Validation of MiROvaR, a microRNA-based predictor of early relapse in early stage epithelial ovarian cancer as a new strategy to optimise patients' prognostic assessment.

Autor: Ditto A; Unit of Gynecologic Oncology, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy., De Cecco L; Department of Applied Research and Technology Development, Integrated Biology Platform, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy., Paolini B; Department of Pathology, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy., Alberti P; Department of Research, Unit of Molecular Therapies, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy., Martinelli F; Unit of Gynecologic Oncology, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy., Leone Roberti Maggiore U; Unit of Gynecologic Oncology, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy., Bogani G; Unit of Gynecologic Oncology, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy., Chiodini P; Medical Statistics Unit, University of Campania 'Luigi Vanvitelli', Naples, Italy., Pignata S; Urogynaecological Medical Oncology Unit, Istituto Nazionale Tumori - IRCCS - 'Fondazione G. Pascale', Naples, Italy., Tomassetti A; Department of Research, Unit of Molecular Therapies, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy., Raspagliesi F; Unit of Gynecologic Oncology, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy., Mezzanzanica D; Department of Research, Unit of Molecular Therapies, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy. Electronic address: delia.mezzanzanica@istitutotumori.mi.it., Bagnoli M; Department of Research, Unit of Molecular Therapies, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy.
Jazyk: angličtina
Zdroj: European journal of cancer (Oxford, England : 1990) [Eur J Cancer] 2022 Jan; Vol. 161, pp. 55-63. Date of Electronic Publication: 2021 Dec 15.
DOI: 10.1016/j.ejca.2021.11.003
Abstrakt: 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.
Competing Interests: Conflict of interest interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article.
(Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)
Databáze: MEDLINE
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