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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.

ORGANISM(S): synthetic construct Homo sapiens

PROVIDER: GSE94320 | GEO | 2017/02/01

SECONDARY ACCESSION(S): PRJNA369375

REPOSITORIES: GEO

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Project description:To identify and evaluate the prognostic ability of progression-free survival-related profile for advanced-stage ovarian cancer, advanced-stage serous ovarian cancer tissues from 110 patients who received primary surgery and a platinum/taxane-based chemotherapy were profiled using oligonucleotide microarrays of more than 40,000 transcripts. We first selected 88 genes by a univariate Cox proportional hazard analysis (p<0.01) and next optimized regression coefficients by ridge regression model using 10-fold cross-validation. The prognostic index was independently associated with PFS time compared to other clinical factors in multivariate analysis [hazard ratio (HR), 3.72; 95% confidence interval (CI), 2.66–5.43; p,0.0001]. In an external dataset, multivariate analysis revealed that this prognostic index was significantly correlated with PFS time (HR, 1.54; 95% CI, 1.20–1.98; p = 0.0008). Furthermore, the correlation between the prognostic index and overall survival time was confirmed in the two independent external datasets (log rank test, p = 0.0010 and 0.0008). In multivariable analysis, our prognostic index was independently associated with progression-free survival times compared to other clinical factors (p<0.001). Furthermore, the prognostic ability of our prognostic index was validated in external, publicly available dataset (n = 87), and was proved in multivariate analysis (p = 0.0032). These results suggest that disease progression or recurrence of advanced-stage serous ovarian cancer can be predicted by gene expression profile. The prognostic ability of our index based on the 88-gene expression profile in ridge regression Cox hazard model was shown to be independent of other clinical factors in predicting cancer prognosis across two distinct datasets. Further study will be necessary to improve predictive accuracy of the prognostic index toward clinical application for evaluation of the risk of recurrence in patients with advanced-stage serous ovarian cancer.

Project description:Introduction: Effective predictive biomarkers for selection of patients benefiting from adjuvant platinum-based chemotherapy in non-small cell lung cancer (NSCLC) are needed. Based on a previously validated methodology, molecular profiles of predicted sensitivity in two patient cohorts are presented. Methods: The profiles are correlations between in vitro sensitivity to cisplatin and vinorelbine and baseline mRNA expression of the 60 cell lines in the National Cancer Institute panel. An applied clinical samples filter focused the profiles to clinically relevant genes. The profiles were tested on 1) snap-frozen tumors from 133 patients with completely resected stage 1B-2 NSCLC randomized to adjuvant cisplatin and vinorelbine (ACV, n=71) or no adjuvant treatment (OBS, n=62) [GSE14814] and 2) formalin-fixed paraffin-embedded (FFPE) pre-treatment tumors from 95 patients with completely resected stage 1A-3B NSCLC receiving adjuvant cisplatin and vinorelbine. Results: The combined cisplatin and vinorelbine profiles showed: 1) univariate Hazard Ratio (HR) for sensitive versus resistant of 0.265 (95% CI:0.079-0.889, p=0.032) in the ACV cohort and a HR of 0.28 in a multivariate model (95% CI:0.08-1.04, p=0.0573); 2) significant prediction at 3 year survival from surgery in univariate (HR=0.138 (95% CI:0.035-0.537), p=0.004) and multivariate analysis (HR=0.14 (95% CI:0.030-0.6), p=0.0081). No discrimination was found in the OBS cohort (HR=1.328, p=0.60). The cisplatin predictor alone had similar figures with 1) univariate HR of 0.37 (95% CI:0.12-1.15, p=0.09) in the ACV cohort and 2) univariate HR of 0.14 (95% CI:0.03-0.59, p=0.0076) to three years. Functional analysis on the cisplatin profile revealed a group of upregulated genes related to RNA splicing as a part of DNA damage repair and apoptosis. Conclusions: Profiles derived from snap-frozen and FFPE NSCLC tissue were prognostic and predictive in the patients that received cisplatin and vinorelbine but not in the cohort that did not receive adjuvant treatment.

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

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