Antonino Ditto1, Loris De Cecco2, Biagio Paolini3, Paola Alberti4, Fabio Martinelli1, Umberto Leone Roberti Maggiore1, Giorgio Bogani1, Paolo Chiodini5, Sandro Pignata6, Antonella Tomassetti4, Francesco Raspagliesi1, Delia Mezzanzanica7, Marina Bagnoli4. 1. Unit of Gynecologic Oncology, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy. 2. Department of Applied Research and Technology Development, Integrated Biology Platform, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy. 3. Department of Pathology, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy. 4. Department of Research, Unit of Molecular Therapies, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy. 5. Medical Statistics Unit, University of Campania "Luigi Vanvitelli", Naples, Italy. 6. Urogynaecological Medical Oncology Unit, Istituto Nazionale Tumori - IRCCS - "Fondazione G. Pascale", Naples, Italy. 7. Department of Research, Unit of Molecular Therapies, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy. Electronic address: delia.mezzanzanica@istitutotumori.mi.it.
Abstract
AIM: Early-stage epithelial ovarian cancer (eEOC) patients have a generally favorable prognosis but unpredictable recurrence. Accurate prediction of risk of relapse is still a major concern, essentially to avoid overtreatment. Our robust tissue-based miRNA signature named MiROvaR, predicting early EOC recurrence in mostly advanced-stage EOC patients, is here challenged in an independent cohort to extend its classifying ability in the early-stage EOC setting. METHODS: We retrospectively selected patients who underwent comprehensive surgical staging at our institution including stages from IA to IIB. miRNA expression profile was analysed in 89 cases and MiROvaR algorithm was applied using the previously validated cut-off for patients' classification. The primary endpoint was progression-free survival (PFS) at 5 years. Complete follow-up time (median = 112 months) was also considered as secondary analysis. RESULTS: MiROvaR was assessable on 87 cases (19 events of disease progression) and classified 68 (78%) low-risk and 19 (22%) high-risk patients. Recurrence rate at primary end-point was 39% for high-risk patients as compared to 9.5% for low-risk ones. Accordingly, their Kaplan-Meier PFS curves were significantly different at both primary and secondary analysis (p = 0.0006 and p = 0.03, respectively). While none of the prominent clinical variables had prognostic relevance, MiROvaR significantly predicted disease recurrence at the 5-year assessment (primary endpoint analysis; HR:5.43, 95%CI:1.82-16.1, p = 0.0024; AUC = 0.78, 95%CI:0.53-0.82) and at complete follow-up time (HR:2.67, 95%CI:1.04-6.8, p = 0.041; AUC:0.68, 95%CI:0.52-0.82). CONCLUSIONS: We validated MiROvaR performance in identifying at diagnosis eEOC patients' at higher risk of early relapse thus enabling selection of the most effective therapeutic approach.
AIM: Early-stage epithelial ovarian cancer (eEOC) patients have a generally favorable prognosis but unpredictable recurrence. Accurate prediction of risk of relapse is still a major concern, essentially to avoid overtreatment. Our robust tissue-based miRNA signature named MiROvaR, predicting early EOC recurrence in mostly advanced-stage EOC patients, is here challenged in an independent cohort to extend its classifying ability in the early-stage EOC setting. METHODS: We retrospectively selected patients who underwent comprehensive surgical staging at our institution including stages from IA to IIB. miRNA expression profile was analysed in 89 cases and MiROvaR algorithm was applied using the previously validated cut-off for patients' classification. The primary endpoint was progression-free survival (PFS) at 5 years. Complete follow-up time (median = 112 months) was also considered as secondary analysis. RESULTS: MiROvaR was assessable on 87 cases (19 events of disease progression) and classified 68 (78%) low-risk and 19 (22%) high-risk patients. Recurrence rate at primary end-point was 39% for high-risk patients as compared to 9.5% for low-risk ones. Accordingly, their Kaplan-Meier PFS curves were significantly different at both primary and secondary analysis (p = 0.0006 and p = 0.03, respectively). While none of the prominent clinical variables had prognostic relevance, MiROvaR significantly predicted disease recurrence at the 5-year assessment (primary endpoint analysis; HR:5.43, 95%CI:1.82-16.1, p = 0.0024; AUC = 0.78, 95%CI:0.53-0.82) and at complete follow-up time (HR:2.67, 95%CI:1.04-6.8, p = 0.041; AUC:0.68, 95%CI:0.52-0.82). CONCLUSIONS: We validated MiROvaR performance in identifying at diagnosis eEOC patients' at higher risk of early relapse thus enabling selection of the most effective therapeutic approach.