Project description:Comparison of various ovarian tumors and ovarian cell lines. Keywords: Various ovarian tumors and cell lines. Samples from ovarian tumors and ovarian cell lines were examined for their microRNA expression patterns.
Project description:MicroRNAs (miRNAs) represent a class of small non-coding RNAs that control gene expression by targeting mRNAs and triggering either translation repression or RNA degradation. Emerging evidence suggests the potential involvement of altered regulation of miRNA in the pathogenesis of cancers, and these genes are thought to function as both tumor suppressors and oncogenes. Using microRNA microarrays, we identify several miRNAs aberrantly expressed in human ovarian cancer tissues and cell lines. miR-221 stands out as a highly elevated miRNA in ovarian cancer, while miR-21 and several members of the let-7 family are found downregulated. Public databases were used to reveal potential targets for the highly differentially expressed miRNAs. In order to experimentally identify transcripts whose stability may be affected by the differentially expressed miRNAs, we transfected precursor miRNAs into human cancer cell lines and used oligonucleotide microarrays to examine changes in the mRNA levels. Keywords: Expression data from various ovarian cancer cell lines transfected with pre-microRNA.
Project description:Schaner, M., et al. Mol Biol Cell. 2003 Nov;14(11):4376-86. Figure 1 Ovarian Cell Lines Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Keywords: Logical Set
Project description:Schaner M., et al.; Mol Biol Cell. 2003 Nov;14(11):4376-86. Figure 1 Unsupervised hierarchical clustering of ovarian cell lines and ovarian cancers. Cell lines were not co-clustered with the tumor specimens, because these cell lines have a very prominent proliferation cluster (Perou et al., 1999; Ross et al., 2000) that significantly influences the clustering of the tumor samples if the two sample sets are not analyzed separately. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Keywords: Logical Set
Project description:To investigate the microRNA profiles of ovarian clear cell carcinoma (OCCC), microRNA sequencing was performed using formalin-fixed, paraffin-embedded (FFPE) and fresh-frozen clinical samples. Moreover, patient-derived xenograft (PDX) tumors and cell lines were also investigated.
Project description:Background: Tumor microenvironment is well known to have a key role in tumor development. Extracellular vesicles are capable in cell signaling transduction and important in regulation of tumor microenvironment. Objective: To investigate whether peritoneal fluid–derived extracellular vesicles help regulate the tumor microenvironment in the malignant transformation of endometriosis. Methods: Samples of peritoneal fluid were taken from women with benign gynecological disease, endometriosis, or endometriosis-associated ovarian cancer. Small extracellular vesicles in the samples were isolated via ultracentrifugation and characterized by western blotting, transmission electron microscopy, and nanoparticle tracking. A global microRNA (miRNA) expression profile array was used to analyze miRNA abundance in peritoneal fluid–derived small extracellular vesicles. Candidate miRNAs were quantified by reverse transcription PCR to assess their potential role in cell migration. Results: A total of 22 miRNAs were identified from the analysis of miRNAs in peritoneal fluid–derived small extracellular vesicles from patients with endometriosis or endometriosis-associated ovarian cancer. We confirmed that each miRNA was expressed in various ovarian cell lines. The miRNA miR-302f was consistently highly expressed in both clinical specimens and ovarian cell lines from patients with endometriosis, yet expression was relatively low in specimens and cell lines from patients with endometriosis-associated ovarian cancer. A bio-functional assay revealed that miR-302f regulates cell migration. Finally, the possible target mRNAs of miR-302f were identified in the Gene Expression Omnibus database. Conclusions: These data may provide a basis for the development of novel therapeutic strategies for endometriosis-associated ovarian cancer patients by downregulating PDGFRA abundance in cancer cells via overexpression of miR-302f.
Project description:A cell line representative of human high-grade serous ovarian cancer (HGSOC) should not only resemble its tumor of origin at the molecular level, but also demonstrate functional utility in pre-clinical investigations. Here we report the integrated proteomic analysis of 26 ovarian cancer cell lines, HGSOC tumors, immortalized ovarian surface epithelial cells, and fallopian tube epithelial cells via a single-run mass spectrometric workflow. The in-depth quantitation of > 10,000 proteins results in three distinct cell line categories: epithelial (group I), clear cell (group II), and mesenchymal (group III). We identify a 67-protein cell line signature, which separates our entire proteomic dataset, as well as a confirmatory publicly available CPTAC/TCGA tumor proteome dataset, into a predominantly epithelial and mesenchymal HGSOC tumor cluster. This proteomics-based epithelial/mesenchymal stratification of cell lines and human tumors indicates a possible origin of HGSOC either from the fallopian tube or from the ovarian surface epithelium.