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

被引：106

作者：

Bagnoli, Marina ^{[1
]}

Canevari, Silvana ^{[2
]}

Califano, Daniela ^{[5
]}

Losito, Simona ^{[6
]}

Di Maio, Massimo ^{[7
]}

Raspagliesi, Francesco ^{[3
]}

Carcangiu, Maria Luisa ^{[4
]}

Toffoli, Giuseppe ^{[9
]}

Cecchin, Erika ^{[9
]}

Sorio, Roberto ^{[10
]}

Canzonieri, Vincenzo ^{[11
]}

Russo, Daniela ^{[5
]}

Scognamiglio, Giosue ^{[6
]}

Chiappetta, Gennaro ^{[5
]}

Baldassarre, Gustavo ^{[12
]}

Lorusso, Domenica ^{[3
]}

Scambia, Giovanni ^{[13
]}

Zannoni, Gian Franco ^{[14
]}

Savarese, Antonella ^{[15
]}

Carosi, Mariantonia ^{[16
]}

Scollo, Paolo ^{[17
]}

Breda, Enrico ^{[18
]}

Murgia, Viviana ^{[19
]}

Perrone, Francesco ^{[7
]}

Pignata, Sandro ^{[8
]}

De Cecco, Loris ^{[2
]}

Mezzanzanica, Delia ^{[1
]}

机构：

[1] Fdn IRCCS Ist Nazl Tumori, Mol Therapies Unit, Dept Expt Oncol & Mol Med, I-20133 Milan, Italy

[2] Fdn IRCCS Ist Nazl Tumori, Funct Genom, Dept Expt Oncol & Mol Med, I-20133 Milan, Italy

[3] Fdn IRCCS Ist Nazl Tumori, Unit Gynaecol Oncol, I-20133 Milan, Italy

[4] Fdn IRCCS Ist Nazl Tumori, Anat Pathol Unit 1, I-20133 Milan, Italy

[5] IRCCS, Fdn G Pascale, Ist Nazl Studio & Cura Tumori, Funct Genom Unit, Naples, Italy

[6] IRCCS, Fdn G Pascale, Ist Nazl Studio & Cura Tumori, Surg Pathol Unit, Naples, Italy

[7] IRCCS, Fdn G Pascale, Ist Nazl Studio & Cura Tumori, Clin Trials Unit, Naples, Italy

[8] IRCCS, Fdn G Pascale, Ist Nazl Studio & Cura Tumori, Dept Urogynaecol Oncol, Naples, Italy

[9] IRCCS, CRO, Expt & Clin Pharmacol Unit, Aviano, Italy

[10] IRCCS, CRO, Med Oncol C, Aviano, Italy

[11] IRCCS, CRO, Unit Pathol, Aviano, Italy

[12] IRCCS, CRO, Div Expt Oncol 2, Aviano, Italy

[13] Univ Cattolica Sacro Cuore, Dept Obstet & Gynecol, Gynecol Oncol Unit, Rome, Italy

[14] Univ Cattolica Sacro Cuore, Dept Human Pathol, Div Gynecol Pathol, Rome, Italy

[15] Regina Elena Inst Canc Res, Div Med Oncol 1, Rome, Italy

[16] Regina Elena Inst Canc Res, Div Pathol, Rome, Italy

[17] Azienda Osped Cannizzaro, Dept Obstet & Gynecol, Catania, Italy

[18] Osped S Giovanni Calibita Fatebenefratelli, Med Oncol Unit, Rome, Italy

[19] Osped S Chiara, Med Oncol Unit, Trento, Italy

来源：

LANCET ONCOLOGY | 2016年 / 17卷 / 08期

关键词：

CARBOPLATIN PLUS PACLITAXEL; TO-MESENCHYMAL TRANSITION; GENE-EXPRESSION; METASTASIS; SUBTYPE; NETWORK; DEFINES; AXIS;

D O I：

10.1016/S1470-2045(16)30108-5

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

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.

引用

页码：1137 / 1146

页数：10

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