Sodium Bisulfite Conversion Research Articles

Hypermethylation and low expression of FOXM1 predisposes women to unexplained recurrent miscarriage by impairing trophoblast stem cell proliferation

Recurrent miscarriage (RM) is a distressing pregnancy complication with an unknown etiology. Increasing evidence indicates the relevance of dysregulation of human trophoblast stem cells (hTSCs), which may play a role in the development of RM. However, the potential molecular regulatory mechanism underlying the initiation and maintenance of hTSCs is yet to be fully elucidated. In this study, we performed data analysis and identified Forkhead box M1 (FOXM1) as a potential factor associated with RM. FOXM1 is a typical transcription factor known for its involvement in various pathophysiological processes, while the precise function of FOXM1 functions in hTSCs and RM remains incompletely understood. Utilizing RNA-seq, CUT&Tag, ChIP-qPCR, and sodium bisulfite conversion methods for methylation analysis, we elucidate the underlying regulatory mechanisms of FOXM1 in hTSCs and its implications in RM. Our findings demonstrate the relative high expression of FOXM1 in proliferating cytotrophoblasts (CTBs) compared to differentiated extravillous cytotrophoblasts (EVTs) and syncytiotrophoblasts (STBs). Besides, we provide evidence supporting a significant correlation between FOXM1 downregulation and the incidence of RM. Furthermore, we demonstrate the significant role of FOXM1 in regulating hTSCs proliferation and cell cycle through the transcriptional regulation of CDKN3, CCNB2, CCNA2, MAD2L1 and CDC25C. Notably, we observed a correlation between the downregulation of FOXM1 in RM and hypermethylation in its promoter region. Collectively, these results provide insights into the impact of FOXM1 on trophoblast regulation and offer a novel perspective on RM.

Abstract 7022: Whole genome and reduced representation enzymatic methyl-seq enable cost effective methylomes

Abstract DNA methylation is an epigenetic regulator of gene expression with important functions in development and diseases such as cancer. Traditionally, sodium bisulfite conversion was used to distinguish 5-methylcytosines (5mC) and 5-hydroxymethylcytosines (5hmC) from cytosines. However, this method damages DNA and introduces significant sequencing bias. NEBNext® Enzymatic Methyl-seq (EM-seq™) is an enzymatic conversion approach that minimizes DNA damage therefore enabling longer insert sizes, lower duplication rates and a more accurate quantification of methylation in DNA samples with inputs ranging from 10 ng to 200 ng. An improved enzymatic conversion method, EM-seq v2, has a more streamlined workflow and an expanded DNA input range of 100 pg to 200 ng. Libraries made using NA12878 genomic DNA show improved yields, consistent global methylation and an even GC bias representation. The increased library yields subsequently reduces sequencing duplications and costs. Sequencing costs are an important consideration when performing whole genome methylome analysis as this often needs high sequencing depth to attain meaningful coverage to accurately call methylation. Reduced representation libraries, a commonly used method to investigate DNA methylation, relies on enrichment of CpGs within libraries digested using MspI. These CpGs are commonly found in regulatory regions. Although lacking comprehensive CpG coverage, for many researchers this method provides enough cost effective CpG methylation coverage for their studies. Reduced Representation EM-seq libraries (RREM-seq) and Reduced Representation Bisulfite libraries (RRBS) were made using 200 ng to 100 pg of NA12878 DNA. EM-seq adaptors were ligated to MspI digested DNA followed by conversion using either EM-seq v2 or sodium bisulfite. Libraries were PCR amplified and sequenced on an Illumina NovaSeq platform. RREM-seq resulted in higher yields and reproducible results regardless of input amounts compared to RRBS libraries. RREM-seq libraries also identified a higher number of CpGs with even coverage facilitating accurate methylation calling. RREM-seq libraries have superior sequencing metrics resulting in robust methylation profiling. Focusing on a subset of the genome generates higher coverage DNA methylation data at a lower DNA sequencing cost. Citation Format: Vaishnavi Panchapakesa, Chaithanya Ponnaluri, Daniel Evanich, Ariel Erijman, Bradley Langhorst, Louise Williams. Whole genome and reduced representation enzymatic methyl-seq enable cost effective methylomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7022.

Molecular monitoring by CDKN2A/p16INK4A and RB1 gene methylation in breast cancer.

This prospective study aimed to provide a comprehensive analysis of the methylation status of two pivotal genes, CDKN2A/p16INK4A (cyclin-dependent kinase inhibitor 2A) and RB1 (retinoblastoma transcriptional corepressor 1), in breast cancer patients. Samples were obtained from 15 women diagnosed with breast cancer and who underwent a total mastectomy. DNA was extracted from the tumor, non-tumor tissue, and peripheral blood (circulating cell-free DNA). The methylation pattern of cell-free DNA extracted from blood collected on the day of mastectomy was compared with the methylation pattern of cell-free DNA from blood collected 1 year post-surgery. The methylation analysis was carried out by sodium bisulfite conversion and polymerase chain reaction, followed by electrophoresis. Methylation of CDKN2A/p16INK4A was identified in 13 tumor samples and 12 non-tumor tissue samples. Two patients exhibited CDKN2A/p16INK4A methylation in the cell-free DNA of the first blood collection, while another showed methylation only in the cell-free DNA of the subsequent blood collection. Regarding RB1, 11 tumors and 8 non-tumor tissue samples presented methylation of the gene. This study presents a novel approach for monitoring breast cancer patients through the analysis of cell-free DNA methylation. This analysis can detect changes in methylation patterns before any visible sign of cancer appears in breast tissue and could help predict the recurrence of malignant breast tumors.

HTERT gene methylation in circulating DNA, tumor, and surrounding tissue in breast cancer: a prospective study.

The human telomerase reverse transcriptase (hTERT) enzyme, encoded by the hTERT gene, synthesizes protective telomeric sequences on chromosomes and plays a fundamental role in cancer formation. Methylation of the hTERT gene has an upregulatory effect, increasing hTERT enzyme synthesis and allowing continuous tumor cell division. In a group of patients with breast cancer, we aimed to analyze the methylation status of hTERT in the tumor, surrounding tissue, and circulating free deoxyribonucleic acid (cfDNA) of blood collected on the day of mastectomy and then approximately one year later. A prospective study was conducted at a university hospital in Rio de Janeiro, Brazil. Samples were collected from 15 women with breast cancer on the day of mastectomy and approximately one year postoperatively. cfDNA was analyzed by sodium bisulfite conversion, followed by polymerase chain reaction, electrophoresis, and silver nitrate staining. Methylation of hTERT was detected in the tumors and surrounding tissues of all 15 patients. Five patients displayed hTERT methylation in the cfDNA from the blood of the first collection. Of the ten patients who returned for the second collection, three showed methylation. Two patients with methylation in the first collection did not display methylation in the second collection. One patient with no methylation in the first collection displayed methylation in the second collection, and one patient had a diminished level of methylation in the second collection. Only one-third of patients displayed methylation in their cfDNA, which may be related to the success of chemotherapy.

A rotationally-driven dynamic solid phase sodium bisulfite conversion disc for forensic epigenetic sample preparation.

The approaches to forensic human identification (HID) are largely comparative in nature, relying upon the comparison of short tandem repeat profiles to known reference materials and/or database profiles. However, many profiles are generated from evidence materials that either do not have a reference material for comparison or do not produce a database hit. As an alternative to individualizing analysis for HID, researchers of forensic DNA have demonstrated that the human epigenome can provide a wealth of information. However, epigenetic analysis requires sodium b̲is̲ulfite c̲onversion (BSC), a sample preparation method that is time-consuming, labor-intensive, prone to contamination, and characterized by DNA loss and fragmentation. To provide an alternative method for BSC that is more amenable to integration with the forensic DNA workflow, we describe a rotationally-driven, microfluidic method for dynamic solid phase-BSC (dSP-BSC) that streamlines the sample preparation process in an automated format, capable of preparing up to four samples in parallel. The method permitted decreased incubation intervals by ∼36% and was assessed for relative DNA recovery and conversion efficiency and compared to gold-standard and enzymatic approaches.

Abstract 6018: Sequencing of 5-hydroxymethylcytosine to single base resolution

Abstract DNA methylation is an epigenetic regulator of gene expression with important functions in development and diseases such as cancer. The modified cytosines, 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) are identified using Illumina sequencing. Libraries are generated using either NEBNext® EM-seq™, an enzyme-based workflow, or by using sodium bisulfite conversion. These methods, however, cannot differentiate between 5mC and 5hmC. Distinguishing these modifications is important as there is increased interest in 5hmCs role in regulating gene expression. Methods currently exist to enable discrimination of 5mC and 5hmC, for example, oxBS-seq and TAB-seq. These methods still rely upon sodium bisulfite conversion and have reduced data quality due to fragmentation and loss of DNA. Here we describe an enzymatic method that enables specific detection of 5hmC. 5hmC is detected using two enzymatic steps. Firstly, 5hmCs are glucosylated, which protects them from subsequent deamination by APOBEC. In contrast, cytosines and 5mCs are deaminated resulting in their conversion to uracil and thymine, respectively. During Illumina sequencing deaminated cytosine and 5mC are read as thymine and the glucosylated 5hmC are read as cytosine. Subtractive analysis of 5hmC data from EM-seq data, which detects both 5mC and 5hmC, permits the identification of individual 5mC and 5hmC sites. 5hmC data were generated for inputs of 0.1 ng to 200 ng DNA isolated from E14 mouse embryonic stem cells and human brain. The 5hmC libraries had similar characteristics to EM-seq libraries, including expected insert sizes due to intact DNA molecules, low duplication rates and minimal GC bias. T4147 phage DNA was used as an internal control, as all cytosines are 5-hydroxymethylated, with 98-99% of cytosines identified as 5hmC. 5mC and 5hmC levels were also profiled during E14 cell differentiation for 10 days. Interestingly, 5hmC levels decreased whereas 5mC levels increased particularly during the first five days of differentiation. LC-MS/MS quantification of this same DNA mirrored the changes observed by sequencing. The ability to discriminate between 5mC and 5hmC will provide key insights into the role of these cytosine modifications in development and disease. Citation Format: Daniel J. Evanich, V. K. Chaithanya Ponnaluri, Vaishnavi Panchapakesa, Ariel Erijman, Matthew A. Campbell, Nan Dai, Bradley W. Langhorst, Romualdas Vaisvila, Louise Williams. Sequencing of 5-hydroxymethylcytosine to single base resolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6018.

Abstract 2290: DNA methylation markers for sensitive detection of circulating tumor DNA in plasma from patients with gastroesophageal adenocarcinomas

Abstract Background: We have previously shown that detection of methylated ctDNA in the three genes c9orf50, KCNQ5, and CLIP4 is a highly sensitive method (named the TriMeth assay) to discriminate patients with colorectal cancer from healthy individuals (1). The publicly available Infinium HumanMethylation450K BreadChip DNA methylation array indicates that these three markers are also highly methylated in gastric and esophageal cancer. In this study, we investigate the ability of the TriMeth assay to detect ctDNA in patients with gastric and gastroesophageal junction (GEJ) adenocarcinomas. Methods: Purified DNA was extracted from tumor tissue and plasma from 63 patients with gastric/GEJ adenocarcinomas. Sodium bisulfite conversion was performed to distinguish methylated from unmethylated cytosines. Droplet digital PCR (ddPCR) with methylation-specific primers and probes was performed to detect hypermethylated sites in the three genes c9orf50, KCNQ5, and CLIP4. The TriMeth assay was considered positive if at least two out of three markers were methylated according to a predefined cut-off. Eleven plasma samples from healthy individuals were used as negative controls.Results: In tumor tissue, methylated copies were detected in all 29 surgical samples (100% sensitivity), with varying allele frequencies. In plasma, methylated copies were detected in 14 out of 18 samples (78% sensitivity) from patients with advanced disease, with varying sensitivity amongst the three markers (AUC for the three markers CLIP4, C9orf50, and KCNQ5 was 0.61, 0.86, and 0.94, respectively). In plasma from patients with resectable disease, methylated copies were detected in 10 of 17 samples (59% sensitivity), although only 7/17 (41% sensitivity) were positive according to the predefined cut-off. All 11 controls were negative for methylation signals (100% specificity). Conclusion and Further Perspectives: Using a pre-defined cut-off value, the TriMeth assay detected methylated DNA in all tumor samples. The sensitivity of the TriMeth assay in plasma was 78% in advanced disease and 41% in resectable disease. Further investigations of the TriMeth assay in patients with resectable gastric and GEJ adenocarcinomas are needed. We plan to validate the sensitivity of the TriMeth assay for treatment monitoring and detection of residual disease.

On the prediction of non-CG DNA methylation using machine learning.

DNA methylation can be detected and measured using sequencing instruments after sodium bisulfite conversion, but experiments can be expensive for large eukaryotic genomes. Sequencing nonuniformity and mapping biases can leave parts of the genome with low or no coverage, thus hampering the ability of obtaining DNA methylation levels for all cytosines. To address these limitations, several computational methods have been proposed that can predict DNA methylation from the DNA sequence around the cytosine or from the methylation level of nearby cytosines. However, most of these methods are entirely focused on CG methylation in humans and other mammals. In this work, we study, for the first time, the problem of predicting cytosine methylation for CG, CHG and CHH contexts on six plant species, either from the DNA primary sequence around the cytosine or from the methylation levels of neighboring cytosines. In this framework, we also study the cross-species prediction problem and the cross-context prediction problem (within the same species). Finally, we show that providing gene and repeat annotations allows existing classifiers to significantly improve their prediction accuracy. We introduce a new classifier called AMPS (annotation-based methylation prediction from sequence)that takes advantage of genomicannotations to achieve higher accuracy.

Assessment of Promoter hypermethylation of APC and BRCA1 in endometrial cancer.

Introduction: Endometrial cancer is one of the most common cancers in women worldwide. Theunderlying cause of endometrial tumorigenesis remains elusive. Several genetic and epigeneticalterations are known to be involved in the carcinogenesis of endometrial carcinoma. One importantand early epigenetic alteration that is attributed to endometrial carcinoma is the aberrant promoterhypermethylation of gene promoters. In this study, we have assessed the aberrant promoterhypermethylation of APC and BRCA1 in 78 endometrial cancer samples. Methods: Histologicallyconfirmed tumour tissue samples were obtained post-surgery and DNA was extracted. The DNA wassubjected to sodium bisulfite conversion and used as a template for a polymerase chain reaction.The PCR was performed using a nested PCR followed by methylation specific PCR. Results: A33.33% and 46.15% methylation frequency was observed for APC and BRCA1 genes respectively. Ahigher percentage of methylation was observed in stage IV for APC (66.66%) and in stage II forBRCA1 (88.88%). Conclusion: Aberrant promoter hypermethylation is an early event inendometrial carcinoma and can serve as a useful molecular marker for diagnosis and prognosis ofthe disease along with existing screening modalities.

DNA Methylation in Solid Tumors: Functions and Methods of Detection

DNA methylation, i.e., addition of methyl group to 5′-carbon of cytosine residues in CpG dinucleotides, is an important epigenetic modification regulating gene expression, and thus implied in many cellular processes. Deregulation of DNA methylation is strongly associated with onset of various diseases, including cancer. Here, we review how DNA methylation affects carcinogenesis process and give examples of solid tumors where aberrant DNA methylation is often present. We explain principles of methods developed for DNA methylation analysis at both single gene and whole genome level, based on (i) sodium bisulfite conversion, (ii) methylation-sensitive restriction enzymes, and (iii) interactions of 5-methylcytosine (5mC) with methyl-binding proteins or antibodies against 5mC. In addition to standard methods, we describe recent advances in next generation sequencing technologies applied to DNA methylation analysis, as well as in development of biosensors that represent their cheaper and faster alternatives. Most importantly, we highlight not only advantages, but also disadvantages and challenges of each method.

Quantification of DNA methylation independent of sodium bisulfite conversion using methylation-sensitive restriction enzymes and digital PCR.

Epigenetic regulation is important in human health and disease, but the exact mechanisms remain largely enigmatic. DNA methylation represents one epigenetic aspect but is challenging to quantify. In this study, we introduce a digital approach for the quantification of the amount and density of DNA methylation. We designed an experimental setup combining efficient methylation‐sensitive restriction enzymes with digital polymerase chain reaction (PCR) to quantify a targeted density of DNA methylation independent of bisulfite conversion. By using a stable reference and comparing experiments treated and untreated with these enzymes, copy number instability could be properly normalized. In silico simulations demonstrated the mathematical validity of the setup and showed that the measurement precision depends on the amount of input DNA and the fraction methylated alleles. This uncertainty could be successfully estimated by the confidence intervals. Quantification of RASSF1 promoter methylation in a variety of healthy and malignant samples and in a calibration curve confirmed the high accuracy of our approach, even in minute amounts of DNA. Overall, our results indicate the possibility of quantifying DNA methylation with digital PCR, independent of bisulfite conversion. Moreover, as the context‐density of methylation can also be determined, biological mechanisms can now be quantitatively assessed.

CpGtools: a python package for DNA methylation analysis.

DNA methylation can be measured at the single CpG level using sodium bisulfite conversion of genomic DNA followed by sequencing or array hybridization. Many analytic tools have been developed, yet there is still a high demand for a comprehensive and multifaceted tool suite to analyze, annotate, QC and visualize the DNA methylation data. We developed the CpGtools package to analyze DNA methylation data generated from bisulfite sequencing or Illumina methylation arrays. The CpGtools package consists of three types of modules: (i) 'CpG position modules' focus on analyzing the genomic positions of CpGs, including associating other genomic and epigenomic features to a given list of CpGs and generating the DNA motif logo enriched in the genomic contexts of a given list of CpGs; (ii) 'CpG signal modules' are designed to analyze DNA methylation values, such as performing the PCA or t-SNE analyses, using Bayesian Gaussian mixture modeling to classify CpG sites into fully methylated, partially methylated and unmethylated groups, profiling the average DNA methylation level over user-specified genomics regions and generating the bean/violin plots and (iii) 'differential CpG analysis modules' focus on identifying differentially methylated CpGs between groups using different statistical methods including Fisher's Exact Test, Student's t-test, ANOVA, non-parametric tests, linear regression, logistic regression, beta-binomial regression and Bayesian estimation. CpGtools is written in Python under the open-source GPL license. The source code and documentation are freely available at https://github.com/liguowang/cpgtools. Supplementary data are available at Bioinformatics online.

MethylToSNP: identifying SNPs in Illumina DNA methylation array data

BackgroundCurrent array-based methods for the measurement of DNA methylation rely on the process of sodium bisulfite conversion to differentiate between methylated and unmethylated cytosine bases in DNA. In the absence of genotype data this process can lead to ambiguity in data interpretation when a sample has polymorphisms at a methylation probe site. A common way to minimize this problem is to exclude such potentially problematic sites, with some methods removing as much as 60% of array probes from consideration before data analysis.ResultsHere, we present an algorithm implemented in an R Bioconductor package, MethylToSNP, which detects a characteristic data pattern to infer sites likely to be confounded by polymorphisms. Additionally, the tool provides a stringent reliability score to allow thresholding on SNP predictions. We calibrated parameters and thresholds used by the algorithm on simulated and real methylation data sets. We illustrate findings using methylation data from YRI (Yoruba in Ibadan, Nigeria), CEPH (European descent) and KhoeSan (southern African) populations. Our polymorphism predictions made using MethylToSNP have been validated through SNP databases and bisulfite and genomic sequencing.ConclusionsThe benefits of this method are threefold. First, it prevents extensive data loss by considering only SNPs specific to the individuals in the study. Second, it offers the possibility to identify new polymorphisms in samples for which there is little known about the genetic landscape. Third, it identifies variants as they exist in functional regions of a genome, such as in CTCF (transcriptional repressor) sites and enhancers, that may be common alleles or personal mutations with potential to deleteriously affect genomic regulatory activities. We demonstrate that MethylToSNP is applicable to the Illumina 450K and Illumina 850K EPIC array data and is also backwards compatible to the 27K methylation arrays. Going forward, this kind of nuanced approach can increase the amount of information derived from precious data sets by considering samples of the project individually to enable more informed decisions about data cleaning.

Abstract 3655: DNA methylation analysis in liquid biopsy: A detailed study on quality control, sample storage and whole genome amplification procedures for downstream applications

Abstract Background: Studies on epigenetic alterations and especially DNA methylation in liquid biopsy samples like plasma circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs) are of growing interest nowadays. To ensure the reliability of DNA methylation results prior to any clinical applications in liquid biopsy, there is an urgent need to standardize a plethora of parameters. The aim of our study was to evaluate: a) the stability of DNA methylation in plasma, b) the stability of sodium bisulfite (SB) converted DNA samples under different storage temperatures, and c) the accuracy and precision of whole genome amplification (WGA) protocols for downstream DNA methylation analysis. Methods: a) Stability of DNA methylation in plasma: Plasma from healthy donors was pooled and aliquoted in six tubes and spiked with genomic DNA (gDNA) isolated from 106 MCF-7 cells. Five aliquots were kept at -700C, while one was immediately processed for ctDNA isolation and SB treatment. Stored aliquots were processed in the same way after storage for a period of 3 months. All SB-treated DNA samples were further evaluated by real time methylation specific PCR (MSP) for ACTB and SOX17. b) Stability of SB-treated DNA: gDNA was isolated from 106 SKBR3 cells and processed for downstream SB-treatment. SB-treated DNA was split into aliquots and stored at -20°C and -70°C. One aliquot, used as control, was immediately processed for SB treatment followed by real time MSP for ACTB and BRMS1 amplification. The remaining aliquots were processed in exactly the same way after storage for different time points with a maximum period of one year. Additionally, a sample that was subjected to repeated freeze-thaw cycles was added in each run. c) Evaluation of WGA for SB-treated DNA: we evaluated two different SB conversion kits, EZ DNA Methylation-Gold (Zymo), and Epitect Fast Bisulfite, (Qiagen) in combination with downstream WGA (EpiTect Whole Bisulfitome Kit, Qiagen), using 0%, 100% methylated DNA standards and MCF-7, SKBR3 cell lines. Results: a) DNA methylation in plasma is stable at -700C for at least 3 months, since the average Cqs detected, varied from 1 to 2 cycles for ACTB and SOX17, respectively, b) Quality of SB-treated DNA is not affected by repeated freezing-thawing cycles; SB-treated DNA samples are stable when kept for up to one year both at -200C and -700C. c) Identical results by real time MSP were obtained before and after WGA amplification (Qiagen), after using either the Zymo or Qiagen kits for SB conversion. Conclusions: Plasma and SB-treated DNA samples are stable and can be safely used for multiple real time MSP assays over time when kept at -70°C. Downstream WGA of SB-treated DNA could bypass the limited amount of available sample for liquid biopsy applications. In any case, quality control checking should be included in each step of analysis. Citation Format: Sofia Mastoraki, Maria Chimonidou, Eleni Tzanikou, Evi S. Lianidou. DNA methylation analysis in liquid biopsy: A detailed study on quality control, sample storage and whole genome amplification procedures for downstream applications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3655.

Impact of Lactational Exposure to Polychlorinated Biphenyl Causes Epigenetic Modification and Impairs Sertoli Cells Functional Regulators in F1 Progeny

Polychlorinated biphenyl (PCB) is an endocrine-disrupting chemical. Sertoli cells (SCs) provide physical and nutritional support for developing germ cells. Dysfunction in SCs has adverse effects on spermatogenesis. Previously, we found that the lactational exposure of PCBs (1, 2, and 5 mg/kg birth weight/day, orally from postnatal days 1 to 20) decreased the follicle-stimulating hormone receptor (FSHR) and androgen receptor (AR) expression in SCs of F1 progeny. Transcription factors initiate and regulate the transcription of genes. DNA methylation plays an important role in epigenetic gene regulation. Hence, this study was aimed to identify the level of transcription factors regulating FSHR, AR gene expression, and DNA methylation in the promoter of these genes in SCs of both F1 prepuberal and puberal offspring. DNA methylation in the promoter of FSHR and AR genes was examined by sodium bisulfite conversion technique. The protein levels of transcription factors (steroidogenic factor 1 [SF1], upstream stimulatory factors 1 and 2, c-fos, c-jun, and CREB-binding protein) and enzymes DNA methyltransferases (Dnmt1, Dnmt3ab, Dnmt3l, and histone deacetylase 1 [HDAC1]) were analyzed by Western blotting. The transcription factors that regulate the FSHR and AR gene in SCs were decreased in both the PCB-exposed F1 progeny. Methylation was observed in the promoter of FSHR, AR, and SF1. The protein levels of Dnmt1, Dnmt3ab, Dnmt3l, and HDAC1 were increased in the PCBs-treated groups. Subsequently, it leads to transcriptional repression of the genes in SCs. Our finding suggests that PCBs caused epigenetic change in SCs, thereby it impaired SCs function in F1 progeny.

MethyLight and Digital MethyLight.

MethyLight is a quantitative, fluorescence-based, real-time PCR method to sensitively detect and quantify DNA methylation of candidate regions of the genome. MethyLight is uniquely suited for detecting low-frequency methylated DNA regions against a high background of unmethylated DNA, as it combines methylation-specific priming with methylation-specific fluorescent probing. The quantitative accuracy of real-time PCR and the ability to design bisulfite-dependent, DNA methylation-independent control reactions together allow for a quantitative assessment of these low frequency methylation events. Here we describe the experimental steps of MethyLight analysis in detail. Furthermore, we present principles and design examples for three types of quality control reactions. QC-1 reactions are methylation-independent reactions to monitor sample quantity and integrity. QC-2 reactions are bisulfite-independent reactions to monitor recovery efficiencies of the bisulfite conversion methodology used. QC-3 reactions are bisulfite-independently primed reactions with variable bisulfite-dependent probing to monitor completeness of the sodium bisulfite treatment. We show that these control reactions perform as expected in a time course experiment interrupting sodium bisulfite conversion at various timepoints. Finally, we describe Digital MethyLight, in which MethyLight is combined with Digital PCR, for the highly sensitive detection of individual methylated molecules, with use in disease detection and screening.

Methylation-Specific Multiplex Ligation-Dependent Probe Amplification (MS-MLPA).

This chapter describes a method for the rapid assessment of promoter hypermethylation levels or methylation of imprinted regions in human genomic DNA extracted from various sources using methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA). Multiplex ligation-dependent probe amplification (MLPA) is a powerful and easy-to-perform PCR-based technique that can identify gains, amplifications, losses, deletions, methylation and mutations of up to 55 targets in a single reaction, while requiring only minute quantities of DNA (about 50ng) extracted from blood, fresh frozen or formalin-fixed paraffin-embedded materials. Methylation-specific MLPA (MS-MLPA) is a variant of MLPA, which does not require sodium bisulfite conversion of unmethylated cytosine residues, but instead makes use of the methylation-sensitive endonuclease HhaI. MS-MLPA probes are designed to contain a HhaI recognition site (GCGC) and thus target one CpG dinucleotide within a CpG island. If the HhaI recognition site is not methylated, HhaI will cut the probe-sample DNA hybrid and no PCR product will be formed. If the target DNA is methylated, HhaI is not able to cut, and the fragment will be amplified during subsequent PCR. For data analysis, MS-MLPA peak patterns of the HhaI-treated and -untreated reactions are compared, leading to calculation of a methylation percentage. The methylation profile of a test sample is assessed by comparing the probe methylation percentages obtained on the test sample to the percentages of the reference samples. MS-MLPA can be combined with copy number and point mutation detection in the same reaction.

Promoter Hypermethylation of the ATM Gene as a Novel Biomarker for Breast Cancer

Background:Breast cancer may be induced by activation of protooncogenes to oncogenes and in many cases inactivation of tumor suppressor genes. Ataxia telangiectasia mutated (ATM) is an important tumor suppressor gene which plays central roles in the maintenance of genomic integrity by activating cell cycle checkpoints and promoting repair of double-strand breaks of DNA. In breast cancer, decrease ATM expression correlates with a poor outcome; however, the molecular mechanisms underlying downregulation are still unclear. Promoter hypermethylation may contribute in downregulation. Hence the present investigation was designed to evaluate promoter methylation and expression of the ATM gene in breast cancer cases, and to determine links with clinical and demographic manifestations, in a South Indian population.Methods:Tumor biopsy samples were collected from 50 pathologically confirmed sporadic breast cancer cases. DNA was isolated from tumor and adjacent non-tumorous regions, and sodium bisulfite conversion and methylation-specific PCR were performed using MS-PCR primers for the ATM promoter region. In addition, ATM mRNA expression was also analyzed for all samples using real-time PCR.Results:Fifty eight percent (58%) of cancer tissue samples showed promoter hypermethylation for the ATM gene, in contrast to only 4.44% of normal tissues (p= 0.0001). Furthermore, ATM promoter methylation was positively associated with age (p = 0.01), tumor size (p=0.045) and advanced stage of disease i.e. stages III and IV (p =0.019). An association between promoter hypermethylation and lower expression of ATM mRNA was also found (p=0.035).Conclusion:We report for the first time that promoter hypermethylation of ATM gene may be useful as a potential new biomarker for breast cancer, especially in the relatively young patients.

Illumina Sequencing of Bisulfite-Converted DNA Libraries.

Here we describe a standard MethylC-seq protocol using single-read sequencing on an Illumina Genome Analyzer II platform. The protocol involves ligation of methylated sequencing adaptors to sonicated genomic DNA, gel purification, sodium bisulfite conversion, polymerase chain reaction (PCR) amplification, and sequencing.

Detection and monitoring of hypermethylated RASSF1A in serum from patients with metastatic breast cancer.

BackgroundCirculating hypermethylated RASSF1A could be a novel and potential useful marker for monitoring patients with metastatic breast cancer. Technical obstacles include fragmentation of the circulating DNA, fluctuations in the concentration, low concentrations of circulating tumor DNA, and different locations of methylation in the RASSF1A gene among patients. One common method for detection of hypermethylated genes is sodium bisulfite conversion of non-methylated cytosine to uracil, followed by detection with PCR. However, the method relies on full conversion of all non-methylated cytosines, cause strand breaks, and loss of DNA. Alternatively, methylation-sensitive restriction enzymes have been used to digest genomic DNA, as well as sodium bisulfite-treated DNA. By flanking different regions of the RASSF1A with different PCR primer pairs, we analyzed for methylated genomic regions resistant to cleavage by the methylation-sensitive restriction enzymes HpaII and BstUI. The goal was to find region(s) in RASSF1A with high sensitivity and specificity that could be used for monitoring.ResultsThe serum was spiked with non-human control DNA. By tracing the spiking control, the isolation procedure of the rare circulating tumor DNA was initially optimized. By analysis of production of PCR amplicons from HpaII- or BstUI-treated DNA isolated from 24 patients with metastatic breast cancer, we located four regions resulting in sensitivities from 63 to 83 %. When examining samples from 24 control subjects, these four regions gave a specificity of 100 %. Among these four regions, the primer pair with the highest PCR efficacy was selected to monitor the RASSF1A concentration in 31 collected serum samples. The spiked DNA was then used to calculate the tumor RASSF1A concentrations independent of fluctuations in circulating non-tumor DNA. As a proof of principle, there was concordance in the kinetics of the RASSF1A and the serological cancer biomarkers CA 15-3, CEA, and TPA.ConclusionsMethylation-sensitive restriction enzymes may be a useful methodological approach for monitoring circulating hypermethylated RASSF1A among patients with metastatic breast cancer.