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Gene expression profiles of ovarian cancer cell lines in the presence and absence of a DNA methyltransferase inhibitor

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

SUBMITTER: Murphy Susan

PROVIDER: S-ECPF-GEOD-25428 | biostudies-other |

REPOSITORIES: biostudies-other

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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 39 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.

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.

Project description:BackgroundEpithelial ovarian carcinoma is a significant cause of cancer mortality in women worldwide and in the United States. Epithelial ovarian cancer comprises several histological subtypes, each with distinct clinical and molecular characteristics. The natural history of this heterogeneous disease, including the cell types of origin, is poorly understood. This study applied recently developed methods for high-throughput DNA methylation profiling to characterize ovarian cancer cell lines and tumors, including representatives of three major histologies.Methodology/principal findingsWe obtained DNA methylation profiles of 1,505 CpG sites (808 genes) in 27 primary epithelial ovarian tumors and 15 ovarian cancer cell lines. We found that the DNA methylation profiles of ovarian cancer cell lines were markedly different from those of primary ovarian tumors. Aggregate DNA methylation levels of the assayed CpG sites tended to be higher in ovarian cancer cell lines relative to ovarian tumors. Within the primary tumors, those of the same histological type were more alike in their methylation profiles than those of different subtypes. Supervised analyses identified 90 CpG sites (68 genes) that exhibited 'subtype-specific' DNA methylation patterns (FDR<1%) among the tumors. In ovarian cancer cell lines, we estimated that for at least 27% of analyzed autosomal CpG sites, increases in methylation were accompanied by decreases in transcription of the associated gene.SignificanceThe significant difference in DNA methylation profiles between ovarian cancer cell lines and tumors underscores the need to be cautious in using cell lines as tumor models for molecular studies of ovarian cancer and other cancers. Similarly, the distinct methylation profiles of the different histological types of ovarian tumors reinforces the need to treat the different histologies of ovarian cancer as different diseases, both clinically and in biomarker studies. These data provide a useful resource for future studies, including those of potential tumor progenitor cells, which may help illuminate the etiology and natural history of these cancers.

Project description:BACKGROUND:Ovarian cancer is an epithelial malignancy that intrigues people for its poor outcome and lack of efficient treatment, while methylation is an important mechanism that have been recognized in many malignancies. In this study, we attempt to assess abnormally methylated gene markers and pathways in ovarian cancer by integrating three microarray datasets. METHODS:Three datasets including expression (GSE26712 and GSE66957) and methylation (GSE81224) datasets were accessed. GEO2R platform was used to detect abnormally methylated-differentially expressed genes. Protein-protein interaction (PPI) networks were built and analysed for hypermethylated and hypermethylated differentially expressed genes using Cytoscape software and Mcode app. GEPIA and cBioPortal platforms were used to validate the expression of the hub genes and the correlation between their mRNA expressions and methylation levels. Kaplan Meier-plotter platform were used to assess the prognostic significance of the hub genes. RESULTS:Six hundred eighty-one hypomethylated-upregulated genes were detected and involved in Rap1 signaling pathway, biosynthesis of amino acids, endocrine resistance, apoptosis, pathways in cancer. The hub genes were TNF, UBC, SRC, ESR1, CDK1, PECAM1, CXCR4, MUC1, IKBKG. Additionally, 337 hypermethylated-downregulated genes were detected and involved in pathways in cancer, focal adhesion, sphingolipid signaling pathway, EGFR tyrosine kinase inhibitor resistance, cellular senescence. The hub genes were BDNF, CDC42, CD44, PPP2R5C, PTEN, UBB, BMP2, FOXO1, KLHL2. TNF, ESR1, MUC1, CD44, PPP2R5C, PTEN, UBB and FOXO1 showed significant negative correlation between their mRNA expressions and methylation levels. TNF, ESR1 and FOXO1 showed prognostic significance. CONCLUSIONS:Two novel gene networks were found for ovarian cancer. TNF, ESR1, MUC1 and FOXO1 are our candidate genes that might take part in ovarian cancer progression in an epigenetic approach, TNF, ESR1 and FOXO1 may serve as potential markers for ovarian cancer prognosis evaluation.

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Gene expression profiles of ovarian cancer cell lines in the presence and absence of a DNA methyltransferase inhibitor

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