Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Gene expression profiling in A2780, CP70 and CP70 following Decitabine and/or PXD101 treatment

ABSTRACT: 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 gene expression profiling method on HGU133plus2 array, we identified a total of 1370 genes showing significant gene expression changes with 687 genes going up and 683 genes going down in the resistant (cp70) versus sensitive cell lines (A2780) by Rank Product (FDR<5%). Combining expression profiling with methylation profiling data we found out of 245 hypermethylated and down-regulated genes in the resistant cell line, 41 genes were up-regulated following Decitabine treatment alone, 45 genes up-regulated following combined treatment of Decitabine and PXD101, and only 10 genes up-regulated following PXD101 treatment alone. Altogether we found a small set of genes as being 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. Gene expression profiling was obtained from A2780, and CP70 before and after Decitabine and/or PXD101 treatment. Each sample have biological triplicates. Using Rank Product package in R (version 2.10.1), differentially expressed genes with FDR<5% were identified.

ORGANISM(S): Homo sapiens

SUBMITTER: Wei Dai

PROVIDER: E-GEOD-28646 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Epithelial ovarian cancer is the leading cause of death among gynecologic malignancies. Diagnosis usually occurs after metastatic spread, largely reflecting vague symptoms of early disease combined with lack of an effective screening strategy. Epigenetic mechanisms of gene regulation, including DNA methylation, are fundamental to normal cellular function and also play a major role in carcinogenesis. To elucidate the biological and clinical relevance of DNA methylation in ovarian cancer, we conducted expression microarray analysis of 43 cell lines and 17 primary culture specimens grown in the presence or absence of DNA methyltransferase (DNMT) inhibitors. Two parameters, induction of expression and standard deviation among untreated samples, identified 378 candidate methylated genes, many relevant to TGF-beta signaling. We analyzed 43 of these genes and they all exhibited methylation. Treatment with DNMT inhibitors increased TGF-beta pathway activity. Hierarchical clustering of ovarian cancers using the 378 genes reproducibly generated a distinct gene cluster strongly correlated with TGF-beta pathway activity that discriminates patients based on age. These data suggest that accumulation of age-related epigenetic modifications leads to suppression of TGF-beta signaling and contributes to ovarian carcinogenesis. The cancer stem cell hypothesis posits that malignant growth arises from a rare population of progenitor cells within a tumor that provide it with unlimited regenerative capacity. Such cells also possess increased resistance to chemotherapeutic agents. Resurgence of chemoresistant disease following primary therapy typifies epithelial ovarian cancer and may be attributable to residual cancer stem cells, or cancer initiating cells, that survive initial treatment. As the cell surface marker CD133 identifies cancer initiating cells in a number of other malignancies, we sought to determine the potential role of CD133+ cells in epithelial ovarian cancer. We detected CD133 on ovarian cancer cell lines, in primary cancers, and on purified epithelial cells from ascitic fluid of ovarian cancer patients. We found CD133+ ovarian cancer cells generate both CD133+ and CD133- daughter cells, whereas CD133- cells divide symmetrically. CD133+ cells exhibit enhanced resistance to platinum-based therapy, drugs commonly used as first line agents for treatment of ovarian cancer. Sorted CD133+ ovarian cancer cells also form more aggressive tumor xenografts at a lower inoculum than their CD133- progeny. Epigenetic changes may be integral to the behavior of cancer progenitor cells and their progeny. In this regard, we found that CD133 transcription is controlled by both histone modifications and promoter methylation. Sorted CD133- ovarian cancer cells treated with DNA methyltransferase and histone deacetylase inhibitors show a synergistic increase in cell surface CD133 expression. Moreover, DNA methylation at the ovarian tissue active P2 promoter is inversely correlated with CD133 transcription. We also found that promoter methylation increases in CD133- progeny of CD133+ cells, with CD133+ cells retaining a less methylated or unmethylated state. Taken together, our results show that CD133 expression in ovarian cancer is directly regulated by epigenetic modifications and support the idea that CD133 demarcates an ovarian cancer initiating cell population. The activity of these cells may be epigenetically detected and such cells might serve as pertinent chemotherapeutic targets for reducing disease recurrence. The objective of the study was to identify genes that are subject to DNA methylation through pharmacological inhibition of DNA methyltransferase activity in a panel of cancer cell lines. Cells were mock treated with culture media (mock treated) or treated with 5 µM decitabine for 72 hours. Resulting expression profiles were compared to identify genes with altered expression following decitabine treatment. These data represent two experiments: In the first, 43 established cell lines were mock treated or treated with decitabine to enable identification of genes differentially expressed as a result of inhibition of DNA methyltransferase activity. HEYA8-decitabine treated cells were run in replicate. In the second experiment, A2780 and PEO1 cells underwent flow activated cell sorting to separate CD133(+) from CD133(-) cells in each cell line; the sorted cell populations were cultured in the same manner as the first experiment and similarly mock treated or treated with decitabine. All specimens were arrayed in parallel and used for RMA normalization.

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Gene expression profiling in A2780, CP70 and CP70 following Decitabine and/or PXD101 treatment

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