MiROvaR, a microRNA-based predictor of early relapse for ovarian cancer patients
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PROVIDER: PRJNA297358 | ENA |
REPOSITORIES: ENA
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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.
2016-10-31 | GSE73581 | GEO
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.
2016-10-31 | GSE73582 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2016-10-31 | GSE73584 | GEO
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: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:We used copy number analysis of paired primary and relapse ovarian tumours to identify genes associated with acquired resistance
2012-06-21 | GSE38787 | GEO
Project description:Stage 1 epithelial ovarian cancer (EOC) has generally a favorable prognosis, but a significant percentage (30%) of patients relapse after treatment and die. The currently available markers are neither sensitive nor specific enough to predict the risk of relapse, thus low risk and high risk patients are treated in the same manner.
This study is a characterization of microRNA and microRNA isoforms (isomiR) in a cohort of Stage 1 epithelial ovarian cancer samples collected from two independent tissue collections, as part of an effort to find new biomarkers with diagnostic and prognostic value.
| EGAS00001006617 | EGA
Project description:We used copy number analysis of paired primary and relapse ovarian tumours to identify genes associated with acquired resistance Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from ovarian tumours. Copy number profiles of 22 primary and matched ascites samples. Multiple biopsies of four samples were also profiled to assess the intra tumour heterogeneity in samples.
2012-06-20 | E-GEOD-38787 | biostudies-arrayexpress
Project description:Background: We have previously shown that the Gene expression Grade Index (GGI) was able to identify two subtypes of estrogen receptor (ER)-positive tumors that were associated with statistically distinct clinical outcomes in both untreated and tamoxifen-treated patients. Here, we aim to investigate the ability of the GGI to predict relapses in postmenopausal women who were treated with tamoxifen (T) or letrozole (L) within the BIG 1-98 trial. Methods: We generated gene expression profiles (Affymetrix) and computed the GGI for a matched, case-control sample of patients enrolled in the BIG 1-98 trial from the two hospitals where frozen samples were available. All relapses (cases) were identified from patients randomized to receive monotherapy or from the switching treatment arms for whom relapse occurred before the switch. Each case was randomly matched with four controls based upon nodal status and treatment (T or L). The prognostic value of GGI was assessed as a continuous predictor and divided at the median. Predictive accuracy of GGI was estimated using time-dependent area under the curve (AUC) of the ROC curves. Results: Frozen samples were analyzable for 48 patients (10 cases and 38 controls). Seven of the 10 cases had been assigned to receive L. Cases and controls were comparable with respect to menopausal and nodal status, local and chemotherapy, and HER2 positivity. Cases were slightly older than controls and had a larger proportion of large, poorly differentiated ER+/PgR- tumors. The GGI was significantly and linearly related to risk of relapse: each 10-unit increase in GGI resulted in an increase of approximately 11% in the hazard rate (p=0.02). Within the subgroups of patients with node-positive disease or who were treated with L, the hazard of relapse was significantly greater for patients with GGI at or above the median. AUC reached a maximum of 78% at 27 months. Conclusions: This analysis supports the GGI as a good predictor of relapse for ER-positive patients, even among patients who receive L. Validation of these results, in a larger series from BIG 1-98, is planned using the simplified GGI represented by a smaller set of genes and tested by qRT-PCR on paraffin-embedded tissues. Test whether the Gene expression Grade Index (GGI) is a potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 1-98 trial. 55 microarray experiments from primary breast tumors of endocrine-treated patients. No replicate, no reference sample.
2009-07-09 | E-GEOD-16391 | biostudies-arrayexpress
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.
2008-06-29 | E-GEOD-10150 | biostudies-arrayexpress