Background Chronic myeloid leukaemia is in principle a treatable malignancy but drug resistance is lowering survival. Recent drug discoveries have opened up new options for drug combinations, which is a concept used in other areas for preventing drug resistance. Two of these are (I) Axitinib, which inhibits the T315I mutation of BCR-ABL1, a main source of drug resistance, and (II) Asciminib, which has been developed as an allosteric BCR-ABL1 inhibitor, targeting an entirely different binding site, and as such does not compete for binding with other drugs. These drugs offer new treatment options. Methods We measured the proliferation of KCL-22 cells exposed to imatinib–dasatinib, imatinib–asciminib and dasatinib–asciminib combinations and calculated combination index graphs for each case. Moreover, using the median–effect equation we calculated how much axitinib can reduce the growth advantage of T315I mutant clones in combination with available drugs. In addition, we calculated how much the total drug burden could be reduced by combinations using asciminib and other drugs, and evaluated which mutations such combinations might be sensitive to. Results Asciminib had synergistic interactions with imatinib or dasatinib in KCL-22 cells at high degrees of inhibition. Interestingly, some antagonism between asciminib and the other drugs was present at lower degrees on inhibition. Simulations revealed that asciminib may allow for dose reductions, and its complementary resistance profile could reduce the risk of mutation based resistance. Axitinib, however, had only a minor effect on T315I growth advantage. Conclusions Given how asciminib combinations were synergistic in vitro, our modelling suggests that drug combinations involving asciminib should allow for lower total drug doses, and may result in a reduced spectrum of observed resistance mutations. On the other hand, a combination involving axitinib was not shown to be useful in countering drug resistance.

Background The population growth rate is an important characteristic of any cell culture. During sustained experiments, the growth rate may vary due to competition or adaptation. For instance, in presence of a toxin or a drug, an increasing growth rate indicates that the cells adapt and become resistant. Consequently, time-dependent growth rates are fundamental to follow on the adaptation of cells to a changing evolutionary landscape. However, as there are no tools to calculate the time-dependent growth rate directly by cell counting, it is common to use only end point measurements of growth rather than tracking the growth rate continuously. Results We present a computer program for inferring the growth rate over time in suspension cells using nothing but cell counts, which can be measured non-destructively. The program was tested on simulated and experimental data. Changes were observed in the initial and absolute growth rates, betraying resistance and adaptation. Conclusions For experiments where adaptation is expected to occur over a longer time, our method provides a means of tracking growth rates using data that is normally collected anyhow for monitoring purposes. The program and its documentation are freely available at https://github.com/Sandalmoth/ratrack under the permissive zlib license.

Background Resistance towards targeted cancer treatments caused by single nucleotide variations is a major issue in many malignancies. Currently, there are a number of available drugs for chronic myeloid leukaemia (CML), which are overcome by different sets of mutations. The main aim of this study was to explore if it can be possible to exploit this and create a treatment protocol that outperforms each drug on its own. Methods We present a computer program to test different treatment protocols against CML, based on available resistance mutation growth data. The evolution of a relatively stable pool of cancer stem cells is modelled as a stochastic process, with the growth of cells expressing a tumourigenic protein (here, Abl1) and any emerging mutants determined principally by the drugs used in the therapy. Results There can be some benefit to Bosutinib-Ponatinib rotation therapy even if the mutation status is unknown, whereas Imatinib-Nilotinib rotation is unlikely to improve the outcomes. Furthermore, an interplay between growth inhibition and selection effects generates a non-linear relationship between drug doses and the risk of developing resistance. Conclusions Drug rotation therapy might be able to delay the onset of resistance in CML patients without costly ongoing observation of mutation status. Moreover, the simulations give credence to the suggestion that lower drug concentrations may achieve better results following major molecular response in CML. Electronic supplementary material The online version of this article (10.1186/s12885-019-5690-5) contains supplementary material, which is available to authorized users.

Background Acute myeloid leukaemia (AML) is an aggressive blood cancer. In approximately 30% of the cases, driver mutations in the FLT3 gene are identified. FLT3 inhibitors are used in treatment of such patients together with cytotoxic drugs or (in refractory AML) as single agents. Unfortunately, resistance to FLT3 inhibitors limits their efficacy. Resistance is often due to secondary mutations in the gene encoding the molecular target. The gatekeeper mutation F691L confers resistance to specific FLT3 inhibitors such as quizartinib, but pexidartinib is much less resistance to this mutation. Pexidartinib alone is however sensitive to many other resistance mutations. In chronic myeloid leukaemia (CML), it has been suggested that rotation between drugs with a different landscape of resistance mutations might postpone the emergence of resistance. Methods We studied the effect of quizartinib and pexidartinib in AML cell lines that express FLT3 (MOLM-14 and MV4-11). Using a rotation protocol, we further examined whether the emergence of resistance could be postponed. Computational modelling was used to analyse the onset of resistance and suggest which mutations are most likely to occur in a quantitative fashion. Results The cells were sensitive to both inhibitors but quickly developed resistance that could be inherited, suggesting a genetic origin. Rotation protocols were not useful to postpone the emergence of resistance, which implies that such protocols, or changing from pexidartinib to quizartinib (or vice-versa) should not be used in patients. The computational modelling led to similar conclusions and suggested that F691L is the most common mutation to occur with quizartinib, and also when both drugs are used in rotation. Conclusions AML patients are not likely to benefit from a quizartinib/pexidartinib rotation protocol. A combination of tyrosine kinase inhibitors (with different molecular targets) might be more useful in the future. Development of specific FLT3 inhibitors that are less sensitive to resistance mutations might also lead to a better outcome.

Targeted therapies for chronic myeloid leukaemia (CML) are effective, but rarely curative. Patients typically require treatment indefinitely, which gives ample time for drug resistance to evolve. Drug resistance issues are one of the main causes of death owing to CML, thus any means of preventing resistance are of importance. Drug rotations, wherein treatment is switched periodically between different drugs are one such option, and have been theorized to delay the onset of resistance. In vitro testing of drug rotation therapy is a first step towards applying it in animal or human trials. We developed a method for testing drug rotation protocols in CML cell lines based around culturing cells with a moderate amount of inhibitors interspersed with washing procedures and drug swaps. Drug rotations of imatinib and ponatinib were evaluated in a CML specific cell line, KCL-22. The growth of KCL-22 cells was initially reduced by a drug rotation, but the cells eventually adapted to the protocol. Our results show that ponatinib in a drug rotation temporarily sensitizes the cells to imatinib, but the effect is short-lived and is eventually lost after a few treatment cycles. Possible explanations for this observation are discussed.