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.

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.

Lymphoid malignancies are a group of highly heterogeneous diseases frequently associated with constitutive activation of the nuclear factor kappa B (NF-κB) signaling pathway. Parthenolide is a natural compound used to treat migraines and arthritis and found to act as a potent NF-κB signaling inhibitor. This study evaluated in vitro parthenolide efficacy in lymphoid neoplasms. We assessed parthenolide metabolic activity in NCI-H929 (MM), Farage (GCB-DLBCL), Raji (BL), 697 and KOPN-8 (B-ALL), and CEM and MOLT-4 (T-ALL), by resazurin assay. Cell death, cell cycle, mitochondrial membrane potential (ΔΨ_mit), reactive oxygen species (ROS) and reduced glutathione (GSH) levels, activated caspase-3, FAS-ligand, and phosphorylated NF-κB p65 were evaluated using flow cytometry. CMYC, TP53, GPX1, and TXRND1 expression levels were assessed using qPCR. Our results showed that parthenolide promoted a metabolic activity decrease in all cell lines in a time-, dose-, and cell-line-dependent manner. The mechanism induced by parthenolide was demonstrated to be cell line dependent. Nonetheless, parthenolide promoted cell death by apoptosis with significant ROS increase (peroxides and superoxide anion) and GSH decrease combined with a ΔΨ_mit reduction across all studied cell lines. Despite the need to further understand parthenolide mechanisms, parthenolide should be considered as a possible new therapeutic approach for B- and T-lymphoid malignancies.