DNA methylation signatures for breast cancer classification and prognosis

Artificial light-at-night - a novel lifestyle risk factor for metabolic disorder and cancer morbidity

Both obesity and breast cancer are already recognized worldwide as the most common syndromes in our modern society. Currently, there is accumulating evidence from epidemiological and experimental studies suggesting that these syndromes are closely associated with circadian disruption. It has been suggested that melatonin (MLT) and the circadian clock genes both play an important role in the development of these syndromes. However, we still poorly understand the molecular mechanism underlying the association between circadian disruption and the modern health syndromes. One promising candidate is epigenetic modifications of various genes, including clock genes, circadian-related genes, oncogenes, and metabolic genes. DNA methylation is the most prominent epigenetic signaling tool for gene expression regulation induced by environmental exposures, such as artificial light-at-night (ALAN). In this review, we first provide an overview on the molecular feedback loops that generate the circadian regulation and how circadian disruption by ALAN can impose adverse impacts on public health, particularly metabolic disorders and breast cancer development. We then focus on the relation between ALAN-induced circadian disruption and both global DNA methylation and specific loci methylation in relation to obesity and breast cancer morbidities. DNA hypo-methylation and DNA hyper-methylation, are suggested as the most studied epigenetic tools for the activation and silencing of genes that regulate metabolic and monostatic responses. Finally, we discuss the potential clinical and therapeutic roles of MLT suppression and DNA methylation patterns as novel biomarkers for the early detection of metabolic disorders and breast cancer development.

Survival differences of CIMP subtypes integrated with CNA information in human breast cancer

CpG island methylator phenotype of breast cancer is associated with widespread aberrant methylation at specified CpG islands and distinct patient outcomes. However, the influence of copy number contributing to the prognosis of tumors with different CpG island methylator phenotypes is still unclear. We analyzed both genetic (copy number) and epigenetic alterations in 765 breast cancers from The Cancer Genome Atlas data portal and got a panel of 15 biomarkers for copy number and methylation status evaluation. The gene panel identified two groups corresponding to distinct copy number profiles. In status of mere-loss copy number, patients were faced with a greater risk if they presented a higher CpG islands methylation pattern in biomarker panels. But for samples presenting merely-gained copy number, higher methylation level of CpG islands was associated with improved viability. In all, the integration of copy number alteration and methylation information enhanced the classification power on prognosis. Moreover, we found the molecular subtypes of breast cancer presented different distributions in two CpG island methylation phenotypes. Generated by the same set of human methylation 450K data, additional copy number information could provide insights into survival prediction of cancers with less heterogeneity and might help to determine the biomarkers for diagnosis and treatment for breast cancer patients in a more personalized approach.

Epigenetic Mechanisms of Tamoxifen Resistance in Luminal Breast Cancer

Breast cancer is one of the most common cancers and the second leading cause of cancer death in the United States. Estrogen receptor (ER)-positive cancer is the most frequent subtype representing more than 70% of breast cancers. These tumors respond to endocrine therapy targeting the ER pathway including selective ER modulators (SERMs), selective ER downregulators (SERDs) and aromatase inhibitors (AIs). However, resistance to endocrine therapy associated with disease progression remains a significant therapeutic challenge. The precise mechanisms of endocrine resistance remain unclear. This is partly due to the complexity of the signaling pathways that influence the estrogen-mediated regulation in breast cancer. Mechanisms include ER modifications, alteration of coregulatory function and modification of growth factor signaling pathways. In this review, we provide an overview of epigenetic mechanisms of tamoxifen resistance in ER-positive luminal breast cancer. We highlight the effect of epigenetic changes on some of the key mechanisms involved in tamoxifen resistance, such as tumor-cell heterogeneity, ER signaling pathway and cancer stem cells (CSCs). It became increasingly recognized that CSCs are playing an important role in driving metastasis and tamoxifen resistance. Understanding the mechanism of tamoxifen resistance will provide insight into the design of novel strategies to overcome the resistance and make further improvements in breast cancer therapeutics.

Genome-wide analysis of DNA methylation in hypothalamus and ovary of Capra hircus

BACKGROUND

DNA methylation is a frequently studied epigenetic modification due to its role in regulating gene expression and hence in biological processes and in determining phenotypic plasticity in organisms. Rudimentary DNA methylation patterns for some livestock species are publically available: among these, goat methylome deserves to be further explored.

RESULTS

Genome-wide DNA methylation maps of the hypothalamus and ovary from Saanen goats were generated using Methyl-CpG binding domain protein sequencing (MBD-seq). Analysis of DNA methylation patterns indicate that the majority of methylation peaks found within genes are located gene body regions, for both organs. Analysis of the distribution of methylated sites per chromosome showed that chromosome X had the lowest number of methylation peaks. The X chromosome has one of the highest percentages of methylated CpG islands in both organs, and approximately 50% of the CpG islands in the goat epigenome are methylated in hypothalamus and ovary. Organ-specific Differentially Methylated Genes (DMGs) were correlated with the expression levels.

CONCLUSIONS

The comparison between transcriptome and methylome in hypothalamus and ovary showed that a higher level of methylation is not accompanied by a higher gene suppression. The genome-wide DNA methylation map for two goat organs produced here is a valuable starting point for studying the involvement of epigenetic modifications in regulating goat reproduction performance.

Aflatoxin B1-induced epigenetic alterations: An overview

Aflatoxin B1 (AFB1) is widely distributed in nature, especially in a variety of food commodities. It is confirmed to be the most toxic of all the aflatoxins. The toxicity of AFB1 has been well investigated, and it may result in severe health problems including carcinogenesis, mutagenesis, growth retardation, and immune suppression. Epigenetic modifications including DNA methylation, histone modifications and regulation of non-coding RNA play an important role in AFB1-induced disease and carcinogenesis. To better understand the evidence for AFB1-induced epigenetic alterations and the potential mechanisms of the toxicity of AFB1, we conducted a review of published studies of AFB1-induced epigenetic alterations.

Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns

Despite numerous studies done on understanding the role of DNA methylation, limited work has focused on systems integration of cell type-specific interplay between DNA methylation and gene transcription. Through a genome-wide analysis of DNA methylation across 19 cell types with T-47D as reference, we identified 106,252 cell type-specific differentially-methylated CpGs categorized into 7,537 differentially (46.6% hyper- and 53.4% hypo-) methylated regions. We found 44% promoter regions and 75% CpG islands were T-47D cell type-specific methylated. Pyrosequencing experiments validated the cell type-specific methylation across three benchmark cell lines. Interestingly, these DMRs overlapped with 1,145 known tumor suppressor genes. We then developed a Bayesian Gaussian Regression model to measure the relationship among DNA methylation, genomic segment distribution, differential gene expression and tumor suppressor gene status. The model uncovered that 3′UTR methylation has much less impact on transcriptional activity than other regions. Integration of DNA methylation and 82 transcription factor binding information across the 19 cell types suggested diverse interplay patterns between the two regulators. Our integrative analysis reveals cell type-specific and genomic region-dependent regulatory patterns and provides a perspective for integrating hundreds of various omics-seq data together.

BRCA promoter methylation in sporadic versus BRCA germline mutation-related breast cancers

Background

In breast cancer, BRCA promoter hypermethylation and BRCA germline mutations are said to occur together rarely, but this property has not yet been translated into a clinical test. Our aim in this study was to investigate the diagnostic value of BRCA1/2 methylation in distinguishing breast carcinomas of BRCA1 and BRCA2 germline mutation carriers from sporadic breast carcinomas using a recently developed BRCA methylation assay based on methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA).

Methods

MS-MLPAs were performed to assess BRCA1 and BRCA2 methylation in breast carcinoma tissues from 39 BRCA1 and 33 BRCA2 germline mutation carriers, 80 patients with sporadic breast cancer, and normal breast tissues from 5 BRCA1 and 4 BRCA2 mutation carriers and 5 nonmutation carriers.

Results

Methylation frequencies varied considerably between CpG sites across the BRCA1 and BRCA2 promoters. Some CpG sites were methylated more frequently in BRCA1/2-related than in sporadic carcinomas, whereas other CpG sites were methylated more frequently in sporadic carcinomas, with large variances in sensitivity and specificity as a consequence.

Conclusions

The diagnostic value of BRCA promoter methylation analysis in distinguishing BRCA1/2-related from sporadic breast carcinomas seems to be considerably dependent on the targeted CpG sites. These findings are important for adequate use of BRCA methylation analysis as a prescreening tool for BRCA germline genetic testing or to identify BRCAness patients who may benefit from targeted therapies such as poly(adenosine diphosphate-ribose) polymerase inhibitors.

Hypermethylation of CDKN2A exon 2 in tumor, tumor-adjacent and tumor-distant tissues from breast cancer patients

BACKGROUND

Breast carcinogenesis is a multistep process involving genetic and epigenetic changes. Tumor tissues are frequently characterized by gene-specific hypermethylation and global DNA hypomethylation. Aberrant DNA methylation levels have, however, not only been found in tumors, but also in tumor-surrounding tissue appearing histologically normal. This phenomenon is called field cancerization. Knowledge of the existence of a cancer field and its spread are of clinical relevance. If the tissue showing pre-neoplastic lesions is not removed by surgery, it may develop into invasive carcinoma.

METHODS

We investigated the prevalence of gene-specific and global DNA methylation changes in tumor-adjacent and tumor-distant tissues in comparison to tumor tissues from the same breast cancer patients (n = 18) and normal breast tissues from healthy women (n = 4). Methylation-sensitive high resolution melting (MS-HRM) analysis was applied to determine methylation levels in the promoters of APC, BRCA1, CDKN2A (p16), ESR1, HER2/neu and PTEN, in CDKN2A exon 2 and in LINE-1, as indicator for the global DNA methylation extent. The methylation status of the ESR2 promoter was determined by pyrosequencing.

RESULTS

Tumor-adjacent and tumor-distant tissues frequently showed pre-neoplastic gene-specific and global DNA methylation changes. The APC promoter (p = 0.003) and exon 2 of CDKN2A (p < 0.001) were significantly higher methylated in tumors than in normal breast tissues from healthy women. For both regions, significant differences were also found between tumor and tumor-adjacent tissues (p = 0.001 and p < 0.001, respectively) and tumor and tumor-distant tissues (p = 0.001 and p < 0.001, respectively) from breast cancer patients. In addition, tumor-adjacent (p = 0.002) and tumor-distant tissues (p = 0.005) showed significantly higher methylation levels of CDKN2A exon 2 than normal breast tissues serving as control. Significant correlations were found between the proliferative activity and the methylation status of CDKN2A exon 2 in tumor (r = -0.485, p = 0.041) and tumor-distant tissues (r = -0.498, p = 0.036).

CONCLUSIONS

From our results we can conclude that methylation changes in CDKN2A exon 2 are associated with breast carcinogenesis. Further investigations are, however, necessary to confirm that hypermethylation of CDKN2A exon 2 is associated with tumor proliferative activity.

Pan-cancer analysis of frequent DNA co-methylation patterns reveals consistent epigenetic landscape changes in multiple cancers

Background

DNA methylation is the major form of epigenetic modifications through which the cell regulates the gene expression and silencing. There have been extensive studies on the roles of DNA methylation in cancers, and several cancer drugs were developed targeting this process. However, DNA co-methylation cluster has not been examined in depth, and co-methylation in multiple cancer types has never been studied previously.

Results

In this study, we applied newly developed lmQCM algorithm to mine co-methylation clusters using methylome data from 11 cancer types in TCGA database, and found frequent co-methylated gene clusters exist in these cancer types. Among the four identified frequent clusters, two of them separate the tumor sample from normal sample in 10 out of 11 cancer types, which indicates that consistent epigenetic landscape changes exist in multiple cancer types.

Conclusion

This discovery provides new insight on the epigenetic regulation in cancers and leads to potential new direction for epigenetic biomarker and cancer drug discovery. We also found that genes commonly believed to be silenced via hypermethylation in cancers may still display highly variable methylation levels among cancer cells, and should be considered while using them as epigenetic biomarkers.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3259-0) contains supplementary material, which is available to authorized users.

Subtype-specific CpG island shore methylation and mutation patterns in 30 breast cancer cell lines

Background

Aberrant epigenetic modifications, including DNA methylation, are key regulators of gene activity in tumorigenesis. Breast cancer is a heterogeneous disease, and large-scale analyses indicate that tumor from normal and benign tissues, as well as molecular subtypes of breast cancer, can be distinguished based on their distinct genomic, transcriptomic, and epigenomic profiles. In this study, we used affinity-based methylation sequencing data in 30 breast cancer cell lines representing functionally distinct cancer subtypes to investigate methylation and mutation patterns at the whole genome level.

Results

Our analysis revealed significant differences in CpG island (CpGI) shore methylation and mutation patterns among breast cancer subtypes. In particular, the basal-like B type, a highly aggressive form of the disease, displayed distinct CpGI shore hypomethylation patterns that were significantly associated with downstream gene regulation. We determined that mutation rates at CpG sites were highly correlated with DNA methylation status and observed distinct mutation rates among the breast cancer subtypes. These findings were validated by using targeted bisulfite sequencing of differentially expressed genes (n=85) among the cell lines.

Conclusions

Our results suggest that alterations in DNA methylation play critical roles in gene regulatory process as well as cytosine substitution rates at CpG sites in molecular subtypes of breast cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0356-2) contains supplementary material, which is available to authorized users.

'Omics Approaches in Breast Cancer Research and Clinical Practice

Our understanding of the natural history of breast cancer has evolved alongside technologies to study its genomic, transcriptomic, proteomic, and metabolomics landscapes. These technologies have helped decipher multiple molecular pathways dysregulated in breast cancer. First-generation 'omics analyses considered each of these dimensions individually, but it is becoming increasingly clear that more holistic, integrative approaches are required to fully understand complex biological systems. The 'omics represent an exciting era of discovery in breast cancer research, although important issues need to be addressed to realize the clinical utility of these data through precision cancer care. How can the data be applied to predict response to molecular-targeted therapies? When should treatment decisions be based on tumor genetics rather than histology? And with the sudden explosion of "big data" from large 'omics consortia and new precision clinical trials, how do we now negotiate evidence-based pathways to clinical translation through this apparent sea of opportunity? The aim of this review is to provide a broad overview of 'omics technologies used in breast cancer research today, the current state-of-play in terms of applying this new knowledge in the clinic, and the practical and ethical issues that will be central to the public discussion on the future of precision cancer care.

MSP-HTPrimer: a high-throughput primer design tool to improve assay design for DNA methylation analysis in epigenetics

Background

Bisulfite (BS) conversion-based and methylation-sensitive restriction enzyme (MSRE)-based PCR methods have been the most commonly used techniques for locus-specific DNA methylation analysis. However, both methods have advantages and limitations. Thus, an integrated approach would be extremely useful to quantify the DNA methylation status successfully with great sensitivity and specificity. Designing specific and optimized primers for target regions is the most critical and challenging step in obtaining the adequate DNA methylation results using PCR-based methods. Currently, no integrated, optimized, and high-throughput methylation-specific primer design software methods are available for both BS- and MSRE-based methods. Therefore an integrated, powerful, and easy-to-use methylation-specific primer design pipeline with great accuracy and success rate will be very useful.

Results

We have developed a new web-based pipeline, called MSP-HTPrimer, to design primers pairs for MSP, BSP, pyrosequencing, COBRA, and MSRE assays on both genomic strands. First, our pipeline converts all target sequences into bisulfite-treated templates for both forward and reverse strand and designs all possible primer pairs, followed by filtering for single nucleotide polymorphisms (SNPs) and known repeat regions. Next, each primer pairs are annotated with the upstream and downstream RefSeq genes, CpG island, and cut sites (for COBRA and MSRE). Finally, MSP-HTPrimer selects specific primers from both strands based on custom and user-defined hierarchical selection criteria. MSP-HTPrimer produces a primer pair summary output table in TXT and HTML format for display and UCSC custom tracks for resulting primer pairs in GTF format.

Conclusions

MSP-HTPrimer is an integrated, web-based, and high-throughput pipeline and has no limitation on the number and size of target sequences and designs MSP, BSP, pyrosequencing, COBRA, and MSRE assays. It is the only pipeline, which automatically designs primers on both genomic strands to increase the success rate. It is a standalone web-based pipeline, which is fully configured within a virtual machine and thus can be readily used without any configuration. We have experimentally validated primer pairs designed by our pipeline and shown a very high success rate of primer pairs: out of 66 BSP primer pairs, 63 were successfully validated without any further optimization step and using the same qPCR conditions. The MSP-HTPrimer pipeline is freely available from http://sourceforge.net/p/msp-htprimer.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-016-0269-3) contains supplementary material, which is available to authorized users.

Epigenetic silencing of endothelin-3 in colorectal cancer

Endothelins are expressed in a variety of human tissue and are involved in the processes as proliferation, migration and differentiation. The signal transduction pathway is a result of the endothelin-1-3 (ET1-3) binding to their receptors (ETAR, ETBR). ET-3 is a new candidate tumour suppressor gene, which is often downregulated or silenced in human cancer.The aim of the study was to examine DNA methylation of ET-3 genes in colorectal cancer (CRC) tissue samples in relation to the clinical stage (CS) of cancer. The paper is a continuation of our previously published results, which showed a four-fold transcriptional silencing of the ET-3 gene in the samples of colorectal cancer in comparison to normal tissues.A total of 66 paired CRC and normal (surgical margin) tissue samples were used in the study. The tumour tissues were collected from CRC patients in CS I-IV according the 7th edition of UICC TNM Classification of Malignant Tumours (CS I, n = 8; CS II, n = 20; CS III, n = 27; CS IV, n = 11). Assessment of epigenetic silencing of the ET-3 encoding gene was performed in three steps. The silencing of the ET-3 encoding gene was a result from methylation of the promoter sequence using methylation-specific PCR (MS-PCR). Analyses were performed using primers complementary for a CpG island in the first exon of the gene encoding ET-3. An epigenetic silence through methylation of 7.5% (5/66) in comparison to control was observed, including 10% of CS II (2/20), 7% of CS III (2/27) and 9% of CS IV (1/11). The controls and the samples of tumour in CS I showed no epigenetic silencing via methylation. In conclusion, epigenetic silencing of ET-3 in CRC could play a role in the progression than in the induction process. EDN3 would be a future target for epigenetic therapy in colorectal cancer, but further clinical studies are needed.

On Predicting lung cancer subtypes using 'omic' data from tumor and tumor-adjacent histologically-normal tissue

BACKGROUND

Adenocarcinoma (ADC) and squamous cell carcinoma (SCC) are the most prevalent histological types among lung cancers. Distinguishing between these subtypes is critically important because they have different implications for prognosis and treatment. Normally, histopathological analyses are used to distinguish between the two, where the tissue samples are collected based on small endoscopic samples or needle aspirations. However, the lack of cell architecture in these small tissue samples hampers the process of distinguishing between the two subtypes. Molecular profiling can also be used to discriminate between the two lung cancer subtypes, on condition that the biopsy is composed of at least 50 % of tumor cells. However, for some cases, the tissue composition of a biopsy might be a mix of tumor and tumor-adjacent histologically normal tissue (TAHN). When this happens, a new biopsy is required, with associated cost, risks and discomfort to the patient. To avoid this problem, we hypothesize that a computational method can distinguish between lung cancer subtypes given tumor and TAHN tissue.

METHODS

Using publicly available datasets for gene expression and DNA methylation, we applied four classification tasks, depending on the possible combinations of tumor and TAHN tissue. First, we used a feature selector (ReliefF/Limma) to select relevant variables, which were then used to build a simple naïve Bayes classification model. Then, we evaluated the classification performance of our models by measuring the area under the receiver operating characteristic curve (AUC). Finally, we analyzed the relevance of the selected genes using hierarchical clustering and IPA® software for gene functional analysis.

RESULTS

All Bayesian models achieved high classification performance (AUC > 0.94), which were confirmed by hierarchical cluster analysis. From the genes selected, 25 (93 %) were found to be related to cancer (19 were associated with ADC or SCC), confirming the biological relevance of our method.

CONCLUSIONS

The results from this study confirm that computational methods using tumor and TAHN tissue can serve as a prognostic tool for lung cancer subtype classification. Our study complements results from other studies where TAHN tissue has been used as prognostic tool for prostate cancer. The clinical implications of this finding could greatly benefit lung cancer patients.

Genome-Wide Epigenetic Studies in Human Disease: A Primer on -Omic Technologies

Epigenetic information encoded in covalent modifications of DNA and histone proteins regulates fundamental biological processes through the action of chromatin regulators, transcription factors, and noncoding RNA species. Epigenetic plasticity enables an organism to respond to developmental and environmental signals without genetic changes. However, aberrant epigenetic control plays a key role in pathogenesis of disease. Normal epigenetic states could be disrupted by detrimental mutations and expression alteration of chromatin regulators or by environmental factors. In this primer, we briefly review the epigenetic basis of human disease and discuss how recent discoveries in this field could be translated into clinical diagnosis, prevention, and treatment. We introduce platforms for mapping genome-wide chromatin accessibility, nucleosome occupancy, DNA-binding proteins, and DNA methylation, primarily focusing on the integration of DNA methylation and chromatin immunoprecipitation-sequencing technologies into disease association studies. We highlight practical considerations in applying high-throughput epigenetic assays and formulating analytical strategies. Finally, we summarize current challenges in sample acquisition, experimental procedures, data analysis, and interpretation and make recommendations on further refinement in these areas. Incorporating epigenomic testing into the clinical research arsenal will greatly facilitate our understanding of the epigenetic basis of disease and help identify novel therapeutic targets.

DNA Methyltransferase Activity Assays: Advances and Challenges

DNA methyltransferases (MTases), a family of enzymes that catalyse the methylation of DNA, have a profound effect on gene regulation. A large body of evidence has indicated that DNA MTase is potentially a predictive biomarker closely associated with genetic disorders and genetic diseases like cancer. Given the attention bestowed onto DNA MTases in molecular biology and medicine, highly sensitive detection of DNA MTase activity is essential in determining gene regulation, epigenetic modification, clinical diagnosis and therapeutics. Conventional techniques such as isotope labelling are effective, but they often require laborious sample preparation, isotope labelling, sophisticated equipment and large amounts of DNA, rendering them unsuitable for uses at point-of-care. Simple, portable, highly sensitive and low-cost assays are urgently needed for DNA MTase activity screening. In most recent technological advances, many alternative DNA MTase activity assays such as fluorescent, electrochemical, colorimetric and chemiluminescent assays have been proposed. In addition, many of them are coupled with nanomaterials and/or enzymes to significantly enhance their sensitivity. Herein we review the progress in the development of DNA MTase activity assays with an emphasis on assay mechanism and performance with some discussion on challenges and perspectives. It is hoped that this article will provide a broad coverage of DNA MTase activity assays and their latest developments and open new perspectives toward the development of DNA MTase activity assays with much improved performance for uses in molecular biology and clinical practice.

Cancer Biomarkers from Genome-Scale DNA Methylation: Comparison of Evolutionary and Semantic Analysis Methods

DNA methylation profiling exploits microarray technologies, thus yielding a wealth of high-volume data. Here, an intelligent framework is applied, encompassing epidemiological genome-scale DNA methylation data produced from the Illumina’s Infinium Human Methylation 450K Bead Chip platform, in an effort to correlate interesting methylation patterns with cancer predisposition and, in particular, breast cancer and B-cell lymphoma. Feature selection and classification are employed in order to select, from an initial set of ~480,000 methylation measurements at CpG sites, predictive cancer epigenetic biomarkers and assess their classification power for discriminating healthy versus cancer related classes. Feature selection exploits evolutionary algorithms or a graph-theoretic methodology which makes use of the semantics information included in the Gene Ontology (GO) tree. The selected features, corresponding to methylation of CpG sites, attained moderate-to-high classification accuracies when imported to a series of classifiers evaluated by resampling or blindfold validation. The semantics-driven selection revealed sets of CpG sites performing similarly with evolutionary selection in the classification tasks. However, gene enrichment and pathway analysis showed that it additionally provides more descriptive sets of GO terms and KEGG pathways regarding the cancer phenotypes studied here. Results support the expediency of this methodology regarding its application in epidemiological studies.

Deregulated Expression of SRC, LYN and CKB Kinases by DNA Methylation and Its Potential Role in Gastric Cancer Invasiveness and Metastasis

Kinases are downstream modulators and effectors of several cellular signaling cascades and play key roles in the development of neoplastic disease. In this study, we aimed to evaluate SRC, LYN and CKB protein and mRNA expression, as well as their promoter methylation, in gastric cancer. We found elevated expression of SRC and LYN kinase mRNA and protein but decreased levels of CKB kinase, alterations that may have a role in the invasiveness and metastasis of gastric tumors. Expression of the three studied kinases was also associated with MYC oncogene expression, a possible biomarker for gastric cancer. To understand the mechanisms that regulate the expression of these genes, we evaluated the DNA promoter methylation of the three kinases. We found that reduced SRC and LYN methylation and increased CKB methylation was associated with gastric cancer. The reduced SRC and LYN methylation was associated with increased levels of mRNA and protein expression, suggesting that DNA methylation is involved in regulating the expression of these kinases. Conversely, reduced CKB methylation was observed in samples with reduced mRNA and protein expression, suggesting CKB expression was found to be only partly regulated by DNA methylation. Additionally, we found that alterations in the DNA methylation pattern of the three studied kinases were also associated with the gastric cancer onset, advanced gastric cancer, deeper tumor invasion and the presence of metastasis. Therefore, SRC, LYN and CKB expression or DNA methylation could be useful markers for predicting tumor progression and targeting in anti-cancer strategies.

The clinicopathological significance and drug target potential of FHIT in breast cancer, a meta-analysis and literature review

FHIT is a bona fide tumor-suppressor gene and its loss contributes to tumorigenesis of epithelial cancers including breast cancer (BC). However, the association and clinicopathological significance between FHIT promoter hypermethylation and BC remains unclear. The purpose of this study is to conduct a meta-analysis and literature review to investigate the clinicopathological significance of FHIT methylation in BC. A detailed literature search was performed in PubMed, EMBASE, Web of Science, and Google Scholar databases. The data were extracted and assessed by two reviewers independently. Odds ratios with 95% corresponding confidence intervals were calculated. A total of seven relevant articles were available for meta-analysis, which included 985 patients. The frequency of FHIT hypermethylation was significantly increased in invasive ductal carcinoma compared to benign breast disease, the pooled odds ratio was 8.43, P<0.00001. The rate of FHIT hypermethylation was not significantly different between stage I/II and stage III/IV, odds ratio was 2.98, P=0.06. In addition, FHIT hypermethylation was not significantly associated with ER and PR status. FHIT hypermethylation was not significantly correlated with premenopausal and postmenopausal patients with invasive ductal carcinoma. In summary, our meta-analysis indicated that the frequency of FHIT hypermethylation was significantly increased in BC compared to benign breast disease. The rate of FHIT hypermethylation in advanced stages of BC was higher than in earlier stages; however, the difference was not statistically significant. Our data suggested that FHIT methylation could be a diagnostic biomarker of BC carcinogenesis. FHIT is a potential drug target for development of demethylation treatment for patients with BC.

Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential

BACKGROUND

Development of human cancer can proceed through the accumulation of different genetic changes affecting the structure and function of the genome. Combined analyses of molecular data at multiple levels, such as DNA copy-number alteration, mRNA and miRNA expression, can clarify biological functions and pathways deregulated in cancer. The integrative methods that are used to investigate these data involve different fields, including biology, bioinformatics, and statistics.

RESULTS

These methodologies are presented in this review, and their implementation in breast cancer is discussed with a focus on integration strategies. We report current applications, recent studies and interesting results leading to the identification of candidate biomarkers for diagnosis, prognosis, and therapy in breast cancer by using both individual and combined analyses.

CONCLUSION

This review presents a state of art of the role of different technologies in breast cancer based on the integration of genetics and epigenetics, and shares some issues related to the new opportunities and challenges offered by the application of such integrative approaches.

Applicability of HIN-1, MGMT and RASSF1A promoter methylation as biomarkers for detecting field cancerization in breast cancer

Introduction

It has been shown in some articles that genetic and epigenetic abnormalities cannot only be found in tumor tissues but also in adjacent regions that appear histologically normal. This phenomenon is metaphorically called field cancerization or field defect. Field cancerization is regarded as clinically significant because it is assumed to be an important factor in local recurrence of cancer. As the field showing these molecular abnormalities may not be removed completely by surgery, these changes might lead to neoplasms and subsequent transformation to a tumor. We aimed to investigate the applicability of the methylation status of six tumor suppressor genes as biomarkers for detecting field cancerization in breast cancer.

Methods

The promoter methylation status of CCND2, DAPK1, GSTP1, HIN-1, MGMT and RASSF1A was determined by methylation-sensitive high-resolution melting (MS-HRM) analysis. MS-HRM methods for CCND2, MGMT and RASSF1A were developed in-house, primer sequences for DAPK1, GSTP1 and HIN-1 have already been published. Biopsy samples were taken from tumor, tumor-adjacent and tumor-distant tissue from 17 breast cancer patients. Normal breast tissues of four healthy women served as controls.

Results

All MS-HRM methods proved to be very sensitive. LODs were in the range from 0.1 to 1.5 %, LOQs ranged from 0.3 to 5.3 %. A total of 94 %, 82 % and 65 % of the tumors showed methylation of RASSF1A, HIN-1 and MGMT promoters, respectively. The methylation status of these promoters was significantly lower in tumor-distant tissues than in tumor tissues. Tumor-adjacent tissues showed higher methylation status of RASSF1A, HIN-1 and MGMT promoters than tumor-distant tissues, indicating field cancerization. The methylation status of the HIN-1 promoter in tumor-adjacent tissues was found to correlate strongly with that in the corresponding tumors (r = 0.785, p < 0.001), but not with that in the corresponding tumor-distant tissues (r = 0.312, p = 0.239).

Conclusions

Among the gene promoters investigated, the methylation status of the HIN-1 promoter can be considered the best suitable biomarker for detecting field cancerization. Further investigation is needed to test whether it can be used for defining surgical margins in order to prevent future recurrence of breast cancer.

Intratumor heterogeneity and transcriptional profiling in glioblastoma: translational opportunities

The study of phenotypic and genetic intratumor heterogeneity in glioblastoma is attracting a lot of attention. Recent studies have demonstrated that transcriptional profiling analysis can help interpret the complexity of this disease. Previously proposed molecular classifiers have been recently challenged due to the unexpected degree of intratumor heterogeneity that has been described spatially and at single-cell level. Different computational methods have been employed to analyze this huge amount of data, but new experimental designs including multisampling from individual patients and single-cell experiments require new specific approaches. In light of these results, there is hope that integration of genetic, phenotypic and transcriptional data coupled with functional experiments might help define new therapeutic strategies and classify patients according to key pathways and molecular targets that can be further investigated to develop personalized and combinatorial treatment strategies.

An evaluation of statistical methods for DNA methylation microarray data analysis

BACKGROUND

DNA methylation offers an excellent example for elucidating how epigenetic information affects gene expression. β values and M values are commonly used to quantify DNA methylation. Statistical methods applicable to DNA methylation data analysis span a number of approaches such as Wilcoxon rank sum test, t-test, Kolmogorov-Smirnov test, permutation test, empirical Bayes method, and bump hunting method. Nonetheless, selection of an optimal statistical method can be challenging when different methods generate inconsistent results from the same data set.

RESULTS

We compared six statistical approaches relevant to DNA methylation microarray analysis in terms of false discovery rate control, statistical power, and stability through simulation studies and real data examples. Observable differences were noticed between β values and M values only when methylation levels were correlated across CpG loci. For small sample size (n=3 or 6 in each group), both the empirical Bayes and bump hunting methods showed appropriate FDR control and the highest power when methylation levels across CpG loci were independent. Only the bump hunting method showed appropriate FDR control and the highest power when methylation levels across CpG sites were correlated. For medium (n=12 in each group) and large sample sizes (n=24 in each group), all methods compared had similar power, except for the permutation test whenever the proportion of differentially methylated loci was low. For all sample sizes, the bump hunting method had the lowest stability in terms of standard deviation of total discoveries whenever the proportion of differentially methylated loci was large. The apparent test power comparisons based on raw p-values from DNA methylation studies on ovarian cancer and rheumatoid arthritis provided results as consistent as those obtained in the simulation studies. Overall, these results provide guidance for optimal statistical methods selection under different scenarios.

CONCLUSIONS

For DNA methylation studies with small sample size, the bump hunting method and the empirical Bayes method are recommended when DNA methylation levels across CpG loci are independent, while only the bump hunting method is recommended when DNA methylation levels are correlated across CpG loci. All methods are acceptable for medium or large sample sizes.

Episensitization: Defying Time's Arrow

The development of cancer is driven by complex genetic and epigenetic changes that result in aberrant and uncontrolled cellular growth. Epigenetic changes, in particular, are implicated in the silencing or activation of key genes that control cellular growth and apoptosis and contribute to transformative potential. The purpose of this review is to define and assess the treatment strategy of “episensitization,” or the ability to sensitize cancer cells to subsequent therapy by resetting the epigenetic infrastructure of the tumor. One important facet is resensitization by epigenetic mechanisms, which goes against the norm, i.e., challenges the long-held doctrine in oncology that the reuse of previously tried and failed therapies is a clinically pointless endeavor. Thus, episensitization is a hybrid term, which covers recent clinically relevant observations and refers to the epigenomic mechanism of resensitization. Among the many formidable challenges in the treatment of cancer, the most inevitable is the development of acquired therapeutic resistance. Here, we present the basic principles behind episensitization and highlight the evidence suggesting that epigenetically mediated histone hypoacetylation and DNA hypermethylation events may reverse clinical drug resistance. The potential reversibility of epigenetic changes and the microenvironmental impact of epigenetic control on gene expression may mediate a return to a baseline state of treatment susceptibility. Episensitization is a novel and highly practical management strategy both to prevent the practice of permanent treatment discontinuation with the occurrence of resistance, which rapidly exhausts remaining options in the pharmaceutical armamentarium and to significantly extend patient survival. Accordingly, this review highlights several epigenetic agents including decitabine, vorinostat, entinostat, 5-azacitidine, oncolytic viruses, and RRx-001.

Methylome sequencing in triple-negative breast cancer reveals distinct methylation clusters with prognostic value

Epigenetic alterations in the cancer methylome are common in breast cancer and provide novel options for tumour stratification. Here, we perform whole-genome methylation capture sequencing on small amounts of DNA isolated from formalin-fixed, paraffin-embedded tissue from triple-negative breast cancer (TNBC) and matched normal samples. We identify differentially methylated regions (DMRs) enriched with promoters associated with transcription factor binding sites and DNA hypersensitive sites. Importantly, we stratify TNBCs into three distinct methylation clusters associated with better or worse prognosis and identify 17 DMRs that show a strong association with overall survival, including DMRs located in the Wilms tumour 1 (WT1) gene, bi-directional-promoter and antisense WT1-AS. Our data reveal that coordinated hypermethylation can occur in oestrogen receptor-negative disease, and that characterizing the epigenetic framework provides a potential signature to stratify TNBCs. Together, our findings demonstrate the feasibility of profiling the cancer methylome with limited archival tissue to identify regulatory regions associated with cancer.

The increasing roles of epigenetics in breast cancer: Implications for pathogenicity, biomarkers, prevention and treatment

Nowadays, the mechanisms governing the occurrence of cancer are thought to be the consequence not only of genetic defects but also of epigenetic modifications. Therefore, epigenetic has become a very attractive and increasingly investigated field of research in order to find new ways of prevention and treatment of neoplasia, and this is particularly the case for breast cancer (BC). Thus, this review will first develop the main known epigenetic modifications that can occur in cancer and then expose the future role that control of epigenetic modifications might play in prevention, prognostication, follow-up and treatment of BC. Indeed, epigenetic biomarkers found in peripheral blood might become new tools to detect BC, to define its prognostic and to predict its outcome, whereas epi-drugs might have an increasing potential of development in the next future. However, if DNA methyltransferase inhibitors and histone desacetylase inhibitors have shown encouraging results in BC, their action remains nonspecific. Thus, additional clinical studies are needed to evaluate more precisely the effects of these molecules, even if they have provided encouraging results in cotreatment and combined therapies. This review will also deal with the potential of RNA interference (RNAi) as epi-drugs. Finally, we will focus on the potential prevention of BC through epigenetic based on diet and we will particularly develop the possible place of isothiocyanates from cruciferous vegetables or of Genistein from soybean in a dietary program that might potentially reduce the risk of BC in large populations.

Statistical methods for detecting differentially methylated loci and regions

DNA methylation, the reversible addition of methyl groups at CpG dinucleotides, represents an important regulatory layer associated with gene expression. Changed methylation status has been noted across diverse pathological states, including cancer. The rapid development and uptake of microarrays and large scale DNA sequencing has prompted an explosion of data analytic methods for processing and discovering changes in DNA methylation across varied data types. In this mini-review, we present a compact and accessible discussion of many of the salient challenges, such as experimental design, statistical methods for differential methylation detection, critical considerations such as cell type composition and the potential confounding that can arise from batch effects. From a statistical perspective, our main interests include the use of empirical Bayes or hierarchical models, which have proved immensely powerful in genomics, and the procedures by which false discovery control is achieved.

DNA methylation of heparanase promoter influences its expression and associated with the progression of human breast cancer

Heparanase promotes tumor invasion and metastasis in several malignancies including breast cancer. However, the roles and regulation mechanisms of heparanase during breast cancer progression are still not fully understood. The aim of this study is to determine the differential regulation of heparanase gene expression in specific stages of breast cancer by DNA methylation. We detected levels of heparanase expression and DNA methylation patterns of its promoter in breast cancer cell lines (MCF-7 and MDA-MB-435) and clinical tissues, respectively. It has been observed that heparanase is highly expressed in the invasive MDA-MB-435 cells with low methylation modification in the heparanase promoter. In contrast, lower expression of heparanase in MCF-7 cells is accompanied by higher methylation in the promoter. Treatment of MCF-7 cells with 5-aza-2'-deoxycytidine (5-aza-dC), a potent demethylating agent, results in induction of heparanase expression and higher invasion potential in vitro and leads to an advantage of tumor formation in vivo. In 54 tissue samples, cancer samples at late stages (stage IV) showed the highest heparanase expression accomplished by little DNA methylation. On the contrary, methylation prevalence is highest in normal tissue and inversely correlated with heparanase expression. A significant correlation between DNA methylation and clinical stage was demonstrated (p = 0.012). Collectively, these results demonstrate that DNA methylation play the regulation role in heparanase gene in different stages of breast cancer and present a direct effect on tumor progression.

PIAS1 regulates breast tumorigenesis through selective epigenetic gene silencing

Epigenetic gene silencing by histone modifications and DNA methylation is essential for cancer development. The molecular mechanism that promotes selective epigenetic changes during tumorigenesis is not understood. We report here that the PIAS1 SUMO ligase is involved in the progression of breast tumorigenesis. Elevated PIAS1 expression was observed in breast tumor samples. PIAS1 knockdown in breast cancer cells reduced the subpopulation of tumor-initiating cells, and inhibited breast tumor growth in vivo. PIAS1 acts by delineating histone modifications and DNA methylation to silence the expression of a subset of clinically relevant genes, including breast cancer DNA methylation signature genes such as cyclin D2 and estrogen receptor, and breast tumor suppressor WNT5A. Our studies identify a novel epigenetic mechanism that regulates breast tumorigenesis through selective gene silencing.

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.

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.

Comparison of methylation profiling in cancerous and their corresponding normal tissues from korean patients with breast cancer

BACKGROUND

Aberrant DNA hypermethylation plays a pivotal role in carcinogenesis and disease progression; therefore, accurate measurement of differential gene methylation patterns among many genes is likely to reveal biomarkers for improved risk assessment. We evaluated the gene hypermethylation profiles of primary breast tumors and their corresponding normal tissues and investigated the association between major clinicopathological features and gene hypermethylation.

METHODS

A single reaction using methylation-specific multiplex ligation-dependent probe amplification was used to analyze the DNA methylation status of 24 tumor suppressor genes in 60 cancerous tissues and their corresponding normal tissues from patients with primary breast cancer.

RESULTS

In cancerous breast tissues, 21 of 24 genes displayed promoter methylation in one or more samples. The most frequently methylated genes included RASSF1 (43.3%), APC (31.7%), CDKN2B (25.0%), CDH13 (23.3%), GSTP1 (16.7%), and BRCA1 (10%). APC was associated with lymph node metastasis, and BRCA1 was associated with negative estrogen receptor and negative progesterone receptor expression. In normal breast tissues, 8 of 24 tumor suppressor genes displayed promoter hypermethylation; CDKN2B (28.3%) and RASSF1 (8.3%) hypermethylation were most frequently observed.

CONCLUSIONS

RASSF1 and CDKN2B hypermethylation in Korean breast cancer patients were the most frequent in cancerous tissue and corresponding normal tissue, respectively. Our data indicates that methylation of specific genes is a frequent event in morphologically normal breast tissues adjacent to breast tumors as well as the corresponding breast cancers. This study also suggests that gene methylation is linked to various pathological features of breast cancer; however, this requires confirmation in a larger study.

Shift work and cancer risk: potential mechanistic roles of circadian disruption, light at night, and sleep deprivation

Shift work that includes a nighttime rotation has become an unavoidable attribute of today's 24-h society. The related disruption of the human circadian time organization leads in the short-term to an array of jet-lag-like symptoms, and in the long-run it may contribute to weight gain/obesity, metabolic syndrome/type II diabetes, and cardiovascular disease. Epidemiologic studies also suggest increased cancer risk, especially for breast cancer, in night and rotating female shift workers. If confirmed in more controlled and detailed studies, the carcinogenic effect of night and shift work will constitute additional serious medical, economic, and social problems for a substantial proportion of the working population. Here, we examine the possible multiple and interconnected cancer-promoting mechanisms as a consequence of shift work, i.e., repeated disruption of the circadian system, pineal hormone melatonin suppression by exposure to light at night, sleep-deprivation-caused impairment of the immune system, plus metabolic changes favoring obesity and generation of proinflammatory reactive oxygen species.