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The effects of combination treatments on drug resistance in chronic myeloid leukaemia: an evaluation of the tyrosine kinase inhibitors axitinib and asciminib
Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. (CCBG;Linnaeus Ctr Biomat Chem, BMC)
Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. (CCBG;Linnaeus Ctr Biomat Chem, BMC)ORCID iD: 0000-0001-8696-3104
2020 (English)In: BMC Cancer, E-ISSN 1471-2407, Vol. 20, no 1, article id 397Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
BioMed Central, 2020. Vol. 20, no 1, article id 397
Keywords [en]
Allosteric inhibitor, Targeted therapy, Drug combination
National Category
Cancer and Oncology Bioinformatics and Systems Biology
Research subject
Chemistry, Biochemistry
Identifiers
URN: urn:nbn:se:lnu:diva-94730DOI: 10.1186/s12885-020-06782-9ISI: 000533422600001PubMedID: 32380976Scopus ID: 2-s2.0-85084402613Local ID: 2020OAI: oai:DiVA.org:lnu-94730DiVA, id: diva2:1429902
Funder
Swedish Cancer Society, CAN 2015/387Swedish Cancer Society, CAN 2018/362Available from: 2020-05-13 Created: 2020-05-13 Last updated: 2024-07-04Bibliographically approved
In thesis
1. Modelling the evolution of treatment-induced resistance in Ph+ leukaemias
Open this publication in new window or tab >>Modelling the evolution of treatment-induced resistance in Ph+ leukaemias
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Modellering av uppkomsten till läkemedelsresistens i Ph+ leukemi
Abstract [en]

Targeted therapies are a mainstay of modern cancer treatments. Rather than harming rapidly dividing cells in general, targeted therapies work by directly interfering with oncogenic molecular pathways present in a tumour. Consequently, a targeted therapy typically has less severe side effects. However, specificity comes at a price as comparatively small changes to the target can render the treatment ineffective. Much like the natural selection among plants and animals, individual cancer cells compete with one another for space and resources. Hence, if a single cancer cell acquires a resistance adaptation, the forces of evolution can turn that advantage in a single cell into an untreatable resistant cancer.

This thesis is principally concerned with chronic myeloid leukaemia (CML), characterized by a chromosomal translocation called the Philadelphia chromosome which creates the constitutively active tyrosine kinase Bcr-Abl1. The discovery of tyrosine kinase inhibitors (TKIs) targeting Bcr-Abl1 greatly improved treatment outcomes. Eventually however, resistance emerges. An important mechanism in CML is mutations in the kinase domain of Bcr-Abl1 that affect how well the drugs bind. A number of drugs have been developed that target the mutated kinase to varying degrees, but it is still desirable to prevent drug resistance from occurring in the first place, as the accumulation of multiple mutations is almost certain to create untreatable resistance.

The fitness effects of a drug resistance adaptation depend on the drug treatment, so it may be possible to alter the fitness landscape by modifying the treatment. This work examines different approaches, mainly in CML, to delay or prevent the onset of resistance through modifying the treatment protocol.

Periodically switching between different TKIs, i.e. drug rotations, was shown through modelling to increase the expected time to resistance and seems to have some protective benefits in vitro. Also apparently promising were drug combinations involving a novel inhibitor asciminib, currently in phase III trials, which can reduce overall drug burden while also being seemingly effective against known resistance mutations. Finally, a model of the interaction between resistance mutations and less potent alternate resistance mechanisms revealed how a drug holiday may have resensitizing, or even beneficial effects.

Place, publisher, year, edition, pages
Växjö: Linnaeus University Press, 2020. p. 92
Series
Linnaeus University Dissertations ; 391
Keywords
Chronic myeloid leukaemia, Stochastic modelling, Tyrosine kinase inhibitor, Drug resistance, Clonal evolution
National Category
Bioinformatics and Systems Biology Cancer and Oncology
Research subject
Natural Science, Biomedical Sciences; Chemistry, Medical Chemistry
Identifiers
urn:nbn:se:lnu:diva-98017 (URN)978-91-89081-85-7 (ISBN)978-91-89081-86-4 (ISBN)
Public defence
2020-10-02, Fullriggaren, Magna, Universitetskajen, Kalmar, 09:00 (English)
Opponent
Supervisors
Available from: 2020-09-11 Created: 2020-09-10 Last updated: 2024-02-27Bibliographically approved

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Lindström, JonathanFriedman, Ran

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