Project description:Serous borderline tumours (SBOT) are a challenging group of ovarian tumours positioned between benign and malignant disease. We have profiled the DNA methylomes of 12 low grade serous carcinoma (LGSC), 19 SBOT and 16 benign serous tumours (BST) across 27,578 CpG sites to further characterise the epigenomic relationship between these subtypes of ovarian tumours. Unsupervised hierarchical clustering of DNA methylation levels showed that LGSC differ distinctly from BST, however, not from SBOT. Gene ontology analysis of genes showing differential methylation at linked CpG sites between LGSC and BST revealed significant enrichment of gene groups associated with cell adhesion, cell-cell signalling and the extracellular region consistent with a more invasive phenotype of LGSC as compared to BST. Consensus clustering highlighted differences between SBOT methylomes and returned subgroups with malignant-like or benign-like methylation profiles. Furthermore, a two loci DNA methylation signature can distinguish between these SBOT subgroups with benign-like and malignant-like methylation characteristics. Our findings indicate striking similarities between SBOT and LGSC methylomes which supports a common origin and the view that LGSC may arise from SBOT. A subgroup of SBOT can be classified into tumours with a benign-like or a malignant-like methylation profile which may help in identifying tumours more likely to progress into LGSC.
Project description:The main goal of the study was to measure the epigenetic age (also known as DNA methylation age) of human bone tissue and to relate it to chronological age. Toward this end, we used the epigenetic clock software described in Horvath S (2013) DNA methylation age of human tissues and cell types. Genome Biology.2013, 14:R115. DOI: 10.1186/10.1186/gb-2013-14-10-r115 PMID: 24138928
Project description:Serous borderline tumours (SBOT) are a challenging group of ovarian tumours positioned between benign and malignant disease. We have profiled the DNA methylomes of 12 low grade serous carcinoma (LGSC), 19 SBOT and 16 benign serous tumours (BST) across 27,578 CpG sites to further characterise the epigenomic relationship between these subtypes of ovarian tumours. Unsupervised hierarchical clustering of DNA methylation levels showed that LGSC differ distinctly from BST, however, not from SBOT. Gene ontology analysis of genes showing differential methylation at linked CpG sites between LGSC and BST revealed significant enrichment of gene groups associated with cell adhesion, cell-cell signalling and the extracellular region consistent with a more invasive phenotype of LGSC as compared to BST. Consensus clustering highlighted differences between SBOT methylomes and returned subgroups with malignant-like or benign-like methylation profiles. Furthermore, a two loci DNA methylation signature can distinguish between these SBOT subgroups with benign-like and malignant-like methylation characteristics. Our findings indicate striking similarities between SBOT and LGSC methylomes which supports a common origin and the view that LGSC may arise from SBOT. A subgroup of SBOT can be classified into tumours with a benign-like or a malignant-like methylation profile which may help in identifying tumours more likely to progress into LGSC. Array-based methylation profiling was performed using the Infinium HumanMethylation27 BeadChip in 12 low grade serous carcinoma, 19 serous borderline tumours and 16 benign serous tumours. The reproducibility of the Infinium HumanMethylation27 BeadChips was evaluated using four biological replicates of the high grade serous ovarian cancer cell line PEO1. Differential methylation cutoff was estimated from four biological replicates by bootstrap resampling and set at Δβ ≥ 0.25 corresponding to a FDR ≤ 0.09.
Project description:BackgroundMultiple epigenetic and genetic changes have been reported in colorectal tumors, but few of these have clinical impact. This study aims to pinpoint epigenetic markers that can discriminate between non-malignant and malignant tissue from the large bowel, i.e. markers with diagnostic potential. The methylation status of eleven genes (ADAMTS1, CDKN2A, CRABP1, HOXA9, MAL, MGMT, MLH1, NR3C1, PTEN, RUNX3, and SCGB3A1) was determined in 154 tissue samples including normal mucosa, adenomas, and carcinomas of the colorectum. The gene-specific and widespread methylation status among the carcinomas was related to patient gender and age, and microsatellite instability status. Possible CIMP tumors were identified by comparing the methylation profile with microsatellite instability (MSI), BRAF-, KRAS-, and TP53 mutation status.ResultsThe mean number of methylated genes per sample was 0.4 in normal colon mucosa from tumor-free individuals, 1.2 in mucosa from cancerous bowels, 2.2 in adenomas, and 3.9 in carcinomas. Widespread methylation was found in both adenomas and carcinomas. The promoters of ADAMTS1, MAL, and MGMT were frequently methylated in benign samples as well as in malignant tumors, independent of microsatellite instability. In contrast, normal mucosa samples taken from bowels without tumor were rarely methylated for the same genes. Hypermethylated CRABP1, MLH1, NR3C1, RUNX3, and SCGB3A1 were shown to be identifiers of carcinomas with microsatellite instability. In agreement with the CIMP concept, MSI and mutated BRAF were associated with samples harboring hypermethylation of several target genes.ConclusionMethylated ADAMTS1, MGMT, and MAL are suitable as markers for early tumor detection.
Project description:Genome wide DNA methylation profiling of normal adrenocortical tissue, adrenocortical adenomas and adrenocortical carcinomas. The Illumina Infinium 27k Human DNA methylation Beadchip v1.2 was used to obtain DNA methylation profiles. Samples included 6 normal adrenocortical tissue samples, 27 adenomas and 15 carcinomas.
Project description:Aberrant DNA methylation (DNAm) was first linked to cancer over 25 years ago. Since then, many studies have associated hypermethylation of tumour suppressor genes and hypomethylation of oncogenes to the tumourigenic process. However, most of these studies have been limited to the analysis of promoters and CpG islands (CGIs). Recently, new technologies for whole-genome DNAm (methylome) analysis have been developed, enabling unbiased analysis of cancer methylomes. Using MeDIP-seq, we report a sequencing-based comparative methylome analysis of malignant peripheral nerve sheath tumours (MPNST), benign Neurofibromas and normal Schwann cells. Analysis of these methylomes revealed a complex landscape of DNAm alterations. Contrary to the current dogma, significant global hypomethylation was not observed in the MPNST methylome. However, a highly significant (P<10-100) directional difference in DNAm was found in satellite repeats, suggesting these repeats to be the main target for hypomethylation in MPNST. Comparative analysis of the MPNST and Schwann cell methylomes identified 101,466 cancer-associated differentially methylated regions (cDMRs). Analysis showed these cDMRs to be significantly enriched for two satellite repeat types (SATR1 and ARLα) and suggests an association between aberrant DNAm of these sequences and transition from healthy cells to malignant disease. Significant enrichment of hypermethylated cDMRs in CGI shores (P<10-60), non-CGI-associated promoters (P<10-4) and hypomethylated cDMRs in SINE repeats (P<10-100) was also identified. Integration of DNAm and gene expression data showed that the expression pattern of genes associated with CGI shore cDMRs was able to discriminate between disease phenotypes. This study establishes MeDIP-seq as an effective method to analyse cancer methylomes.
Project description:DNA methylation, an epigenetic alteration typically occurring early in cancer development, could aid in the molecular diagnosis of melanoma. We determined technical feasibility for high-throughput DNA-methylation array-based profiling using formalin-fixed paraffin-embedded tissues for selection of candidate DNA-methylation differences between melanomas and nevi. Promoter methylation was evaluated in 27 common benign nevi and 22 primary invasive melanomas using a 1505 CpG site microarray. Unsupervised hierarchical clustering distinguished melanomas from nevi; 26 CpG sites in 22 genes were identified with significantly different methylation levels between melanomas and nevi after adjustment for age, sex, and multiple comparisons and with β-value differences of ≥ 0.2. Prediction analysis for microarrays identified 12 CpG loci that were highly predictive of melanoma, with area under the receiver operating characteristic curves of > 0.95. Of our panel of 22 genes, 14 were statistically significant in an independent sample set of 29 nevi (including dysplastic nevi) and 25 primary invasive melanomas after adjustment for age, sex, and multiple comparisons. This first report of a DNA-methylation signature discriminating melanomas from nevi indicates that DNA methylation appears promising as an additional tool for enhancing melanoma diagnosis.
Project description:Changes in DNA methylation, whether hypo- or hypermethylation, have been shown to be associated with the progression of colorectal cancer. Methylation changes substantially in the progression from normal mucosa to adenoma and to carcinoma. This phenomenon has not been studied extensively and studies have been restricted to individual CpG islands, rather than taking a whole-genome approach. We aimed to study genome-wide methylation changes in colorectal cancer. We obtained 10 fresh-frozen normal tissue-cancer sample pairs, and five fresh-frozen adenoma samples. These were run on the lllumina HumanMethylation27 whole-genome methylation analysis system. Differential methylation between normal tissue, adenoma and carcinoma was analysed using Bayesian regression modelling, gene set enrichment analysis (GSEA) and hierarchical clustering (HC). The highest-rated individual gene for differential methylation in carcinomas versus normal tissue and adenomas versus normal tissue was GRASP (padjusted ?=?1.59 × 10(-5) , BF = 12.62, padjusted ?=?1.68 × 10(-6) , BF = 14.53). The highest-rated gene when comparing carcinomas versus adenomas was ATM (padjusted ?=?2.0 × 10(-4) , BF = 10.17). Hierarchical clustering demonstrated poor clustering by the CIMP criteria for methylation. GSEA demonstrated methylation changes in the Netrin-DCC and SLIT-ROBO pathways. Widespread changes in DNA methylation are seen in the transition from adenoma to carcinoma. The finding that GRASP, which encodes the general receptor for phosphoinositide 1-associated scaffold protein, was differentially methylated in colorectal cancer is interesting. This may be a potential biomarker for colorectal cancer.
Project description:Genome wide DNA methylation profiling of phyllodes tumour, fibroadenoma and metaplastic breast cancer samples. The Illumina Infinium Methylation EPIC v1.0 BeadChip Array was used to obtain DNA methylation profiles across approximately 866,000 CpGs from primary tumours. Samples included a range of grades of phyllodes tumours (n=29), fibroadenoma (n=2), and metaplastic breast cancer (n=2).