Expression data from exponentially proliferating ovarian cancer cell lines
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE43765 | GEO | 2013/01/26
SECONDARY ACCESSION(S): PRJNA187363
REPOSITORIES: GEO
Similar Datasets
Project description:We used microarrays to assess gene expression in proliferating ovarian cancer cell lines Ovarian cancer cell lines were plated and harvested when 50-80% confluent. RNA was extracted and hybridized on Affymetrix microarrays. At least 3 biological repeats were performed for each cell line.
2013-01-26 | E-GEOD-43765 | biostudies-arrayexpress
Project description:The hallmark of human cancer is heterogeneity, mirroring the complexity of genetic and epigenetic alterations acquired during oncogenesis. We extracted RNA of 34 cultured human ovarian carcinoma cell lines and performed expression microarrays so that cultured cell lines can represent in vivo human tumors.
2013-05-21 | GSE28724 | GEO
Project description:The hallmark of human cancer is heterogeneity, mirroring the complexity of genetic and epigenetic alterations acquired during oncogenesis. We extracted RNA of 34 cultured human ovarian carcinoma cell lines and performed expression microarrays so that cultured cell lines can represent in vivo human tumors. 34 ovarian carcinoma cell lines expression data.
2013-05-21 | E-GEOD-28724 | biostudies-arrayexpress
Project description:Background: Ovarian carcinomas consist of at least five distinct diseases: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and molecular characterization may represent a more biologically relevant basis for grouping and treating this family of tumors, rather than site of origin. Molecular characteristics have become the new standard for clinical pathology, however development of tailored type-specific therapies is hampered by a failure of basic research to recognize that model systems used to study these diseases must also be stratified. Unrelated model systems do offer value for study of biochemical processes but specific cellular context needs to be applied to assess relevant therapeutic strategies. Methods: We have focused on the identification of clear cell carcinoma cell line models. A panel of 32 “ovarian cancer” cell lines has been classified into histological types using a combination of mutation profiles, IHC mutation-surrogates, and a validated immunohistochemical model. All cell lines were identity verified using STR analysis. Results: Many described ovarian clear cell lines have characteristic mutations (including ARID1A and PIK3CA) and an overall molecular/immuno-profile typical of primary tumors. Mutations in TP53 were present in the majority of high-grade serous cell lines. Advanced genomic analysis of bona-fide clear cell carcinoma cell lines also support copy number changes in typical biomarkers such at MET and HNF1B and a lack of any recurrent expressed re-arrangements. Conclusions: As with primary ovarian tumors, mutation status of cancer genes like ARID1A and TP53 and a general immuno-profile serve well for establishing histological type of ovarian cancer cell We describe specific biomarkers and molecular features to re-classify generic “ovarian carcinoma” cell lines into type specific categories. Our data supports the use of prototype clear cell lines, such as TOV21G and JHOC-5, and questions the use of SKOV3 and A2780 as models of high-grade serous carcinoma.
2013-08-01 | GSE48351 | GEO
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.
2008-08-29 | GSE12615 | GEO
Project description:Background: Ovarian carcinomas consist of at least five distinct diseases: high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous. Biomarker and molecular characterization may represent a more biologically relevant basis for grouping and treating this family of tumors, rather than site of origin. Molecular characteristics have become the new standard for clinical pathology, however development of tailored type-specific therapies is hampered by a failure of basic research to recognize that model systems used to study these diseases must also be stratified. Unrelated model systems do offer value for study of biochemical processes but specific cellular context needs to be applied to assess relevant therapeutic strategies. Methods: We have focused on the identification of clear cell carcinoma cell line models. A panel of 32 M-bM-^@M-^\ovarian cancerM-bM-^@M-^] cell lines has been classified into histological types using a combination of mutation profiles, IHC mutation-surrogates, and a validated immunohistochemical model. All cell lines were identity verified using STR analysis. Results: Many described ovarian clear cell lines have characteristic mutations (including ARID1A and PIK3CA) and an overall molecular/immuno-profile typical of primary tumors. Mutations in TP53 were present in the majority of high-grade serous cell lines. Advanced genomic analysis of bona-fide clear cell carcinoma cell lines also support copy number changes in typical biomarkers such at MET and HNF1B and a lack of any recurrent expressed re-arrangements. Conclusions: As with primary ovarian tumors, mutation status of cancer genes like ARID1A and TP53 and a general immuno-profile serve well for establishing histological type of ovarian cancer cell We describe specific biomarkers and molecular features to re-classify generic M-bM-^@M-^\ovarian carcinomaM-bM-^@M-^] cell lines into type specific categories. Our data supports the use of prototype clear cell lines, such as TOV21G and JHOC-5, and questions the use of SKOV3 and A2780 as models of high-grade serous carcinoma. The DNA copy number of 10 ovarian cancer cell lines was examined and changes in copy number of genes whose expression is assumed to be critical to the phenotype of ovarian clear cell carcinoma was evaluated. Copy number data was estimated from signal intensity on Affmetrix SNP 6.0 arrays. Copy number ratio values were generated in Partek Genomics Suite (v 6.6) using a Partek corporation distributed baseline file of normal (2N) genomic DNA and default parameters. Post import values were corrected for localized GC content using the inbuilt Partek feature based on methods described in Diskin et al. (Nucleic Acids Research. 2008. 36:19). The characteristic "literature reported histotype" is the reported histological subtype for each cell line from the originating laboratory or cell bank (repository). The characteristic "Predicted histology" is based on parameters described in Anglesio et al. (PLOS ONE 2013. in press), including immunohistochemical phenotype, presence of typical mutations, consistency in growth characteristics, and DNA copy number. All cell lines were grown under recomended conditions, collected near confluence (80%) and not subjected to any experimental treatments or modifications.
2013-08-01 | E-GEOD-48351 | biostudies-arrayexpress
Project description:Ovarian clear cell carcinoma (OCCC) shows unique clinical features including an association with endometriosis and poor prognosis. We previously reported that the contents of endometriotic cysts, especially high concentrations of free iron, are a possible cause of OCCC carcinogenesis through iron-induced persistent oxidative stress. In this study, we conducted gene expression microarray analysis using 38 ovarian cancer cell lines and identified genes commonly expressed in both OCCC cell lines and clinical samples, which comprise an OCCC gene signature. The OCCC signature reproducibly predicts OCCC specimens in other microarray data sets, suggesting that this gene profile reflects the inherent biological characteristics of OCCC. The OCCC signature contains known markers of OCCC, such as hepatocyte nuclear factor-1b (HNF-1b) and versican (VCAN), and other genes that reflect oxidative stress. Expression of OCCC signature genes was induced by treatment of immortalized ovarian surface epithelial cells with the contents of endometriotic cysts, indicating that the OCCC signature is largely dependent on the tumor microenvironment. Induction of OCCC signature genes is at least in part epigenetically regulated, as we found hypomethylation of HNF-1b and VCAN in OCCC cell lines. This genomewide study indicates that the tumor microenvironment induces specific gene expression profiles that contribute to the development of distinct cancer subtypes.
2011-05-16 | GSE29175 | GEO
Project description:Ovarian clear cell carcinoma (OCCC) shows unique clinical features including an association with endometriosis and poor prognosis. We previously reported that the contents of endometriotic cysts, especially high concentrations of free iron, are a possible cause of OCCC carcinogenesis through iron-induced persistent oxidative stress. In this study, we conducted gene expression microarray analysis using 38 ovarian cancer cell lines and identified genes commonly expressed in both OCCC cell lines and clinical samples, which comprise an OCCC gene signature. The OCCC signature reproducibly predicts OCCC specimens in other microarray data sets, suggesting that this gene profile reflects the inherent biological characteristics of OCCC. The OCCC signature contains known markers of OCCC, such as hepatocyte nuclear factor-1b (HNF-1b) and versican (VCAN), and other genes that reflect oxidative stress. Expression of OCCC signature genes was induced by treatment of immortalized ovarian surface epithelial cells with the contents of endometriotic cysts, indicating that the OCCC signature is largely dependent on the tumor microenvironment. Induction of OCCC signature genes is at least in part epigenetically regulated, as we found hypomethylation of HNF-1b and VCAN in OCCC cell lines. This genomewide study indicates that the tumor microenvironment induces specific gene expression profiles that contribute to the development of distinct cancer subtypes. Affymetrix Human Genome U133A 2.0 Array was conducted for 38 ovarian cancer cell lines (13 OCCC cell lines and 25 non-OCCC cell lines). All specimens were arrayed in parallel and used for RMA normalization.
2011-05-16 | E-GEOD-29175 | biostudies-arrayexpress
Project description:H3K27Ac of Ovarian Cancer Cell Lines
| PRJNA657252 | ENA
Project description:Advanced ovarian cancer is the most lethal gynecologic malignancy in the United States. Currently patients are treated by surgical cytoreductive surgery with the aim of reducing tumor burden to microscopic disease followed by adjuvant combined treatment with a platinum and taxane containing chemotherapy, which affords 80% of patients an initial complete response. However, Abdominal and pelvic recurrence rates are high and response to further chemotherapy is limited. Attempts at introducing biologic therapeutic agents to improve outcome in this disease are ongoing, while prognostic or predictive biomarkers that can stratify patients for treatment are still lacking. Using a 60-mer 22K oligonucleotide-based array comparative genome hybridization (CGH) platform combined with DNA isolated from microdissected tumor tissue samples, Birrer et. al. reported that the amplification of 5q31-35.3 in ovarian cancer cells is a negative prognostic indicator for patients with advanced stage high-grade serous ovarian cancer (HGSC). Further studies showed that fibroblast growth factor 1 (FGF1) located in the amplicon, may be one of the driving genes for ovarian cancer progression (Birrer et. al., 2007). Besides FGF1, located on the same amplicon is one of its receptors fibroblast growth factor receptor 4 (FGFR4), suggesting that it may also be amplified and may be another driving gene involved in ovarian cancer pathogenesis.In this study, we used microarrays to explore and compare gene expression profiles between FGFR4 knock down ovarian cancer cell lines and their corresponding parental cell lines. Two high grade serous ovarian cancer cell lines: SKOV3 and OVCA432 were selected for this study. For each of the cell lines, two different siRNA sequences which both target human FGFR4 were used. While a non-target scramble siRNA sequence was used as control. Ovarian cancer cells were transfected with siRNA using lipofectamine (Invitrogen). RNA extraction was performed 72 hours post-transfection, followed by hybridization on Affymetrix microarrays.
2013-12-03 | E-GEOD-34828 | biostudies-arrayexpress