Genome-wide methylation analysis identifies genes specific to breast cancer hormone receptor status and risk of recurrence

Temporal stability and determinants of white blood cell DNA methylation in the breakthrough generations study

BACKGROUND

Epigenome-wide association studies (EWAS) using measurements of blood DNA methylation are performed to identify associations of methylation changes with environmental and lifestyle exposures and disease risk. However, little is known about the variation of methylation markers in the population and their stability over time, both important factors in the design and interpretation of EWAS. We aimed to identify stable variable methylated probes (VMP), i.e., markers that are variable in the population, yet stable over time.

METHODS

We estimated the intraclass correlation coefficient (ICC) for each probe on the Illumina 450K methylation array in paired samples collected approximately 6 years apart from 92 participants in the Breakthrough Generations Study. We also evaluated relationships with age, reproductive and hormonal history, weight, alcohol intake, and smoking.

RESULTS

Approximately 17% of probes had an ICC > 0.50 and were considered stable VMPs (stable-VMPs). Stable-VMPs were enriched for probes located in "shores" bordering CpG islands, and at approximately 1.3 kb downstream from the transcription start site in the transition between the unmethylated promoter and methylated gene body. Both cross-sectional and longitudinal data analyses provided strong evidence for associations between changes in methylation levels and aging. Smoking-related probes at 2q37.1 and AHRR were stable-VMPs and related to time since quitting. We also observed associations between methylation and weight changes.

CONCLUSION

Our results provide support for the use of white blood cell DNA methylation as a biomarker of exposure in EWAS.

IMPACT

Larger studies, preferably with repeated measures over time, will be required to establish associations between specific probes and exposures.

The CpG island methylator phenotype in breast cancer is associated with the lobular subtype

BACKGROUND

Aberrations in DNA methylation patterns are well-described in human malignancies. However, the existence of the 'CpG island methylator phenotype' (CIMP) in human breast cancer is still controversial.

MATERIALS & METHODS

Illumina's HumanMethylation 450K BeadChip was used to analyze genome-wide DNA methylation patterns. Chromosomal abnormalities were determined by array-based CGH.

RESULTS

Invasive lobular breast carcinomas exhibit the highest number of differentially methylated CpG sites and a strong inverse correlation of aberrant DNA hypermethylation and copy number alterations. Nine differentially methylated regions within seven genes discriminating the investigated subgroups were identified and validated in an independent validation cohort and correlated to a better relapse-free survival.

CONCLUSION

These results depict a clear difference between genetically and epigenetically unstable breast carcinomas indicating different ways of tumor progression and/or initiation, which strongly supports the association of CIMP with the lobular subtype and provide new options for detection and therapy.

DNA methylation profiling in the Carolina Breast Cancer Study defines cancer subclasses differing in clinicopathologic characteristics and survival

INTRODUCTION

Breast cancer is a heterogeneous disease, with several intrinsic subtypes differing by hormone receptor (HR) status, molecular profiles, and prognosis. However, the role of DNA methylation in breast cancer development and progression and its relationship with the intrinsic tumor subtypes are not fully understood.

METHODS

A microarray targeting promoters of cancer-related genes was used to evaluate DNA methylation at 935 CpG sites in 517 breast tumors from the Carolina Breast Cancer Study, a population-based study of invasive breast cancer.

RESULTS

Consensus clustering using methylation (β) values for the 167 most variant CpG loci defined four clusters differing most distinctly in HR status, intrinsic subtype (luminal versus basal-like), and p53 mutation status. Supervised analyses for HR status, subtype, and p53 status identified 266 differentially methylated CpG loci with considerable overlap. Genes relatively hypermethylated in HR+, luminal A, or p53 wild-type breast cancers included FABP3, FGF2, FZD9, GAS7, HDAC9, HOXA11, MME, PAX6, POMC, PTGS2, RASSF1, RBP1, and SCGB3A1, whereas those more highly methylated in HR-, basal-like, or p53 mutant tumors included BCR, C4B, DAB2IP, MEST, RARA, SEPT5, TFF1, THY1, and SERPINA5. Clustering also defined a hypermethylated luminal-enriched tumor cluster 3 that gene ontology analysis revealed to be enriched for homeobox and other developmental genes (ASCL2, DLK1, EYA4, GAS7, HOXA5, HOXA9, HOXB13, IHH, IPF1, ISL1, PAX6, TBX1, SOX1, and SOX17). Although basal-enriched cluster 2 showed worse short-term survival, the luminal-enriched cluster 3 showed worse long-term survival but was not independently prognostic in multivariate Cox proportional hazard analysis, likely due to the mostly early stage cases in this dataset.

CONCLUSIONS

This study demonstrates that epigenetic patterns are strongly associated with HR status, subtype, and p53 mutation status and may show heterogeneity within tumor subclass. Among HR+ breast tumors, a subset exhibiting a gene signature characterized by hypermethylation of developmental genes and poorer clinicopathologic features may have prognostic value and requires further study. Genes differentially methylated between clinically important tumor subsets have roles in differentiation, development, and tumor growth and may be critical to establishing and maintaining tumor phenotypes and clinical outcomes.

DNA methylation age of human tissues and cell types

Background

It is not yet known whether DNA methylation levels can be used to accurately predict age across a broad spectrum of human tissues and cell types, nor whether the resulting age prediction is a biologically meaningful measure.

Results

I developed a multi-tissue predictor of age that allows one to estimate the DNA methylation age of most tissues and cell types. The predictor, which is freely available, was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. I found that DNA methylation age has the following properties: first, it is close to zero for embryonic and induced pluripotent stem cells; second, it correlates with cell passage number; third, it gives rise to a highly heritable measure of age acceleration; and, fourth, it is applicable to chimpanzee tissues. Analysis of 6,000 cancer samples from 32 datasets showed that all of the considered 20 cancer types exhibit significant age acceleration, with an average of 36 years. Low age-acceleration of cancer tissue is associated with a high number of somatic mutations and TP53 mutations, while mutations in steroid receptors greatly accelerate DNA methylation age in breast cancer. Finally, I characterize the 353 CpG sites that together form an aging clock in terms of chromatin states and tissue variance.

Conclusions

I propose that DNA methylation age measures the cumulative effect of an epigenetic maintenance system. This novel epigenetic clock can be used to address a host of questions in developmental biology, cancer and aging research.

Do breast cancer cell lines provide a relevant model of the patient tumor methylome?

It is well documented that tumor cells undergo dramatic genetic and epigenetic changes during initial establishment as cell lines and in subsequent serial passaging, and that the resultant cell lines may have evolved significantly from the primary tumors from which they were derived. This has potential implications due to their widespread use in drug response experiments and studies of genomic function. One approach to optimizing the design of such cell line studies is to identify and use the cell lines that faithfully recapitulate critical features of primary tumors. To evaluate the epigenetic fidelity of breast cancer cell lines in the context of primary tumors, we performed methylation profiling of 55 well-characterized breast cancer cell lines on the Illumina HumanMethylation27 BeadChip platform, and compared them to publicly available methylation profiles of primary breast tumors. We found that the DNA methylation profiles of breast cancer cell lines largely retain the features that characterize primary tumors, although there are crucial differences as well. We describe these similarities and differences between primary tumors and breast cancer cell lines in detail, and develop a quantitative measure of similarity that is used to score each cell line with respect to how faithfully its methylation profile mirrors that of primary tumors.

Evaluation of wild yam (Dioscorea villosa) root extract as a potential epigenetic agent in breast cancer cells

The present study was designed to evaluate the efficacy of wild yam root extract (WYRE) as a potential demethylating agent using two breast cancer cell lines, MCF-7 (estrogen receptor positive; ER(+)) and MDA-MB-231 (Estrogen receptor negative; ER(-)), and a methylated gene, GATA3, as a potential marker of breast cancer development. The cells were treated with WYRE (0-50 μg/mL) for 72 h and used for viability, mRNA, and methylation analyses. WYRE significantly reduced viability of both cell lines and enhanced mRNA content of GATA3 in a concentration-dependent manner; however, DNMT mRNAs (DNMT1, 3A, 3B) were found to increase significantly only in MDA-MB-231 cells. Global DNA methylation, analyzed as 5'-methyl-2'-deoxycytidine (5-mC) and 5-hydroxymethylcytosine (5-hmC), showed a concentration-dependent enhancement of 5-mC with no alteration in 5-hmC level in MCF-7 cells; however, in MDA-MB-231 cells, in contrast to MCF-7 cells, 5-mC remained unaltered but 5-hmC reduced significantly in all WYRE concentrations (10-50 μg/mL) used in this study. Since 5-hmC is generated from 5-mC by ten-eleven-translocation (TET) enzymes, analysis of TET mRNAs (TET1, TET2, and TET3) in MDA-MB-231 cells indicated a concentration-dependent reduction in TET1 and induction of TET3; however, TET2 remained unaltered. No alterations in any of the TET mRNAs were found in MCF-7 cells. Methylation analysis of GATA3 promoter at specific locus indicates probable demethylating activity of WYRE in MDA-MB-231 cells. We conclude that activation of GATA3 gene in ER(-) MDA-MB-231 cells may occur by altering DNA methylation pattern on the promoter region which may be different from the mechanisms operated in ER(+) MCF-7 cells.

Validation of DNA promoter hypermethylation biomarkers in breast cancer--a short report

PURPOSE

DNA promoter hypermethylation of tumor suppressor genes is known to occur early in cancer development, including breast cancer. To improve early breast cancer detection, we aimed to investigate whether the identification of DNA promoter hypermethylation might be of added value.

METHODS

The methylation status of a panel of 19 candidate genes (AKR1B1, ALX1, ARHGEF7, FZD10, GHSR, GPX7, GREM1, GSTP1, HOXD1, KL, LHX2, MAL, MGMT, NDRG2, RASGRF2, SFRP1, SFRP2, TM6SF1 and TMEFF2) was determined in formalin-fixed paraffin-embedded normal breast and breast cancer tissue samples using gel-based methylation-specific PCR (MSP).

RESULTS

The promoters of the AKR1B1, ALX1, GHSR, GREM1, RASGRF2, SFRP2, TM6SF1 and TMEFF2 genes were found to be significantly differentially methylated in normal versus malignant breast tissues. Based on sensitivity, specificity and logistic regression analyses the best performing genes for detecting breast cancer were identified. Through multivariate analyses, we found that AKR1B1 and TM6SF1 could detect breast cancer with an area under the curve (AUC) of 0.986 in a receiver operating characteristic (ROC) assessment.

CONCLUSIONS

Based on our data, we conclude that AKR1B1 and TM6SF1 may serve as candidate methylation biomarkers for early breast cancer detection. Further studies are underway to evaluate the methylation status of these genes in body fluids, including nipple aspirates and blood.

A network-based, integrative approach to identify genes with aberrant co-methylation in colorectal cancer

Epigenetic changes, including aberrations in DNA methylation, are a common hallmark of many cancers. The identification and interpretation of epigenetic changes associated with cancers may benefit from integration with protein interactomes. Based on the assumption that genes implicated in a specific tumor phenotype will show high aberrant co-methylation patterns with their interacting partners, we propose an integrated approach to uncover cancer-associated genes by integrating a DNA methylome with an interactome. Aberrant co-methylated interactions were first identified in the specific cancer, and genes were then prioritized based on their enrichment in aberrant co-methylation. By applying this to a large-scale colorectal cancer (CRC) dataset, the proposed method increases the power to capture known genes. More importantly, genes possessing high aberrant co-methylation patterns, located at the topological center of the original protein-protein interaction network (PPIN), affect several cancer-associated pathways and form hotspots that are frequently hijacked in cancer. Additionally, the top-ranked candidate genes may also be useful as an indicator of CRC diagnosis and prognosis. Five fold cross-validation of the top-ranked genes in diagnosis reveals that it can achieve an area under the receiver operating characteristic (ROC) curve ranging from 82.2% to 98.4% in three independent datasets. Five of these genes form a core repressive module. CCNA1 and ESR1 in particular are evidently silenced by promoter hypermethylation in CRC cell lines and tissues, whose re-expression markedly suppresses tumor cell survival and clonogenicity. These results show that the network-centric method could identify novel disease biomarkers and model how oncogenic lesions mediate epigenetic changes, providing important insights into tumorigenesis.

Epigenetic epidemiology of cancer

Epigenetic epidemiology includes the study of variation in epigenetic traits and the risk of disease in populations. Its application to the field of cancer has provided insight into how lifestyle and environmental factors influence the epigenome and how epigenetic events may be involved in carcinogenesis. Furthermore, it has the potential to bring benefit to patients through the identification of diagnostic markers that enable the early detection of disease and prognostic markers that can inform upon appropriate treatment strategies. However, there are a number of challenges associated with the conduct of such studies, and with the identification of biomarkers that can be applied to the clinical setting. In this review, we delineate the challenges faced in the design of epigenetic epidemiology studies in cancer, including the suitability of blood as a surrogate tissue and the capture of genome-wide DNA methylation. We describe how epigenetic epidemiology has brought insight into risk factors associated with lung, breast, colorectal and bladder cancer and review relevant research. We discuss recent findings on the identification of epigenetic diagnostic and prognostic biomarkers for these cancers.

Remodeling of the methylation landscape in breast cancer metastasis

The development of breast cancer metastasis is accompanied by dynamic transcriptome changes and dramatic alterations in nuclear and chromatin structure. The basis of these changes is incompletely understood. The DNA methylome of primary breast cancers contribute to transcriptomic heterogeneity and different metastatic behavior. Therefore we sought to characterize methylome remodeling during regional metastasis. We profiled the DNA methylome and transcriptome of 44 matched primary breast tumors and regional metastases. Striking subtype-specific patterns of metastasis-associated methylome remodeling were observed, which reflected the molecular heterogeneity of breast cancers. These divergent changes occurred primarily in CpG island (CGI)-poor areas. Regions of methylome reorganization shared by the subtypes were also observed, and we were able to identify a metastasis-specific methylation signature that was present across the breast cancer subclasses. These alterations also occurred outside of CGIs and promoters, including sequences flanking CGIs and intergenic sequences. Integrated analysis of methylation and gene expression identified genes whose expression correlated with metastasis-specific methylation. Together, these findings significantly enhance our understanding of the epigenetic reorganization that occurs during regional breast cancer metastasis across the major breast cancer subtypes and reveal the nature of methylome remodeling during this process.

Novel methylated biomarkers and a robust assay to detect circulating tumor DNA in metastatic breast cancer

The ability to consistently detect cell-free tumor-specific DNA in peripheral blood of patients with metastatic breast cancer provides the opportunity to detect changes in tumor burden and to monitor response to treatment. We developed cMethDNA, a quantitative multiplexed methylation-specific PCR assay for a panel of ten genes, consisting of novel and known breast cancer hypermethylated markers identified by mining our previously reported study of DNA methylation patterns in breast tissue (103 cancer, 21 normal on the Illumina HumanMethylation27 Beadchip) and then validating the 10-gene panel in The Cancer Genome Atlas project breast cancer methylome database. For cMethDNA, a fixed physiologic level (50 copies) of artificially constructed, standard nonhuman reference DNA specific for each gene is introduced in a constant volume of serum (300 μL) before purification of the DNA, facilitating a sensitive, specific, robust, and quantitative assay of tumor DNA, with broad dynamic range. Cancer-specific methylated DNA was detected in training (28 normal, 24 cancer) and test (27 normal, 33 cancer) sets of recurrent stage IV patient sera with a sensitivity of 91% and a specificity of 96% in the test set. In a pilot study, cMethDNA assay faithfully reflected patient response to chemotherapy (N = 29). A core methylation signature present in the primary breast cancer was retained in serum and metastatic tissues collected at autopsy two to 11 years after diagnosis of the disease. Together, our data suggest that the cMethDNA assay can detect advanced breast cancer, and monitor tumor burden and treatment response in women with metastatic breast cancer.

Whole genome DNA methylation signature of HER2-positive breast cancer

In order to obtain a comprehensive DNA methylation signature of HER2-positive breast cancer (HER2+ breast cancer), we performed a genome-wide methylation analysis on 17 HER2+ breast cancer and compared with ten normal breast tissue samples using the Illumina Infinium HumanMethylation450 BeadChip (450K). In HER2+ breast cancer, we found altered DNA methylation in genes involved in multicellular development, differentiation and transcription. Within these genes, we observed an overrepresentation of homeobox family genes, including several genes that have not been previously reported in relation to cancer (DBX1, NKX2-6, SIX6). Other affected genes included several belonging to the PI3K and Wnt signaling pathways. Notably, HER2, AKT3, HK1, and PFKP, genes for which altered methylation has not been previously reported, were also identified in this analysis. In total, we report 69 candidate biomarker genes with maximum differential methylation in HER2+ breast cancer. External validation of gene expression in a selected group of these genes (n = 13) revealed lowered mean gene expression in HER2+ breast cancer. We analyzed DNA methylation in six top candidate genes (AKR1B1, INA, FOXC2, NEUROD1, CDKL2, IRF4) using EpiTect Methyl II Custom PCR Array and confirmed the 450K array findings. Future clinical studies focusing on these genes, as well as on homeobox-containing genes and HER2, AKT3, HK1, and PFKP, are warranted which could provide further insights into the biology of HER2+ breast cancer.

A community effort to assess and improve drug sensitivity prediction algorithms

Predicting the best treatment strategy from genomic information is a core goal of precision medicine. Here we focus on predicting drug response based on a cohort of genomic, epigenomic and proteomic profiling data sets measured in human breast cancer cell lines. Through a collaborative effort between the National Cancer Institute (NCI) and the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we analyzed a total of 44 drug sensitivity prediction algorithms. The top-performing approaches modeled nonlinear relationships and incorporated biological pathway information. We found that gene expression microarrays consistently provided the best predictive power of the individual profiling data sets; however, performance was increased by including multiple, independent data sets. We discuss the innovations underlying the top-performing methodology, Bayesian multitask MKL, and we provide detailed descriptions of all methods. This study establishes benchmarks for drug sensitivity prediction and identifies approaches that can be leveraged for the development of new methods.

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.

Effect of estrogen receptor α binding on functional DNA methylation in breast cancer

Epigenetic modifications introduce an additional layer of regulation that drastically expands the instructional capability of the human genome. The regulatory consequences of DNA methylation is context dependent; it can induce, enhance, and suppress gene expression, or have no effect on gene regulation. Therefore, it is essential to account for the genomic location of its occurrence and the protein factors it associates with to improve our understanding of its function and effects. Here, we use ENCODE ChIP-seq and DNase I hypersensitivity data, along with large-scale breast cancer genomic data from The Cancer Genome Atlas (TCGA) to computationally dissect the intricacies of DNA methylation in regulation of cancer transcriptomes. In particular, we identified a relationship between estrogen receptor α (ERα) activity and DNA methylation patterning in breast cancer. We found compelling evidence that methylation status of DNA sequences at ERα binding sites is tightly coupled with ERα activity. Furthermore, we predicted several transcription factors including FOXA1, GATA1, and SUZ12 to be associated with breast cancer by examining the methylation status of their binding sites in breast cancer. Lastly, we determine that methylated CpGs highly correlated with gene expression are enriched in regions 1kb or more downstream of TSSs, suggesting more significant regulatory roles for CpGs distal to gene TSSs. Our study provides novel insights into the role of ERα in breast cancers.

Candidate luminal B breast cancer genes identified by genome, gene expression and DNA methylation profiling

Breast cancers (BCs) of the luminal B subtype are estrogen receptor-positive (ER+), highly proliferative, resistant to standard therapies and have a poor prognosis. To better understand this subtype we compared DNA copy number aberrations (CNAs), DNA promoter methylation, gene expression profiles, and somatic mutations in nine selected genes, in 32 luminal B tumors with those observed in 156 BCs of the other molecular subtypes. Frequent CNAs included 8p11-p12 and 11q13.1-q13.2 amplifications, 7q11.22-q34, 8q21.12-q24.23, 12p12.3-p13.1, 12q13.11-q24.11, 14q21.1-q23.1, 17q11.1-q25.1, 20q11.23-q13.33 gains and 6q14.1-q24.2, 9p21.3-p24,3, 9q21.2, 18p11.31-p11.32 losses. A total of 237 and 101 luminal B-specific candidate oncogenes and tumor suppressor genes (TSGs) presented a deregulated expression in relation with their CNAs, including 11 genes previously reported associated with endocrine resistance. Interestingly, 88% of the potential TSGs are located within chromosome arm 6q, and seven candidate oncogenes are potential therapeutic targets. A total of 100 candidate oncogenes were validated in a public series of 5,765 BCs and the overexpression of 67 of these was associated with poor survival in luminal tumors. Twenty-four genes presented a deregulated expression in relation with a high DNA methylation level. FOXO3, PIK3CA and TP53 were the most frequent mutated genes among the nine tested. In a meta-analysis of next-generation sequencing data in 875 BCs, KCNB2 mutations were associated with luminal B cases while candidate TSGs MDN1 (6q15) and UTRN (6q24), were mutated in this subtype. In conclusion, we have reported luminal B candidate genes that may play a role in the development and/or hormone resistance of this aggressive subtype.

Comparison of genome-wide DNA methylation in urothelial carcinomas of patients with and without arsenic exposure

BACKGROUND

Arsenic is a well-documented carcinogen of human urothelial carcinoma (UC) with incompletely understood mechanisms.

OBJECTIVES

This study aimed to compare the genome-wide DNA methylation profiles of arsenic-induced UC (AsUC) and non-arsenic-induced UC (Non-AsUC), and to assess associations between site-specific methylation levels and cumulative arsenic exposure.

METHODS

Genome-wide DNA methylation profiles in 14 AsUC and 14 non-AsUC were analyzed by Illumina Infinium methylation27 BeadChip and validated by bisulfite pyrosequencing. Mean methylation levels (β¯) in AsUC and non-AsUC were compared by their ratio (β¯ ratio) and difference (Δβ¯). Associations between site-specific methylation levels in UC and cumulative arsenic exposure were examined.

RESULTS

Among 27,578 methylation sites analyzed, 231 sites had β¯ ratio >2 or <0.5 and 45 sites had Δβ¯ >0.2 or <-0.2. There were 13 sites showing statistically significant (q<0.05) differences in β¯ between AsUC and non-AsUC including 12 hypermethylation sites in AsUC and only one hypermethylation site in non-AsUC. Significant associations between cumulative arsenic exposure and DNA methylation levels of 28 patients were observed in nine CpG sites of nine gens including PDGFD (Spearman rank correlation, 0.54), CTNNA2 (0.48), KCNK17 (0.52), PCDHB2 (0.57), ZNF132 (0.48), DCDC2 (0.48), KLK7 (0.48), FBXO39 (0.49), and NPY2R (0.45). These associations remained statistically significant for CpG sites in CTNNA2, KLK7, NPY2R, ZNF132 and KCNK17 in 20 non-smoking women after adjustment for tumor stage and age.

CONCLUSIONS

Significant associations between cumulative arsenic exposure and methylation level of CTNNA2, KLK7, NPY2R, ZNF132 and KCNK17 were found in smoking-unrelated urothelial carcinoma. Arsenic exposure may cause urothelial carcinomas through the hypermethylation of genes involved in cell adhesion, proteolysis, transcriptional regulation, neuronal pathway, and ion transport. The findings of this study, which are limited by its small sample size and moderate dose-response relation, remain to be validated by further studies with large sample sizes.

Immortality, but not oncogenic transformation, of primary human cells leads to epigenetic reprogramming of DNA methylation and gene expression

Tumourigenic transformation of normal cells into cancer typically involves several steps resulting in acquisition of unlimited growth potential, evasion of apoptosis and non-responsiveness to growth inhibitory signals. Both genetic and epigenetic changes can contribute to cancer development and progression. Given the vast genetic heterogeneity of human cancers and difficulty to monitor cancer-initiating events in vivo, the precise relationship between acquisition of genetic mutations and the temporal progression of epigenetic alterations in transformed cells is largely unclear. Here, we use an in vitro model system to investigate the contribution of cellular immortality and oncogenic transformation of primary human cells to epigenetic reprogramming of DNA methylation and gene expression. Our data demonstrate that extension of replicative life span of the cells is sufficient to induce accumulation of DNA methylation at gene promoters and large-scale changes in gene expression in a time-dependent manner. In contrast, continuous expression of cooperating oncogenes in immortalized cells, although essential for anchorage-independent growth and evasion of apoptosis, does not affect de novo DNA methylation at promoters and induces subtle expression changes. Taken together, these observations imply that cellular immortality promotes epigenetic adaptation to highly proliferative state, whereas transforming oncogenes confer additional properties to transformed human cells.

Mining cancer methylomes: prospects and challenges

There are over 28 million CpG sites in the human genome. Assessing the methylation status of each of these sites will be required to understand fully the role of DNA methylation in health and disease. Genome-wide analysis, using arrays and high-throughput sequencing, has enabled assessment of large fractions of the methylome, but each protocol comes with unique advantages and disadvantages. Notably, except for whole-genome bisulfite sequencing, most commonly used genome-wide methods detect <5% of all CpG sites. Here, we discuss approaches for methylome studies and compare genome coverage of promoters, genes, and intergenic regions, and capacity to quantitate individual CpG methylation states. Finally, we examine the extent of published cancer methylomes that have been generated using genome-wide approaches.

Common gene pathways and families altered by DNA methylation in breast and prostate cancers

Epigenetic modifications, such as DNA methylation, are widely studied in cancer as they are stable and easy to measure genome wide. DNA methylation changes have been used to differentiate benign from malignant tissue and to predict tumor recurrence or patient outcome. Multiple genome wide DNA methylation studies in breast and prostate cancers have identified genes that are differentially methylated in malignant tissue compared with non-malignant tissue or in association with hormone receptor status or tumor recurrence. Although this has identified potential biomarkers for diagnosis and prognosis, what is highlighted by reviewing these studies is the similarities between breast and prostate cancers. In particular, the gene families/pathways targeted by DNA methylation in breast and prostate cancers have significant overlap and include homeobox genes, zinc finger transcription factors, S100 calcium binding proteins, and potassium voltage-gated family members. Many of the gene pathways targeted by aberrant methylation in breast and prostate cancers are not targeted in other cancers, suggesting that some of these targets may be specific to hormonal cancers. Genome wide DNA methylation profiles in breast and prostate cancers will not only define more specific and sensitive biomarkers for cancer diagnosis and prognosis but also identify novel therapeutic targets, which may be direct targets of agents that reverse DNA methylation or which may target novel gene families that are themselves DNA methylation targets.

Genome-wide screening of aberrant DNA methylation which associated with gene expression in mouse skin cancers

Epigenetic alteration of genomic DNA is a common and key process in carcinogenesis. There is considerable evidence indicating that some of the somatic alterations occurring during carcinogenesis in humans also involve the same processes as those observed in mice. Therefore, we analyzed mouse skin cancer tissues induced by the 2-stage carcinogenesis model to identify skin tumor-specific differentially methylated regions (ST-DMRs) during the multistep carcinogenesis process. We have previously identified ST-DMRs using the restriction landmark genomic scanning (RLGS) technique and reported that some of the mouse ST-DMRs were also epigenetically modified in human cancers, such as melanoma, neuroblastoma, and brain tumor. These results encouraged us to pursue global methylation screening in mouse skin carcinogenesis. Using the methylated DNA immunoprecipitation (MeDIP) method combined with the NimbleGen promoter plus CpG island (CpGi) array, we identified 615 ST-DMRs. In combination with global gene expression analysis, 91 of these ST-DMRs were shown to be located on or around the genes differentially expressed between normal skin and tumor tissues, including a candidate human tumor suppressor gene Tfap2e. As observed in human colorectal cancers, Tfap2e was methylated at a CpGi located in intron 3 and downregulated in skin tumors. Our results identified aberrant methylated regions that were associated with gene expression regulation during carcinogenesis, which may indicate critical genetic regions also involved in human carcinogenesis. © 2013 Wiley Periodicals, Inc.

Real-time methylomic aberrations during initiation and progression of induced human mammary epithelial cell tumorigenesis

AIM

Neoplastic transformation provides one of the few existing opportunities to analyze molecular changes in real time during the initiation and progression of breast cancer.

MATERIALS & METHODS

Human mammary epithelial cells underwent neoplastic reprogramming, generating one line of semitransformed, premalignant cells and two separate, temporal lines of fully transformed human mammary epithelial cells (THMECs). An Illumina Infinium HumanMethylation27 BeadChip was used to analyze DNA methylation alterations in 27,578 CpG loci at three consecutive time points over an 80-day (d) transformation period.

RESULTS

The mean β value for semitransformed human mammary epithelial cells CpG loci (0.245) was much greater than for either THMEC-40d (0.055) or THMEC-80d (0.066), indicating a large loss of methylation after neoplastic induction. In addition, 54% of CpG loci were hypermethylated during the THMEC-40d to THMEC-80d transition. We observed that the CpG loci exhibiting DNA methylation changes during early oncogenesis were enriched for biological functions like cellular movement; this was distinctly different than in the later, more progressive stages of the transformation process enriched for processes involving differentiation.

CONCLUSION

The timing of major methylomic changes may be important in directing the cell toward a more cancerous phenotype. In addition, gene-specific hypermethylation appears to silence developmentally related genes, leading to dedifferentiation.

Integrated genomic analysis of breast cancers

Breast cancer is the most frequent and the most deadly cancer in women in Western countries. Different classifications of disease (anatomoclinical, pathological, prognostic, genetic) are used for guiding the management of patients. Unfortunately, they fail to reflect the whole clinical heterogeneity of the disease. Consequently, molecularly distinct diseases are grouped in similar clinical classes, likely explaining the different clinical outcome between patients in a given class, and the fact that selection of the most appropriate diagnostic or therapeutic strategy for each patient is not done accurately. Today, treatment is efficient in only 70.0–75.0% of cases overall. Our repertoire of efficient drugs is limited but is being expanded with the discovery of new molecular targets for new drugs, based on the identification of candidate oncogenes and tumor suppressor genes (TSG) functionally relevant in disease. Development of new drugs makes therapeutical decisions even more demanding of reliable classifiers and prognostic/predictive tests. Breast cancer is a complex, heterogeneous disease at the molecular level. The combinatorial molecular origin and the heterogeneity of malignant cells, and the variability of the host background, create distinct subgroups of tumors endowed with different phenotypic features such as response to therapy and clinical outcome. Cellular and molecular analyses can identify new classes biologically and clinically relevant, as well as provide new clinically relevant markers and targets.

The various stages of mammary tumorigenesis are not clearly defined and the genetic and epigenetic events critical to the development and aggressiveness of breast cancer are not precisely known. Because the phenotype of tumors is dependent on many genes, a large-scale and integrated molecular characterization of the genetic and epigenetic alterations and gene expression deregulation should allow the identification of new molecular classes clinically relevant, as well as among the altered genes and/or pathways, the identification of more accurate molecular diagnostic, prognostic/predictive factors, and for some of them, after functional validation, the identification of new therapeutic targets.

Stage-specific methylome screen identifies that NEFL is downregulated by promoter hypermethylation in breast cancer

Aberrant hypermethylation of promoter regions in specific genes is a key event in the formation and progression of breast cancers, and an increasing number of marker genes have been identified. However, few genes which show methylation change in accordance with the progression of breast cancer have been identified. To identify genes which consistently undergo promoter methylation alterations as the tumor develops from a benign to a malignant form, genome-wide methylation databases of breast cancer cell lines from stage I to stage IV were analyzed. Heatmap and cluster analysis revealed that the genome-wide methylation changes showed a good accordance with tumor progression. Seven out of 14,495 genes were found to be consistently increased alongside the promoter methylation level through the normal cell line to the cancer stage IV cell lines. NEFL, one of the in silico hypermethylated genes in cancer, showed hypermethylation and lower expression in the cancer cell line MDA-MB-231, as well as in cancer tissues (methylation, p<0.05; expression, p<0.01). The expression was restored by inducing demethylation of the promoter in MDA-MB-231 cells. Our findings may lend credence to the possibility of using tumor stage-specific alterations in methylation patterns as biomarkers for estimating prognosis and assessing treatment options for breast cancer.

FastDMA: an infinium humanmethylation450 beadchip analyzer

DNA methylation is vital for many essential biological processes and human diseases. Illumina Infinium HumanMethylation450 Beadchip is a recently developed platform studying genome-wide DNA methylation state on more than 480,000 CpG sites and a few CHG sites with high data quality. To analyze the data of this promising platform, we developed FastDMA which can be used to identify significantly differentially methylated probes. Besides single probe analysis, FastDMA can also do region-based analysis for identifying the differentially methylated region (DMRs). A uniformed statistical model, analysis of covariance (ANCOVA), is used to achieve all the analyses in FastDMA. We apply FastDMA on three large-scale DNA methylation datasets from The Cancer Genome Atlas (TCGA) and find many differentially methylated genomic sites in different types of cancer. On the testing datasets, FastDMA shows much higher computational efficiency than current tools. FastDMA can benefit the data analyses of large-scale DNA methylation studies with an integrative pipeline and a high computational efficiency. The software is freely available via http://bioinfo.au.tsinghua.edu.cn/software/fastdma/.

Genome-wide promoter methylation analysis identifies epigenetic silencing of MAPK13 in primary cutaneous melanoma

The involvement of epigenetic alterations in the pathogenesis of melanoma is increasingly recognized. Here, we performed genome-wide DNA methylation analysis of primary cutaneous melanoma and benign melanocytic nevus interrogating 14 495 genes using BeadChip technology. This genome-wide view of promoter methylation in primary cutaneous melanoma revealed an array of recurrent DNA methylation alterations with potential diagnostic applications. Among 106 frequently hypermethylated genes, there were many novel methylation targets and tumor suppressor genes. Highly recurrent methylation of the HOXA9, MAPK13, CDH11, PLEKHG6, PPP1R3C, and CLDN11 genes was established. Promoter methylation of MAPK13, encoding p38δ, was present in 67% of primary and 85% of metastatic melanomas. Restoration of MAPK13 expression in melanoma cells exhibiting epigenetic silencing of this gene reduced proliferation, indicative of tumor suppressive functions. This study demonstrates that DNA methylation alterations are widespread in melanoma and suggests that epigenetic silencing of MAPK13 contributes to melanoma progression.

DNA methylation signatures identify biologically distinct thyroid cancer subtypes

OBJECTIVE

The purpose of this study was to determine the global patterns of aberrant DNA methylation in thyroid cancer.

RESEARCH DESIGN AND METHODS

We have used DNA methylation arrays to determine, for the first time, the genome-wide promoter methylation status of papillary, follicular, medullary, and anaplastic thyroid tumors.

RESULTS

We identified 262 and 352 hypermethylated and 13 and 21 hypomethylated genes in differentiated papillary and follicular tumors, respectively. Interestingly, the other tumor types analyzed displayed more hypomethylated genes (280 in anaplastic and 393 in medullary tumors) than aberrantly hypermethylated genes (86 in anaplastic and 131 in medullary tumors). Among the genes indentified, we show that 4 potential tumor suppressor genes (ADAMTS8, HOXB4, ZIC1, and KISS1R) and 4 potential oncogenes (INSL4, DPPA2, TCL1B, and NOTCH4) are frequently regulated by aberrant methylation in primary thyroid tumors. In addition, we show that aberrant promoter hypomethylation-associated overexpression of MAP17 might promote tumor growth in thyroid cancer.

CONCLUSIONS

Thyroid cancer subtypes present differential promoter methylation signatures, and nondifferentiated subtypes are characterized by aberrant promoter hypomethylation rather than hypermethylation. Additional studies are needed to determine the potential clinical interest of the tumor subtype-specific DNA methylation signatures described herein and the role of aberrant promoter hypomethylation in nondifferentiated thyroid tumors.

Using epigenome-wide association scans of DNA methylation in age-related complex human traits

With rapid technological advancements emerging epigenetic studies of complex traits have shifted from candidate gene analyses towards epigenome-wide association studies (EWAS). EWAS aim to systematically identify epigenetic variants across the genome that associate with complex phenotypes. Recent EWAS using case-control and disease-discordant identical twin designs have identified phenotype-associated differentially methylated regions for several traits. However, EWAS still face many challenges related to methodology, design and interpretation, owing to the dynamic nature of epigenetic variants over time. This article reviews analytical considerations in conducting EWAS and recent applications of this approach to human aging and age-related complex traits.

A variational Bayes beta mixture model for feature selection in DNA methylation studies

An increasing number of studies are using beadarrays to measure DNA methylation on a genome-wide basis. The purpose is to identify novel biomarkers in a wide range of complex genetic diseases including cancer. A common difficulty encountered in these studies is distinguishing true biomarkers from false positives. While statistical methods aimed at improving the feature selection step have been developed for gene expression, relatively few methods have been adapted to DNA methylation data, which is naturally beta-distributed. Here we explore and propose an innovative application of a recently developed variational Bayesian beta-mixture model (VBBMM) to the feature selection problem in the context of DNA methylation data generated from a highly popular beadarray technology. We demonstrate that VBBMM offers significant improvements in inference and feature selection in this type of data compared to an Expectation-Maximization (EM) algorithm, at a significantly reduced computational cost. We further demonstrate the added value of VBBMM as a feature selection and prioritization step in the context of identifying prognostic markers in breast cancer. A variational Bayesian approach to feature selection of DNA methylation profiles should thus be of value to any study undergoing large-scale DNA methylation profiling in search of novel biomarkers.

DNA-methylome analysis of mouse intestinal adenoma identifies a tumour-specific signature that is partly conserved in human colon cancer

Aberrant CpG methylation is a universal epigenetic trait of cancer cell genomes. However, human cancer samples or cell lines preclude the investigation of epigenetic changes occurring early during tumour development. Here, we have used MeDIP-seq to analyse the DNA methylome of APC^Min adenoma as a model for intestinal cancer initiation, and we present a list of more than 13,000 recurring differentially methylated regions (DMRs) characterizing intestinal adenoma of the mouse. We show that Polycomb Repressive Complex (PRC) targets are strongly enriched among hypermethylated DMRs, and several PRC2 components and DNA methyltransferases were up-regulated in adenoma. We further demonstrate by bisulfite pyrosequencing of purified cell populations that the DMR signature arises de novo in adenoma cells rather than by expansion of a pre-existing pattern in intestinal stem cells or undifferentiated crypt cells. We found that epigenetic silencing of tumour suppressors, which occurs frequently in colon cancer, was rare in adenoma. Quite strikingly, we identified a core set of DMRs, which is conserved between mouse adenoma and human colon cancer, thus possibly revealing a global panel of epigenetically modified genes for intestinal tumours. Our data allow a distinction between early conserved epigenetic alterations occurring in intestinal adenoma and late stochastic events promoting colon cancer progression, and may facilitate the selection of more specific clinical epigenetic biomarkers.

The formation and progression of tumours to metastatic disease is driven by two major mechanisms, i.e. genetic alterations that activate oncogenes or inactivate tumour suppressor genes, and changes in the epigenome that cause variations in the expression of the genetic information. A deeper understanding of the interaction between the genetic and epigenetic mechanisms is critical for the selection of tumour biomarkers and for the future development of therapies. Human tumour specimens and cell lines contain a plethora of genetic and epigenetic changes, which complicate data analysis. In contrast, mouse tumour models such as the APC^Min mouse used in this study arise by a single initiating genetic mutation, yet share key traits with human cancer. Here we show that mouse adenomas acquire a multitude of epigenetic alterations, which are recurring in mouse adenoma and in human colon cancer, representing early and advanced tumours, respectively. The use of a mouse model thus allowed us to uncover a sequence of epigenetic changes occurring in tumours, which may facilitate the identification of novel clinical colon cancer biomarkers.

Vimentin DNA methylation predicts survival in breast cancer

The Vimentin gene plays a pivotal role in epithelial-to-mesenchymal transition and is known to be overexpressed in the prognostically poor basal-like breast cancer subtype. Recent studies have reported Vimentin DNA methylation in association with poor clinical outcomes in other solid tumors, but not in breast cancer. We therefore quantified Vimentin DNA methylation using MALDI-TOF mass spectrometry in breast tumors and matched normal pairs in association with gene expression and survival in a hospital-based study of breast cancer patients. Gene expression data via qRT-PCR in cell lines and oligomicroarray data from breast tissues were correlated with percent methylation in the Vimentin promoter. A threshold of 20 percent average methylation compared with matched normal pairs was set for bivariate and multivariate tests of association between methylation and tumor subtype, tumor histopathology, and survival. Vimentin was differentially methylated in luminal breast cancer cell lines, and in luminal A, luminal B, and HER2-enriched breast tumor subtypes, but was rare in basal-like cell lines and tumors. Increased methylation was strongly correlated with decreased mRNA expression in cell lines, and had a moderate inverse correlation in breast tumors. Vimentin methylation predicted poor overall survival independent of race, subtype, stage, nodal status, or metastatic disease and holds promise as a new prognostic biomarker for breast cancer patients.

Epigenetics as a therapeutic target in breast cancer

Epigenetics refers to alterations in gene expression due to modifications in histone acetylation and DNA methylation at the promoter regions of genes. Unlike genetic mutations, epigenetic alterations are not due to modifications in the gene primary nucleotide sequence. The importance of epigenetics in the initiation and progression of breast cancer has led many investigators to incorporate this novel and exciting field in breast cancer drug development. Several drugs that target epigenetic alterations, including inhibitors of histone deacetylase (HDAC) and DNA methyltransferase (DNMT), are currently approved for treatment of hematological malignancies and are available for clinical investigation in solid tumors. In this manuscript, we review the critical role of epigenetics in breast cancer including the potential for epigenetic alterations to serve as biomarkers determining breast cancer prognosis and response to therapy. We highlight initial promising results to date with use of epigenetic modifiers in patients with breast cancer and the ongoing challenges involved in the successful establishment of these agents for the treatment of breast cancer.

Antiestrogen Resistance and the Application of Systems Biology

Understanding the molecular changes that drive an acquired antiestrogen resistance phenotype is of major clinical relevance. Previous methodologies for addressing this question have taken a single gene/pathway approach and the resulting gains have been limited in terms of their clinical impact. Recent systems biology approaches allow for the integration of data from high throughput "-omics" technologies. We highlight recent advances in the field of antiestrogen resistance with a focus on transcriptomics, proteomics and methylomics.

CpG island shore methylation regulates caveolin-1 expression in breast cancer

Caveolin-1 (Cav1) is an integral membrane, scaffolding protein found in plasma membrane invaginations (caveolae). Cav1 regulates multiple cancer-associated processes. In breast cancer, a tumor suppressive role for Cav1 has been suggested; however, Cav1 is frequently overexpressed in aggressive breast cancer subtypes, suggesting an oncogenic function in advanced-stage disease. To further delineate Cav1 function in breast cancer progression, we evaluated its expression levels among a panel of cell lines representing a spectrum of breast cancer phenotypes. In basal-like (the most aggressive BC subtype) breast cancer cells, Cav1 was consistently upregulated, and positively correlated with increased cell proliferation, anchorage-independent growth, and migration and invasion. To identify mechanisms of Cav1 gene regulation, we compared DNA methylation levels within promoter ‘CpG islands' (CGIs) with ‘CGI shores', recently described regions that flank CGIs with less CG-density. Integration of genome-wide DNA methylation profiles (‘methylomes') with Cav1 expression in 30 breast cancer cell lines showed that differential methylation of CGI shores, but not CGIs, significantly regulated Cav1 expression. In breast cancer cell lines having low Cav1 expression (despite promoter CGI hypomethylation), we found that treatment with a DNA methyltransferase inhibitor induced Cav1 expression via CGI shore demethylation. In addition, further methylome assessments revealed that breast cancer aggressiveness associated with Cav1 CGI shore methylation levels, with shore hypermethylation in minimally aggressive, luminal breast cancer cells and shore hypomethylation in highly aggressive, basal-like cells. Cav1 CGI shore methylation was also observed in human breast tumors, and overall survival rates of breast cancer patients lacking estrogen receptor α (ERα) negatively correlated with Cav1 expression. Based on this first study of Cav1 (a potential oncogene) CGI shore methylation, we suggest this phenomenon may represent a new prognostic marker for ERα-negative, basal-like breast cancer.

Ibandronate increases the expression of the pro-apoptotic gene FAS by epigenetic mechanisms in tumor cells

There is growing evidence that aminobisphosphonates like ibandronate show anticancer activity by an unknown mechanism. Biochemically, they prevent posttranslational isoprenylation of small GTPases, thus inhibiting their activity. In tumor cells, activated RAS-GTPase, the founding member of the gene family, down-regulates the expression of the pro-apoptotic gene FAS via epigenetic DNA-methylation by DNMT1. We compared ibandronate treatment in neoplastic human U-2 osteosarcoma and in mouse CCL-51 breast cancer cells as well as in the immortalized non-neoplastic MC3T3-E1 osteoblastic cells. Ibandronate attenuated cell proliferation in all cell lines tested. In the neoplastic cells we found up-regulation of caspases suggesting apoptosis. Further we found stimulation of FAS-expression as a result of epigenetic DNA demethylation that was due to down-regulation of DNMT1, which was rescued by re-isoprenylation by both geranylgeranyl-pyrophosphate and farnesylpyrophosphate. In contrast, ibandronate did not affect FAS and DNMT1 expression in MC3T3-E1 non-neoplastic cells. Data suggest that bisphosphonates via modulation of the activity of small-GTPases induce apoptosis in neoplastic cells by DNA-CpG-demethylation and stimulation of FAS-expression. In conclusion the shown epigenetic mechanism underlying the anti-neoplastic activity of farnesyl-transferase-inhibition, also explains the clinical success of other drugs, which target this pathway.

Tissue of origin determines cancer-associated CpG island promoter hypermethylation patterns

BACKGROUND

Aberrant CpG island promoter DNA hypermethylation is frequently observed in cancer and is believed to contribute to tumor progression by silencing the expression of tumor suppressor genes. Previously, we observed that promoter hypermethylation in breast cancer reflects cell lineage rather than tumor progression and occurs at genes that are already repressed in a lineage-specific manner. To investigate the generality of our observation we analyzed the methylation profiles of 1,154 cancers from 7 different tissue types.

RESULTS

We find that 1,009 genes are prone to hypermethylation in these 7 types of cancer. Nearly half of these genes varied in their susceptibility to hypermethylation between different cancer types. We show that the expression status of hypermethylation prone genes in the originator tissue determines their propensity to become hypermethylated in cancer; specifically, genes that are normally repressed in a tissue are prone to hypermethylation in cancers derived from that tissue. We also show that the promoter regions of hypermethylation-prone genes are depleted of repetitive elements and that DNA sequence around the same promoters is evolutionarily conserved. We propose that these two characteristics reflect tissue-specific gene promoter architecture regulating the expression of these hypermethylation prone genes in normal tissues.

CONCLUSIONS

As aberrantly hypermethylated genes are already repressed in pre-cancerous tissue, we suggest that their hypermethylation does not directly contribute to cancer development via silencing. Instead aberrant hypermethylation reflects developmental history and the perturbation of epigenetic mechanisms maintaining these repressed promoters in a hypomethylated state in normal cells.

Genome-wide methylation screen in low-grade breast cancer identifies novel epigenetically altered genes as potential biomarkers for tumor diagnosis

Aberrant DNA methylation constitutes a well-established epigenetic marker for breast cancer. Changes in methylation early in cancer development may be clinically relevant for cancer detection and prognosis-based therapeutic decisions. In the present study, a combination of methyl-CpG immunoprecipitation (MCIp) and human CpG island (CGI) arrays was applied to compare genome-wide DNA methylation profiles in 10 low-grade in situ and invasive breast cancers against 10 normal breast samples. In total, 214 CGIs were found to be hypermethylated in ≥6 of 10 tumors. Functional term enrichment analyses revealed an overrepresentation of homeobox genes and genes involved in transcription and regulation of transcription. Significant hypermethylation of 11 selected genes in tumor vs. normal tissue was validated in two independent sample sets (45 tumors and 11 controls, 43 tumors and 8 controls) using quantitative EpiTyper technology. In tumors, median methylation levels of BCAN, HOXD1, KCTD8, KLF11, NXPH1, POU4F1, SIM1, and TCF7L1 were ≥30% higher than in normal samples, representing potential biomarkers for tumor diagnosis. Using the 90th percentile of methylation levels in normal tissue as cutoff value, 62-92% of in situ samples (n=13), 72-97% of invasive samples from the first validation set (n=32), and 86-100% of invasive samples from the second validation set (n=43) were classified as hypermethylated. Hypermethylation of KLF11 and SIM1 might also be associated with increased risk of developing metastases. In summary, early methylation changes are frequent in the low-grade pathway of breast cancer and may be useful in the development of differential diagnostic and possibly also prognostic markers.

Make way for the 'next generation': application and prospects for genome-wide, epigenome-specific technologies in endocrine research

Epigenetic changes, which target DNA and associated histones, can be described as a pivotal mechanism of interaction between genes and the environment. The field of epigenomics aims to detect and interpret epigenetic modifications at the whole genome level. These approaches have the potential to increase resolution of epigenetic changes to the single base level in multiple disease states or across a population of individuals. Identification and comparison of the epigenomic landscape has challenged our understanding of the regulation of phenotype. Additionally, inclusion of these marks as biomarkers in the early detection or progression monitoring of disease is providing novel avenues for future biomedical research. Cells of the endocrine organs, which include pituitary, thyroid, thymus, pancreas ovary and testes, have been shown to be susceptible to epigenetic alteration, leading to both local and systemic changes often resulting in life-threatening metabolic disease. As with other cell types and populations, endocrine cells are susceptible to tumour development, which in turn may have resulted from aberration of epigenetic control. Techniques including high-throughput sequencing and array-based analysis to investigate these changes have rapidly emerged and are continually evolving. Here, we present a review of these methods and their promise to influence our studies on the epigenome for endocrine research and perhaps to uncover novel therapeutic options in disease states.

Cancer heterogeneity: origins and implications for genetic association studies

Genetic association studies have become standard approaches to characterize the genetic and epigenetic variability associated with cancer development, including predispositions and mutations. However, the bewildering genetic and phenotypic heterogeneity inherent in cancer both magnifies the conceptual and methodological problems associated with these approaches and renders difficult the translation of available genetic information into a knowledge that is both biologically sound and clinically relevant. Here, we elaborate on the underlying causes of this complexity, illustrate why it represents a challenge for genetic association studies, and briefly discuss how it can be reconciled with the ultimate goals of identifying targetable disease pathways and successfully treating individual patients.

Loss of cell-surface laminin anchoring promotes tumor growth and is associated with poor clinical outcomes

Perturbations in the composition and assembly of extracellular matrices (ECM) contribute to progression of numerous diseases, including cancers. Anchoring of laminins at the cell surface enables assembly and signaling of many ECMs, but the possible contributions of altered laminin anchoring to cancer progression remain undetermined. In this study, we investigated the prominence and origins of defective laminin anchoring in cancer cells and its association with cancer subtypes and clinical outcomes. We found loss of laminin anchoring to be widespread in cancer cells. Perturbation of laminin anchoring originated from several distinct defects, which all led to dysfunctional glycosylation of the ECM receptor dystroglycan. In aggressive breast and brain cancers, defective laminin anchoring was often due to suppressed expression of the glycosyltransferase LARGE. Reduced expression of LARGE characterized a broad array of human tumors in which it was associated with aggressive cancer subtypes and poor clinical outcomes. Notably, this defect robustly predicted poor survival in patients with brain cancers. Restoring LARGE expression repaired anchoring of exogenous and endogenous laminin and modulated cell proliferation and tumor growth. Together, our findings suggest that defects in laminin anchoring occur commonly in cancer cells, are characteristic of aggressive cancer subtypes, and are important drivers of disease progression.

DNA methylation based biomarkers: practical considerations and applications

A biomarker is a molecular target analyzed in a qualitative or quantitative manner to detect and diagnose the presence of a disease, to predict the outcome and the response to a specific treatment allowing personalized tailoring of patient management. Biomarkers can belong to different types of biochemical molecules such as proteins, DNA, RNA or lipids, whereby protein biomarkers have been the most extensively studied and used, notably in blood-based protein quantification tests or immunohistochemistry. The rise of interest in epigenetic mechanisms has allowed the identification of a new type of biomarker, DNA methylation, which is of great potential for many applications. This stable and heritable covalent modification mostly affects cytosines in the context of a CpG dinucleotide in humans. It can be detected and quantified by a number of technologies including genome-wide screening methods as well as locus- or gene-specific high-resolution analysis in different types of samples such as frozen tissues and FFPE samples, but also in body fluids such as urine, plasma, and serum obtained through non-invasive procedures. In some cases, DNA methylation based biomarkers have proven to be more specific and sensitive than commonly used protein biomarkers, which could clearly justify their use in clinics. However, very few of them are at the moment used in clinics and even less commercial tests are currently available. The objective of this review is to discuss the advantages of DNA methylation as a biomarker, the practical considerations for their development, and their use in disease detection, prediction of outcome or treatment response, through multiple examples mainly focusing on cancer, but also to evoke their potential for complex diseases and prenatal diagnostics.

MethLAB: a graphical user interface package for the analysis of array-based DNA methylation data

Recent evidence suggests that DNA methylation changes may underlie numerous complex traits and diseases. The advent of commercial, array-based methods to interrogate DNA methylation has led to a profusion of epigenetic studies in the literature. Array-based methods, such as the popular Illumina GoldenGate and Infinium platforms, estimate the proportion of DNA methylated at single-base resolution for thousands of CpG sites across the genome. These arrays generate enormous amounts of data, but few software resources exist for efficient and flexible analysis of these data. We developed a software package called MethLAB (http://genetics.emory.edu/conneely/MethLAB) using R, an open source statistical language that can be edited to suit the needs of the user. MethLAB features a graphical user interface (GUI) with a menu-driven format designed to efficiently read in and manipulate array-based methylation data in a user-friendly manner. MethLAB tests for association between methylation and relevant phenotypes by fitting a separate linear model for each CpG site. These models can incorporate both continuous and categorical phenotypes and covariates, as well as fixed or random batch or chip effects. MethLAB accounts for multiple testing by controlling the false discovery rate (FDR) at a user-specified level. Standard output includes a spreadsheet-ready text file and an array of publication-quality figures. Considering the growing interest in and availability of DNA methylation data, there is a great need for user-friendly open source analytical tools. With MethLAB, we present a timely resource that will allow users with no programming experience to implement flexible and powerful analyses of DNA methylation data.

DNA methylation analyses of urothelial carcinoma reveal distinct epigenetic subtypes and an association between gene copy number and methylation status

We assessed DNA methylation and copy number status of 27,000 CpGs in 149 urothelial carcinomas and integrated the findings with gene expression and mutation data. Methylation was associated with gene expression for 1,332 CpGs, of which 26% showed positive correlation with expression, i.e., high methylation and high gene expression levels. These positively correlated CpGs were part of specific transcription factor binding sites, such as sites for MYC and CREBP1, or located in gene bodies. Furthermore, we found genes with copy number gains, low expression and high methylation levels, revealing an association between methylation and copy number levels. This phenomenon was typically observed for developmental genes, such as HOX genes, and tumor suppressor genes. In contrast, we also identified genes with copy number gains, high expression and low methylation levels. This was for instance observed for some keratin genes. Tumor cases could be grouped into four subgroups, termed epitypes, by their DNA methylation profiles. One epitype was influenced by the presence of infiltrating immune cells, two epitypes were mainly composed of non-muscle invasive tumors, and the remaining epitype of muscle invasive tumors. The polycomb complex protein EZH2 that blocks differentiation in embryonic stem cells showed increased expression both at the mRNA and protein levels in the muscle invasive epitype, together with methylation of polycomb target genes and HOX genes. Our data highlights HOX gene silencing and EZH2 expression as mechanisms to promote a more undifferentiated and aggressive state in UC.

Genome-wide DNA methylation profiling of cell-free serum DNA in esophageal adenocarcinoma and Barrett esophagus

Aberrant DNA methylation (DNAm) is a feature of most types of cancers. Genome-wide DNAm profiling has been performed successfully on tumor tissue DNA samples. However, the invasive procedure limits the utility of tumor tissue for epidemiological studies. While recent data indicate that cell-free circulating DNAm (cfDNAm) profiles reflect DNAm status in corresponding tumor tissues, no studies have examined the association of cfDNAm with cancer or precursors on a genome-wide scale. The objective of this pilot study was to evaluate the putative significance of genome-wide cfDNAm profiles in esophageal adenocarcinoma (EA) and Barrett esophagus (BE, EA precursor). We performed genome-wide DNAm profiling in EA tissue DNA (n = 8) and matched serum DNA (n = 8), in serum DNA of BE (n = 10), and in healthy controls (n = 10) using the Infinium HumanMethylation27 BeadChip that covers 27,578 CpG loci in 14,495 genes. We found that cfDNAm profiles were highly correlated to DNAm profiles in matched tumor tissue DNA (r = 0.92) in patients with EA. We selected the most differentially methylated loci to perform hierarchical clustering analysis. We found that 911 loci can discriminate perfectly between EA and control samples, 554 loci can separate EA from BE samples, and 46 loci can distinguish BE from control samples. These results suggest that genome-wide cfDNAm profiles are highly consistent with DNAm profiles detected in corresponding tumor tissues. Differential cfDNAm profiling may be a useful approach for the noninvasive screening of EA and EA premalignant lesions.

Epigenetic alteration of CCDC67 and its tumor suppressor function in gastric cancer

In this study, the promoter of the gene coiled-coil domain-containing 67 (CCDC67) was found to be frequently methylated in gastric cancer cell lines and in primary gastric tumors, as examined by restriction landmark genomic scanning. In addition, CCDC67 expression was down-regulated in 72.7% of gastric cancer cell lines tested. In most cases, gene down-regulation was associated with CpG hypermethylation in the CCDC67 promoter. Treatment with 5-aza-2'-deoxycytidine and/or trichostatin A restored CCDC67 expression in down-regulated cell lines. Pyrosequencing analysis of 150 paired primary gastric cancer samples revealed that promoter CpG methylation was increased in 74% of tested tumors compared with paired adjacent normal tissues, and this hypermethylation correlated significantly with down-regulation of CCDC67. CCDC67 protein was localized to the cell membrane by immunocytochemistry. Stable transfection of a CCDC67 gene in one gastric cancer cell line inhibited adhesion-dependent and -independent colony formation, and CCDC67 expression suppressed tumorigenesis in nude mice. We suggest that CCDC67 is a putative tumor suppressor gene that is silenced in gastric cancers by promoter CpG methylation and that it may play an important role in cell signaling and migration related to tumorigenesis.