Targeting tumor metabolism by energy restriction-mimetic agents (ERMAs) has emerged as a strategy for cancer therapy/prevention. Evidence suggests a mechanistic link between ERMA-mediated antitumor effects and epigenetic gene regulation.
Microarray analysis showed that a novel thiazolidinedione-derived ERMA, CG-12, and glucose deprivation could suppress DNA methyltransferase (DNMT)1 expression and reactivate DNA methylation-silenced tumor suppressor genes in LNCaP prostate cancer cells. Thus, we investigated the effects of a potent CG-12 derivative, CG-5, vis-à-vis 2-deoxyglucose, glucose deprivation and/or 5-aza-deoxycytidine, on DNMT isoform expression (Western blotting, RT-PCR), DNMT1 transcriptional activation (luciferase reporter assay), and expression of genes frequently hypermethylated in prostate cancer (quantitative real-time PCR). Promoter methylation was assessed by pyrosequencing analysis. SiRNA-mediated knockdown and ectopic expression of DNMT1 were used to validate DNMT1 as a target of CG-5.
CG-5 and glucose deprivation upregulated the expression of DNA methylation-silenced tumor suppressor genes, including GADD45a, GADD45b, IGFBP3, LAMB3, BASP1, GPX3, and GSTP1, but also downregulated methylated tumor/invasion-promoting genes, including CD44, S100A4, and TACSTD2. In contrast, 5-aza-deoxycytidine induced global reactivation of these genes. CG-5 mediated these epigenetic effects by transcriptional repression of DNMT1, which was associated with reduced expression of Sp1 and E2F1. SiRNA-mediated knockdown and ectopic expression of DNMT1 corroborated DNMT1's role in the modulation of gene expression by CG-5. Pyrosequencing revealed differential effects of CG-5 versus 5-aza-deoxycytidine on promoter methylation in these genes.
These findings reveal a previously uncharacterized epigenetic effect of ERMAs on DNA methylation-silenced tumor suppressor genes, which may foster novel strategies for prostate cancer therapy.
energy restriction-mimetic agent; prostate cancer; energy restriction; DNA methyltransferases; epigenetics
Aberrant DNA methylation of CpG islands, CpG island shores and first exons is known to play a key role in the altered gene expression patterns in all human cancers. To date, a systematic study on the effect of DNA methylation on gene expression using high resolution data has not been reported. In this study, we conducted an integrated analysis of MethylCap-sequencing data and Affymetrix gene expression microarray data for 30 breast cancer cell lines representing different breast tumor phenotypes. As well-developed methods for the integrated analysis do not currently exist, we created a series of four different analysis methods. On the computational side, our goal is to develop methylome data analysis protocols for the integrated analysis of DNA methylation and gene expression data on the genome scale. On the cancer biology side, we present comprehensive genome-wide methylome analysis results for differentially methylated regions and their potential effect on gene expression in 30 breast cancer cell lines representing three molecular phenotypes, luminal, basal A and basal B. Our integrated analysis demonstrates that methylation status of different genomic regions may play a key role in establishing transcriptional patterns in molecular subtypes of human breast cancer.
Recent genome-wide profiling reveals highly complex regulation networks among ERα and its targets. We integrated estrogen (E2)-stimulated time-series ERα ChIP-seq and gene expression data to identify the ERα-centered transcription factor (TF) hubs and their target genes, and inferred the time-variant hierarchical network structures using a Bayesian multivariate modeling approach. With its recurrent motif patterns, we determined three embedded regulatory modules from the ERα core transcriptional network. The GO analyses revealed the distinct biological function associated with each of three embedded modules. The survival analysis showed the genes in each module were able to render a significant survival correlation in breast cancer patient cohorts. In summary, our Bayesian statistical modeling and modularity analysis not only reveals the dynamic properties of the ERα-centered regulatory network and associated distinct biological functions, but also provides a reliable and effective genomic analytical approach for the analysis of dynamic regulatory network for any given TF.
DNA methylation and histone modifications have essential roles in remodeling chromatin structure of genes necessary for multi-lineage differentiation of mammary stem/progenitor cells. The role of this well-defined epigenetic programming is to heritably maintain transcriptional plasticity of these loci over multiple cell divisions in the differentiated progeny. Epigenetic events can be deregulated in progenitor cells chronically exposed to xenoestrogen or inflammatory microenvironment. In addition, epigenetically mediated silencing of genes associated with tumor suppression can take place, resulting in clonal proliferation of undifferentiated or semidifferentiated cells. Alternatively, microRNAs that negatively regulate the expression of their protein-coding targets may become epigenetically repressed, leading to oncogenic expression of these genes. Here we further discuss interactions between DNA methylation and histone modifications that have significant contributions to the differentiation of mammary stem/progenitor cells and to tumor initiation and progression.
Mammary gland stem cells and their progeny display characteristic DNA methylation and histone modification patterns. Carcinogens and inflammation can disrupt such epigenetic programs, leading to tumorigenesis.
A number of empirical Bayes models (each with different statistical distribution assumptions) have now been developed to analyze differential DNA methylation using high-density oligonucleotide tiling arrays. However, it remains unclear which model performs best. For example, for analysis of differentially methylated regions for conservative and functional sequence characteristics (e.g., enrichment of transcription factor-binding sites (TFBSs)), the sensitivity of such analyses, using various empirical Bayes models, remains unclear. In this paper, five empirical Bayes models were constructed, based on either a gamma distribution or a log-normal distribution, for the identification of differential methylated loci and their cell division—(1, 3, and 5) and drug-treatment-(cisplatin) dependent methylation patterns. While differential methylation patterns generated by log-normal models were enriched with numerous TFBSs, we observed almost no TFBS-enriched sequences using gamma assumption models. Statistical and biological results suggest log-normal, rather than gamma, empirical Bayes model distribution to be a highly accurate and precise method for differential methylation microarray analysis. In addition, we presented one of the log-normal models for differential methylation analysis and tested its reproducibility by simulation study. We believe this research to be the first extensive comparison of statistical modeling for the analysis of differential DNA methylation, an important biological phenomenon that precisely regulates gene transcription.
While tumor suppressor genes frequently undergo epigenetic silencing in cancer, how the instructions directing this transcriptional repression are transmitted in cancer cells remain largely unclear. Expression of cyclin-dependent kinase inhibitor 1C (CDKN1C), an imprinted gene on chromosomal band 11 p15.5, is reduced or lost in the majority of breast cancers. Here, we report that CDKN1C is suppressed by estrogen through epigenetic mechanisms involving the chromatin-interacting noncoding RNA KCNQ1OT1 and CCCTC-binding factor (CTCF). Activation of estrogen signaling reduced CDKN1C expression 3-fold (P < 0.001) and established repressive histone modifications at the 5′ regulatory region of the locus. These events were concomitant with induction of KCNQ1OT1 expression as well as increased recruitment of CTCF to both the distal KCNQ1OT1 promoter-associated imprinting control region (ICR) and the CDKN1C locus. Transient depletion of CTCF by small interfering RNA increased CDKN1C expression and significantly reduced the estrogen-mediated repression of CDKN1C. Further studies in breast cancer cell lines indicated that the epigenetic silencing of CDKN1C occurs in part as the result of genetic loss of the inactive methylated 11p15.5 ICR allele (R2 = 0.612, P < 0.001). We also found a novel cis-encoded antisense transcript, CDKN1C-AS, which is induced by estrogen signaling following pharmacologic inhibition of DNA methyltransferase and histone deacetylase activity. Forced expression of CDKN1C-AS was capable of repressing endogenous CDKN1C in vivo. Our findings suggest that in addition to promoter hypermethylation, epigenetic repression of tumor suppressor genes by CTCF and noncoding RNA transcripts could be more common and important than previously understood.
It is now established that, as compared to normal cells, the cancer cell genome has an overall inverse distribution of DNA methylation (“methylome”), i.e., predominant hypomethylation and localized hypermethylation, within “CpG islands” (CGIs). Moreover, although cancer cells have reduced methylation “fidelity” and genomic instability, accurate maintenance of aberrant methylomes that underlie malignant phenotypes remains necessary. However, the mechanism(s) of cancer methylome maintenance remains largely unknown. Here, we assessed CGI methylation patterns propagated over 1, 3, and 5 divisions of A2780 ovarian cancer cells, concurrent with exposure to the DNA cross-linking chemotherapeutic cisplatin, and observed cell generation-successive increases in total hyper- and hypo-methylated CGIs. Empirical Bayesian modeling revealed five distinct modes of methylation propagation: (1) heritable (i.e., unchanged) high- methylation (1186 probe loci in CGI microarray); (2) heritable (i.e., unchanged) low-methylation (286 loci); (3) stochastic hypermethylation (i.e., progressively increased, 243 loci); (4) stochastic hypomethylation (i.e., progressively decreased, 247 loci); and (5) considerable “random” methylation (582 loci). These results support a “stochastic model” of DNA methylation equilibrium deriving from the efficiency of two distinct processes, methylation maintenance and de novo methylation. A role for cis-regulatory elements in methylation fidelity was also demonstrated by highly significant (p<2.2×10−5) enrichment of transcription factor binding sites in CGI probe loci showing heritably high (118 elements) and low (47 elements) methylation, and also in loci demonstrating stochastic hyper-(30 elements) and hypo-(31 elements) methylation. Notably, loci having “random” methylation heritability displayed nearly no enrichment. These results demonstrate an influence of cis-regulatory elements on the nonrandom propagation of both strictly heritable and stochastically heritable CGIs.
DNA methylation is a hallmark in a subset of right-sided colorectal cancers. Methylation-based screening may improve prevention and survival rate for this type of cancer, which is often clinically asymptomatic in the early stages. We aimed to discover prognostic or diagnostic biomarkers for colon cancer by comparing DNA methylation profiles of right-sided colon tumours and paired normal colon mucosa using an 8.5 k CpG island microarray. We identified a diagnostic CpG-rich region, located in the first intron of the protein-tyrosine phosphatase gamma gene (PTPRG) gene, with altered methylation already in the adenoma stage, that is, before the carcinoma transition. Validation of this region in an additional cohort of 103 sporadic colorectal tumours and 58 paired normal mucosa tissue samples showed 94% sensitivity and 96% specificity. Interestingly, comparable results were obtained when screening a cohort of Lynch syndrome-associated cancers. Functional studies showed that PTPRG intron 1 methylation did not directly affect PTPRG expression, however, the methylated region overlapped with a binding site of the insulator protein CTCF. Chromatin immunoprecipitation (ChIP) showed that methylation of the locus was associated with absence of CTCF binding. Methylation-associated changes in CTCF binding to PTPRG intron 1 could have implications on tumour gene expression by enhancer blocking, chromosome loop formation or abrogation of its insulator function. The high sensitivity and specificity for the PTPRG intron 1 methylation in both sporadic and hereditary colon cancers support biomarker potential for early detection of colon cancer.
PTPRG; colorectal cancer; CTCF; DNA methylation; Lynch syndrome
Trimethylation of histone 3 lysine 27 (H3K27me3) is a critical epigenetic mark for the maintenance of gene silencing. Additional accumulation of DNA methylation in target loci is thought to cooperatively support this epigenetic silencing during tumorigenesis. However, molecular mechanisms underlying the complex interplay between the two marks remain to be explored. Here we demonstrate that activation of PI3K/AKT signaling can be a trigger of this epigenetic processing at many downstream target genes. We also find that DNA methylation can be acquired at the same loci in cancer cells, thereby reinforcing permanent repression in those losing the H3K27me3 mark. Because of a link between PI3K/AKT signaling and epigenetic alterations, we conducted epigenetic therapies in conjunction with the signaling-targeted treatment. These combined treatments synergistically relieve gene silencing and suppress cancer cell growth in vitro and in xenografts. The new finding has important implications for improving targeted cancer therapies in the future.
Epigenetic silencing; H3K27me3; DNA methylation; PI3K/AKT signaling; breast cancer
This study evaluated the effects of black raspberries (BRBs) on biomarkers of tumor development in the human colon and rectum including methylation of relevant tumor suppressor genes, cell proliferation, apoptosis, angiogenesis and expression of Wnt pathway genes.
Biopsies of adjacent normal tissues and colorectal adenocarcinomas were taken from 20 patients before and after oral consumption of BRB powder (60g/day) for 1-to-9 wks. Methylation status of promoter regions of five tumor suppressor genes was quantified. Protein expression of DNA methyltransferase 1 (DNMT1) and genes associated with cell proliferation, apoptosis, angiogenesis, and Wnt signaling were measured.
The methylation of three Wnt inhibitors, SFRP2, SFRP5, and WIF1, upstream genes in Wnt pathway, and PAX6a, a developmental regulator, was modulated in a protective direction by BRBs in normal tissues and in colorectal tumors only in patients who received an average of 4 wks of BRB treatment, but not in all 20 patients with 1-to-9 wks of BRB treatment. This was associated with decreased expression of DNMT1. BRBs modulated expression of genes associated with Wnt pathway, proliferation, apoptosis and angiogenesis in a protective direction.
These data provide evidence of the ability of BRBs to demethylate tumor suppressor genes and to modulate other biomarkers of tumor development in the human colon and rectum. While demethylation of genes did not occur in colorectal tissues from all treated patients, the positive results with the secondary endpoints suggest that additional studies of BRBs for the prevention of colorectal cancer in humans now appear warranted.
Substantial evidence indicates that exposure to bisphenol A (BPA) during early development may increase breast cancer risk later in life. The changes may persist into puberty and adulthood, suggesting an epigenetic process being imposed in differentiated breast epithelial cells. The molecular mechanisms by which early memory of BPA exposure is imprinted in breast progenitor cells and then passed onto their epithelial progeny are not well understood. The aim of this study was to examine epigenetic changes in breast epithelial cells treated with low-dose BPA. We also investigated the effect of BPA on the ERα signaling pathway and global gene expression profiles. Compared to control cells, nuclear internalization of ERα was observed in epithelial cells preexposed to BPA. We identified 170 genes with similar expression changes in response to BPA. Functional analysis confirms that gene suppression was mediated in part through an ERα-dependent pathway. As a result of exposure to BPA or other estrogen-like chemicals, the expression of lysosomal-associated membrane protein 3 (LAMP3) became epigenetically silenced in breast epithelial cells. Furthermore, increased DNA methylation in the LAMP3 CpG island was this repressive mark preferentially occurred in ERα-positive breast tumors. These results suggest that the in vitro system developed in our laboratory is a valuable tool for exposure studies of BPA and other xenoestrogens in human cells. Individual and geographical differences may contribute to altered patterns of gene expression and DNA methylation in susceptible loci. Combination of our exposure model with epigenetic analysis and other biochemical assays can give insight into the heritable effect of low-dose BPA in human cells.
Bisphenol A; Estrogen; DNA methylation; Epigenetics; Breast cancer
Deregulation of the transforming growth factor-β (TGFβ) signaling pathway in epithelial ovarian cancer has been reported, but the precise mechanism underlying disrupted TGFβ signaling in the disease remains unclear. We performed chromatin immunoprecipitation followed by sequencing (ChIP-seq) to investigate genome-wide screening of TGFβ-induced SMAD4 binding in epithelial ovarian cancer. Following TGFβ stimulation of the A2780 epithelial ovarian cancer cell line, we identified 2,362 SMAD4 binding loci and 318 differentially expressed SMAD4 target genes. Comprehensive examination of SMAD4-bound loci, revealed four distinct binding patterns: 1) Basal; 2) Shift; 3) Stimulated Only; 4) Unstimulated Only. TGFβ stimulated SMAD4-bound loci were primarily classified as either Stimulated only (74%) or Shift (25%), indicating that TGFβ-stimulation alters SMAD4 binding patterns in epithelial ovarian cancer cells. Furthermore, based on gene regulatory network analysis, we determined that the TGFβ-induced, SMAD4-dependent regulatory network was strikingly different in ovarian cancer compared to normal cells. Importantly, the TGFβ/SMAD4 target genes identified in the A2780 epithelial ovarian cancer cell line were predictive of patient survival, based on in silico mining of publically available patient data bases. In conclusion, our data highlight the utility of next generation sequencing technology to identify genome-wide SMAD4 target genes in epithelial ovarian cancer and link aberrant TGFβ/SMAD signaling to ovarian tumorigenesis. Furthermore, the identified SMAD4 binding loci, combined with gene expression profiling and in silico data mining of patient cohorts, may provide a powerful approach to determine potential gene signatures with biological and future translational research in ovarian and other cancers.
Methyl-CpG binding domain protein sequencing (MBD-seq) is widely used to survey DNA methylation patterns. However, the optimal experimental parameters for MBD-seq remain unclear and the data analysis remains challenging. In this study, we generated high depth MBD-seq data in MCF-7 cell and developed a bi-asymmetric-Laplace model (BALM) to perform data analysis. We found that optimal efficiency of MBD-seq experiments was achieved by sequencing ∼100 million unique mapped tags from a combination of 500 mM and 1000 mM salt concentration elution in MCF-7 cells. Clonal bisulfite sequencing results showed that the methylation status of each CpG dinucleotides in the tested regions was accurately detected with high resolution using the proposed model. These results demonstrated the combination of MBD-seq and BALM could serve as a useful tool to investigate DNA methylome due to its low cost, high specificity, efficiency and resolution.
DNA promoter methylation is an epigenetic phenomenon for long-term gene silencing during tumorigenesis. The purpose of this study is to identify novel hypermethylated loci associated with clinicopathologic variables in endometrioid endometrial carcinomas.
To find hypermethylated promoter loci, we used differential methylation hybridization coupling with microarray and further validated by combined bisulfite restriction analysis and MassARRAY assay. Methylation levels of candidate loci were corrected with clinicopathologic factors of endometrial carcinomas.
Increased promoter methylation of CIDE, HAAO and RXFP3 was detected in endometrial carcinomas compared with adjacent normal tissues, and was associated with decreased gene expression of all three genes. In a clinical cohort, promoter hypermethylation on CIDEA, HAAO and RXFP3 was detected in 85, 63 and 71% of endometrial carcinomas, respectively (n=118, P<0.001) compared with uninvolved normal endometrium. Methylation status of CIDEA, HAAO and RXFP3 had significant association with microsatellite instability in tumors (P<0.001). Furthermore, methylation levels of HAAO were further found to relate to disease-free survivals (P=0.034).
Hypermethylation of CIDEA, HAAO and RXFP3 promoter regions appears to be a frequent event in endometrial carcinomas. Hypermethylation at these loci is strongly associated with microsatellite instability status. Moreover, HAAO methylation predicts disease-free survival in this cohort of patients with endometrioid endometrial cancer.
Endometrial carcinoma; Hypermethylation; CIDEA; HAAO; RXFP3
DNA cytosine methylation is a central epigenetic modification which plays critical roles in cellular processes including genome regulation, development and disease. Here, we review current and emerging microarray and next-generation sequencing based technologies that enhance our knowledge of DNA methylation profiling. Each methodology has limitations and their unique applications, and combinations of several modalities may help build the entire methylome. With advances on next-generation sequencing technologies, it is now possible to globally map the DNA cytosine methylation at single-base resolution, providing new insights into the regulation and dynamics of DNA methylation in genomes.
DNA methylation; Microarray; Next-generation sequencing
Genetic amplification, mutation, and translocation are known to play a causal role in the up-regulation of an oncogene in cancer cells. Here we report an emerging role of microRNA, the epigenetic deregulation of which may also lead to this oncogenic activation. SOX4, an oncogene belonging to the SRY-related high-mobility-group-box family, was found to be over-expressed (P<0.005) in endometrial tumors (n=74) compared with uninvolved controls (n=20). This gene is computationally predicted to be the target of a microRNA, miR-129-2. When compared to the matched endometria, the expression of miR-129-2 was lost in 27 of 31 primary endometrial tumors that also showed a concomitant gain of SOX4 expression (P<0.001). This inverse relationship is associated with hypermethylation of the miR-129-2 CpG island, which was observed in endometrial cancer cell lines (n=6) and 68% of 117 endometrioid endometrial tumors analyzed. Reactivation of miR-129-2 in cancer cells by pharmacological induction of histone acetylation and DNA demethylation resulted in decreased SOX4 expression. In addition, restoration of miR-129-2 by cell transfection led to decreased SOX4 expression and reduced proliferation of cancer cells. Further analysis found a significant correlation of hypermethylated miR-129-2 with microsatellite instability and MLH1 methylation status (P<0.001), and poor overall survival (P<0.039) in patients. Therefore, these results imply that the aberrant expression of SOX4 is, in part, caused by epigenetic repression of miR-129-2 in endometrial cancer. Unlike the notion that promoter hypomethylation may up-regulate an oncogene, we present a new paradigm in which hypermethylation-mediated silencing of a microRNA de-represses its oncogenic target in cancer cells.
DNA methylation; epigenetics; miR-129-2; SOX4
MicroRNAs are small non-coding RNAs involved in post-transcriptional regulation of gene expression. Due to the poor annotation of primary microRNA (pri-microRNA) transcripts, the precise location of promoter regions driving expression of many microRNA genes is enigmatic. This deficiency hinders our understanding of microRNA-mediated regulatory networks. In this study, we develop a computational approach to identify the promoter region and transcription start site (TSS) of pri-microRNAs actively transcribed using genome-wide RNA Polymerase II (RPol II) binding patterns derived from ChIP-seq data. Based upon the assumption that the distribution of RPol II binding patterns around the TSS of microRNA and protein coding genes are similar, we designed a statistical model to mimic RPol II binding patterns around the TSS of highly expressed, well-annotated promoter regions of protein coding genes. We used this model to systematically scan the regions upstream of all intergenic microRNAs for RPol II binding patterns similar to those of TSS from protein coding genes. We validated our findings by examining the conservation, CpG content, and activating histone marks in the identified promoter regions. We applied our model to assess changes in microRNA transcription in steroid hormone-treated breast cancer cells. The results demonstrate many microRNA genes have lost hormone-dependent regulation in tamoxifen-resistant breast cancer cells. MicroRNA promoter identification based upon RPol II binding patterns provides important temporal and spatial measurements regarding the initiation of transcription, and therefore allows comparison of transcription activities between different conditions, such as normal and disease states.
Metastable and somatically heritable patterns of DNA methylation provide an important level of genomic regulation. In this article, we review methods for analyzing these genome-wide epigenetic patterns and offer a perspective on the ever-expanding literature, which we hope will be useful for investigators who are new to this area. The historical aspects that we cover will be helpful in interpreting this literature and we hope that our discussion of the newest analytical methods will stimulate future progress. We emphasize that no single approach can provide a complete view of the overall methylome, and that combinations of several modalities applied to the same sample set will give the clearest picture. Given the unexpected epigenomic patterns and new biological principles, as well as new disease markers, that have been uncovered in recent studies, it is likely that important discoveries will continue to be made using genome-wide DNA methylation profiling.
bisulfite sequencing; CpG island; differential methylation hybridization; DNA methylation; methylation profiling; methylated CpG island recovery assay; methylated DNA immunoprecipitation; methylation-sensitive SNP chip analysis; next-generation DNA sequencing
Alternative promoters that are differentially used in various cellular contexts and tissue types add to the transcriptional complexity in mammalian genome. Identification of alternative promoters and the annotation of their activity in different tissues is one of the major challenges in understanding the transcriptional regulation of the mammalian genes and their isoforms. To determine the use of alternative promoters in different tissues, we performed ChIP-seq experiments using antibody against RNA Pol-II, in five adult mouse tissues (brain, liver, lung, spleen and kidney). Our analysis identified 38 639 Pol-II promoters, including 12 270 novel promoters, for both protein coding and non-coding mouse genes. Of these, 6384 promoters are tissue specific which are CpG poor and we find that only 34% of the novel promoters are located in CpG-rich regions, suggesting that novel promoters are mostly tissue specific. By identifying the Pol-II bound promoter(s) of each annotated gene in a given tissue, we found that 37% of the protein coding genes use alternative promoters in the five mouse tissues. The promoter annotations and ChIP-seq data presented here will aid ongoing efforts of characterizing gene regulatory regions in mammalian genomes.
Early exposure to xenoestrogens may predispose to breast cancer risk later in adult life. It is likely that long-lived, self-regenerating epithelial progenitor cells are more susceptible to these exposure injuries over time and transmit the injured memory through epigenetic mechanisms to their differentiated progeny. Here, we used progenitor-containing mammospheres as an in vitro exposure model to study this epigenetic effect. Expression profiling identified that, relative to control cells, 9.1% of microRNAs (82 of 898 loci) were altered in epithelial progeny derived from mammospheres exposed to a synthetic estrogen, diethylstilbestrol. Repressive chromatin marks, trimethyl Lys27 of histone H3 (H3K27me3) and dimethyl Lys9 of histone H3 (H3K9me2), were found at a down-regulated locus, miR-9-3, in epithelial cells preexposed to diethylstilbestrol. This was accompanied by recruitment of DNA methyltransferase 1 that caused an aberrant increase in DNA methylation of its promoter CpG island in mammosphere-derived epithelial cells on diethylstilbestrol preexposure. Functional analyses suggest that miR-9-3 plays a role in the p53-related apoptotic pathway. Epigenetic silencing of this gene, therefore, reduces this cellular function and promotes the proliferation of breast cancer cells. Promoter hypermethylation of this microRNA may be a hallmark for early breast cancer development, and restoration of its expression by epigenetic and microRNA-based therapies is another viable option for future treatment of this disease.
Epigenetic alterations of the genome such as DNA promoter methylation and chromatin remodeling play an important role in tumorigenesis. Recent findings indicate epigenetic modifications as key factors in breast carcinogenesis. These modifications are quite appealing as targets for preventative care and therapeutics because of their potential for reversal. Future medical care for breast cancer patients will likely depend upon a better understanding of the roles epigenetic modifications play in carcinogenesis. Here, we discuss the importance of epigenetics in breast cancer detection, prognosis, and therapy with an emphasis on mechanisms and epigenetic contributions to field cancerization effects.
epigenetics; breast cancer; field cancerization BRCA; ER
It is becoming increasingly evident that discrete genetic alterations in neoplastic cells alone cannot explain multistep carcinogenesis whereby tumor cells are able to express diverse phenotypes during the complex phases of tumor development and progression. The epigenetic model posits that the host microenvironment exerts an initial, inhibitory constraint on tumor growth that is followed by acceleration of tumor progression through complex cell–matrix interactions. This review emphasizes the epigenetic aspects of breast cancer development in light of such interactions between epithelial cells (“seed”) and the tumor microenvironment (“soil”). Our recent research findings suggest that epigenetic perturbations induced by the tumor microenvironment may play a causal role in promoting breast cancer development. It is believed that abrogation of these initiators could offer a promising therapeutic strategy.
Breast cancer; Tumor microenvironment; Stromal fibroblast; Epigenetics; DNA methylation; Chromatin remodeling
The methylated DNA immunoprecipitation microarray (MeDIP-chip) is a genome-wide, high-resolution approach to detect DNA methylation in whole genome or CpG (cytosine base followed by a guanine base) islands. The method utilizes anti-methylcytosine antibody to immunoprecipitate DNA that contains highly methylated CpG sites. Enriched methylated DNA can be interrogated using DNA microarrays or by massive parallel sequencing techniques. This combined approach allows researchers to rapidly identify methylated regions in a genome-wide manner, and compare DNA methylation patterns between two samples with diversely different DNA methylation status. MeDIP-chip has been applied successfully for analyses of methylated DNA in the different targets including animal and plant tissues (1, 2). Here we present a MeDIP-chip protocol that is routinely used in our laboratory, illustrated with specific examples from MeDIP-chip analysis of breast cancer cell lines. Potential technical pitfalls and solutions are also provided to serve as workflow guidelines.
DNA methylation; epigenetics; MeDIP-chip; microarray; cancer
Differential Methylation Hybridization (DMH) is a high-throughput DNA methylation screening tool that utilizes methylation-sensitive restriction enzymes to profile methylated fragments by hybridizing them to a CpG island microarray. This array contains probes spanning all the 27,800 islands annotated in the UCSC Genome Browser. Herein we describe a DMH protocol with clearly identified quality control points. In this manner, samples that are unlikely to provide good read-outs for differential methylation profiles between the test and the control samples will be identified and repeated with appropriate modifications. The step-by-step laboratory DMH protocol is described. In addition, we provide descriptions regarding DMH data analysis, including image quantification, background correction, and statistical procedures for both exploratory analysis and more formal inferences. Issues regarding quality control are addressed as well.
DNA methylation; Differential Methylation Hybridization (DMH); CpG islands (CGI); microarray
Ovarian cancer ranks the most lethal among gynecologic neoplasms in women. To develop potential bio-markers for diagnosis, we have identified five novel genes (CYP39A1, GTF2A1, FOXD4L4, EBP, and HAAO) that are hypermethylated in ovarian tumors, compared with the non-malignant normal ovarian surface epithelia, using the quantitative methylation-specific polymerase chain reactions. Interestingly enough, multivariate Cox regression analysis has identified hypermethylation of CYP39A1 correlated with an increase rate of relapsing (P=0.032, hazard ratio >1). Concordant hypermethylation in at least three loci was observed in 50 out of 55 (91%) of ovarian tumors examined. The test sensitivity and specificity were assessed to be 96 and 67% for CYP39A1; 95 and 88% for GTF2A1; 93 and 67% for FOXD4L4; 81 and 67% for EBP; 89 and 82% for HAAO, respectively. Our data have identified, for the first time, GTF2A1 alone, or GTF2A1 plus HAAO are excellent candidate biomarkers for detecting this disease. Moreover, the known functions of these gene products further implicate dys-regulated transcriptional control, cholesterol metabolism, or synthesis of quinolinic acids, may play important roles in attributing to ovarian neoplasm. Molecular therapies, by reversing the aberrant epigenomes using inhibitory agents or by abrogating the upstream signaling pathways that convey the epigenomic perturbations, may be developed into promising treatment regimens.
ovarian cancer; epigenetics; DNA methylation; biomarkers; quantitative methylation-specific polymerase chain reaction