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https://hdl.handle.net/10316/107377
Title: | MicroRNA signature refine response prediction in CML | Authors: | Alves, Raquel Gonçalves, Ana Cristina Jorge, Joana Marques, Gilberto João Padilha Luís, Dino Ribeiro, André B. Tavares, Paulo Oliveiros, Bárbara Almeida, António M. Ribeiro, Ana Bela Sarmento |
Issue Date: | 4-Jul-2019 | Publisher: | Springer Nature | Project: | SFRH/ BD/51994/2012 CIMAGO (Project 10/14), by Faculty of Medicine of the University of Coimbra and Santander Totta Bank with the grant (FMUC-BST-2016-214) FCT/ MCTES/PIDDAC (CNC.IBILI. Centre Reference: UID/NEU/04539/2013) |
Serial title, monograph or event: | Scientific Reports | Volume: | 9 | Issue: | 1 | Abstract: | microRNAs (miRs) dysregulation have emerged as a crucial step in tumorigenesis, being related with cancer development, progression and response to treatment. In chronic myeloid leukaemia (CML), the resistance to tyrosine kinase inhibitors (TKI) is responsible for treatment failure and could be linked to changes in miRs expression. This work aimed to correlate the expression levels of 3 miRs, miR-21, miR-26b and miR-451, with response to TKI treatment in CML patients. miR-451 levels at diagnosis were significantly higher in patients with optimal response after 6 and 12 months of therapy. Conversely, patients without optimal response had highest levels of miR-21. miR-21 and miR-451 appear to be good biomarkers of response, able to predict optimal TKI responders (p < 0.05). Using the combined profile of both miRs, we create a predictive model of optimal response after one year of treatment. This study highlights the role of miR-21 and miR-451 expression levels at diagnosis in predicting which patients achieve the optimal response. | URI: | https://hdl.handle.net/10316/107377 | ISSN: | 2045-2322 | DOI: | 10.1038/s41598-019-46132-9 | Rights: | openAccess |
Appears in Collections: | I&D CNC - Artigos em Revistas Internacionais I&D ICBR - Artigos em Revistas Internacionais FMUC Medicina - Artigos em Revistas Internacionais |
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MicroRNA-signature-refine-response-prediction-in-CMLScientific-Reports.pdf | 1.42 MB | Adobe PDF | View/Open |
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