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Prognostic Evidence of the miRNA-Based Ovarian Cancer Signature MiROvaR in Independent Datasets

SIMPLE SUMMARY: Epithelial ovarian cancers (EOC) have an unpredictable frequent recurrence often associated with incurable chemo-resistant disease. Basing on the miRNA expression profile of 892 EOC patients, we previously developed a 35 miRNA-based classifier, MiROvaR, able to predict EOC risk of ea...

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Autores principales: De Cecco, Loris, Bagnoli, Marina, Chiodini, Paolo, Pignata, Sandro, Mezzanzanica, Delia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8037414/
https://www.ncbi.nlm.nih.gov/pubmed/33801595
http://dx.doi.org/10.3390/cancers13071544
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author De Cecco, Loris
Bagnoli, Marina
Chiodini, Paolo
Pignata, Sandro
Mezzanzanica, Delia
author_facet De Cecco, Loris
Bagnoli, Marina
Chiodini, Paolo
Pignata, Sandro
Mezzanzanica, Delia
author_sort De Cecco, Loris
collection PubMed
description SIMPLE SUMMARY: Epithelial ovarian cancers (EOC) have an unpredictable frequent recurrence often associated with incurable chemo-resistant disease. Basing on the miRNA expression profile of 892 EOC patients, we previously developed a 35 miRNA-based classifier, MiROvaR, able to predict EOC risk of early relapse. Further independent analysis of prediction accuracy represents a crucial step in the test-validation phase. Here we exploited an external and independently collected, handled and profiled EOC cohort, to challenge MirovaR accuracy. Our analysis confirmed the MiROvaR prognostic power, thus opening the way to its prospective validation as a clinical grade assay entering into clinical practice to help in the refinement of therapeutic intervention for high risk EOC patients. ABSTRACT: Epithelial ovarian cancer (EOC) remains the second most common cause of gynecological cancer deaths. To improve patients’ outcomes, we still need reliable biomarkers of early relapse, of which external independent validation is a crucial process. Our previously established prognostic signature, MiROvaR, including 35 microRNAs (miRNA) able to stratify EOC patients for their risk of relapse, was challenged on a new independent cohort of 197 EOC patients included in the Pelvic Mass Study whose miRNA profile was made publically available, thus resulting in the only accessible database aside from the EOC TCGA collection. Following accurate data matrix adjustment to account for the use of different miRNA platforms, MiROvaR confirmed its ability to discriminate early relapsing patients. The model’s original cutoff separated 156 (79.2%) high- and 41 (20.8%) low-risk patients with median progression free survival (PFS) of 16.3 months and not yet reached (NYR), respectively (hazard ratio (HR): 2.42–95% Confidence Interval (CI) 1.49–3.93; Log-rank p = 0.00024). The MiROvaR predictive accuracy (area under the curve (AUC) = 0.68; 95% Cl 0.57–0.79) confirms its prognostic value. This external validation in a totally independently collected, handled and profiled EOC cohort suggests that MiROvaR is a strong and reliable biomarker of EOC early relapse, warranting prospective validation.
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spelling pubmed-80374142021-04-12 Prognostic Evidence of the miRNA-Based Ovarian Cancer Signature MiROvaR in Independent Datasets De Cecco, Loris Bagnoli, Marina Chiodini, Paolo Pignata, Sandro Mezzanzanica, Delia Cancers (Basel) Communication SIMPLE SUMMARY: Epithelial ovarian cancers (EOC) have an unpredictable frequent recurrence often associated with incurable chemo-resistant disease. Basing on the miRNA expression profile of 892 EOC patients, we previously developed a 35 miRNA-based classifier, MiROvaR, able to predict EOC risk of early relapse. Further independent analysis of prediction accuracy represents a crucial step in the test-validation phase. Here we exploited an external and independently collected, handled and profiled EOC cohort, to challenge MirovaR accuracy. Our analysis confirmed the MiROvaR prognostic power, thus opening the way to its prospective validation as a clinical grade assay entering into clinical practice to help in the refinement of therapeutic intervention for high risk EOC patients. ABSTRACT: Epithelial ovarian cancer (EOC) remains the second most common cause of gynecological cancer deaths. To improve patients’ outcomes, we still need reliable biomarkers of early relapse, of which external independent validation is a crucial process. Our previously established prognostic signature, MiROvaR, including 35 microRNAs (miRNA) able to stratify EOC patients for their risk of relapse, was challenged on a new independent cohort of 197 EOC patients included in the Pelvic Mass Study whose miRNA profile was made publically available, thus resulting in the only accessible database aside from the EOC TCGA collection. Following accurate data matrix adjustment to account for the use of different miRNA platforms, MiROvaR confirmed its ability to discriminate early relapsing patients. The model’s original cutoff separated 156 (79.2%) high- and 41 (20.8%) low-risk patients with median progression free survival (PFS) of 16.3 months and not yet reached (NYR), respectively (hazard ratio (HR): 2.42–95% Confidence Interval (CI) 1.49–3.93; Log-rank p = 0.00024). The MiROvaR predictive accuracy (area under the curve (AUC) = 0.68; 95% Cl 0.57–0.79) confirms its prognostic value. This external validation in a totally independently collected, handled and profiled EOC cohort suggests that MiROvaR is a strong and reliable biomarker of EOC early relapse, warranting prospective validation. MDPI 2021-03-27 /pmc/articles/PMC8037414/ /pubmed/33801595 http://dx.doi.org/10.3390/cancers13071544 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Communication
De Cecco, Loris
Bagnoli, Marina
Chiodini, Paolo
Pignata, Sandro
Mezzanzanica, Delia
Prognostic Evidence of the miRNA-Based Ovarian Cancer Signature MiROvaR in Independent Datasets
title Prognostic Evidence of the miRNA-Based Ovarian Cancer Signature MiROvaR in Independent Datasets
title_full Prognostic Evidence of the miRNA-Based Ovarian Cancer Signature MiROvaR in Independent Datasets
title_fullStr Prognostic Evidence of the miRNA-Based Ovarian Cancer Signature MiROvaR in Independent Datasets
title_full_unstemmed Prognostic Evidence of the miRNA-Based Ovarian Cancer Signature MiROvaR in Independent Datasets
title_short Prognostic Evidence of the miRNA-Based Ovarian Cancer Signature MiROvaR in Independent Datasets
title_sort prognostic evidence of the mirna-based ovarian cancer signature mirovar in independent datasets
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8037414/
https://www.ncbi.nlm.nih.gov/pubmed/33801595
http://dx.doi.org/10.3390/cancers13071544
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