MiROvaR, a microRNA-based predictor of early relapse for ovarian cancer patients [validation set; OC133]
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE73582 | GEO | 2016/10/31
SECONDARY ACCESSION(S): PRJNA297361
REPOSITORIES: GEO
Similar Datasets
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:MiROvaR, a microRNA-based predictor of early relapse for ovarian cancer patients
| PRJNA297358 | ENA
Project description:Integration of several ovarian cancer datasets to identify a reproducible predictors of survival Four microarray datasets from different institutions were reprocessed in a uniform manner, into a single training dataset. Survival analysis was performed and a validation cohort (61 patients from 3 institutions) was profiled using a custom array to confirm the prognostic value of the predictors. The four datasets were obtained from the following reports: Spentzos D, Levine DA, Ramoni MF, et al. Gene expression signature with independent prognostic significance in epithelial ovarian cancer. J Clin Oncol 2004;22:4700-10 Bild AH, Yao G, Chang JT, et al. Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature 2006;439:353-7 Marquez RT, Baggerly KA, Patterson AP, et al. Patterns of gene expression in different histotypes of epithelial ovarian cancer correlate with those in normal fallopian tube, endometrium, and colon. Clin Cancer Res 2005;11:6116-26 Zhang L, Volinia S, Bonome T, et al. Genomic and epigenetic alterations deregulate microRNA expression in human epithelial ovarian cancer. Proc Natl Acad Sci U S A 2008;105:7004-9 61 samples
2011-06-15 | E-GEOD-19161 | biostudies-arrayexpress
Project description:Integration of several ovarian cancer datasets to identify a reproducible predictors of survival Four microarray datasets from different institutions were reprocessed in a uniform manner, into a single training dataset. Survival analysis was performed and a validation cohort (61 patients from 3 institutions) was profiled using a custom array to confirm the prognostic value of the predictors. The four datasets were obtained from the following reports: Spentzos D, Levine DA, Ramoni MF, et al. Gene expression signature with independent prognostic significance in epithelial ovarian cancer. J Clin Oncol 2004;22:4700-10 Bild AH, Yao G, Chang JT, et al. Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature 2006;439:353-7 Marquez RT, Baggerly KA, Patterson AP, et al. Patterns of gene expression in different histotypes of epithelial ovarian cancer correlate with those in normal fallopian tube, endometrium, and colon. Clin Cancer Res 2005;11:6116-26 Zhang L, Volinia S, Bonome T, et al. Genomic and epigenetic alterations deregulate microRNA expression in human epithelial ovarian cancer. Proc Natl Acad Sci U S A 2008;105:7004-9
2011-06-15 | GSE19161 | GEO
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:Epithelial ovarian cancer is the leading cause of death from gynecological malignancies. Currently platinum-based chemotherapy, coupled with a taxane based drug is the primary treatment for ovarian cancer. Approximately 25% of patients either present with or rapidly develop resistance to platinum based chemotherapy and all recurrent tumors ultimately become resistant. Epigenetic modifications have been associated with tumor formation and progression and may contribute to therapy response. We performed a methylation screen on a set of tumors and have found a number of genes and family members differentially methylated between resistant patients and sensitive patients. Here we show that loss of expression of CHD3, a member of the Mi-2/NuRD complex, causes increased resistance to platinum chemotherapy drugs. Additionally, ovarian cell lines transcriptionally silenced for CHD3 are more invasive, have migratory ability, and display a transformed epithelial to mesenchymal (EMT) phenotype. Taken together, we provide the first evidence of a role for CHD3 as an important epigenetic regulator of chemoresistance in ovarian cancer and hypothesize EMT as one of the underlying mechanisms. Furthermore, CHD3 expression might represent a therapy response predictor and could be a future therapeutic target for ovarian cancer. We have developed a method to profile genome wide methylation. 71 ovarian tumor samples and 9 normal tissue samples from individuals were analyzed for CpG methylation. Some of these regions were validated for their methylation as a proof of principle for the method. Kamalakaran S., et. al. Mol Oncol. 2011;5:77-92 (PMID: 21169070).
2012-05-14 | E-GEOD-33011 | biostudies-arrayexpress
Project description:PURPOSE: To develop a predictive test for response and survival following neoadjuvant taxane-anthracycline chemotherapy for HER2-negative invasive breast cancer. METHODS: We developed a microarray-based gene expression test from pre-treatment tumor biopsies (310 patients) to predict favorable outcome based on estrogen receptor (ER) status,pathologic response to chemotherapy, 3-year disease outcomes, and sensitivity to endocrine therapy. Tumors were classified as treatment-sensitive if predicted to have pathologic response (and not resistance) to chemotherapy, or sensitive to endocrine therapy. We tested predictive accuracy, with 95% confidence interval (CI), for pathologic response (PPV, positive predictive value), distant relapse-free survival (DRFS), and absolute risk reduction at median follow-up in 198 other patients. Independence from clinical-pathologic factors was assessed in a multivariate Cox regression analysis based on the likelihood ratio test. Other evaluable, published response predictors (genomic grade index (GGI), intrinsic subtype (PAM50), pCR predictor (DLDA30)) were compared. Neoadjuvant study of 310 HER2-negative breast cancer cases treated with taxane-anthracycline chemotherapy pre-operatively and endocrine therapy if ER-positive. Response was assessed at the end of neoadjuvant treatment and distant-relapse-free survival was followed for at least 3 years post-surgery.
2011-05-11 | E-GEOD-25055 | biostudies-arrayexpress
Project description:PURPOSE: To develop a predictive test for response and survival following neoadjuvant taxane-anthracycline chemotherapy for HER2-negative invasive breast cancer. METHODS: We developed a microarray-based gene expression test from pre-treatment tumor biopsies (310 patients) to predict favorable outcome based on estrogen receptor (ER) status,pathologic response to chemotherapy, 3-year disease outcomes, and sensitivity to endocrine therapy. Tumors were classified as treatment-sensitive if predicted to have pathologic response (and not resistance) to chemotherapy, or sensitive to endocrine therapy. We tested predictive accuracy, with 95% confidence interval (CI), for pathologic response (PPV, positive predictive value), distant relapse-free survival (DRFS), and absolute risk reduction at median follow-up in 198 other patients. Independence from clinical-pathologic factors was assessed in a multivariate Cox regression analysis based on the likelihood ratio test. Other evaluable, published response predictors (genomic grade index (GGI), intrinsic subtype (PAM50), pCR predictor (DLDA30)) were compared. Neoadjuvant validation cohort of 198 HER2-negative breast cancer cases treated with taxane-anthracycline chemotherapy pre-operatively and endocrine therapy if ER-positive. Response was assessed at the end of neoadjuvant treatment and distant-relapse-free survival was followed for at least 3 years post-surgery.
2011-05-11 | E-GEOD-25065 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the following subset Series: GSE25055: Discovery cohort for genomic predictor of response and survival following neoadjuvant taxane-anthracycline chemotherapy in breast cancer GSE25065: Validation cohort for genomic predictor of response and survival following neoadjuvant taxane-anthracycline chemotherapy in breast cancer Refer to individual Series
2011-05-11 | E-GEOD-25066 | biostudies-arrayexpress
Project description:MiROvaR, a microRNA-based predictor of early relapse for ovarian cancer patients [training set OC179]
| PRJNA297360 | ENA