Unknown,Transcriptomics,Genomics,Proteomics

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DNA Methylation Profiling of Melanoma Cell Lines

ABSTRACT: Epigenetic regulation of tumor suppressor genes (TSGs) has been shown to play a central role in melanomagenesis. Integrating gene expression and methylation array analysis we identified novel candidate TSGs frequently methylated in melanoma. We validated the methylation status of the most promising TSGs using the highly sensitive, specific and comprehensive Sequenom Epityper assay in a large panel of melanoma cell lines and resected melanomas, and compared the findings with that from cultured melanocytes. We found transcript levels of UCHL1, COL1A2, THBS1 and TNFRSF10D were inversely correlated with promoter methylation. The effect of this methylation on expression was confirmed at the protein level. Identification of these candidate TSGs and how their silencing is related to melanoma development will increase our understanding of the etiology of this cancer and may provide tools for its early diagnosis. Analysed samples consisted of 11 melanoma cell lines and 1 neonatal foreskin melanocyte pool as a reference. Melanoma cell lines overlap with members of the DNA copy number analysis series GSE9003 and expression profiling series GSE7127 . The matching copy number data GEO samples IDs are noted in characteristics: Matching CN Sample ID and characteristics: Matching expn Sample ID columns respectively.

ORGANISM(S): Homo sapiens

SUBMITTER: Derek Nancarrow

PROVIDER: E-GEOD-28356 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Tumor suppressor genes (TSGs) are sometimes inactivated by transcriptional silencing through promoter hypermethylation. To identify novel methylated TSGs in melanoma, we carried out global mRNA expression proﬁling on a panel of 12 melanoma cell lines treated with a combination of 5-Aza-2-deoxycytidine (5AzadC) and an inhibitor of histone deacetylase, Trichostatin A. Reactivation of gene expression after drug treatment was assessed using Illumina whole-genome microarrays. After qRT-PCR conﬁrmation, we followed up 8 genes (AKAP12, ARHGEF16, ARHGAP27, ENC1, PPP1R3C, PPP1R14C, RARRES1, and TP53INP1) by quantitative DNA methylation analysis using mass spectrometry of base-speciﬁc cleaved ampliﬁcation products in panels of melanoma cell lines and fresh tumors. PPP1R3C, ENC1, RARRES1, and TP53INP1, showed reduced mRNA expression in 35–59% of the melanoma cell lines compared to melanocytes and which was correlated with a high proportion of promoter methylation (>40–60%). The same genes also showed extensive promoter methylation in 6–25% of the tumor samples, thus conﬁrming them as novel candidate TSGs in melanoma. We sought to identify melanoma TSGs silenced by promoter methylation by carrying out an array-based analysis in a well-annotated panel of 12 cell lines after combined treatment with 5AzadC and an inhibitor of histone deacetylase, Trichostatin A (TSA). Expression profiles were generated for each cell line before and after drug treatment using Illumina Sentrix Human-6 Expression version 2 BeadChips. Genes reactivated in all 12 cell lines were removed from further analysis since they are likely responding to drug treatment as part of the ‘‘cellular stress response,’’ or due to promoter demethylation of genes normally silenced in the melanocytic lineage. Genes were further ﬁltered to identify those with an average of >4-fold increased expression in at least four samples in the panel of 12 lines and >10-fold increase in at least one of the cell lines.

Project description:TET2 is a close relative of TET1, an enzyme that converts 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) in DNA. The gene encoding TET2 resides at chromosome 4q24, in a region showing recurrent microdeletions and copy-neutral loss of heterozygosity (CN-LOH) in patients with diverse myeloid malignancies. Somatic TET2 mutations are frequently observed in myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPN), MDS/MPN overlap syndromes including chronic myelomonocytic leukaemia (CMML), acute myeloid leukaemias (AML) and secondary AML (sAML). We show here that TET2 mutations associated with myeloid malignancies compromise catalytic activity. Bone marrow samples from patients with TET2 mutations displayed uniformly low levels of 5hmC in genomic DNA compared to bone marrow samples from healthy controls. Moreover, small hairpin RNA (shRNA)-mediated depletion of Tet2 in mouse haematopoietic precursors skewed their differentiation towards monocyte/macrophage lineages in culture. There was no significant difference in DNA methylation between bone marrow samples from patients with high 5hmC versus healthy controls, but samples from patients with low 5hmC showed hypomethylation relative to controls at the majority of differentially methylated CpG sites. Our results demonstrate that Tet2 is important for normal myelopoiesis, and suggest that disruption of TET2 enzymatic activity favours myeloid tumorigenesis. Measurement of 5hmC levels in myeloid malignancies may prove valuable as a diagnostic and prognostic tool, to tailor therapies and assess responses to anticancer drugs. Genome wide DNA methylation profiling of patients samples with various myeloid malignancies and diffrential levels of 5hmC.The Illumina Infinium 27k Human DNA methylation Beadchip v1.2 was used to obtain DNA methylation profiles across approximately 27,000 CpGs in bone marrow samples and occasionally peripheral blood samples. Samples included 28 control healthy bone marrows, 29 patients samples with low 5hmC levels (7 patients with wild-type TET2 and 22 mutant TET2) and 24 with high levels of 5hmC (22 with wild-type TET2 and 2 mutant TET2). Bisulphite converted DNA from 81 samples was hybridised to the Illumina Infinium 27k Human Methylation Beadchip v1.2

Project description:Human aging implies many phenotypic modifications and an increased susceptibility to many common diseases, phenomena that cannot be fully explained by the constrained genetic setting. An alternative pathway that could explain the age-associated alterations is epigenetic drifts. To address this issue, we performed Whole Genome Bisulfite Sequencing (WGBS) of a newborn and of a centenarian. The centenarian DNA exhibited a significant loss in DNA methylation and a poor correlation in the methylation status of neighboring CpGs throughout the genome. From a gene-regulatory region standpoint, we observed that the DNA hypomethylation events occurred mainly at CpG-poor promoters and in tissue-specific genes, whereas a greater level of DNA methylation was observed in CpG island promoters. Most importantly, we extended the study to a larger cohort of newborn and nonagenarian samples using a 450,000 CpG-site DNA methylation microarray. The 450K DNA methylation approach enabled validation of the WGBS data and revealed additional age-related DNA methylation events. Interestingly, we also observed the DNA methylation fingerprint characteristic of a healthy aged cell in samples from patients with premature-aging disorders such as Hutchinson-Gilford progeria and Werner syndrome. Overall, we suggest that defects in the physiological DNA methylation profile contribute to the process of human aging. As the disease associated cells were immortalized B cells, the effect of EBV immortalization was determined in advance to the study using immortalized and naive B cells. DNA was quantified by Quant-iT PicoGreen dsDNA Reagent (Invitrogen) and the integrity was analyzed in a 1.3% agarose gel. Bisulfite conversion of 600 ng of each sample was perform according to the manufacturer's recommendation for Illumina Infinium Assay. Effective bisulphite conversion was checked for three controls that were converted simultaneously with the samples. 4 ul of bisulfite converted DNA were used to hybridize on Infinium HumanMethylation 450 BeadChip, following Illumina Infinium HD Methylation protocol. Chip analysis was performed using Illumina HiScan SQ fluorescent scanner. The intensities of the images are extracted using GenomeStudio (2010.3) Methylation module (1.8.5) software. Methylation score of each CpG is represented as beta value.

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DNA Methylation Profiling of Melanoma Cell Lines

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