Prognostic Evidence of the miRNA-Based Ovarian Cancer Signature MiROvaR in Independent Datasets

Abstract

Epithelial ovarian cancer (EOC) remains the second most common cause of gynecological cancer deaths. To improve patients’ outcomes, we still need reliable biomarkers of early relapse, of which external independent validation is a crucial process. Our previously established prognostic signature, MiROvaR, including 35 microRNAs (miRNA) able to stratify EOC patients for their risk of relapse, was challenged on a new independent cohort of 197 EOC patients included in the Pelvic Mass Study whose miRNA profile was made publically available, thus resulting in the only accessible database aside from the EOC TCGA collection. Following accurate data matrix adjustment to account for the use of different miRNA platforms, MiROvaR confirmed its ability to discriminate early relapsing patients. The model’s original cutoff separated 156 (79.2%) high- and 41 (20.8%) low-risk patients with median progression free survival (PFS) of 16.3 months and not yet reached (NYR), respectively (hazard ratio (HR): 2.42–95% Confidence Interval (CI) 1.49–3.93; Log-rank p = 0.00024). The MiROvaR predictive accuracy (area under the curve (AUC) = 0.68; 95% Cl 0.57–0.79) confirms its prognostic value. This external validation in a totally independently collected, handled and profiled EOC cohort suggests that MiROvaR is a strong and reliable biomarker of EOC early relapse, warranting prospective validation.

Keywords

• epithelial ovarian cancer
• microRNA
• molecular predictor
• early relapse
• independent validation