2026-05-17T05:52:42Zhttps://repisalud.isciii.es/rest/oai/requestoai:repisalud.isciii.es:20.500.12105/199672024-11-29T01:08:45Zcom_20.500.12105_15322com_20.500.12105_2051col_20.500.12105_16967
Repisalud
author
Prior, Celia
author
Luis Perez-Gracia, Jose
author
Garcia-Donas, Jesus
author
Rodriguez-Antona, Cristina
author
Guruceaga, Elizabeth
author
Esteban, Emilio
author
Suarez, Cristina
author
Castellano, Danie
author
Gonzalez del Alba, Aranzazu
author
Dolores Lozano, Maria
author
Carles, Joan
author
Angel Climent, Miguel
author
Angel Arranz, Jose
author
Gallardo, Enrique
author
Puente, Javier
author
Bellmunt, Joaquim
author
Gurpide, Alfonso
author
Maria Lopez-Picazo, Jose
author
Gonzalez Hernandez, Alvaro
author
Mellado, Begona
author
Martinez, Esther
author
Moreno, Fernando
author
Font, Albert
author
Calvo, Alfonso
2024-07-03T11:01:22Z
2024-07-03T11:01:22Z
2014-01-24
Prior C, Perez-Gracia JL, Garcia-Donas J, Rodriguez-Antona C, Guruceaga E, Esteban E, et al. Identification of Tissue microRNAs Predictive of Sunitinib Activity in Patients with Metastatic Renal Cell Carcinoma. PLoS One. 2014 Jan 24;9(1):e86263.
10.1371/journal.pone.0086263
1932-6203
PloS One
http://hdl.handle.net/20.500.13003/11360
24475095
L373030799
2-s2.0-84898478153
http://hdl.handle.net/20.500.12105/19967
330339800035
Purpose: To identify tissue microRNAs predictive of sunitinib activity in patients with metastatic renal-cell-carcinoma (MRCC) and to evaluate in vitro their mechanism of action in sunitinib resistance. Methods: We screened 673 microRNAs using TaqMan Low-density-Arrays (TLDAs) in tumors from MRCC patients with extreme phenotypes of marked efficacy and resistance to sunitinib, selected from an identification cohort (n = 41). The most relevant differentially expressed microRNAs were selected using bioinformatics-based target prediction analysis and quantified by qRT-PCR in tumors from patients presenting similar phenotypes selected from an independent cohort (n = 101). In vitro experiments were conducted to study the role of miR-942 in sunitinib resistance. Results: TLDAs identified 64 microRNAs differentially expressed in the identification cohort. Seven candidates were quantified by qRT-PCR in the independent series. MiR-942 was the most accurate predictor of sunitinib efficacy (p = 0.0074). High expression of miR-942, miR-628-5p, miR-133a, and miR-484 was significantly associated with decreased time to progression and overall survival. These microRNAs were also overexpressed in the sunitinib resistant cell line Caki-2 in comparison with the sensitive cell line. MiR-942 overexpression in Caki-2 up-regulates MMP-9 and VEGF secretion which, in turn, promote HBMEC endothelial migration and sunitinib resistance. Conclusions: We identified differentially expressed microRNAs in MRCC patients presenting marked sensitivity or resistance to sunitinib. MiR-942 was the best predictor of efficacy. We describe a novel paracrine mechanism through which high miR-942 levels in MRCC cells up-regulates MMP-9 and VEGF secretion to enhance endothelial migration and sunitinib resistance. Our results support further validation of these miRNA in clinical confirmatory studies.
eng
Identification of Tissue microRNAs Predictive of Sunitinib Activity in Patients with Metastatic Renal Cell Carcinoma
research article