The integrative epigenomic-transcriptomic landscape of ER positive breast cancer

Background While recent integrative analyses of copy number and gene expression data in breast cancer have revealed a complex molecular landscape with multiple subtypes and many oncogenic/tumour suppressor driver events, much less is known about the role of DNA methylation in shaping breast cancer taxonomy and defining driver events. Results Here, we applied a powerful integrative network algorithm to matched DNA methylation and RNA-Seq data for 724 estrogen receptor (ER)-positive (ER+) breast cancers and 111 normal adjacent tissue specimens from The Cancer Genome Atlas (TCGA) project, in order to identify putative epigenetic driver events and to explore the resulting molecular taxonomy. This revealed the existence of nine functionally deregulated epigenetic hotspots encompassing a total of 146 genes, which we were able to validate in independent data sets encompassing over 1000 ER+ breast cancers. Integrative clustering of the matched messenger RNA (mRNA) and DNA methylation data over these genes resulted in only two clusters, which correlated very strongly with the luminal-A and luminal B subtypes. Overall, luminal-A and luminal-B breast cancers shared the same epigenetically deregulated hotspots but with luminal-B cancers exhibiting increased aberrant DNA methylation patterns relative to normal tissue. We show that increased levels of DNA methylation and mRNA expression deviation from the normal state define a marker of poor prognosis. Our data further implicates epigenetic silencing of WNT signalling antagonists and bone morphogenetic proteins (BMP) as key events underlying both luminal subtypes but specially of luminal-B breast cancer. Finally, we show that DNA methylation changes within the identified epigenetic interactome hotspots do not exhibit mutually exclusive patterns within the same cancer sample, instead exhibiting coordinated changes within the sample. Conclusions Our results indicate that the integrative DNA methylation and transcriptomic landscape of ER+ breast cancer is surprisingly homogeneous, defining two main subtypes which strongly correlate with luminal-A/B subtype status. In particular, we identify WNT and BMP signalling as key epigenetically deregulated tumour suppressor pathways in luminal ER+ breast cancer, with increased deregulation seen in luminal-B breast cancer

The influence of obesity on survival in early, high-risk breast cancer: results from the randomized SUCCESS A trial

Introduction: Obese breast cancer patients have worse prognosis than normal weight patients, but the level at which obesity is prognostically unfavorable is unclear. Methods: This retrospective analysis was performed using data from the SUCCESS A trial, in which 3754 patients with high-risk early breast cancer were randomized to anthracycline- and taxane-based chemotherapy with or without gemcitabine. Patients were classified as underweight/normal weight (body mass index (BMI) < 25.0), overweight (BMI 25.0–29.9), slightly obese (BMI 30.0–34.9), moderately obese (BMI 35.0–39.9) and severely obese (BMI ≥ 40.0), and the effect of BMI on disease-free survival (DFS) and overall survival (OS) was evaluated (median follow-up 65 months). In addition, subgroup analyses were conducted to assess the effect of BMI in luminal A-like, luminal B-like, HER2 (human epidermal growth factor 2)-positive and triple-negative tumors. Results: Multivariate analyses revealed an independent prognostic effect of BMI on DFS (p = 0.001) and OS (p = 0.005). Compared with underweight/normal weight patients, severely obese patients had worse DFS (hazard ratio (HR) 2.70, 95 % confidence interval (CI) 1.71–4.28, p < 0.001) and OS (HR 2.79, 95 % CI 1.63–4.77, p < 0.001), while moderately obese, slightly obese and overweight patients did not differ from underweight/normal weight patients with regard to DFS or OS. Subgroup analyses showed a similar significant effect of BMI on DFS and OS in patients with triple-negative breast cancer (TNBC), but not in patients with other tumor subtypes. Conclusions: Severe obesity (BMI ≥ 40) significantly worsens prognosis in early breast cancer patients, particularly for triple-negative tumors. Trial registration: Clinicaltrials.gov NCT02181101. Registered September 200

Gene promoter hypermethylation in ductal lavage fluid from healthy BRCA gene mutation carriers and mutation-negative controls

INTRODUCTION: Female germline BRCA gene mutation carriers are at increased risk for developing breast cancer. The purpose of our study was to establish whether healthy BRCA mutation carriers demonstrate an increased frequency of aberrant gene promoter hypermethylation in ductal lavage (DL) fluid, compared with predictive genetic test negative controls, that might serve as a surrogate marker of BRCA1/2 mutation status and/or breast cancer risk. METHODS: The pattern of CpG island hypermethylation within the promoter region of a panel of four genes (RAR-β, HIN-1, Twist and Cyclin D2) was assessed by methylation-specific polymerase chain reaction using free DNA extracted from DL fluid. RESULTS: Fifty-one DL samples from 24 healthy women of known BRCA mutation status (7 BRCA1 mutation carriers, 12 BRCA2 mutation carriers and 5 controls) were available for methylation analysis. Eight of 19 (42.1%) BRCA mutation carriers were found to have at least one hypermethylated gene in the four-gene panel. Two BRCA mutation carriers, in whom aberrant methylation was found, also had duct epithelial cell atypia identified. No hypermethylation was found in DL samples from 5 negative controls(p = 0.13). CONCLUSION: We found substantial levels of aberrant methylation, with the use of a four-gene panel, in the fluid from the breasts of healthy BRCA mutation carriers compared with controls. Methylation analysis of free DNA in DL fluid may offer a useful surrogate marker for BRCA1/2 mutation status and/or breast cancer risk. Further studies are required for the evaluation of the specificity and predictive value of aberrant methylation in DL fluid for future breast cancer development in BRCA1/2 mutation carriers

The influence of obesity on survival in early, high-risk breast cancer: results from the randomized SUCCESS A trial

Introduction Obese breast cancer patients have worse prognosis than normal weight patients, but the level at which obesity is prognostically unfavorable is unclear. Methods This retrospective analysis was performed using data from the SUCCESS A trial, in which 3754 patients with high-risk early breast cancer were randomized to anthracycline- and taxane-based chemotherapy with or without gemcitabine. Patients were classified as underweight/normal weight (body mass index (BMI) < 25.0), overweight (BMI 25.0–29.9), slightly obese (BMI 30.0–34.9), moderately obese (BMI 35.0–39.9) and severely obese (BMI ≥ 40.0), and the effect of BMI on disease-free survival (DFS) and overall survival (OS) was evaluated (median follow-up 65 months). In addition, subgroup analyses were conducted to assess the effect of BMI in luminal A-like, luminal B-like, HER2 (human epidermal growth factor 2)-positive and triple-negative tumors. Results Multivariate analyses revealed an independent prognostic effect of BMI on DFS (p = 0.001) and OS (p = 0.005). Compared with underweight/normal weight patients, severely obese patients had worse DFS (hazard ratio (HR) 2.70, 95 % confidence interval (CI) 1.71–4.28, p < 0.001) and OS (HR 2.79, 95 % CI 1.63–4.77, p < 0.001), while moderately obese, slightly obese and overweight patients did not differ from underweight/normal weight patients with regard to DFS or OS. Subgroup analyses showed a similar significant effect of BMI on DFS and OS in patients with triple-negative breast cancer (TNBC), but not in patients with other tumor subtypes. Conclusions Severe obesity (BMI ≥ 40) significantly worsens prognosis in early breast cancer patients, particularly for triple-negative tumors. Trial registration Clinicaltrials.gov NCT02181101. Registered September 2005

MMASS: an optimized array-based method for assessing CpG island methylation

We describe an optimized microarray method for identifying genome-wide CpG island methylation called microarray-based methylation assessment of single samples (MMASS) which directly compares methylated to unmethylated sequences within a single sample. To improve previous methods we used bioinformatic analysis to predict an optimized combination of methylation-sensitive enzymes that had the highest utility for CpG-island probes and different methods to produce unmethylated representations of test DNA for more sensitive detection of differential methylation by hybridization. Subtraction or methylation-dependent digestion with McrBC was used with optimized (MMASS-v2) or previously described (MMASS-v1, MMASS-sub) methylation-sensitive enzyme combinations and compared with a published McrBC method. Comparison was performed using DNA from the cell line HCT116. We show that the distribution of methylation microarray data is inherently skewed and requires exogenous spiked controls for normalization and that analysis of digestion of methylated and unmethylated control sequences together with linear fit models of replicate data showed superior statistical power for the MMASS-v2 method. Comparison with previous methylation data for HCT116 and validation of CpG islands from PXMP4, SFRP2, DCC, RARB and TSEN2 confirmed the accuracy of MMASS-v2 results. The MMASS-v2 method offers improved sensitivity and statistical power for high-throughput microarray identification of differential methylation

Genome-scale screen for DNA methylation-based detection markers for ovarian cancer.

The identification of sensitive biomarkers for the detection of ovarian cancer is of high clinical relevance for early detection and/or monitoring of disease recurrence. We developed a systematic multi-step biomarker discovery and verification strategy to identify candidate DNA methylation markers for the blood-based detection of ovarian cancer

hTERT promoter activity and CpG methylation in HPV-induced carcinogenesis

<p>Abstract</p> <p>Background</p> <p>Activation of telomerase resulting from deregulated hTERT expression is a key event during high-risk human papillomavirus (hrHPV)-induced cervical carcinogenesis. In the present study we examined hTERT promoter activity and its relation to DNA methylation as one of the potential mechanisms underlying deregulated hTERT transcription in hrHPV-transformed cells.</p> <p>Methods</p> <p>Using luciferase reporter assays we analyzed hTERT promoter activity in primary keratinocytes, HPV16- and HPV18-immortalized keratinocyte cell lines and cervical cancer cell lines. In the same cells as well as cervical specimens we determined hTERT methylation by bisulfite sequencing analysis of the region spanning -442 to +566 (relative to the ATG) and quantitative methylation specific PCR (qMSP) analysis of two regions flanking the hTERT core promoter.</p> <p>Results</p> <p>We found that in most telomerase positive cells increased hTERT core promoter activity coincided with increased hTERT mRNA expression. On the other hand basal hTERT promoter activity was also detected in telomerase negative cells with no or strongly reduced hTERT mRNA expression levels. In both telomerase positive and negative cells regulatory sequences flanking both ends of the core promoter markedly repressed exogenous promoter activity.</p> <p>By extensive bisulfite sequencing a strong increase in CpG methylation was detected in hTERT positive cells compared to cells with no or strongly reduced hTERT expression. Subsequent qMSP analysis of a larger set of cervical tissue specimens revealed methylation of both regions analyzed in 100% of cervical carcinomas and 38% of the high-grade precursor lesions, compared to 9% of low grade precursor lesions and 5% of normal controls.</p> <p>Conclusions</p> <p>Methylation of transcriptionally repressive sequences in the hTERT promoter and proximal exonic sequences is correlated to deregulated hTERT transcription in HPV-immortalized cells and cervical cancer cells. The detection of DNA methylation at these repressive regions may provide an attractive biomarker for early detection of cervical cancer.</p

Polycomb Target Genes Are Silenced in Multiple Myeloma

Multiple myeloma (MM) is a genetically heterogeneous disease, which to date remains fatal. Finding a common mechanism for initiation and progression of MM continues to be challenging. By means of integrative genomics, we identified an underexpressed gene signature in MM patient cells compared to normal counterpart plasma cells. This profile was enriched for previously defined H3K27-tri-methylated genes, targets of the Polycomb group (PcG) proteins in human embryonic fibroblasts. Additionally, the silenced gene signature was more pronounced in ISS stage III MM compared to stage I and II. Using chromatin immunoprecipitation (ChIP) assay on purified CD138+ cells from four MM patients and on two MM cell lines, we found enrichment of H3K27me3 at genes selected from the profile. As the data implied that the Polycomb-targeted gene profile would be highly relevant for pharmacological treatment of MM, we used two compounds to chemically revert the H3K27-tri-methylation mediated gene silencing. The S-adenosylhomocysteine hydrolase inhibitor 3-Deazaneplanocin (DZNep) and the histone deacetylase inhibitor LBH589 (Panobinostat), reactivated the expression of genes repressed by H3K27me3, depleted cells from the PRC2 component EZH2 and induced apoptosis in human MM cell lines. In the immunocompetent 5T33MM in vivo model for MM, treatment with LBH589 resulted in gene upregulation, reduced tumor load and increased overall survival. Taken together, our results reveal a common gene signature in MM, mediated by gene silencing via the Polycomb repressor complex. The importance of the underexpressed gene profile in MM tumor initiation and progression should be subjected to further studies

DNA Methylation in the Human Cerebral Cortex Is Dynamically Regulated throughout the Life Span and Involves Differentiated Neurons

The role of DNA cytosine methylation, an epigenetic regulator of chromatin structure and function, during normal and pathological brain development and aging remains unclear. Here, we examined by MethyLight PCR the DNA methylation status at 50 loci, encompassing primarily 5′ CpG islands of genes related to CNS growth and development, in temporal neocortex of 125 subjects ranging in age from 17 weeks of gestation to 104 years old. Two psychiatric disease cohorts—defined by chronic neurodegeneration (Alzheimer's) or lack thereof (schizophrenia)—were included. A robust and progressive rise in DNA methylation levels across the lifespan was observed for 8/50 loci (GABRA2, GAD1, HOXA1, NEUROD1, NEUROD2, PGR, STK11, SYK) typically in conjunction with declining levels of the corresponding mRNAs. Another 16 loci were defined by a sharp rise in DNA methylation levels within the first few months or years after birth. Disease-associated changes were limited to 2/50 loci in the Alzheimer's cohort, which appeared to reflect an acceleration of the age-related change in normal brain. Additionally, methylation studies on sorted nuclei provided evidence for bidirectional methylation events in cortical neurons during the transition from childhood to advanced age, as reflected by significant increases at 3, and a decrease at 1 of 10 loci. Furthermore, the DNMT3a de novo DNA methyl-transferase was expressed across all ages, including a subset of neurons residing in layers III and V of the mature cortex. Therefore, DNA methylation is dynamically regulated in the human cerebral cortex throughout the lifespan, involves differentiated neurons, and affects a substantial portion of genes predominantly by an age-related increase