Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling of human tumor-conditioned versus quiescent HUVEC cells, and 5-aza-2a??-deoxycytidine and trichostatin AI treated cells to identify epigenetically silenced genes

ABSTRACT: Tumor angiogenesis requires intricate regulation of gene expression in endothelial cells (EC). We recently showed that DNA methyltransferase (DNMT)- and histone deacetylase (HDAC) inhibitors directly repress EC growth and tumor angiogenesis, suggesting that epigenetic modifications mediated by DNMTs and HDACs are involved in regulation of EC gene expression during tumor angiogenesis. To understand the mechanisms behind the epigenetic regulation of tumor angiogenesis, we used microarray analysis to perform a comprehensive screen to identify genes downregulated in tumor-conditioned versus quiescent EC, and re-expressed by 5-aza-2â-deoxycytidine and trichostatin A. Among the 81 genes identified, 77% harboured a promoter CpG island. Validation of mRNA levels of a subset of genes confirmed significant downregulation in tumor-conditioned EC and reactivation by treatment with a combination of 5-aza-2â-deoxycytidine and trichostatin A, as well as by both compounds separately. Silencing of these genes in tumor-conditioned EC correlated with promoter histone H3 deacetylation and loss of H3 lysine 4 methylation, however did not involve DNA methylation of promoter CpG islands. For six genes, downregulation in microdissected human tumor endothelium was confirmed. Functional validation by RNA interference revealed that clusterin, fibrillin 1 and quiescin Q6 are negative regulators of EC growth and angiogenesis. In summary, our data identify novel angiogenesis suppressing genes which become silenced in tumor-conditioned EC in association with promoter histone modifications and reactivated by DNMT- and HDAC inhibitors through reversal of these epigenetic modifications, providing a mechanism for epigenetic regulation of tumor angiogenesis. Experiment Overall Design: A commercial pool (a mixture of 32 donors) of HUVEC (Tebu-bio, Heerhugowaard, The Netherlands) was used for DNA microarray experiments. Total RNA was isolated using the RNeasy RNA isolation kit (Qiagen) according to the supplier's protocol. Possible genomic DNA contaminations were removed by on column DNase treatment with the RNase-free DNase set (Qiagen). The purified RNA was quantified using a Nanodrop spectrophotometer, and RNA quality was evaluated using the Agilent 2100 Bioanalyzer. cDNA synthesis was performed using the Agilent Fluorescent Direct Labelkit with direct incorporation of either cyanine 5 (Cy5) or Cy3 âdCTP nucleotides (Perkin Elmer) according to the manufacturerâs instructions. Labeled cDNA was purified using QIAquick PCR purification columns (Qiagen), followed by concentration by vacuum centrifugation. The Agilent human 1A cDNA microarray (Agilent Technologies, Amstelveen, The Netherlands) contained ~15000 cDNA probes. Labeled cDNA was resuspended in hybridisation buffer and hybridised to Agilent human 1A cDNA microarray for 17 h at 65Â°C, according to the Agilent protocols. All hybridisations were replicated with cy dyes switched. Two fluorescent microarray comparisons were performed: (1) A comparison of tumor-conditioned HUVEC and quiescent HUVEC and (2) a comparison of tumor-conditioned HUVEC treated with or without a combination of DAC and TSA. Experiment Overall Design: Microarray data processing and statistical analysis Experiment Overall Design: The image file was processed using Agilent's Feature Extraction software (version A.6.1.1, Agilent Technologies). This Feature Extraction program was used to identify pixels corresponding to fluorescent signal (as opposed to background) and to remove pixels with intensities that met the default criteria for outliers. The different normalisation routines applied (Local Background, Minimum signal (feature or background) & Average of all background areas) resulted in comparable results. For each identified area of signal and each of the two dyes, the basic measure of RNA abundance was taken to be the mean intensity over pixels in the identified signal area. The log ratio of the red to green intensities for each signal area was used for statistical analyses, with all subsequent analyses done using the R statistical software package (version 1.2). We selected fold change 1.5 as a threshold, since the 4 hybridisations increase the likelihood of statistical reliability.

ORGANISM(S): Homo sapiens

SUBMITTER: Debby Hellebrekers

PROVIDER: E-GEOD-7132 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Identification of epigenetically silenced genes in tumor endothelial cells.

Hellebrekers Debby M E I DM Melotte Veerle V Viré Emmanuelle E Langenkamp Elise E Molema Grietje G Fuks François F Herman James G JG Van Criekinge Wim W Griffioen Arjan W AW van Engeland Manon M

Cancer research 20070501 9

Tumor angiogenesis requires intricate regulation of gene expression in endothelial cells. We recently showed that DNA methyltransferase (DNMT) and histone deacetylase (HDAC) inhibitors directly repress endothelial cell growth and tumor angiogenesis, suggesting that epigenetic modifications mediated by DNMTs and HDAC are involved in regulation of endothelial cell gene expression during tumor angiogenesis. To understand the mechanisms behind the epigenetic regulation of tumor angiogenesis, we used ...[more]

PMID: 17483324

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Dataset Information

Transcription profiling of human tumor-conditioned versus quiescent HUVEC cells, and 5-aza-2a??-deoxycytidine and trichostatin AI treated cells to identify epigenetically silenced genes

Publications

Identification of epigenetically silenced genes in tumor endothelial cells.

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