Web of Science: 18 citations, Scopus: 20 citations, Google Scholar: citations,
Five microRNAs in Serum Are Able to Differentiate Breast Cancer Patients From Healthy Individuals
Feliciano, Andrea (Hospital Universitari Vall d'Hebron. Institut de Recerca)
González, Lucila (Hospital Universitari Vall d'Hebron. Institut de Recerca)
Garcia Mayea, Yoelsis (Hospital Universitari Vall d'Hebron. Institut de Recerca)
Mir Pérez, Cristina (Hospital Universitari Vall d'Hebron. Institut de Recerca)
Artola, Mireia (Institut Català de la Salut. Centre d'Atenció Primària Vallcarca-Sant Gervasi)
Barragán-Brun, Nieves (Institut Català de la Salut. Centre d'Atenció Primària Vallcarca-Sant Gervasi)
Martín, Remedios (Institut Català de la Salut. Centre d'Atenció Primària Vallcarca-Sant Gervasi)
Altés, Anna (Institut Català de la Salut. Centre d'Atenció Primària Vallcarca-Sant Gervasi)
Castellvi, Josep (Hospital Universitari Vall d'Hebron. Institut de Recerca)
Benavente, Sergi (Hospital Universitari Vall d'Hebron. Institut de Recerca)
Ramón y Cajal, Santiago (Hospital Universitari Vall d'Hebron. Institut de Recerca)
Espinosa-Bravo, Martín (Hospital Universitari Vall d'Hebron)
Cortés Castán, Javier (Vall d'Hebron Institut d'Oncologia)
Rubio, Isabel T. (Clínica Universidad de Navarra)
LLeonart, Matilde E. (Centro de Investigación Biomédica en Red de Oncología (CIBERONC))
Universitat Autònoma de Barcelona

Date: 2020
Abstract: Breast cancer is the cancer with the most incidence and mortality in women. microRNAs are emerging as novel prognosis/diagnostic tools. Our aim was to identify a serum microRNA signature useful to predict cancer development. We focused on studying the expression levels of 30 microRNAs in the serum of 96 breast cancer patients vs. 92 control individuals. Bioinformatic studies provide a microRNA signature, designated as a predictor, based on the expression levels of five microRNAs. Then, we tested the predictor in a group of 60 randomly chosen women. Lastly, a proteomic study unveiled the overexpression and downregulation of proteins differently expressed in the serum of breast cancer patients vs. that of control individuals. Twenty-six microRNAs differentiate cancer tissue from healthy tissue, and 16 microRNAs differentiate the serum of cancer patients from that of the control group. The tissue expression of miR-99a, miR-497, miR-362, and miR-1274, and the serum levels of miR-141 correlated with patient survival. Moreover, the predictor consisting of miR-125b, miR-29c, miR-16, miR-1260, and miR-451 was able to differentiate breast cancer patients from controls. The predictor was validated in 20 new cases of breast cancer patients and tested in 60 volunteer women, assigning 11 out of 60 women to the cancer group. An association of low levels of miR-16 with a high content of CD44 protein in serum was found. Circulating microRNAs in serum can represent biomarkers for cancer prediction. Their clinical relevance and the potential use of the predictor here described are discussed.
Grants: Ministerio de Economía, Industria y Competitividad FISPI15/01262
Rights: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. Creative Commons
Language: Anglès
Document: Article ; recerca ; Versió publicada
Subject: Breast cancer ; Serum ; Micrornas ; Prognosis ; Diagnosis
Published in: Frontiers in Oncology, Vol. 10 (november 2020) , ISSN 2234-943X

DOI: 10.3389/fonc.2020.586268
PMID: 33224883


10 p, 1.8 MB

The record appears in these collections:
Articles > Research articles
Articles > Published articles

 Record created 2022-02-07, last modified 2025-10-14



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