Project description:Despite a pathological complete response, risk-of-relapse remains a challenge for most of epithelial ovarian cancer (EOC) patients and an ad-hoc predictor can be a valuable clinical tool. We developed a 35 miRNAs-based predictor of Risk of Ovarian Cancer Relapse (MiROvaR) using a training set of patients from MITO-2 (Multicentre Italian Trials in Ovarian Cancer-2; Pignata S et al. J Clin Oncol. 2011 Sep 20). MiROvaR performance was confirmed in two independent validation cohorts.
Project description:Despite a pathological complete response, risk-of-relapse remains a challenge for most of epithelial ovarian cancer (EOC) patients and an ad-hoc predictor can be a valuable clinical tool. We developed a 35 miRNAs-based predictor of Risk of Ovarian Cancer Relapse (MiROvaR) using a training set of patients from MITO-2 (Multicentre Italian Trials in Ovarian Cancer-2; Pignata S et al. J Clin Oncol. 2011 Sep 20). MiROvaR performance was confirmed in two independent validation cohorts.
Project description:In order to investigate miRNA alterations associated to early relapse in ovarian cancer patients, we analyzed miRNA expression profile in a training set of 55 surgical specimens including 30 early relapsing and 25 late relapsing patients.
Project description:This SuperSeries is composed of the following subset Series: GSE25202: microRNA alterations associated to clinical response in advanced stage ovarian cancer patients (training set). GSE25203: microRNA alterations associated to clinical response in advanced stage ovarian cancer patients (test set). Refer to individual Series
Project description:In order to investigate miRNA alterations associated to early relapse in ovarian cancer patients, we analyzed miRNA expression profile in a training set of 55 surgical specimens including 30 early relapsing and 25 late relapsing patients. Patients were selected on the basis of residual disease after primary surgery and time to relapse (TTR) after front-line chemotherapy. For training set, a selection of the outliers concerning TTR was made: as early relapsing were defined optimally debulked (OD) patients with a TTR< 12 months and sub-optimally debulked (SOD) patients with TTR< 6 months; late relapsing were defined OD patients with TTR> 36 months and SOD patients with TTR> 12 months. Clinical codes: Histotype: according to International Federation of Gynecological and Obstetrics guidelines Stage: according to International Federation of Gynecological and Obstetrics guidelines Grading: according to International Federation of Gynecological and Obstetrics guidelines Debulking: NED: not evident disease; mRD: minimal residual disease; GRD: gross residual disease Therapy code: P: Platinum without taxanes; PT: Platinum/paclitaxel End Point: Early: relapse whithin 12 and 6 months from the end of therapy for optimally (NED+ mRD) and sub-optimally (GRD) debulked patients respectively. Late: median time to relapse 48 and 34 months from the end of therapy for optimally and sub-optimally debulked patients respectively.
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
Project description:A set of 45 surgical specimens has been profiled for miRNA expression to validate miRNA alterations associated to early relapse in advanced stage ovarian cancer patients.
