Transcriptomics

Dataset Information

0

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 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE25428 | GEO | 2010/11/17

SECONDARY ACCESSION(S): PRJNA142615

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2010-11-17 | E-GEOD-25428 | biostudies-arrayexpress
2010-11-17 | E-GEOD-25427 | biostudies-arrayexpress
2010-11-17 | GSE25427 | GEO
2019-03-05 | GSE127763 | GEO
2019-03-05 | GSE127828 | GEO
2013-12-31 | E-GEOD-40266 | biostudies-arrayexpress
2013-12-31 | GSE40266 | GEO
| PRJNA244104 | ENA
2015-04-07 | GSE56621 | GEO
2015-04-07 | E-GEOD-56621 | biostudies-arrayexpress