Evolution of Resistance to Aurora Kinase B Inhibitors in Leukaemia Cells

Aurora kinase inhibitors are new mitosis-targeting drugs currently in clinical trials for the treatment of haematological and solid malignancies. However, knowledge of the molecular factors that influence sensitivity and resistance remains limited. Herein, we developed and characterised an in vitro leukaemia model of resistance to the Aurora B inhibitor ZM447439. Human T-cell acute lymphoblastic leukaemia cells, CCRF-CEM, were selected for resistance in 4 µM ZM447439. CEM/AKB4 cells showed no cross-resistance to tubulin-targeted and DNA-damaging agents, but were hypersensitive to an Aurora kinase A inhibitor. Sequencing revealed a mutation in the Aurora B kinase domain corresponding to a G160E amino acid substitution. Molecular modelling of drug binding in Aurora B containing this mutation suggested that resistance is mediated by the glutamate substitution preventing formation of an active drug-binding motif. Progression of resistance in the more highly selected CEM/AKB8 and CEM/AKB16 cells, derived sequentially from CEM/AKB4 in 8 and 16 µM ZM447439 respectively, was mediated by additional defects. These defects were independent of Aurora B and multi-drug resistance pathways and are associated with reduced apoptosis mostly likely due to reduced inhibition of the catalytic activity of aurora kinase B in the presence of drug. Our findings are important in the context of the use of these new targeted agents in treatment regimes against leukaemia and suggest resistance to therapy may arise through multiple independent mechanisms

Scattering-Parameter-Based Macromodel for Transient Analysis of Interconnect Networks with Nonlinear Terminations

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix Acknowledgment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x Chapter 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Chapter 2. Scattering-Parameter-Based Macromodel . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.1. Scattering Parameters of Distributed-Lumped Components . . . . . . . . . . . . . . 6 2.2. Scattering-Parameter-Based Macromodel . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Chapter 3. Capturing Time-of-flight Delay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.1. Properties of Time-of-Flight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3.2. Scattering Parameters of Components with Time-of-Flight Captured . . . . . 19 3.3. Keeping Track of Tim..