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A Tetra-Panel of Serum Circulating miRNAs for the Diagnosis of the Four Most Prevalent Tumor Types

The purpose of this study is to clinically validate a series of circulating miRNAs that distinguish between the 4 most prevalent tumor types (lung cancer (LC); breast cancer (BC); colorectal cancer (CRC); and prostate cancer (PCa)) and healthy donors (HDs). A total of 18 miRNAs and 3 housekeeping mi...

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Autores principales: Pastor-Navarro, Belén, García-Flores, María, Fernández-Serra, Antonio, Blanch-Tormo, Salvador, Martínez de Juan, Fernando, Martínez-Lapiedra, Carmen, Maia de Alcantara, Fernanda, Peñalver, Juan Carlos, Cervera-Deval, José, Rubio-Briones, José, García-Rupérez, Jaime, López-Guerrero, José Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215589/
https://www.ncbi.nlm.nih.gov/pubmed/32316350
http://dx.doi.org/10.3390/ijms21082783
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author Pastor-Navarro, Belén
García-Flores, María
Fernández-Serra, Antonio
Blanch-Tormo, Salvador
Martínez de Juan, Fernando
Martínez-Lapiedra, Carmen
Maia de Alcantara, Fernanda
Peñalver, Juan Carlos
Cervera-Deval, José
Rubio-Briones, José
García-Rupérez, Jaime
López-Guerrero, José Antonio
author_facet Pastor-Navarro, Belén
García-Flores, María
Fernández-Serra, Antonio
Blanch-Tormo, Salvador
Martínez de Juan, Fernando
Martínez-Lapiedra, Carmen
Maia de Alcantara, Fernanda
Peñalver, Juan Carlos
Cervera-Deval, José
Rubio-Briones, José
García-Rupérez, Jaime
López-Guerrero, José Antonio
author_sort Pastor-Navarro, Belén
collection PubMed
description The purpose of this study is to clinically validate a series of circulating miRNAs that distinguish between the 4 most prevalent tumor types (lung cancer (LC); breast cancer (BC); colorectal cancer (CRC); and prostate cancer (PCa)) and healthy donors (HDs). A total of 18 miRNAs and 3 housekeeping miRNA genes were evaluated by qRT-PCR on RNA extracted from serum of cancer patients, 44 LC, 45 BC, 27 CRC, and 40 PCa, and on 45 HDs. The cancer detection performance of the miRNA expression levels was evaluated by studying the area under the curve (AUC) of receiver operating characteristic (ROC) curves at univariate and multivariate levels. miR-21 was significantly overexpressed in all cancer types compared with HDs, with accuracy of 67.5% (p = 0.001) for all 4 tumor types and of 80.8% (p < 0.0001) when PCa cases were removed from the analysis. For each tumor type, a panel of miRNAs was defined that provided cancer-detection accuracies of 91%, 94%, 89%, and 77%, respectively. In conclusion, we have described a series of circulating miRNAs that define different tumor types with a very high diagnostic performance. These panels of miRNAs would constitute the basis of different approaches of cancer-detection systems for which clinical utility should be validated in prospective cohorts.
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spelling pubmed-72155892020-05-22 A Tetra-Panel of Serum Circulating miRNAs for the Diagnosis of the Four Most Prevalent Tumor Types Pastor-Navarro, Belén García-Flores, María Fernández-Serra, Antonio Blanch-Tormo, Salvador Martínez de Juan, Fernando Martínez-Lapiedra, Carmen Maia de Alcantara, Fernanda Peñalver, Juan Carlos Cervera-Deval, José Rubio-Briones, José García-Rupérez, Jaime López-Guerrero, José Antonio Int J Mol Sci Article The purpose of this study is to clinically validate a series of circulating miRNAs that distinguish between the 4 most prevalent tumor types (lung cancer (LC); breast cancer (BC); colorectal cancer (CRC); and prostate cancer (PCa)) and healthy donors (HDs). A total of 18 miRNAs and 3 housekeeping miRNA genes were evaluated by qRT-PCR on RNA extracted from serum of cancer patients, 44 LC, 45 BC, 27 CRC, and 40 PCa, and on 45 HDs. The cancer detection performance of the miRNA expression levels was evaluated by studying the area under the curve (AUC) of receiver operating characteristic (ROC) curves at univariate and multivariate levels. miR-21 was significantly overexpressed in all cancer types compared with HDs, with accuracy of 67.5% (p = 0.001) for all 4 tumor types and of 80.8% (p < 0.0001) when PCa cases were removed from the analysis. For each tumor type, a panel of miRNAs was defined that provided cancer-detection accuracies of 91%, 94%, 89%, and 77%, respectively. In conclusion, we have described a series of circulating miRNAs that define different tumor types with a very high diagnostic performance. These panels of miRNAs would constitute the basis of different approaches of cancer-detection systems for which clinical utility should be validated in prospective cohorts. MDPI 2020-04-16 /pmc/articles/PMC7215589/ /pubmed/32316350 http://dx.doi.org/10.3390/ijms21082783 Text en © 2020 by the authors. 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/).
spellingShingle Article
Pastor-Navarro, Belén
García-Flores, María
Fernández-Serra, Antonio
Blanch-Tormo, Salvador
Martínez de Juan, Fernando
Martínez-Lapiedra, Carmen
Maia de Alcantara, Fernanda
Peñalver, Juan Carlos
Cervera-Deval, José
Rubio-Briones, José
García-Rupérez, Jaime
López-Guerrero, José Antonio
A Tetra-Panel of Serum Circulating miRNAs for the Diagnosis of the Four Most Prevalent Tumor Types
title A Tetra-Panel of Serum Circulating miRNAs for the Diagnosis of the Four Most Prevalent Tumor Types
title_full A Tetra-Panel of Serum Circulating miRNAs for the Diagnosis of the Four Most Prevalent Tumor Types
title_fullStr A Tetra-Panel of Serum Circulating miRNAs for the Diagnosis of the Four Most Prevalent Tumor Types
title_full_unstemmed A Tetra-Panel of Serum Circulating miRNAs for the Diagnosis of the Four Most Prevalent Tumor Types
title_short A Tetra-Panel of Serum Circulating miRNAs for the Diagnosis of the Four Most Prevalent Tumor Types
title_sort tetra-panel of serum circulating mirnas for the diagnosis of the four most prevalent tumor types
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215589/
https://www.ncbi.nlm.nih.gov/pubmed/32316350
http://dx.doi.org/10.3390/ijms21082783
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