Project description:Methylation of CpG islands associated with genes can affect the expression of the proximal gene, and methylation of non associated CpG islands correlates to genomic instability. This epigenetic modification has been shown to be important in many pathologies, from development and disease to cancer. We report the development of a novel high-resolution microarray that detects the methylation status of over 25,000 CpG islands in the human genome. Experiments were performed to demonstrate low system noise in the methodology and that the array probes have a high signal to noise ratio. Methylation measurements between different cell lines were validated demonstrating the accuracy of measurement. We then identified alterations in CpG islands, both those associated with gene promoters, as well as non-promoter associated islands in a set of breast and ovarian tumors. We demonstrate that this methodology accurately identifies methylation profiles in cancer and in principle it can differentiate any CpG methylation alterations and can be adapted to analyze other species. We have developed a method to profile genome wide methylation. 7 ovarian normal samples and 11 tumor samples from other individuals were analyzed for CpG methylation. After inter array normalization, the tumor samples were taken together and the methylation compared to that of the normal samples to identify regions of the CpG islands that are significantly altered between the two datasets. Some of these regions were validated for their methylation as a proof of principle for the method.
Project description:We have systematically profiled DNA methylation at promoter CpG islands (CGIs) in ovarian cancer. Epithelial ovarian tumours, excluding mucinous and clear cell cancers, prospectively collected through a cohort study, were analyzed by differential methylation hybridization (DMH) (Nouzova M et al, 2004) in duplicates. The loci targeted by the custom-designed microarray are the promoter CpG islands (Gardiner-Garden and Frommer, 1987) of the genes involved in the Wnt, p53, AKT/mTOR, BRCA1/2 and Redox pathways, DNA repair (HR, NHEJ and MMR), FA family and IgLON family.
Project description:We have systematically profiled DNA methylation at promoter CpG islands (CGIs) in ovarian cancer. Epithelial ovarian tumours, excluding mucinous and clear cell cancers, prospectively collected through a cohort study, were analyzed by differential methylation hybridization (DMH) (Nouzova M et al, 2004) in duplicates. The loci targeted by the custom-designed microarray are the promoter CpG islands (Gardiner-Garden and Frommer, 1987) of the genes involved in the Wnt, p53, AKT/mTOR, BRCA1/2 and Redox pathways, DNA repair (HR, NHEJ and MMR), FA family and IgLON family. 111 ovarian tumor samples were assayed by DMH in duplicates. McrBC digested (Cy5) and undigested (Cy3) samples were competitively hybridized on the Agilent custom-designed microarrays 8x15k.
Project description:Methylation of CpG islands associated with genes can affect the expression of the proximal gene, and methylation of non associated CpG islands correlates to genomic instability. This epigenetic modification has been shown to be important in many pathologies, from development and disease to cancer. We report the development of a novel high-resolution microarray that detects the methylation status of over 25,000 CpG islands in the human genome. Experiments were performed to demonstrate low system noise in the methodology and that the array probes have a high signal to noise ratio. Methylation measurements between different cell lines were validated demonstrating the accuracy of measurement. We then identified alterations in CpG islands, both those associated with gene promoters, as well as non-promoter associated islands in a set of breast and ovarian tumors. We demonstrate that this methodology accurately identifies methylation profiles in cancer and in principle it can differentiate any CpG methylation alterations and can be adapted to analyze other species.
Project description:Methylation of CpG islands associated with genes can affect the expression of the proximal gene, and methylation of non associated CpG islands correlates to genomic instability. This epigenetic modification has been shown to be important in many pathologies, from development and disease to cancer. We report the development of a novel high-resolution microarray that detects the methylation status of over 25,000 CpG islands in the human genome. Experiments were performed to demonstrate low system noise in the methodology and that the array probes have a high signal to noise ratio. Methylation measurements between different cell lines were validated demonstrating the accuracy of measurement. We then identified alterations in CpG islands, both those associated with gene promoters, as well as non-promoter associated islands in a set of breast and ovarian tumors. We demonstrate that this methodology accurately identifies methylation profiles in cancer and in principle it can differentiate any CpG methylation alterations and can be adapted to analyze other species.
Project description:Methylation of CpG islands associated with genes can affect the expression of the proximal gene, and methylation of non associated CpG islands correlates to genomic instability. This epigenetic modification has been shown to be important in many pathologies, from development and disease to cancer. We report the development of a novel high-resolution microarray that detects the methylation status of over 25,000 CpG islands in the human genome. Experiments were performed to demonstrate low system noise in the methodology and that the array probes have a high signal to noise ratio. Methylation measurements between different cell lines were validated demonstrating the accuracy of measurement. We then identified alterations in CpG islands, both those associated with gene promoters, as well as non-promoter associated islands in a set of breast and ovarian tumors. We demonstrate that this methodology accurately identifies methylation profiles in cancer and in principle it can differentiate any CpG methylation alterations and can be adapted to analyze other species. We have developed a method to profile genome wide methylation. 12 breast normal samples and matching tumors from these individuals and an additional 28 tumor samples from other individuals were analyzed for CpG methylation. After inter array normalization, the tumor samples were taken together and the methylation compared to that of the normal samples to identify regions of the CpG islands that are significantly altered between the two datasets. Some of these regions were validated for their methylation as a proof of principle for the method.
Project description:Multiple DNA methylation changes have been associated with the acquisition of drug resistance; however it remains uncertain how many of these changes may represent critical DNA methylation drivers of chemoresistance. Using genome-wide DNA methylation profiling across 27,578 CpG sites on Illumina HumanMethylation27 bead array we identified loci at 4092 genes becoming hypermethylated in the chemoresistant A2780/cp70 ovarian tumour cell line compared to the parental sensitive A2780 line. Hypermethylation at CpG islands (CGI) is often associated with transcriptional silencing, however only 245 of these hypermethylated genes become down-regulated in A2780/cp70 as measured by microarray expression profiling. Treatment with the demethylating agent Decitabine induces re-sensitisation to cisplatin and resulted in re-expression of 41 of the down-regulated genes in cisplatin-resistant cells at the time point when re-sensitisation occurs. 13 of the 41 genes were consistently hypermethylated in two further independent cisplatin-resistant A2780 cell derivatives. Nine out of the 13 genes (ARHGDIB, ARMCX2, COL1A, FLNA, FLNC, MEST, MLH1, NTS, PSMB9) acquired methylation at CpG sites in ovarian tumours at relapse following chemotherapy or chemoresistant cell lines derived at the time of patient relapse. Furthermore, 5/13 candidate genes acquired methylation in drug-resistant in vivo-derived ovarian cancer sustaining (side population) cells. Therefore, this small set of genes are potential key drivers of chemoresistance and should be further evaluated as predictive biomarkers, both to existing chemotherapies, but also to epigenetic therapies used to modulate drug resistance. Array-based methylation profiling was performed using the Infinium HumanMethylation27 BeadChip in two cisplatin sensitive cell lines and three cisplatin resistant cell lines derived in vitro, four pairs of cisplatin sensitive and resistant cell lines derived in vivo, 7 pairs of tumour tissues obtained from patients before chemotherapy and at disease relapse, 2 pairs of IGROV1 SP and NSP cells. The reproducibility of the Infinium HumanMethylation27 BeadChips was evaluated using biological and technical replicates of matched chemosensitive/chemoresistant ovarian cancer cell lines PEO1/PEO4. Differential methylation cutoff was estimated from two biological replicates by bootstrap resampling.
Project description:Methylation of CpG islands is associated with transcriptional repression and, in cancer, leads to the abnormal silencing of tumor-suppressor genes. Genome wide methylation profiling of myeloid leukemia cell lines identified a large number of genes with aberrantly methylated CpG islands. Comparative mRNA expression analysis suggests that more than half of these genes show extremely low or absent expression in normal cells, suggesting that hypermethylation in cancer may be independent of the transcriptional status of the affected gene. Experiment Overall Design: The expression profiles of the three leukemia cell lines KG-1, U937 and THP-1 was compared to normal human blood monocytes (reference). The set includes a single hybridization for each sample.
Project description:The aim of the present study was to identify novel DNA methylation markers in bladder cancer (BCa) through genome-wide profiling of bladder cancer cell lines and subsequent MSP screening in urine samples. Experimental Design: MBD methylCap/seq was carried out to screen differentially methylated CpG islands using two BCa cell lines (5637 and T24) and two normal bladder mucosa (BM) samples. The top one hundred most hypermethylated targets were screened using Methylation Specific PCR (MSP) in small and big cohort of urine samples from BCa patients and normal controls. The diagnostic performance of the gene panel was further evaluated in different clinical scenarios. Results: In total, 1,627 gene promoter regions hypermethylated in BCa cell line were identified in genomic level methylation profiling. The followed screening procedure in clinical urine sample generated eight genes (VAX1, KCNV1, ECEL1, TMEM26, TAL1, PROX1, SLC6A20, and LMX1A) capable of differentiating BCa from normal control. Subsequent validation in a large sample size enabled the optimisation of 5 methylation targets (VAX1, KCNV1, TAL1, PPOX1 and CFTR) for BCa diagnosis with sensitivity and specificity of 86.32% and 87.13%, respectively. In addition, VAX1 and LMX1A methylation could predict the tumour recurrence. Conclusions: Tumor specific biomarkers of BCa could be established by first performing genome level methylation profiling with cell lines and then screening the potential targets in urine samples. The panel of methylated genes identified was promising for the early non-invasive detection and surveillance of BCa. MBD methylCap/seq was carried out to screen differentially methylated CpG islands using two BCa cell lines (5637 and T24), and two normal bladder tissue mix as control.