Quantitative DNA methylation analyses reveal stage dependent DNA methylation and association to clinico-pathological factors in breast tumors.

BACKGROUND: Aberrant DNA methylation of regulatory genes has frequently been found in human breast cancers and correlated to clinical outcome. In the present study we investigate stage specific changes in the DNA methylation patterns in order to identify valuable markers to understand how these changes affect breast cancer progression. METHODS: Quantitative DNA methylation analyses of 12 candidate genes ABCB1, BRCCA1, CDKN2A, ESR1, GSTP1, IGF2, MGMT, HMLH1, PPP2R2B, PTEN, RASSF1A and FOXC1 was performed by pyrosequencing a series of 238 breast cancer tissue samples from DCIS to invasive tumors stage I to IV. RESULTS: Significant differences in methylation levels between the DCIS and invasive stage II tumors were observed for six genes RASSF1A, CDKN2A, MGMT, ABCB1, GSTP1 and FOXC1. RASSF1A, ABCB1 and GSTP1 showed significantly higher methylation levels in late stage compared to the early stage breast carcinoma. Z-score analysis revealed significantly lower methylation levels in DCIS and stage I tumors compared with stage II, III and IV tumors. Methylation levels of PTEN, PPP2R2B, FOXC1, ABCB1 and BRCA1 were lower in tumors harboring TP53 mutations then in tumors with wild type TP53. Z-score analysis showed that TP53 mutated tumors had significantly lower overall methylation levels compared to tumors with wild type TP53. Methylation levels of RASSF1A, PPP2R2B, GSTP1 and FOXC1 were higher in ER positive vs. ER negative tumors and methylation levels of PTEN and CDKN2A were higher in HER2 positive vs. HER2 negative tumors. Z-score analysis also showed that HER2 positive tumors had significantly higher z-scores of methylation compared to the HER2 negative tumors. Univariate survival analysis identifies methylation status of PPP2R2B as significant predictor of overall survival and breast cancer specific survival. CONCLUSIONS: In the present study we report that the level of aberrant DNA methylation is higher in late stage compared with early stage of invasive breast cancers and DCIS for genes mentioned above.

DNA methylation profiling in doxorubicin treated primary locally advanced breast tumours identifies novel genes associated with survival and treatment response.

BACKGROUND: Breast cancer is the most frequent cancer in women and consists of a heterogeneous collection of diseases with distinct histopathological, genetic and epigenetic characteristics. In this study, we aimed to identify DNA methylation based biomarkers to distinguish patients with locally advanced breast cancer who may benefit from neoadjuvant doxorubicin treatment. RESULTS: We investigated quantitatively the methylation patterns in the promoter regions of 14 genes (ABCB1, ATM, BRCA1, CDH3, CDKN2A, CXCR4, ESR1, FBXW7, FOXC1, GSTP1, IGF2, HMLH1, PPP2R2B, and PTEN) in 75 well-described pre-treatment samples from locally advanced breast cancer and correlated the results to the available clinical and molecular parameters. Six normal breast tissues were used as controls and 163 unselected breast cancer cases were used to validate associations with histopathological and clinical parameters.Aberrant methylation was detected in 9 out of the 14 genes including the discovery of methylation at the FOXC1 promoter. Absence of methylation at the ABCB1 promoter correlated with progressive disease during doxorubicin treatment. Most importantly, the DNA methylation status at the promoters of GSTP1, FOXC1 and ABCB1 correlated with survival, whereby the combination of methylated genes improved the subdivision with respect to the survival of the patients. In multivariate analysis GSTP1 and FOXC1 methylation status proved to be independent prognostic markers associated with survival. CONCLUSIONS: Quantitative DNA methylation profiling is a powerful tool to identify molecular changes associated with specific phenotypes. Methylation at the ABCB1 or GSTP1 promoter improved overall survival probably due to prolonged availability and activity of the drug in the cell while FOXC1 methylation might be a protective factor against tumour invasiveness. FOXC1 proved to be general prognostic factor, while ABCB1 and GSTP1 might be predictive factors for the response to and efficacy of doxorubicin treatment. Pharmacoepigenetic effects such as the reported associations in this study provide molecular explanations for differential responses to chemotherapy and it might prove valuable to take the methylation status of selected genes into account for patient management and treatment decisions.

Identification and quantification of differentially methylated loci by the pyrosequencing technology.

Most available protocols for gene-specific DNA methylation analysis are either labor intensive, not quantitative, or limited to the measurement of the methylation status of only one or very few CpG positions. Pyrosequencing is a real-time sequencing technology that overcomes these limitations. After bisulfite modification of genomic DNA, a region of interest is amplified by polymerase chain reaction (PCR) with one of the two primers being biotinylated. The PCR-generated template is rendered single stranded and a pyrosequencing primer is annealed to analyze quantitatively CpGs within 120 bases. Advantages of the pyrosequencing technology are the ease of its implementation, the high quality and the quantitative nature of the results, and its ability to identify differentially methylated positions in close proximity. A minimum amount of 10 ng of bisulfite-treated DNA is necessary to obtain high reproducibility and avoid random amplification. The required DNA amount can be provided by an individual sample or a pool of samples to rapidly investigate the presence of variable DNA methylation patterns. The use of pools and serial pyrosequencing, that is, the successive use of several pyrosequencing primers on the same DNA template, significantly reduces cost, labor, and analysis time as well as saving precious DNA samples for the analysis of gene-specific DNA methylation patterns.

Quantitative DNA Methylation Analysis at Single-Nucleotide Resolution by Pyrosequencing®.

Many protocols for gene-specific DNA methylation analysis are either labor intensive, not quantitative and/or limited to the measurement of the methylation status of only one or very few CpG positions. Pyrosequencing is a real-time sequencing technology that overcomes these limitations. After bisulfite modification of genomic DNA, a region of interest is amplified by PCR with one of the two primers being biotinylated. The PCR generated template is rendered single-stranded and a pyrosequencing primer is annealed to analyze quantitatively cytosine methylation. In comparative studies, pyrosequencing has been shown to be among the most accurate and reproducible technologies for locus-specific DNA methylation analyses and has become a widely used tool for the validation of DNA methylation changes identified in genome-wide studies as well as for locus-specific analyses with clinical impact such as methylation analysis of the MGMT promoter. Advantages of the Pyrosequencing technology are the ease of its implementation, the high quality and the quantitative nature of the results, and its ability to identify differentially methylated positions in close proximity.

Rapid identification of promoter hypermethylation in hepatocellular carcinoma by pyrosequencing of etiologically homogeneous sample pools.

Aberrant DNA methylation patterns have been identified in a variety of human diseases, particularly cancer. Pyrosequencing has evolved in recent years as a sensitive and accurate method for the analysis and quantification of the degree of DNA methylation in specific target regions. However, the number of candidate genes that can be analyzed in clinical specimens is often restricted by the limited amount of sample available. Here, we present a novel screening approach that enables the rapid identification of differentially methylated regions such as promoters by pyrosequencing of etiologically homogeneous sample pools after bisulfite treatment. We exemplify its use by the analysis of five genes (CDKN2A, GSTP1, MLH1, IGF2, and CTNNB1) involved in the pathogenesis of human hepatocellular carcinoma using pools stratified for different parameters of clinical importance. Results were confirmed by the individual analysis of the samples. The screening identified all genes displaying differential methylation successfully, and no false positives occurred. Quantitative comparison of the pools and the samples in the pool analyzed individually showed a deviation of approximately 1.5%, making the method ideally suited for the identification of diagnostic markers based on DNA methylation while saving precious DNA material.

DNA methylation profiles distinguish different subtypes of gastroenteropancreatic neuroendocrine tumors.

AIM: Most studies have considered gastroenteropancreatic neuroendocrine tumors (GEP-NETs) as a homogenous group of samples or distinguish only gastrointestinal from pancreatic endocrine tumors. This article investigates if DNA methylation patterns could distinguish subtypes of GEP-NETs. MATERIALS & METHODS: The DNA methylation level of 807 cancer-related genes was investigated in insulinomas, gastrinomas, non-functioning pancreatic endocrine tumors and small intestine endocrine tumors. RESULTS: DNA methylation patterns were found to be tumor type specific for each of the pancreatic tumor subtypes and identified two distinct methylation-based groups in small intestine endocrine tumors. Differences of DNA methylation levels were validated by pyrosequencing for 20 candidate genes and correlated with differences at the transcriptional level for four candidate genes. CONCLUSION: The heterogeneity of DNA methylation patterns in the different subtypes of gastroenteropancreatic neuroendocrine tumors suggests different underlying pathways and, therefore, these tumors should be considered as distinct entities in molecular and clinical studies.

Hypermethylation of the IGF2 differentially methylated region 2 is a specific event in insulinomas leading to loss-of-imprinting and overexpression.

Prediction of the evolution of endocrine pancreatic tumors remains difficult based on histological criteria alone. We have previously demonstrated that epigenetic changes are an early event in a mouse model developing insulinomas. Particularly, overexpression of the imprinted IGF2 was caused by the hypermethylation of CpGs in the differentially methylated region 2 (DMR2). Here, we investigated whether IGF2 hypermethylation is also observed in human insulinomas and whether this alteration is common to other human endocrine tumors of the pancreas and the digestive tract. We analyzed the methylation status of 40 CpGs located in the DMR0 and DMR2 of the IGF2 as well as in the H19 DMR by pyrosequencing in a cohort of 62 patients with pancreatic or small intestine endocrine tumors. Altered methylation patterns were observed in all tumor types for the different regions of IGF2, but not for H19. However, hypermethylation of the IGF2 DMR2 was specific for insulinomas and did not occur in any of the other types of tumors which were characterized by a loss of methylation in this region. Gain of methylation in the IGF2 DMR2 in insulinomas correlated with loss-of-imprinting and promoter 4 mediated overexpression of IGF2 at the RNA and protein level. Furthermore, a decreasing degree of methylation in the different regions of IGF2 correlated well with increasing degree of malignancy according to the WHO classification of pancreatic endocrine tumors (PETs), suggesting that methylation of IGF2 might be a useful biomarker for classification and staging of PETs.

Data integration from two microarray platforms identifies bi-allelic genetic inactivation of RIC8A in a breast cancer cell line.

BACKGROUND: Using array comparative genomic hybridization (aCGH), a large number of deleted genomic regions have been identified in human cancers. However, subsequent efforts to identify target genes selected for inactivation in these regions have often been challenging. METHODS: We integrated here genome-wide copy number data with gene expression data and non-sense mediated mRNA decay rates in breast cancer cell lines to prioritize gene candidates that are likely to be tumour suppressor genes inactivated by bi-allelic genetic events. The candidates were sequenced to identify potential mutations. RESULTS: This integrated genomic approach led to the identification of RIC8A at 11p15 as a putative candidate target gene for the genomic deletion in the ZR-75-1 breast cancer cell line. We identified a truncating mutation in this cell line, leading to loss of expression and rapid decay of the transcript. We screened 127 breast cancers for RIC8A mutations, but did not find any pathogenic mutations. No promoter hypermethylation in these tumours was detected either. However, analysis of gene expression data from breast tumours identified a small group of aggressive tumours that displayed low levels of RIC8A transcripts. qRT-PCR analysis of 38 breast tumours showed a strong association between low RIC8A expression and the presence of TP53 mutations (P = 0.006). CONCLUSION: We demonstrate a data integration strategy leading to the identification of RIC8A as a gene undergoing a classical double-hit genetic inactivation in a breast cancer cell line, as well as in vivo evidence of loss of RIC8A expression in a subgroup of aggressive TP53 mutant breast cancers.