Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/103806
Title: Resistance to Tyrosine Kinase Inhibitors in Chronic Myeloid Leukemia-From Molecular Mechanisms to Clinical Relevance
Authors: Alves, Raquel 
Gonçalves, Ana Cristina 
Rutella, Sergio
Almeida, António M
De Las Rivas, Javier
Trougakos, Ioannis P
Sarmento-Ribeiro, Ana Bela 
Keywords: CML; TKI resistance; epigenetics; immune system; new targeted therapies; patient adherence; bioinformatics and artificial intelligence
Issue Date: 26-Sep-2021
Publisher: MDPI
Project: UIDB/04539/2020 
UIDP/04539/2020 
John and Lucille van Geest Foundation. I.P.T. 
Hellenic General Secretariat for Research and Innovation grants, Nutra-Food (MIS 5050734), CosmAGE (MIS 5070022), and DDIOL (MIS 5070020) 
Carlos III Institute of Health (ISCiii) from the Spanish Ministry of Science and Innovation (project PI18/00591) 
COST Action STRATAGEM, CA17104, supported by COST (European Cooperation in Science and Technology), www.cost.eu (accessed on 30 August 2021) 
Serial title, monograph or event: Cancers
Volume: 13
Issue: 19
Abstract: Resistance to targeted therapies is a complex and multifactorial process that culminates in the selection of a cancer clone with the ability to evade treatment. Chronic myeloid leukemia (CML) was the first malignancy recognized to be associated with a genetic alteration, the t(9;22)(q34;q11). This translocation originates the BCR-ABL1 fusion gene, encoding the cytoplasmic chimeric BCR-ABL1 protein that displays an abnormally high tyrosine kinase activity. Although the vast majority of patients with CML respond to Imatinib, a tyrosine kinase inhibitor (TKI), resistance might occur either de novo or during treatment. In CML, the TKI resistance mechanisms are usually subdivided into BCR-ABL1-dependent and independent mechanisms. Furthermore, patients' compliance/adherence to therapy is critical to CML management. Techniques with enhanced sensitivity like NGS and dPCR, the use of artificial intelligence (AI) techniques, and the development of mathematical modeling and computational prediction methods could reveal the underlying mechanisms of drug resistance and facilitate the design of more effective treatment strategies for improving drug efficacy in CML patients. Here we review the molecular mechanisms and other factors involved in resistance to TKIs in CML and the new methodologies to access these mechanisms, and the therapeutic approaches to circumvent TKI resistance.
URI: https://hdl.handle.net/10316/103806
ISSN: 2072-6694
DOI: 10.3390/cancers13194820
Rights: openAccess
Appears in Collections:I&D ICBR - Artigos em Revistas Internacionais

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