miRNA expression profiling in early-stage epithelial ovarian cancer

Early-stage epithelial ovarian cancer (eEOC) patients have a generally favorable prognosis but heterogeneous behavior at recurrence. Accurate prediction of the risk of relapse is still a major concern, essentially to avoid overtreatment. We have identified a robust miRNA-based signature named MiROvaR able to predict early disease recurrence in case materials of mostly advanced-stage EOC patients. We challenged MiROvaR in the eEOC sub-setting (stage IA-IIB) and it proved to accurately classify eEOC patients according to their risk of relapse. We retrospectively selected patients diagnosed with early stage ovarian cancer who underwent comprehensive surgical staging at our institution and whose FFPE blocks were available. 89 cases of stages from IA to IIB were included. After profiling on Agilent SurePrint 8x60K human miRNA arrays, 87 cases were eligible for data analysis. The historical retrospective case material (1993-2015) has been entirely revised by the specialized pathologist who is in charge of the gynecological oncology diseases classification at INT. Classyfing process followed the current clinical practice in accordance with the current criteria asssessed in 2014 by FIGO and WHO. Clinical variables: Age (yr) at diagnosis; grade/stage, according to FIGO (2014); histology according to WHO (2014)