RNA differential expression between OAW42 ovarian cancer cells and its chemoresistant counterpart OAW42-R
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PROVIDER: PRJNA682177 | ENA |
REPOSITORIES: ENA
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Project description:We were interested in exploring transcriptional differences between the two cell lines Transcriptional differences would inform about the process of acquiring resistance to cisplatin, common therapeutic treatment in ovarian cancer
2020-12-03 | GSE162538 | GEO
Project description:Whole genome characterisation of chemoresistant ovarian cancer
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Project description:The patient-derived xenograft (PDX) model retains the heterogeneity of patient tumors, allowing a means to not only examine efficacy of a therapy across a population, but also study crucial aspects of cancer biology in response to treatment. Herein we describe the development and characterization of an ovarian-PDX model in order to study the development of chemoresistance. We demonstrate that PDX tumors are not simply composed of tumor-initiating cells, but recapitulate the original tumor’s heterogeneity, oncogene expression profiles, and clinical response to chemotherapy. Combined carboplatin/paclitaxel treatment of PDX tumors enriches the cancer stem cell populations, but persistent tumors are not entirely composed of these populations. RNA-Seq analysis of treated PDX tumors compared to untreated tumors demonstrates a consistently contrasting genetic profile after therapy, suggesting similar, but few, pathways are mediating chemoresistance. The pathways most significantly altered included Protein Kinase A signaling, GNRH signaling, and sphingosine-1-phosphate signaling. Pathways and genes identified by this methodology represent novel approaches to targeting the chemoresistant population in ovarian cancer 6 pairs of Patient-Derived Xenografts (PDX) were ananlyzed using RNA-seq for a total of 12 samples. Each pair consists of a treated and untreated PDX of ovarian cancer. Treated Ovarian cancer PDXs were treated with 4 weeks of a combination of carboplatin and taxol. RNA was isolated and converted to cDNA. RNA-seq was conductred on the Illumina HiSeq 2000 with 50 bp paired end sequencing
2015-06-17 | E-GEOD-58586 | biostudies-arrayexpress
Project description:Chemotherapy (CT) resistance in ovarian cancer is broad and encompasses diverse, unrelated drugs, suggesting more than one mechanism of resistance. We aimed to analyze the gene expression patterns in primary serous epithelial ovarian cancer (EOC) samples displaying different responses to first-line CT in an attempt to identify specific molecular signatures associated with response to CT. Initially, the expression profiles of 15 chemoresistant serous EOC tumors [time to recurrence (TTR) ≤6 months] and 10 chemosensitive serous EOC tumors (TTR ≥30 months) were independently analyzed which allowed the identification of specific sets of differentially expressed genes that might be functionally implicated in the evolution of the chemoresistant or the chemosensitive phenotype. Our data suggest that the intrinsic chemoresistance in serous EOC cells may be attributed to the combined action of different molecular mechanisms and factors linked with drug influx and efflux and cell proliferation, as possible implications of other molecular events including altered metabolism, apoptosis and inflammation cannot be excluded. Next, gene expression comparison using hierarchical clustering clearly distinguished chemosensitive and chemo- resistant tumors from the 25 serous EOC samples (training set), and consecutive class prediction analysis was used to develop a 43-gene classifier that was further validated in an independent cohort of 15 serous EOC patients and 2 patients with other ovarian cancer histotypes (test set). The 43-gene predictor set properly classified serous EOC patients at high risk for early (≤22 months) versus late (>22 months) relapse after initial CT. Thus, gene expression array technology can effectively classify serous EOC tumors according to CT response. The proposed 43-gene model needs further validation. 2 condition experiment: chemoresistant clinical samples versus chemosensitive samples
2011-07-23 | E-GEOD-28739 | biostudies-arrayexpress
Project description:The patient-derived xenograft (PDX) model retains the heterogeneity of patient tumors, allowing a means to not only examine efficacy of a therapy across a population, but also study crucial aspects of cancer biology in response to treatment. Herein we describe the development and characterization of an ovarian-PDX model in order to study the development of chemoresistance. We demonstrate that PDX tumors are not simply composed of tumor-initiating cells, but recapitulate the original tumor’s heterogeneity, oncogene expression profiles, and clinical response to chemotherapy. Combined carboplatin/paclitaxel treatment of PDX tumors enriches the cancer stem cell populations, but persistent tumors are not entirely composed of these populations. RNA-Seq analysis of treated PDX tumors compared to untreated tumors demonstrates a consistently contrasting genetic profile after therapy, suggesting similar, but few, pathways are mediating chemoresistance. The pathways most significantly altered included Protein Kinase A signaling, GNRH signaling, and sphingosine-1-phosphate signaling. Pathways and genes identified by this methodology represent novel approaches to targeting the chemoresistant population in ovarian cancer
2015-06-17 | GSE58586 | GEO
Project description:Two expression profilings were conducted in order to identify drug-associated genes in ovarian cancers. The first expression profiling was performed between RNAs from chemosensitive ovarian cancers and chemoresistant ovarian cancers. The second analysis was using a drug sensitive ovarian cancer cell line and a multi-drug resistant ovarian cancer cell line.
2010-06-30 | E-GEOD-2058 | biostudies-arrayexpress
Project description:Chemoresistance remains the major barrier to effective ovarian cancer treatment. The molecular features and associated biological functions of this phenotype remain poorly understood. We developed carboplatin resistant cell line models using OVCAR5 and CaOV3 cell lines with the aim of identifying chemoresistance-specific molecular features. Mass spectrometry analysis was used to analyse the metabolome of these cell lines and was able to separate these populations based on their molecular features. It revealed signaling and metabolic perturbations in chemoresistant cell lines. A comprehensive analysis of a larger patient cohort, including advanced in vitro and in vivo models, promises to help better understand the molecular mechanisms of chemo-resistance and associated enhancement of migration and invasion.
2021-12-05 | ST002010 | MetabolomicsWorkbench
Project description:Two expression profilings were conducted in order to identify drug-associated genes in ovarian cancers. The first expression profiling was performed between RNAs from chemosensitive ovarian cancers and chemoresistant ovarian cancers. The second analysis was using a drug sensitive ovarian cancer cell line and a multi-drug resistant ovarian cancer cell line. Keywords: other
2005-12-11 | GSE2058 | GEO
Project description:Ovarian tumors of the borderline subtype (BOL) are epithelial cancers tumors with very specific features. They rarely progress towards malignancy but their evolutionary profile, although remaining local, is distinct from that of benign cancers. At the cellular level, BOL are undistinguishable from malignant tumors (cytonuclear abnormalities, abnormal mitoses, anarchical proliferation), however they never invade the stroma, which makes them clearly distinct from carcinoma. BOL tumors are of good prognosis. Even when they relapse, these tumors remain local and are, most of the time, not invasive. Thus, comparing BOL with ovarian adenocarcinomas (ADK) is of major interest to decipher potential gene alterations underlying the process of invasion, a key step of oncogenesis. In this study, 20 BOL and 19 ADK were recruited at the Gustave Roussy, frozen and analyzed by pathologists. RNA extraction followed by gene expression analysis, in association with clinical and histological data of these two groups of tumors, may provide a gene signature characterizing ovarian cancer invasion. Gene expression was performed in dual color on Agilent Whole Human Genome Oligo Microarray A-AGIL11(design 012391). Differential expression has been analysed between the 2 sets of ovary samples : 19 ADK and 20 BOL labelled in one color (Cy5) versus a pool of all samples (Cy3).
2022-12-31 | E-MTAB-11177 | biostudies-arrayexpress
Project description:Ovarian cancer is one of the most lethal gynaecological malignancies among female population. The high mortality rate of this disease is due to its poor prognosis and most patients present at an advanced stage accompanied with metastasis. The frequent tumor recurrence rate associated with metastasis and chemoresistance are the major obstacles in clinical management of the disease. Different from other solid tumors, ovarian cancer perfers transcoelomic metastasis amd mounting evidence has suggested ovarian cancer patients who have peritoneal metastasis are usually poor prognosis and highly chemoresistant recurrence. In this study, we examined the differential gene expression profile between the primary tumors and their paired metastastic lesions with a view to discover novel target therapies in combating ovarian cancer.
2021-06-26 | GSE178913 | GEO