Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA142789 | ENA |
REPOSITORIES: ENA
Similar Datasets
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
2012-03-09 | E-GEOD-25204 | biostudies-arrayexpress
Project description:microRNA alterations associated to clinical response in advanced stage ovarian cancer patients (test set)
| PRJNA142791 | ENA
Project description:microRNA alterations associated to early relapse in advanced stage ovarian cancer patients (validation set)
| PRJNA280993 | ENA
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. Fresh frozen samples were collected from a series of consecutive patients with high-grade advanced stage ovarian cancer who underwent primary surgery at INT-Milan. After surgery all patients received postoperative platinum-based chemotherapy. All patients signed an Institutional Review Board approved consent for bio-banking, clinical data collection and molecular analysis. Clinical codes: Histotype: according to WHO classification guidelines Stage: according to International Federation of Gynecological and Obstetrics (FIGO) guidelines Grading: according to WHO classification guidelines Debulking: NED: not evident disease; mRD: minimal residual disease; GRD: gross residual disease Therapy code: P: Platinum without taxanes; PT: Platinum/paclitaxel
2015-04-30 | E-GEOD-67819 | biostudies-arrayexpress
Project description:Objectives: MicroRNAs (miRNAs) are a class of small non-coding RNAs that negatively regulate gene expression primarily through post-transcriptional modification. We tested the hypothesis that miRNA expression is associated with overall survival in advanced ovarian cancer. Methods: Cases included newly diagnosed patients with stage III or IV serous ovarian cancer. RNA from a training set of 62 cases was hybridized to an miRNA microarray containing 470 mature human transcripts. Cox regression was performed to identify miRNAs associated with overall survival. External validation was performed using quantitative RT-PCR miRNA assays in an independent test set of 123 samples. MiRNA targets and associated biologic pathways were predicted in silico. Results: Of all patients, 80% had high-grade, stage IIIC tumors and 64% underwent optimal cytoreduction. The median survival for the entire cohort was 49 ± 4 months. The training set identified 3 miRNAs associated with survival - miR-337, miR-410, and miR-645. An miRNA signature containing miR-410 and miR-645 was most strongly associated with overall survival in the training set (HR=2.96, 95% CI: 1.51-5.78). This miRNA survival signature (MiSS) was validated in the test set (HR=1.71, 95% CI: 1.05-2.78). The MiSS was independent of FIGO stage and surgical debulking. Conclusions: The data suggest that an MiSS that contains miR-410 and miR-645 is negatively associated with overall survival in advanced serous ovarian cancer. This signature, when further validated, may be useful in individualizing care for the ovarian cancer patient. Pathway analyses identify biologically plausible mechanisms. Cases included newly diagnosed patients with stage III or IV serous ovarian cancer. RNA from a training set of 62 cases was hybridized to an miRNA microarray containing 470 mature human transcripts. Cox regression was performed to identify miRNAs associated with overall survival.
2011-02-15 | E-GEOD-27290 | biostudies-arrayexpress
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.
2015-04-30 | GSE67819 | GEO
Project description:Objectives: MicroRNAs (miRNAs) are a class of small non-coding RNAs that negatively regulate gene expression primarily through post-transcriptional modification. We tested the hypothesis that miRNA expression is associated with overall survival in advanced ovarian cancer. Methods: Cases included newly diagnosed patients with stage III or IV serous ovarian cancer. RNA from a training set of 62 cases was hybridized to an miRNA microarray containing 470 mature human transcripts. Cox regression was performed to identify miRNAs associated with overall survival. External validation was performed using quantitative RT-PCR miRNA assays in an independent test set of 123 samples. MiRNA targets and associated biologic pathways were predicted in silico. Results: Of all patients, 80% had high-grade, stage IIIC tumors and 64% underwent optimal cytoreduction. The median survival for the entire cohort was 49 ± 4 months. The training set identified 3 miRNAs associated with survival - miR-337, miR-410, and miR-645. An miRNA signature containing miR-410 and miR-645 was most strongly associated with overall survival in the training set (HR=2.96, 95% CI: 1.51-5.78). This miRNA survival signature (MiSS) was validated in the test set (HR=1.71, 95% CI: 1.05-2.78). The MiSS was independent of FIGO stage and surgical debulking. Conclusions: The data suggest that an MiSS that contains miR-410 and miR-645 is negatively associated with overall survival in advanced serous ovarian cancer. This signature, when further validated, may be useful in individualizing care for the ovarian cancer patient. Pathway analyses identify biologically plausible mechanisms.
2011-02-15 | GSE27290 | GEO
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.
2012-03-09 | GSE25202 | GEO
Project description:Ovarian cancer is the leading cause of death in gynaecological malignancies in women. However, currently there are no clinical or pathologic parameters available that can reliably predict clinical outcome. In a previously published pilot study we explored the performance of microarrays in predicting clinical behaviour of ovarian tumours. For this purpose we performed microarray analysis on 20 patients and estimated that we could predict disease stage with 100% accuracy and the response to platin-based chemotherapy with 76.92% accuracy using leave-one-out cross validation techniques in combination with Least Squares Support Vector Machines (LS-SVMs). In the current study we prospectively evaluate models, built on the pilot data set, on a set of 49 new patients. Principal component analysis showed that the gene expression data from stage I, platin-sensitive advanced stage and platin-resistant advanced stage tumours in the prospective study did not correspond to their respective classes in the pilot study. Additionally, LS-SVM models built using the data from the pilot study, only misclassified one of four stage I tumours and correctly classified all 45 advanced stage tumours but this model was not able to predict resistance to platin-based chemotherapy. We discuss possible reasons for prospective failure of these models and conclude that existing results based on gene expression patterns of ovarian tumours need to be thoroughly scrutinized before this technology could be considered ready for clinical use.
2007-12-31 | E-MEXP-995 | biostudies-arrayexpress