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Título: | MicroRNAs as potential predictors of extreme response to tyrosine kinase inhibitors in renal cell cancer |
Autor: | Garrigos, Carmen CSIC ORCID; Molina-Pinelo, Sonia CSIC ORCID; Meléndez Cadenas, Ricardo CSIC; Espinosa-Montaño, Marta; Lerma, Antonio; Taron Roca, Miguel CSIC; García-Donas, Jesús; Rodríguez-Antona, Cristina; Durán, Ignacio CSIC ORCID | Palabras clave: | miRNAs Renal Cell Carcinoma Biomarkers Tyrosine kinase inhibitors Gene expression |
Fecha de publicación: | jul-2020 | Editor: | Elsevier | Citación: | Urologic Oncology - Seminars and Original Investigations 38(7): 640.e23-640.e29 (2020) | Resumen: | Background: MicroRNAs play an important role as modulators of gene expression in several biological processes and are closely related to development and cell differentiation regulation. Previous works have revealed a potential predictive role for miRNAs in different tumor types. This study aims to analyze the ability of miRNAs in segregating metastatic renal cell carcinoma patients according to their responses to tyrosine kinase inhibitors (TKIs). Methods: Extreme responders were considered in the study and were defined as those patients that either had a long-term response (LR) (progression-free survival ˃11 months) or those that were primary refractory (PR) (progression as best response). The expression of 754 miRNAs was analyzed in tumor tissue of these 2 sets of patients. Results: In a study cohort (n = 15) 4 miRNAs were significantly associated with patient response and differentially expressed in PR vs. LR (up-regulated in PR vs. LR: miR-425-5p, down-regulated in PR vs. LR: miR-139-3p, let-7d and let-7e). Further analysis in a validation cohort (n = 36) revealed similar results. Conclusion: The present data strength the potential role of miRNAs as a tool to predict treatment outcomes in patients with metastatic renal cell carcinoma treated with TKIs. | Versión del editor: | http://dx.doi.org/10.1016/j.urolonc.2020.01.012 | URI: | http://hdl.handle.net/10261/237894 | DOI: | 10.1016/j.urolonc.2020.01.012 | Identificadores: | doi: 10.1016/j.urolonc.2020.01.012 issn: 1078-1439 |
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