticity in cancer stem cell populations compared to ordinary cancer cells. Importantly, network entropy also allows identification of key differentiation pathways. Our results are consistent with the view that pluripotency is a statistical property defined at the cellular population level, correlating with intra-sample heterogeneity, and driven by the degree of signaling promiscuity in cells. In summary, network entropy provides a quantitative measure of a cell's undifferentiated state, defining its elevation in Waddington's landscape.
doi:10.1038/srep03039
PMCID: PMC3807110  PMID: 24154593
8.  Corruption of the Intra-Gene DNA Methylation Architecture Is a Hallmark of Cancer 
PLoS ONE  2013;8(7):e68285.
Epigenetic processes - including DNA methylation - are increasingly seen as having a fundamental role in chronic diseases like cancer. It is well known that methylation levels at particular genes or loci differ between normal and diseased tissue. Here we investigate whether the intra-gene methylation architecture is corrupted in cancer and whether the variability of levels of methylation of individual CpGs within a defined gene is able to discriminate cancerous from normal tissue, and is associated with heterogeneous tumour phenotype, as defined by gene expression. We analysed 270985 CpGs annotated to 18272 genes, in 3284 cancerous and 681 normal samples, corresponding to 14 different cancer types. In doing so, we found novel differences in intra-gene methylation pattern across phenotypes, particularly in those genes which are crucial for stem cell biology; our measures of intra-gene methylation architecture are a better determinant of phenotype than measures based on mean methylation level alone (K-S test in all 14 diseases tested). These per-gene methylation measures also represent a considerable reduction in complexity, compared to conventional per-CpG beta-values. Our findings strongly support the view that intra-gene methylation architecture has great clinical potential for the development of DNA-based cancer biomarkers.
doi:10.1371/journal.pone.0068285
PMCID: PMC3712966  PMID: 23874574
9.  CDK-mediated activation of the SCFFBXO28 ubiquitin ligase promotes MYC-driven transcription and tumourigenesis and predicts poor survival in breast cancer 
EMBO Molecular Medicine  2013;5(7):999-1018.
SCF (Skp1/Cul1/F-box) ubiquitin ligases act as master regulators of cellular homeostasis by targeting key proteins for ubiquitylation. Here, we identified a hitherto uncharacterized F-box protein, FBXO28 that controls MYC-dependent transcription by non-proteolytic ubiquitylation. SCFFBXO28 activity and stability are regulated during the cell cycle by CDK1/2-mediated phosphorylation of FBXO28, which is required for its efficient ubiquitylation of MYC and downsteam enhancement of the MYC pathway. Depletion of FBXO28 or overexpression of an F-box mutant unable to support MYC ubiquitylation results in an impairment of MYC-driven transcription, transformation and tumourigenesis. Finally, in human breast cancer, high FBXO28 expression and phosphorylation are strong and independent predictors of poor outcome. In conclusion, our data suggest that SCFFBXO28 plays an important role in transmitting CDK activity to MYC function during the cell cycle, emphasizing the CDK-FBXO28-MYC axis as a potential molecular drug target in MYC-driven cancers, including breast cancer.
doi:10.1002/emmm.201202341
PMCID: PMC3721474  PMID: 23776131
Breast cancer; CDK; F-box protein; FBXO28; MYC
10.  A randomised controlled trial comparing surgical intervention rates between two protocols for the management of asymptomatic adnexal tumours in postmenopausal women 
BMJ Open  2012;2(6):e002248.
Introduction
Detection of asymptomatic adnexal tumours in postmenopausal women has increased due to wider use of diagnostic ultrasound and imaging quality improvements. Reliable methods to differentiate between benign and malignant tumours are required to avoid delays in treating ovarian cancer and to prevent unnecessary interventions for benign lesions. In the UK, the Royal College of Obstetricians and Gynaecologists has issued guidance for the management of adnexal cysts in postmenopausal women, which is considered standard in routine clinical practice. The protocol utilises the Risk of Malignancy Index to assess the risk of adnexal lesion being malignant. This protocol has a relatively high intervention rate in order to avoid a delay in a cancer diagnosis. The Simple Rules Protocol designed by International Ovarian Tumour Analysis Group reports a low false-positive rate in the diagnosis of ovarian cancer without a loss of sensitivity and therefore has the potential to reduce unnecessary interventions in asymptomatic postmenopausal women with benign cysts.
Methods and analysis
140 postmenopausal women aged 40–80, with incidentally detected adnexal tumours on ultrasound scan will be recruited to this study. They will be randomly allocated, to be assessed and managed according to either of the two protocols under investigation. In both arms of the study the tumours will be classified into three groups: high, intermediate or low risk of malignancy. Women with high risk of malignancy will be referred for management in a tertiary cancer centre, women with low-risk tumours will be managed expectantly, while those with intermediate risk findings have surgery in their local hospital units. Analysis will be on an intention-to-treat basis.
Ethics and dissemination
Research ethical approval was granted by the North London Research Ethical Committee 2 (10/H0724/48). Trial results will be published according to the CONSORT statement.
Trial registration number
Registration at http://www.controlled-trials.com/ISRCTN89034131/. ISRCTN89034131
doi:10.1136/bmjopen-2012-002248
PMCID: PMC3533090  PMID: 23233701
Cancer; Gynaecology; Imaging
11.  A comparison of feature selection and classification methods in DNA methylation studies using the Illumina Infinium platform 
BMC Bioinformatics  2012;13:59.
Background
The 27k Illumina Infinium Methylation Beadchip is a popular high-throughput technology that allows the methylation state of over 27,000 CpGs to be assayed. While feature selection and classification methods have been comprehensively explored in the context of gene expression data, relatively little is known as to how best to perform feature selection or classification in the context of Illumina Infinium methylation data. Given the rising importance of epigenomics in cancer and other complex genetic diseases, and in view of the upcoming epigenome wide association studies, it is critical to identify the statistical methods that offer improved inference in this novel context.
Results
Using a total of 7 large Illumina Infinium 27k Methylation data sets, encompassing over 1,000 samples from a wide range of tissues, we here provide an evaluation of popular feature selection, dimensional reduction and classification methods on DNA methylation data. Specifically, we evaluate the effects of variance filtering, supervised principal components (SPCA) and the choice of DNA methylation quantification measure on downstream statistical inference. We show that for relatively large sample sizes feature selection using test statistics is similar for M and β-values, but that in the limit of small sample sizes, M-values allow more reliable identification of true positives. We also show that the effect of variance filtering on feature selection is study-specific and dependent on the phenotype of interest and tissue type profiled. Specifically, we find that variance filtering improves the detection of true positives in studies with large effect sizes, but that it may lead to worse performance in studies with smaller yet significant effect sizes. In contrast, supervised principal components improves the statistical power, especially in studies with small effect sizes. We also demonstrate that classification using the Elastic Net and Support Vector Machine (SVM) clearly outperforms competing methods like LASSO and SPCA. Finally, in unsupervised modelling of cancer diagnosis, we find that non-negative matrix factorisation (NMF) clearly outperforms principal components analysis.
Conclusions
Our results highlight the importance of tailoring the feature selection and classification methodology to the sample size and biological context of the DNA methylation study. The Elastic Net emerges as a powerful classification algorithm for large-scale DNA methylation studies, while NMF does well in the unsupervised context. The insights presented here will be useful to any study embarking on large-scale DNA methylation profiling using Illumina Infinium beadarrays.
doi:10.1186/1471-2105-13-59
PMCID: PMC3364843  PMID: 22524302
DNA methylation; Classification; Feature selection; Beadarrays
12.  Association of serum sex steroid receptor bioactivity and sex steroid hormones with breast cancer risk in postmenopausal women 
Endocrine-Related Cancer  2012;19(2):137-147.
Postmenopausal women with elevated serum sex steroids have an increased risk of breast cancer. Most of this risk is believed to be exerted through binding of the sex steroids to their receptors. For the first time, we investigate the association of estrogen receptor (ER) and androgen receptor (AR) serum bioactivity (SB) in addition to hormone levels in samples from women with breast cancer collected before diagnosis. Two hundred postmenopausal women participating in the UK Collaborative Trial of Ovarian Cancer Screening who developed ER-positive breast cancer 0.6–5 years after sample donation were identified and matched to 400 controls. ER and AR bioassays were used to measure ERα, ERβ, and AR SB. Androgen and estrogen levels were measured with immunoassays. Subjects were classified according to quintiles of the respective marker among controls and the associations between SB and hormones with breast cancer risk were determined by logistic regression analysis. ERα and ERβ SB were significantly higher before diagnosis compared with controls, while estrogens showed no difference. Women had a twofold increased breast cancer risk if ERα SB (odds ratio (OR), 2.114; 95% confidence interval (CI), 1.050–4.425; P=0.040) was in the top quintile >2 years before diagnosis or estrone (OR, 2.205; 95% CI, 1.104–4.586; P=0.029) was in the top quintile <2 years before diagnosis. AR showed no significant association with breast cancer while androstenedione (OR, 3.187; 95% CI, 1.738–6.044; P=0.0003) and testosterone (OR, 2.145; 95% CI, 1.256–3.712; P=0.006) were significantly higher compared with controls and showed a strong association with an almost threefold increased breast cancer risk independent of time to diagnosis. This study provides further evidence on the association of androgens and estrogens with breast cancer. In addition, it reports that high ER but not AR SB is associated with increased breast risk >2 years before diagnosis.
doi:10.1530/ERC-11-0310
PMCID: PMC3322660  PMID: 22199143
13.  Epigenetic variability in cells of normal cytology is associated with the risk of future morphological transformation 
Genome Medicine  2012;4(3):24.
Background
Recently, it has been proposed that epigenetic variation may contribute to the risk of complex genetic diseases like cancer. We aimed to demonstrate that epigenetic changes in normal cells, collected years in advance of the first signs of morphological transformation, can predict the risk of such transformation.
Methods
We analyzed DNA methylation (DNAm) profiles of over 27,000 CpGs in cytologically normal cells of the uterine cervix from 152 women in a prospective nested case-control study. We used statistics based on differential variability to identify CpGs associated with the risk of transformation and a novel statistical algorithm called EVORA (Epigenetic Variable Outliers for Risk prediction Analysis) to make predictions.
Results
We observed many CpGs that were differentially variable between women who developed a non-invasive cervical neoplasia within 3 years of sample collection and those that remained disease-free. These CpGs exhibited heterogeneous outlier methylation profiles and overlapped strongly with CpGs undergoing age-associated DNA methylation changes in normal tissue. Using EVORA, we demonstrate that the risk of cervical neoplasia can be predicted in blind test sets (AUC = 0.66 (0.58 to 0.75)), and that assessment of DNAm variability allows more reliable identification of risk-associated CpGs than statistics based on differences in mean methylation levels. In independent data, EVORA showed high sensitivity and specificity to detect pre-invasive neoplasia and cervical cancer (AUC = 0.93 (0.86 to 1) and AUC = 1, respectively).
Conclusions
We demonstrate that the risk of neoplastic transformation can be predicted from DNA methylation profiles in the morphologically normal cell of origin of an epithelial cancer. Having profiled only 0.1% of CpGs in the human genome, studies of wider coverage are likely to yield improved predictive and diagnostic models with the accuracy needed for clinical application.
Trial registration
The ARTISTIC trial is registered with the International Standard Randomised Controlled Trial Number ISRCTN25417821.
doi:10.1186/gm323
PMCID: PMC3446274  PMID: 22453031
15.  The Dynamics and Prognostic Potential of DNA Methylation Changes at Stem Cell Gene Loci in Women's Cancer 
PLoS Genetics  2012;8(2):e1002517.
Aberrant DNA methylation is an important cancer hallmark, yet the dynamics of DNA methylation changes in human carcinogenesis remain largely unexplored. Moreover, the role of DNA methylation for prediction of clinical outcome is still uncertain and confined to specific cancers. Here we perform the most comprehensive study of DNA methylation changes throughout human carcinogenesis, analysing 27,578 CpGs in each of 1,475 samples, ranging from normal cells in advance of non-invasive neoplastic transformation to non-invasive and invasive cancers and metastatic tissue. We demonstrate that hypermethylation at stem cell PolyComb Group Target genes (PCGTs) occurs in cytologically normal cells three years in advance of the first morphological neoplastic changes, while hypomethylation occurs preferentially at CpGs which are heavily Methylated in Embryonic Stem Cells (MESCs) and increases significantly with cancer invasion in both the epithelial and stromal tumour compartments. In contrast to PCGT hypermethylation, MESC hypomethylation progresses significantly from primary to metastatic cancer and defines a poor prognostic signature in four different gynaecological cancers. Finally, we associate expression of TET enzymes, which are involved in active DNA demethylation, to MESC hypomethylation in cancer. These findings have major implications for cancer and embryonic stem cell biology and establish the importance of systemic DNA hypomethylation for predicting prognosis in a wide range of different cancers.
Author Summary
DNA methylation is an important chemical modification of DNA that can affect and regulate the activity of genes in human tissue. Abnormal DNA methylation and its subsequent effects on gene activity are a hallmark of cancer, yet when precisely these DNA methylation changes occur and how they contribute to the development of cancer remains largely unexplored. In this work we measure the methylation state of DNA at over 14,000 genes in over 1,475 samples, including normal and benign cells, invasive cancers, and metastatic cancer tissue. Using cervical cancer as a model, we show that gain of abnormal methylation at genes typically un-methylated in stem cells can be detected up to 3 years in advance of the appearance of pre-cancerous cells, while those genes typically methylated in stem cells lose this methylation progressively throughout cancer development. Furthermore, we discover that this process of methylation loss during cancer progression is a marker of poor disease outcome common to all four major women-specific cancers: breast, ovarian, endometrial, and cervical cancers. Finally we demonstrate the relationship between loss of methylation and cancer-specific over-production of a specific protein known to play an active role in removing methylation from DNA. Taken together these findings highlight the complex nature of DNA methylation dynamics in cancer development as well as their potential exploitation for clinical gain.
doi:10.1371/journal.pgen.1002517
PMCID: PMC3276553  PMID: 22346766
16.  Genome-Scale Screen for DNA Methylation-Based Detection Markers for Ovarian Cancer 
PLoS ONE  2011;6(12):e28141.
Background
The identification of sensitive biomarkers for the detection of ovarian cancer is of high clinical relevance for early detection and/or monitoring of disease recurrence. We developed a systematic multi-step biomarker discovery and verification strategy to identify candidate DNA methylation markers for the blood-based detection of ovarian cancer.
Methodology/Principal Findings
We used the Illumina Infinium platform to analyze the DNA methylation status of 27,578 CpG sites in 41 ovarian tumors. We employed a marker selection strategy that emphasized sensitivity by requiring consistency of methylation across tumors, while achieving specificity by excluding markers with methylation in control leukocyte or serum DNA. Our verification strategy involved testing the ability of identified markers to monitor disease burden in serially collected serum samples from ovarian cancer patients who had undergone surgical tumor resection compared to CA-125 levels.
We identified one marker, IFFO1 promoter methylation (IFFO1-M), that is frequently methylated in ovarian tumors and that is rarely detected in the blood of normal controls. When tested in 127 serially collected sera from ovarian cancer patients, IFFO1-M showed post-resection kinetics significantly correlated with serum CA-125 measurements in six out of 16 patients.
Conclusions/Significance
We implemented an effective marker screening and verification strategy, leading to the identification of IFFO1-M as a blood-based candidate marker for sensitive detection of ovarian cancer. Serum levels of IFFO1-M displayed post-resection kinetics consistent with a reflection of disease burden. We anticipate that IFFO1-M and other candidate markers emerging from this marker development pipeline may provide disease detection capabilities that complement existing biomarkers.
doi:10.1371/journal.pone.0028141
PMCID: PMC3233546  PMID: 22163280
17.  Toll-Like Receptor 9 expression in breast and ovarian cancer is associated with poorly differentiated tumors 
Cancer science  2010;101(4):1059-1066.
Summary
Toll-like-receptor-9 (TLR9) activates the innate immune response when exposed to non-methylated CpG-DNA. TLR9 was recently shown to be expressed by cancer cells which have been previously characterized by global hypomethylation. We set out to examine the expression and molecular activity of TLR9 in breast and ovarian cancer cells. Firstly, we confirmed higher levels of hypomethylated DNA in the serum of patients with metastatic breast cancer (n=18) versus age-matched tumor free women (n=18). In breast cancer cell lines and tissues, TLR9 mRNA-expression was associated with estrogen-receptor (ER) status (n=124, P=0.005). Expression also correlated with increasing tumor grade in both breast (P=0.03) and ovarian cancer specimens (n=138, P=0.04). Immunohistochemical analysis of formalin-fixed paraffin embedded (FFPE) breast cancer tissues revealed higher TLR9 protein-expression in hormone-receptor (HR) negative specimens (n=116, P=<0.001). Using an in vitro scratch assay, we observed that cell lines transfected to overexpress TLR9 demonstrated increased cellular migration when stimulated with CpG-DNA. When assessing the molecular activity of TLR9 in breast cancer, we found a strong positive correlation of nuclear factor Kappa B (NF-κB) activity with TLR9 mRNA-expression (correlation coefficient r=0.7, P<0.001). Finally, immunofluorescence analysis of BT-20 and Hs578T breast cancer cell lines showed partial colocalizations of CpG-DNA with TLR9, which diminished when the cells were exposed to methylated CpG-DNA (mCpG-DNA) or control GpC-DNA.
In summary we demonstrate that TLR9 expression is associated with poor differentiation in breast and ovarian cancer specimens, and that TLR9-overexpression and stimulation with hypomethylated DNA augments the migratory capacity of cancer cells lines.
doi:10.1111/j.1349-7006.2010.01491.x
PMCID: PMC3188854  PMID: 20156214
TLR9; Breast cancer; Ovarian cancer; Hormone receptors
18.  A Genome-Wide Association Study Identifies Susceptibility Loci for Ovarian Cancer at 2q31 and 8q24 
Goode, Ellen L. | Chenevix-Trench, Georgia | Song, Honglin | Ramus, Susan J. | Notaridou, Maria | Lawrenson, Kate | Widschwendter, Martin | Vierkant, Robert A. | Larson, Melissa C. | Kjaer, Susanne K. | Birrer, Michael J. | Berchuck, Andrew | Schildkraut, Joellen | Tomlinson, Ian | Kiemeney, Lambertus A. | Cook, Linda S. | Gronwald, Jacek | Garcia-Closas, Montserrat | Gore, Martin E. | Campbell, Ian | Whittemore, Alice S. | Sutphen, Rebecca | Phelan, Catherine | Anton-Culver, Hoda | Pearce, Celeste Leigh | Lambrechts, Diether | Rossing, Mary Anne | Chang-Claude, Jenny | Moysich, Kirsten B. | Goodman, Marc T. | Dörk, Thilo | Nevanlinna, Heli | Ness, Roberta B. | Rafnar, Thorunn | Hogdall, Claus | Hogdall, Estrid | Fridley, Brooke L. | Cunningham, Julie M. | Sieh, Weiva | McGuire, Valerie | Godwin, Andrew K. | Cramer, Daniel W. | Hernandez, Dena | Levine, Douglas | Lu, Karen | Iversen, Edwin S. | Palmieri, Rachel T. | Houlston, Richard | van Altena, Anne M. | Aben, Katja K.H. | Massuger, Leon F.A.G. | Brooks-Wilson, Angela | Kelemen, Linda E. | Le, Nhu D. | Jakubowska, Anna | Lubinski, Jan | Medrek, Krzysztof | Stafford, Anne | Easton, Douglas F. | Tyrer, Jonathan | Bolton, Kelly L. | Harrington, Patricia | Eccles, Diana | Chen, Ann | Molina, Ashley N. | Davila, Barbara N. | Arango, Hector | Tsai, Ya-Yu | Chen, Zhihua | Risch, Harvey A. | McLaughlin, John | Narod, Steven A. | Ziogas, Argyrios | Brewster, Wendy | Gentry-Maharaj, Aleksandra | Menon, Usha | Wu, Anna H. | Stram, Daniel O. | Pike, Malcolm C. | Beesley, Jonathan | Webb, Penelope M. | Chen, Xiaoqing | Ekici, Arif B. | Thiel, Falk C. | Beckmann, Matthias W. | Yang, Hannah | Wentzensen, Nicolas | Lissowska, Jolanta | Fasching, Peter A. | Despierre, Evelyn | Amant, Frederic | Vergote, Ignace | Doherty, Jennifer | Hein, Rebecca | Wang-Gohrke, Shan | Lurie, Galina | Carney, Michael E. | Thompson, Pamela J. | Runnebaum, Ingo | Hillemanns, Peter | Dürst, Matthias | Antonenkova, Natalia | Bogdanova, Natalia | Leminen, Arto | Butzow, Ralf | Heikkinen, Tuomas | Stefansson, Kari | Sulem, Patrick | Besenbacher, Sören | Sellers, Thomas A. | Gayther, Simon A. | Pharoah, Paul D.P.
Nature genetics  2010;42(10):874-879.
Ovarian cancer (OC) accounts for more deaths than all other gynecological cancers combined. To identify common low-penetrance OC susceptibility genes, we conducted a genome-wide association study (GWAS) of 507,094 SNPs in 1,768 cases and 2,354 controls, with follow-up of 21,955 SNPs in 4,162 cases and 4,810 controls, leading to the identification of a confirmed susceptibility locus at 9p22 (BNC2)1. Here, we report on nine additional candidate loci (p≤10-4), identified after stratifying cases by histology, genotyped in an additional 4,353 cases and 6,021 controls. Two novel susceptibility loci with p≤5×10-8 were confirmed (8q24, p=8.0×10-15 and 2q31, p=3.8×10-14); two additional loci were also identified that approached genome-wide significance (3q25, p=7.1×10-8 and 17q21, p=1.4×10-7). The associations with serous OC were generally stronger than other subtypes. Analysis of HOXD1, MYC, TiPARP, and SKAP1 at these loci, and BNC2 at 9p22, supports a functional role for these genes in OC development.
doi:10.1038/ng.668
PMCID: PMC3020231  PMID: 20852632
19.  Osteoclast differentiation factor RANKL controls development of progestin-driven mammary cancer 
Nature  2010;468(7320):98-102.
Breast cancer is one of the most common cancers in humans and will on average affect up to one in eight women in their lifetime in the United States and Europe1. The Women’s Health Initiative and the Million Women Study have shown that hormone replacement therapy is associated with an increased risk of incident and fatal breast cancer2,3. In particular, synthetic progesterone derivatives (progestins) such as medroxyprogesterone acetate (MPA), used in millions of women for hormone replacement therapy and contraceptives, markedly increase the risk of developing breast cancer. Here we show that the in vivo administration of MPA triggers massive induction of the key osteoclast differentiation factor RANKL (receptor activator of NF-κB ligand) in mammary-gland epithelial cells. Genetic inactivation of the RANKL receptor RANK in mammary-gland epithelial cells prevents MPA-induced epithelial proliferation, impairs expansion of the CD49fhi stem-cell-enriched population, and sensitizes these cells to DNA-damage-induced cell death. Deletion of RANK from the mammary epithelium results in a markedly decreased incidence and delayed onset of MPA-driven mammary cancer. These data show that the RANKL/RANK system controls the incidence and onset of progestin-driven breast cancer.
doi:10.1038/nature09387
PMCID: PMC3084017  PMID: 20881962
20.  Inactivation of FBXW7/hCDC4-β expression by promoter hypermethylation is associated with favorable prognosis in primary breast cancer 
Breast Cancer Research : BCR  2010;12(6):R105.
Introduction
Mutational inactivation of the FBXW7/hCDC4 tumor suppressor gene (TSG) is common in many cancer types, but infrequent in breast cancers. This study investigates the presence and impact of FBXW7/hCDC4 promoter methylation in breast cancer.
Methods
FBXW7/hCDC4-β expression and promoter methylation was assessed in 161 tumors from two independent breast cancer cohorts. Associations between methylation status and clinicopathologic characteristics were assessed by Fisher's exact test. Survival was analyzed using the Kaplan-Meier method in addition to modeling the risk by use of a multivariate proportional hazard (Cox) model adjusting for possible confounders of survival.
Results
Methylation of the promoter and loss of mRNA expression was found both in cell lines and primary tumors (43% and 51%, respectively). Using Cox modeling, a trend was found towards decreased hazard ratio (HR) for death in women with methylation of FBXW7/hCDC4-β in both cohorts (HR 0.53 (95% CI 0.23 to 1.23) and HR 0.50 (95% CI 0.23 to 1.08), respectively), despite an association between methylation and high-grade tumors (P = 0.017). Interestingly, in subgroups of patients whose tumors are p53 mutated or lymph-node positive, promoter methylation identified patients with significantly improved survival (P = 0.048 and P = 0.017, respectively).
Conclusions
We demonstrate an alternative mechanism for inactivation of the TSG FBXW7/hCDC4, namely promoter specific methylation. Importantly, in breast cancer, methylation of FBXW7/hCDC4-β is related to favorable prognosis despite its association with poorly differentiated tumors. Future work may define whether FBXW7/hCDC4 methylation is a biomarker of the response to chemotherapy and a target for epigenetic modulation therapy.
doi:10.1186/bcr2788
PMCID: PMC3046450  PMID: 21122106
21.  Development and Validation of a Method for Profiling Post-Translational Modification Activities Using Protein Microarrays 
PLoS ONE  2010;5(6):e11332.
Background
Post-translational modifications (PTMs) impact on the stability, cellular location, and function of a protein thereby achieving a greater functional diversity of the proteome. To fully appreciate how PTMs modulate signaling networks, proteome-wide studies are necessary. However, the evaluation of PTMs on a proteome-wide scale has proven to be technically difficult. To facilitate these analyses we have developed a protein microarray-based assay that is capable of profiling PTM activities in complex biological mixtures such as whole-cell extracts and pathological specimens.
Methodology/Principal Findings
In our assay, protein microarrays serve as a substrate platform for in vitro enzymatic reactions in which a recombinant ligase, or extracts prepared from whole cells or a pathological specimen is overlaid. The reactions include labeled modifiers (e.g., ubiquitin, SUMO1, or NEDD8), ATP regenerating system, and other required components (depending on the assay) that support the conjugation of the modifier. In this report, we apply this methodology to profile three molecularly complex PTMs (ubiquitylation, SUMOylation, and NEDDylation) using purified ligase enzymes and extracts prepared from cultured cell lines and pathological specimens. We further validate this approach by confirming the in vivo modification of several novel PTM substrates identified by our assay.
Conclusions/Significance
This methodology offers several advantages over currently used PTM detection methods including ease of use, rapidity, scale, and sample source diversity. Furthermore, by allowing for the intrinsic enzymatic activities of cell populations or pathological states to be directly compared, this methodology could have widespread applications for the study of PTMs in human diseases and has the potential to be directly applied to most, if not all, basic PTM research.
doi:10.1371/journal.pone.0011332
PMCID: PMC2893156  PMID: 20596523
22.  An Epigenetic Signature in Peripheral Blood Predicts Active Ovarian Cancer 
PLoS ONE  2009;4(12):e8274.
Background
Recent studies have shown that DNA methylation (DNAm) markers in peripheral blood may hold promise as diagnostic or early detection/risk markers for epithelial cancers. However, to date no study has evaluated the diagnostic and predictive potential of such markers in a large case control cohort and on a genome-wide basis.
Principal Findings
By performing genome-wide DNAm profiling of a large ovarian cancer case control cohort, we here demonstrate that active ovarian cancer has a significant impact on the DNAm pattern in peripheral blood. Specifically, by measuring the methylation levels of over 27,000 CpGs in blood cells from 148 healthy individuals and 113 age-matched pre-treatment ovarian cancer cases, we derive a DNAm signature that can predict the presence of active ovarian cancer in blind test sets with an AUC of 0.8 (95% CI (0.74–0.87)). We further validate our findings in another independent set of 122 post-treatment cases (AUC = 0.76 (0.72–0.81)). In addition, we provide evidence for a significant number of candidate risk or early detection markers for ovarian cancer. Furthermore, by comparing the pattern of methylation with gene expression data from major blood cell types, we here demonstrate that age and cancer elicit common changes in the composition of peripheral blood, with a myeloid skewing that increases with age and which is further aggravated in the presence of ovarian cancer. Finally, we show that most cancer and age associated methylation variability is found at CpGs located outside of CpG islands.
Significance
Our results underscore the potential of DNAm profiling in peripheral blood as a tool for detection or risk-prediction of epithelial cancers, and warrants further in-depth and higher CpG coverage studies to further elucidate this role.
doi:10.1371/journal.pone.0008274
PMCID: PMC2793425  PMID: 20019873
23.  Epigenotyping in Peripheral Blood Cell DNA and Breast Cancer Risk: A Proof of Principle Study 
PLoS ONE  2008;3(7):e2656.
Background
Epigenetic changes are emerging as one of the most important events in carcinogenesis. Two alterations in the pattern of DNA methylation in breast cancer (BC) have been previously reported; active estrogen receptor-α (ER-α) is associated with decreased methylation of ER-α target (ERT) genes, and polycomb group target (PCGT) genes are more likely than other genes to have promoter DNA hypermethylation in cancer. However, whether DNA methylation in normal unrelated cells is associated with BC risk and whether these imprints can be related to factors which can be modified by the environment, is unclear.
Methodology/Principal Findings
Using quantitative methylation analysis in a case-control study (n = 1,083) we found that DNA methylation of peripheral blood cell DNA provides good prediction of BC risk. We also report that invasive ductal and invasive lobular BC is characterized by two different sets of genes, the latter particular by genes involved in the differentiation of the mesenchyme (PITX2, TITF1, GDNF and MYOD1). Finally we demonstrate that only ERT genes predict ER positive BC; lack of peripheral blood cell DNA methylation of ZNF217 predicted BC independent of age and family history (odds ratio 1.49; 95% confidence interval 1.12–1.97; P = 0.006) and was associated with ER-α bioactivity in the corresponding serum.
Conclusion/Significance
This first large-scale epigenotyping study demonstrates that DNA methylation may serve as a link between the environment and the genome. Factors that can be modulated by the environment (like estrogens) leave an imprint in the DNA of cells that are unrelated to the target organ and indicate the predisposition to develop a cancer. Further research will need to demonstrate whether DNA methylation profiles will be able to serve as a new tool to predict the risk of developing chronic diseases with sufficient accuracy to guide preventive measures.
doi:10.1371/journal.pone.0002656
PMCID: PMC2442168  PMID: 18628976
24.  5-Methylcytosine—The Fifth Base of DNA: The Fifth Wheel on a Car or a Highly Promising Diagnostic and Therapeutic Target in Cancer? 
Disease Markers  2007;23(1-2):1-3.
doi:10.1155/2007/860404
PMCID: PMC3851080  PMID: 17325422
DNA methylation; epigenetics; 5-methylcytosine; biomarkers

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