Development and validation of a microRNA-based signature (MiROvaR) to predict early relapse or progression of epithelial ovarian cancer: a cohort study - 01/08/16

Doi : 10.1016/S1470-2045(16)30108-5

Marina Bagnoli, PhD ^a,^{^{†
Contributed equally as first authors}}, Silvana Canevari, PhD ^b,^{^{†
Contributed equally as first authors}}, Daniela Califano, PhD ^e, Simona Losito, MD ^f, Massimo Di Maio, ProfMD ^g, Francesco Raspagliesi, MD ^c, Maria Luisa Carcangiu, MD ^d, Giuseppe Toffoli, MD ⁱ, Erika Cecchin, PhD ⁱ, Roberto Sorio, MD ^j, Vincenzo Canzonieri, MD ^k, Daniela Russo, PhD ^e, Giosué Scognamiglio, PhD ^f, Gennaro Chiappetta, PhD ^e, Gustavo Baldassarre, MD ^l, Domenica Lorusso, MD ^c, Giovanni Scambia, ProfMD ^m, Gian Franco Zannoni, ProfMD ⁿ, Antonella Savarese, MD ^o, Mariantonia Carosi, MD ^p, Paolo Scollo, MD ^q, Enrico Breda, MD ^r, Viviana Murgia, MD ^s, Francesco Perrone, MD ^g, Sandro Pignata, MD ^h,^{^{‡
Contributed equally as senior authors}}, Loris De Cecco, PhD ^b,^{^{‡
Contributed equally as senior authors}}, Delia Mezzanzanica, DrPhD ^a,^⁎,^{^{‡
Contributed equally as senior authors}}
for the
Multicentre Italian Trials in Ovarian cancer (MITO) translational group

^a Molecular Therapies Unit, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy

^b Functional Genomics, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy

^c Unit of Gynaecological Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy

^d Anatomic Pathology 1 Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy

^e Functional Genomic Unit, Istituto Nazionale per lo Studio e la Cura dei Tumori “Fondazione G Pascale”, IRCCS, Naples, Italy

^f Surgical Pathology Unit, Istituto Nazionale per lo Studio e la Cura dei Tumori “Fondazione G Pascale”, IRCCS, Naples, Italy

^g Clinical Trials Unit, Istituto Nazionale per lo Studio e la Cura dei Tumori “Fondazione G Pascale”, IRCCS, Naples, Italy

^h Department of Urogynaecological Oncology, Istituto Nazionale per lo Studio e la Cura dei Tumori “Fondazione G Pascale”, IRCCS, Naples, Italy

ⁱ Experimental and Clinical Pharmacology Unit, Centro di Riferimento Oncologico, Istituto Ricovero e Cura Carattere Scientifico (CRO-IRCCS), Aviano, Italy

^j Medical Oncology C, Centro di Riferimento Oncologico, Istituto Ricovero e Cura Carattere Scientifico (CRO-IRCCS), Aviano, Italy

^k Unit of Pathology, Centro di Riferimento Oncologico, Istituto Ricovero e Cura Carattere Scientifico (CRO-IRCCS), Aviano, Italy

^l Division of Experimental Oncology 2, Centro di Riferimento Oncologico, Istituto Ricovero e Cura Carattere Scientifico (CRO-IRCCS), Aviano, Italy

^m Department of Obstetrics and Gynecology, Gynecologic Oncology Unit, Catholic University of the Sacred Heart, Rome, Italy

ⁿ Department of Human Pathology, Division of Gynecologic Pathology, Catholic University of the Sacred Heart, Rome, Italy

^o Division of Medical Oncology 1, Regina Elena Cancer Institute, Rome, Italy

^p Division of Pathology, Regina Elena Cancer Institute, Rome, Italy

^q Department of Obstetrics and Gynecology, Azienda Ospedaliera Cannizzaro, Catania, Italy

^r Medical Oncology Unit Ospedale S Giovanni Calibita Fatebenefratelli, Rome, Italy

^s Medical Oncology Unit Ospedale S Chiara, Trento, Italy

^* Correspondence to: Dr Delia Mezzanzanica, Unit of Molecular Therapies, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan 20133, Italy Correspondence to: Dr Delia Mezzanzanica Unit of Molecular Therapies Department of Experimental Oncology and Molecular Medicine Fondazione IRCCS Istituto Nazionale dei Tumori Milan 20133 Italy

Summary

Background

Risk of relapse or progression remains high in the treatment of most patients with epithelial ovarian cancer, and development of a molecular predictor could be a valuable tool for stratification of patients by risk. We aimed to develop a microRNA (miRNA)-based molecular classifier that can predict risk of progression or relapse in patients with epithelial ovarian cancer.

Methods

We analysed miRNA expression profiles in three cohorts of samples collected at diagnosis. We used 179 samples from a Multicenter Italian Trial in Ovarian cancer trial (cohort OC179) to develop the model and 263 samples from two cancer centres (cohort OC263) and 452 samples from The Cancer Genome Atlas epithelial ovarian cancer series (cohort OC452) to validate the model. The primary clinical endpoint was progression-free survival, and we adapted a semi-supervised prediction method to the miRNA expression profile of OC179 to identify miRNAs that predict risk of progression. We assessed the independent prognostic role of the model using multivariable analysis with a Cox regression model.

Findings

We identified 35 miRNAs that predicted risk of progression or relapse and used them to create a prognostic model, the 35-miRNA-based predictor of Risk of Ovarian Cancer Relapse or progression (MiROvaR). MiROvaR was able to classify patients in OC179 into a high-risk group (89 patients; median progression-free survival 18 months [95% CI 15–22]) and a low-risk group (90 patients; median progression-free survival 38 months [24–not estimable]; hazard ratio [HR] 1·85 [1·29–2·64], p=0·00082). MiROvaR was a significant predictor of progression in the two validation sets (OC263 HR 3·16, 95% CI 2·33–4·29, p<0·0001; OC452 HR 1·39, 95% CI 1·11–1·74, p=0·0047) and maintained its independent prognostic effect when adjusted for relevant clinical covariates using multivariable analyses (OC179: adjusted HR 1·48, 95% CI 1·03–2·13, p=0·036; OC263: adjusted HR 3·09 [2·24–4·28], p<0·0001; and OC452: HR 1·41 [1·11–1·79], p=0·0047).

Interpretation

MiROvaR is a potential predictor of epithelial ovarian cancer progression and has prognostic value independent of relevant clinical covariates. MiROvaR warrants further investigation for the development of a clinical-grade prognostic assay.

Funding

AIRC and CARIPLO Foundation.

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Vol 17 - N° 8

P. 1137-1146 - août 2016 Retour au numéro

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Development and validation of a microRNA-based signature (MiROvaR) to predict early relapse or progression of epithelial ovarian cancer: a cohort study - 01/08/16

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