Transcriptomics,Genomics

Dataset Information

27

Clinical Validation of Chemotherapy Predictors Developed on Global MicroRNA Expression in the NCI60 Cell Line Panel Tested in Ovarian Cancer.


ABSTRACT: summary Ovarian cancer is the leading cause of death among gynecologic malignancies. This is partly due to a non-durable response to chemotherapy. Prediction of resistance to chemotherapy could be a key role in more personalized treatment. In the current study we aimed to examine if microRNA based predictors could predict resistance to chemotherapy in ovarian cancer, and to investigate if the predictors could be prognostic factors for progression free and overall survival. Methods Predictors of chemotherapy-resistance were developed based on correlation between miRNA expression and differences in measured growth inhibition in a variety of human cancer cell lines in the presence of Carboplatin, Paclitaxel and Docetaxel (deposited under accession number E-MTAB-327 in the ArrayExpress database of the European Bioinformatics Institute, 2012). These predictors were then, retrospectively, blindly validated in a cohort of 170 epithelial ovarian cancer patients treated with Carboplatin and Paclitaxel or Docetaxel as first line treatment. Results In a multivariate cox proportional analysis the predictors of chemotherapy-resistance were not able to predict time to progression after end of chemotherapy (hazard ratio: 0.64, 95% CI: 0.36 – 1.12, P=0.117). However, in a multivariate logistic analysis, where time to progression was considered as either more or less than 6 months, the predictors match clinical observed chemotherapy-resistance (odds ratio: 0.19, 95% CI: 0.05-0.73, P=0.015). Neither univariate nor multivariate, time-dependent, cox analysis for progression free survival (PFS) or overall survival (OS) in all 170 patients showed to match predicted resistance to chemotherapy (PFS: hazard ratio: 0.69, 95% CI: 0.40-1.19, P=0.183, OS: hazard ratio: 0.76, 95% CI: 0.42-1.40, P=0.386). Conclusion In the current study, microRNA based predictors of chemotherapy-resistance did not demonstrate any convincing correlation to clinical observed chemotherapy-resistance, progression free survival, or overall survival, in patients with epithelial ovarian cancer. However the predictors did reflect relapse more or less than 6 months. Overall design: A total of 198 epithelial ovarian cancer patients were analyzed for miRNA expression. Of these, detailed clinical information were available for 170 patients. Predictors of chemotherapy-resistance were developed based on correlation between miRNA expression and differences in measured growth inhibition in a variety of human cancer cell lines in the presence of Carboplatin, Paclitaxel and Docetaxel. These predictors were then, retrospectively, blindly validated in the cohort of 170 epithelial ovarian cancer patients treated with Carboplatin and Paclitaxel or Docetaxel as first line treatment. Under EU data protection legislation it is a violation of patient privacy to publish de-identified individual patient information. Therefore, clinical data (eg, chemotherapy-resistance, progression free survival, or overall survival discussed in the summary etc.) were not provided.

INSTRUMENT(S): [miRNA-1] Affymetrix Multispecies miRNA-1 Array

SUBMITTER: Anker Hansen  

PROVIDER: GSE94320 | GEO | 2017-02-01

SECONDARY ACCESSION(S): PRJNA369375

REPOSITORIES: GEO

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Publications

Identification and validation of potential prognostic and predictive miRNAs of epithelial ovarian cancer.

Prahm Kira Philipsen KP   Høgdall Claus C   Karlsen Mona Aarenstrup MA   Christensen Ib Jarle IJ   Novotny Guy Wayne GW   Høgdall Estrid E  

PloS one 20181126 11


BACKGROUND:Ovarian cancer is the leading cause of death by gynecologic cancers in the Western world. The aim of the study was to identify microRNAs (miRNAs) associated with prognosis and/or resistance to chemotherapy among patients with epithelial ovarian cancer. METHODS:Using information from the Pelvic Mass Study we identified a cohort of women with epithelial ovarian cancer. Tumor tissues were then collected and analyzed by global miRNA microarrays. MiRNA profiling was then linked to survival  ...[more]

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